Employment, Output and Productivity

ISSUES IN DEVELOPMENT
Discussion Paper
33
PAKISTAN:
Employment, Output and
Productivity
Nomaan Majid
International Labour Office Geneva
Copyright © International Labour Organization 2000
ISBN 92-2-111977-7
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TABLE OF CONTENTS
ACKNOWLEDGEMENTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii
PREFACE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . viii
INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
A.
Recent changes in the macro environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
B.
The argument . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
CHAPTER ONE - Labour Force and Employment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
1.
The data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
2.
Growth of population and labour force . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
3.
Labour force and employment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
Definitions of labour utilization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
The self-employed amongst the employed . . . . . . . . . . . . . . . . . . . . . . . . . 10
Underemployment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
Unemployment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
Employment and labour force: An overview . . . . . . . . . . . . . . . . . . . . . . . 12
4.
Changing trends in the rural-urban distribution of labour force . . . . . . . . . . . . . . . 12
5.
Why are labour force participation rates (LFPRs) low? . . . . . . . . . . . . . . . . . . . . . 13
Education and the labour force . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
Emigration and the labour force . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
Gender and the labour force . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
6.
On the changing abilities of the labour force . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
Labour force expectations and the structure of the job market . . . . . . . . . . 16
7.
Upshot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
Participation Rates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
Training and skills . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
Implications for a strategy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
CHAPTER TWO - Output Employment and Productivity: Lessons for an Employment Strategy . .
1.
A dual focus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.
Examining shares of employment and output . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.
Sectoral shares of employment and output . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.
Growth of employment and output . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.
Sectoral employment absorption . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
6.
Decomposing output growth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
7.
Wages and poverty . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Real Wages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Poverty Trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Poverty, Wages and Growth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
8.
Elasticity, employment, labour productivity and output: An integrated view . . . . .
9.
Employment and output growth linkages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
10.
The agenda for an employment strategy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
18
18
18
19
19
20
22
22
23
24
25
26
28
29
CHAPTER THREE - The Agricultural Sector . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
1.
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
2.
The special nature of employment and output in agriculture . . . . . . . . . . . . . . . . . . 31
iii
Measurement of employment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
The special nature of output . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
A combined effect . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Output and employment growth rates in Pakistan’s agriculture . . . . . . . . . . . . . .
Agricultural employment and total employment . . . . . . . . . . . . . . . . . . . . . . . . . . .
Decomposing the sources of output growth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Unemployment and underemployment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Labour demand . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Cropping patterns and profitability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Size and productivity: Increasing family labour use . . . . . . . . . . . . . . . . . .
Mechanization: Reducing labour requirements . . . . . . . . . . . . . . . . . . . . .
Tenurial shifts: Creating an available labour pool . . . . . . . . . . . . . . . . . . .
Wages and poverty . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Upshot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
31
31
32
33
34
34
35
36
36
37
37
37
37
38
CHAPTER FOUR - The Manufacturing Sector . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1.
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.
Elasticity, employment and output growth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.
Decomposing output growth in the manufacturing sector . . . . . . . . . . . . . . . . . . . .
4.
Output and employment in the manufacturing sector . . . . . . . . . . . . . . . . . . . . . . .
5.
The large-scale sector: Main features . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
6.
An examination of productivity in the large-scale manufacturing sector . . . . . . . . .
7.
The structure of large-scale manufacturing in the 1980s and 1990s . . . . . . . . . . . .
The high-growth 1980s . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
The 1990s: A period of low growth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
8.
Towards a policy outline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Criteria of sectoral choices in an employment-friendly investment plan . . .
Fiscal expansion and demand . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
The budget deficit and working capital . . . . . . . . . . . . . . . . . . . . . . . . . . .
Promotion of sub-sectors through tariff rationalizations . . . . . . . . . . . . . . .
Capital pricing and directing new investment . . . . . . . . . . . . . . . . . . . . . . .
The co-ordination of capital flows . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
The revival of sick industries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Tax policy and flow of goods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Energy pricing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
9.
Upshot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
40
40
40
41
42
44
45
46
47
49
50
51
51
51
51
51
52
52
52
52
52
CHAPTER FIVE - The Small-Scale Enterprise Sector . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1.
Information and data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.
Definitions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.
Estimates of output and employment in SSE manufacturing . . . . . . . . . . . . . . . . . .
4.
Characteristics of the SSE sector . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
The SSE firm: Subcontracting and demand . . . . . . . . . . . . . . . . . . . . . . . .
Labour use in the SSEs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Capital stock ratios . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Credit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Incomes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.
Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
54
54
54
54
56
56
57
57
58
58
59
3.
4.
5.
6.
7.
8.
9.
iv
6.
The Supply and demand for sse goods and services . . . . . . . . . . . . . . . . . . . . . . . .
Changes in purchasing power of social groups and demand . . . . . . . . . . . .
Remittances . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
The green revolution and differentiation of the peasantry . . . . . . . . . . . . . .
The income and technical change effect of the green revolution . . . . . . . . .
Depreciation of exchange rates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Some inferences . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Policy areas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Credit policy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Tax policy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Infrastructure policy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
A strategic policy corollary and some specific measures . . . . . . . . . . . . . . . . . . . .
Upshot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
59
59
60
60
60
60
61
61
62
62
62
62
63
CHAPTER SIX - An Employment Strategy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1.
Elements of an employment strategy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
On labour force and employment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
On sectoral strategies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
65
65
65
66
APPENDIX -The Economic Reforms Context of Growth and Employment . . . . . . . . . . . . . . . . . .
The periodization and salient features of Pakistan’s development history . . . . . . . . . . . . . .
The non-economic correlates of macroeconomic policies and growth . . . . . . . . . . . . . . . . .
Two symptoms of the problem of growth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Assessing the policy-growth linkage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
The aggregate overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Indicators on economic growth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Indicators on price stability in the economy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Indicator on external balance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Indicators on labour market conditions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
A thematic assessment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
On the sequencing of reforms and the reform policies . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Fiscal Policy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Monetary Policy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Trade and exchange rate liberalization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Exchange Rate Reforms (1982- ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Trade liberalization (1983- ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Non-tariff barriers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Tariff reforms (1990-) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Upshot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
70
70
71
72
73
73
74
75
75
75
76
76
77
79
82
82
83
83
84
85
7.
8.
9.
10.
ANNEXES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88
CHAPTER ONE
Annex 1.1:
Sources of data on labour and human resources . . . . . . . . . . . . . . . . . . . . 89
Annex 1.2:
Youth employment and child labour . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91
Annex 1.3:
Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95
CHAPTER TWO
Annex 2.
Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105
v
CHAPTER THREE
Annex 3.
Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115
CHAPTER FOUR
Annex 4
Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 128
CHAPTER FIVE
Annex 5.1:
The small-scale enterprise sector in main data sources . . . . . . . . . . . . . .
Rates of growth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Broad characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Annex 5.2:
Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
137
137
137
142
BIBLIOGRAPHY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159
vi
Acknowledgments
This report is based on the work carried out during 1997-98. Nomaan Majid of the Employment Sector
of the ILO, Geneva is the coordinator and principal author of the report. The work is based on
contributions from a team comprising of Arshad Zaman Associates, A.R.Kemal, M. Irfan, M. Mahmood,
G. Chaudhry and Nomaan Majid. Particular thanks are due to A.K. Ghose, M. Mahmood and Akmal
Hussain for detailed comments on earlier drafts. Thanks are also due to Samir Radwan, Rolph Van der
Hoeven and Rashid Amjad for suggestions on the final draft. A.S.Oberai of ILO-SAAT, provided constant
support and encouragement for the project from its inception. ILO-SAAT, the ILO Office in Islamabad
and the UNDP in Islamabad actively facilitated the progress of this report, in its most critical phases.
Very special thanks are due to them.
vii
PREFACE
This report is an outcome of work done by the ILO, on an employment strategy for Pakistan during 1997
and 1998, an activity which was funded under the UNDP’s SPPD facilty. One objective of the core work
done for this exercise was to contribute an input to Planning Commission for their employment and
manpower related work on the Ninth five Year Plan. Another objective was to produce a employment
strategy document, that was cognizant both of sectoral employment issues and the macro economic
environment in which a future employment strategy needs to be conceived. It is hoped that work is seen
as a step in the right direction. More thinking however, needs to be done in detailing the proposed
employment strategy, in addition to addressing the implications of this strategy for social groups within
sectors. It is expected that the ILO in collaboration with the UN agency system will carry this work further.
Two central issues need to be emphasized. This document argues that in the Pakistan context the key to
an employment growth revival is the revival of the manufacturing sector. The particular forms that such
a revival may take, the linkages with other sectors, and some of the policy elements required for such a
revival are delineated. The document also suggests in a separate section why the role of the macro policy
environment in the growth process is critical from an employment perspective. It argues where and how
Pakistan came to its fiscal crisis. This event, which is a result of imperatives on the part of State as well
as ill-conceived reform sequencing on the part of donors, preceded the post nuclear situation of additional
economic constraints that the country has faced and the more recent changes in government.
Today when the elements of adjustment packages and their relationship to growth are being seriously
questioned by Bretton Woods institutions themselves because of the high social costs of adjustment as
evidenced by the Asian and Russian crises, it is important to directly examine the nature of policy
packages necessary for a revival of employment-friendly growth in developing countries. The challenge
is not easy for Pakistan, but the international environment is sufficiently changed and the domestic
employment crisis sufficiently serious, to pursue the matter with new vigour.
Samir Radwan
Director, Development Policies Department
viii
INTRODUCTION
This study on employment in Pakistan was conducted in 1997-98. Its objective has been to
analyse trends in the labour market in the country, and develop possible elements of an
employment strategy during Pakistan’s Ninth Five Year Plan period ( 1997-98 to 2001-02).
A. Recent Changes in the macro environment.
Since the completion of this work in 1998, some factors have entered into Pakistan’s planning
process that have affected it significantly. The first is a rapidly changing macro environment.
The second are the results of the 1998 Population Census. The report argues that these factors
heighten the need for an employment strategy being proposed in this document. Its should
however be finessed towards the transforming macro environment, and our better post-census
perception of it.
Pakistan’s macroeconomic performance, while showing indications of improvement at the time
of the 1998 budget, has since been subject to fiscal stress. The central point that is worth making
is that over the fiscal year 1997/98, growth had picked up in Pakistan to the five per cent level,
while the IMF stipulated targets in macro fundamentals were met to the satisfaction of the
evaluating mission to Pakistan at the time. However, domestic fiscal policy, perhaps in
anticipation of an impending sanctions based global environment due to the nuclearisation of the
country, (and possible investment behaviour based on this global environment), moved towards
regulation in a number of areas1. A major result of this macro transformation had been the
cessation of the Enhanced Structural Adjustment Facility (ESAF) and Extended Fund Facility
(EFF) agreements signed with the IMF, and a renegotiated new loan.
Although the external environment is now more stable, and donor links have been reestablished,
changes in the macro environment need to be tracked as they can have critical implications for
growth and employment in Pakistan. Clearly this issue needs to be assessed in future work. It is
also critical to recognise the status of the specific macroeconomic policy environment for the
question of whether growth is employment-friendly or not. Since the link between macropolicies
and employment is generally mediated by growth, this provides an overarching context to
understanding different phases of (employment focussed) economic development in Pakistan. The
report devotes a separate Appendix to this issue. The reason to keep this discussion separate from
the main body of the report is two fold. First that the assessment of the linkage between
macropolicies and employment in this report is itself limited to an historical overview. Second,
that it is the last phase of macropolicies in operation in Pakistan that are of greater importance
to an employment strategy, than what can be argued for earlier phases.
B. The argument
The position of this study on employment and its determinants in Pakistan is the following. Wage
employment in Pakistan is approximately one half of all employment, its proportion is high for a
1
The policy of non convertibility of domestic foreign currency deposits that was compelled, according to the central
bank, by excessive public borrowing against these deposits, was an effort to miser precious foreign reserves.
low income country. On the other hand self-employment comprises the other half of employment
(Chapter 1). The share of the labour force in the estimated population for 1997, according to
pre-1998 Census projections( on which this study has been based, and on which more below) is
low. It was 37 million from a universe 135 million, which suggests a low participation rate. In fact
the labour force participation rate (LFPR) in Pakistan has been decreasing over time. It is now
down to around 27 per cent, therefore implying a high and increasing dependency ratio for the
rest of the population. While we can explain to some extent, the drop in the LFPR to be due to
increasing school enrollments (which is therefore in some respect desirable), there is clearly a
possible trade off involved due the narrowing of the earning base in the country, which can put
downward pressures on per capita income. This can have implications for poverty and living
conditions of households. We actually find a mixed result on poverty in Pakistan, but it is one
which is not inconsistent with the hypothesis of a downward pressure on living standards due to
increasing dependence during the growth process.
The next question the report asks is what determines the low labour force participation and its
income? The labour force, by definition, comprises of the employed and the unemployed, given
at around 35 million and 2 million respectively. Before summarising the answer to this question,
some qualifiers need to be made. There has been considerable debate and now recognition, in
Pakistan, that women’s income enhancing labour, whether in self-employment or in the wage
labour market has been considerably under-enumerated due to non-sampling errors like male
social biases, that render women’s labour “invisible”. This feature also reduces the overall
estimates of the size of the employed. The second qualification is that under enumeration of the
unemployed obtains because the survey- definition used in Pakistan requires them to be available
for work in the reference week. Moreover it is to be remembered that these qualifiers obtain in
the context of a labour market where formal institutions for employment are eclipsed by informal
institutions. So, our estimates of both the employed and the unemployed, and the size of the total
labour force are probably low.
This study assumes that given the labour force size, perhaps in this case based on consistent
underestimation, what will determine the level of employment in the economy is firstly growth
itself. On the other hand what determines the earnings of the employed are the wage rate and
returns to self-employment in different sectors of the economy. In order to investigate the
relationship between employment and growth, this study uses two analytical devices. One is a
standard elasticity coefficient for employment with respect to growth. Problematic as the specific
magnitude of the elasticity measure is, in the view taken here, it is considered at least qualitatively
and directionally indicative of the employment-output linkage. This of course gives a range of
values indicating say high, medium, or low responsiveness of employment to growth. The second
device dis-aggregates change in output over time into (i) an output change caused by
employment change; (ii) an output change that is caused by productivity changes; and (iii) an
output change that is caused by a multiple effect of both employment and productivity changes.
We refer to this as the decomposition exercise. The results of both exercises ( elasticity and
decomposition) are used as summary perspective devices in the overview as well as sectoral
chapters.
Chapter 2 of this study shows that over the last three decades, Pakistan’s growth has been high
for a low income country, around six per cent on trend till 1992/93, with a two per cent variation.
However, against this high GDP growth, employment growth has been much lower, at two per
2
cent on trend. As a result the elasticity of employment has remained medium to low, ranging
between 0.6 and 0.3. The periodicity of this growth of output and employment is revealing, if we
abstract for the moment from the issue of the particular periodisation chosen.
Output growth in Pakistan was low over the 1970s at under five per cent, it increased over the
1980s to above six per cent, and has dropped again over the 1990s to near about four per cent.
Employment growth interestingly follows an opposite pattern, being at its highest at three per
cent over the 1970s and lapsing to two per cent over the 1980s and the 1990s. Does this
constitute some prima facie evidence for a trade off between employment and output growth?
A further subdivision of these periods shows that there was a period of high employment in the
1970s, stable employment till the mid-1980s and a total break between growth and employment
subsequently. The aforementioned decomposition exercise adds an insight to this pattern.
Growth of output was based predominantly on an employment effect in the 1970s, on a
productivity effect in the 1980s, and a mixed productivity and employment effect in the 1990s.
So the answer to the trade off question posed above is not straight forward, and apart from having
a source of output growth dimension ( productivity or employment) the answer is likely to have
a sectoral dimension as well.
We know that generally low elasticities accompanying growth in Pakistan tend to conceal the
fact that the source of growth (employment or productivity) itself has been varying over time.
This is an important point to note. It is this changing relationship between growth of output and
employment over time that is traced to its major sectoral components in the rest of the report.
In output growth, manufacturing is the leading sector (and agriculture contributes progressively
less over time), over the low growth period of the 1970s, the high growth period of the 1980s,
and the lower growth period of the 1990s. In employment growth, during the low growth
period of the 1970s manufacturing leads, and with the relapsed of growth of the 1990s,
employment growth in manufacturing turns negative.
The explanation for the changing overall relationship between output and employment growth
over time then finds a possible sectoral reason. It has been said that employment growth was
high over the 1970s and then stable till the mid 1980s, after which it de-linked from output
growth. Manufacturing contributed relatively more to employment growth than agriculture in the
1970s, relatively less than agriculture in the 1980s, and negatively in the 1990s. So the overall
break between output growth and employment seems to be more associated with the
manufacturing sector. It is also true that we find some evidence to suggest that agriculture and
construction are becoming possible refuge sectors for labour after this de-linking of employment
and output growth. This explanation is further enhanced when we examine output and
employment growth relationships at the sectoral level through the same two analytical devices of
sectoral elasticities and the decomposition exercises. Chapters 3 to 5 examine sectors.
Chapter 3 on agriculture shows that output growth and employment growth (and therefore,
employment elasticity) were stable in the 1970s till the mid-1980s, barring states of nature based
interventions. Therefore, output and employment growth are connected till the mid-1980s. After
the mid-1980s, output and employment growth became volatile. The elasticity of employment
in agriculture is thus positive and stable till the mid-1980s then subsequently starts fluctuating.
The decomposition exercise for agriculture shows that agricultural output growth was driven
3
predominantly by the employment effect in the 1970s, largely by the productivity effect in the
1980s and then again largely by the employment effect in the 1990s. The report does pursue
alternative explanations for the contribution of agriculture to the fluctuations in employment from
the mid-1980s onwards, in terms of the increasing sensitivity of a post-High Yielding Variety
(HYV) agriculture to states of nature, and the casualisation of the labour force based on
increasing mechanisation.
In contrast, to agriculture, Chapter 4 shows that in the case of manufacturing, employment
growth was stable and high over the 1970s, when in fact output growth was low. In the 1980s,
output growth in manufacturing rose, but employment growth dropped to a stable low, the
aforementioned critical disjuncture become evident by 1980. By the mid 1980s, output and
employment growth both become unstable. Elasticity of employment in manufacturing, barring
a peak in the mid-1970s remains at a continuously low level. The decomposition exercise for the
manufacturing sector highlights this break between employment and output growth after the
1970s. Over the 1970s output growth in manufacturing is driven equally by the employment
effect and the productivity effect. Over the 1980s the employment effect becomes negligible,
while over the 1990s it turns negative.
So, the disjuncture between employment and output growth rates in manufacturing reflect and
track the economy-wide break between employment and output growth rates better. Low output
growth accompanies high employment in the aggregate over the 1970s, high output growth
accompanies low but stable employment growth till the mid-1980s, after which employment and
output growth become volatile. It is fairly clear that both agriculture and manufacturing contribute
to output through a predominant employment effect in the 1970s, but for the 1980s and 1990s,
only agriculture contributes through an employment effect, while manufacturing’s employment
growth breaks away from its growth of output.
Having focussed on the manufacturing sector, we need to trace the causality further. In other
words we need to determine the causes for this break between employment and output growth
in manufacturing itself. The first point to note here is that while the share of manufacturing in
GDP has increased over time from 15 per cent to 18 per cent, its share in employment has
declined from 14 per cent to 10 per cent. To explain why the manufacturing sector has become
entirely labour productivity driven rather than in some measure employment-driven, we have to
recognise some structural features of the sector. The critical feature of manufacturing in Pakistan,
as in many developing economies is its duality. The large scale (LS) sector and a small scale (SS)
sector are two classifications of manufacturing and the cutoff point between the two has been
defined variously over time by the government of Pakistan (GOP)2. The LS sector (examined in
Chapter 4), produces two-thirds of the value added in manufacturing, but employs only 17 pre
cent of the approximately 4 million labour force in manufacturing. The SS sector (examined in
Chapter 5), produces one third of the value added in manufacturing, but employs 83 per cent of
the labour. So the LS sector dominates output, while the SS sector dominates employment.
Further, the output and employment shares of the LS and SS sectors have remained fairly stable
over the last two decades.
2
For effective purposes the 1934 Factories Act cuts off enterprises employing more than ten workers, from those
employing less.
4
The differential between the two manufacturing sectors, LS and SS, is in labour productivity; and
this in turn is reflected in a differential in their capital-labour ratios. The LS sector has a higher
capital labour ratio by a factor of 17, and therefore a much higher labour productivity. It also has
higher wage rates and greater job security, and it is argued over the course of Chapters 3 and 4,
that LS growth rates are higher growth rates than those in the SS sector. Other production
characteristics of the SS sector are detailed in Chapter 5, these are fragile vending linkages to
other parts of the economy and negligible formal credit. The typical SS unit is based on self
employment and family labour; with earnings approximating the LS sector’s wage rate, with low
vintage, and limited vertical transition out of the sector. These characteristics of the SS sector,
while not completely homogenising potentially render a large part of it, a refuge labour sector in
Pakistan.
The following question then is, if the SS sector has in large part been or become moribund with
all its disincentives, why has the LS sector failed to expand its employment levels significantly
over time, say between 1980 and 1995, when employment grew at 2.3 per cent, employment in
the LS sector grew at under 1.8 per cent. The first element in our answer is an increase in capital
productivity in large scale manufacturing over time3. Furthermore, Chapter 4 also shows for the
LS sector, that while this increase in capital productivity was positively correlated to labour
productivity, it was significantly negatively correlated to employment. As a result the wage share
in output dropped from 0.4 to 0.29. This is accompanied by the fact, as Chapter 1 shows, that
the real wage in Pakistani industry barely creeps up over the last two decades. It is worth
pointing out that this pattern of growth in the LS sector was enabled by a large increase in
investment in manufacturing, and liberal financial sector lending. So over the period 1982/83 to
1992/93, private investment in manufacturing increased from 1.7 per cent of GDP to 4.2 per cent.
In other words, the pattern of investment and growth in manufacturing, over the 1980s, was
capital augmenting and labour displacing, and it increased profitability and reduced the wage
share in output. The evidence tends to favour this view 4.
The second element in our answer to the disjuncture between growth of output and employment
in the LS sector lies in the creation of excess capacity in the 1990s. Private investment in
manufacturing halves after 1993/94 from 4.2 per cent of GDP to 2.2 per cent with a declining
trend, as Chapter 4 shows. This results in a declining trend in capacity utilisation in the four
major industries of the LS sector, spinning, weaving, cement and sugar. The economic position
taken here is that this downturn in investment, capacity utilisation, and growth in manufacturing
is caused in large part by a failure in demand, significantly associated with the deflationary
policies pursued by GOP in accordance with the Structural Adjustment (SA) programme signed
with the IMF, in successive protocols since the 1988 .
What probably happened was a coincidence of events. Growth in Pakistan has always been
susceptible to states of nature caused downs in agriculture, given its preponderant reliance on the
3
Chapter 4 shows that over the 1980s the capital labour ratio in the LS sector increased from Rs. 50,000/ to Rs.
192,000/.
4
This was akin to the pattern of restructuring of capital followed in some Industrialised countries (ICs) over the
1980s, in reprisal to the three decades of post-war Keynesian full employment policies.
5
textile industry and export of cotton and its products. The dips in GDP in each decade, examined
in Chapter 2, are related to flooding in agriculture in the early 1970s and in the early 1980s, and
a pest attack on cotton in 1992/93. However in the 1970s and the 1980s, the economy recovered
with a one to two-year lag, returning to trend growth. In the 1990s, however, this return to trend
growth has arguably been inhibited by the simultaneity of deflationary SA policies with the
massive decline in cotton output for two years running. Just when the state of nature caused
slump needed a reflationary policy, the SA programme veered the economic managers towards
policies effectively increasing the incidence of general taxation and a decline in subsidies. This was
affected through the imposition of a Value Added Tax (VAT) and successive annual increases
in its rate and coverage; and through a reduction in the budgetary deficit especially affecting
agricultural subsidies and therefore production and recovery. This was also manifested in a
decreased purchasing power and effective demand.
In summary, we have found that the relationship between growth in employment and output is
strong over the 1970s, and stable over the first half of the 1980s, but becomes negative
subsequently. Manufacturing is the leading sector in growth of output and employment in the
1970s, but contributes little to employment in the 1990s. The manufacturing sector is seen to be
characterised by a dualism, with an LS sector dominating output, and an SS sector dominating
employment over time. Given low capital labour ratios in the SS sector and all the disadvantages
in production conditions that this entails, the central question that emerged was why the relatively
more advantaged LS sector had constrained its employment levels over time, especially over the
1980s and the 1990s. Two elements were identified to answer this question. One, that over the
1980s, the LS sector in Pakistan followed an internationally established pattern of capital
augmenting, labour substituting growth, increasing profit shares and reducing the wage share.
Two, that over the 1990s, deflationary SA policies dampened recovery from a state of nature
caused blip in growth, especially for manufacturing, constraining capacity utilisation and
employment further.
An employment strategy for Pakistan must then seek to redress this disjuncture between growth
of output and employment, caused in large part by the LS sector in manufacturing. This is what
is proposed in this report. The key constraints are an overwhelming capital augmenting growth
path, and deflationary SA policies. This brings us back full circle to the starting point this
argument. With an impending, and even larger, SA programme in the offing, Pakistan faces the
prospect of possibly low growth and low rate of recovery from a fiscal crisis as in 1992/93, and
possibly employment-less growth as in the 1980s. This makes a planned employment strategy for
the NFYP period difficult but imperative. On the other hand, the more recent changes in the
thinking of Bretton Woods institutions, with respect to the recognition of social outfalls of
adjustment programmes, allows Pakistan, as indeed other developing countries, a better context
in which to make a case for a macro and social policy framework which is consistent with a
positive employment strategy.
6
CHAPTER ONE
Labour Force and Employment
1.
THE DATA
A well-known shortcoming of analysis on labour markets in Pakistan is the internal limitations of the data
produced on population, labour force and employment. Coverage of the labour force surveys (LFS) is
known to be low, with the result that both participation rates and employment elasticities based on LFS
data are thought to be underestimated. The population census scheduled for 1991 had been delayed, leaving
a gap of over seventeen years since the previous census was taken. The full results of the Population
Census of 1998 were still unavailable at the time of the writing of this report. The absence of regular and
better data confines us to work, with due care, with the data available (Annex 1). There is, however, a
distinction (if not a choice) here which needs to be made. In view of the weight of empirical evidence that
does (or does not) exist, there are two courses open for further investigation. The first is to accept the
trends from large-scale data as a starting point and then investigate the issues and problems this data
throws up at the disaggregated level, in order to qualify the existing trends – both sectorally and with
respect to special categories/groups of labour that require focus. The second course is to reject the census
and survey data on the grounds that the true labour supply is understated1 and proceed with analyses
supported by the micro evidence that can be marshalled, without regard for the larger picture.
The view taken in this report is that there is a need for greater caution in rejecting the burden of numerous
surveys, irregular and imperfect as they may be and even if they yield apparent inconsistencies in their
results, as surveys anywhere are apt to do. The size of the information that does exist in Pakistan is
substantial. In order to judge the validity of anomalies in the larger data sets, what is ideally needed is a
specific survey, of equal or greater coverage, which provides empirical proof of the alleged bias in
previous census and survey data. There is both an absence and a critical need for information on labour
market indicators in Pakistan. Given the lack of a perfect series or a second-best one, we will work with
what is available, using annual data from labour force surveys. These are subject to much fluctuation,
suggesting a weakness in data source. Our emphasis is therefore more on trends than on explaining annual
fluctuations, where they seem inexplicable.
The earliest and, probably, still the more reliable data on population and labour force are provided by the
population censuses of 1951, 1961, 1972, and 19812 (See tables A1.1, A1.2 and A1.3). In lieu of the much
delayed census for 1991, we have used population and labour force data from the Demographic Survey of
1991 and the annual labour force surveys carried out since. These are used to assess the employment
situation, especially after 1981 (Table A1.2).3
1
For example, due to exclusion of women’s household work and of women and men’s work in the informal sector
(especially in the school-going age group).
2
Population censuses have been conducted every ten years 1880. The census for 1971 was delayed by one year, and
that for 1991 has not been conducted so far. There is now evidence to show that there may be serious problems associated with
the 1961 census. Consequently the need for a consistent series is real. The 1997 figures are estimates.
3
Since 1990-91 the surveys are based on an improved questionnaire.
7
2.
GROWTH OF POPULATION AND LABOUR FORCE
The labour force (around 37 million in 1997) is not a very large proportion of the population (135 million
in 1997) in Pakistan. Its is estimated to be around 28-29 per cent. Population growth had been increasing
over the years, up to and including 1970s. Although the last census was carried out in 1980, projections
on the population growth rate suggest that it is likely to have fallen and has probably stabilized now to
just under 3 per cent4.
Labour force growth rates on the other hand were higher than that of population in 1970s (figure 1.1 and
Table A1.1) but have been generally lower after the 1970s. Although the labour force survey figures for
the 1990s can also be interpreted to suggest a decline in labour force growth on trend5, there are problems
in comparing the labour force trends before and after 1990-916. There is however a clear decline between
the two definitionaly comparable periods of the 1970s and 1980s.
This means that labour force growth, which is significantly lower than population growth, is likely to be
falling while the growth of population is likely to be stabilizing.
8 .0 0
Figure 1.1: Growth of Population, Labour Force and
Employment
6 .0 0
%
4 .0 0
2 .0 0
-
- 2 .0 0
- 4 .0 0
Grth(Pop)
4
Grth(LF)
Years
Grth(Emp)
This is subject to confirmation by the impending Population Census.
5
Average growth of population for the 1970s (1970-80) was 3.14 per cent; for the 1980s (1981-1990) it was 3.10 per
cent and for the 1990s (1992-1996) it has been estimated at 2.98 per cent. Labour force growth for the same periods has been
3.31 per cent; 2.42 per cent and 2.4 per cent. The last-mentioned is the case only if we exclude 1990-91(which is the
definitional change year). Strictly speaking, it is not legitimate to compare trends before and after 1990-91. The 1970s to 1980s
trend shows a decline in labour force growth, which is likely to have continued.
6
The 1990-91 Labour Force Survey changed some definitions in such a way that (a) activity rates of women
increased by inclusion of some homeworkers as part of the labour force; (b) total labour force increased; and (c) unemployment
rates increased. This essentially makes the comparison of pre- and post-1990-91 LFSs difficult.
8
F ig u r e 1 .2 : P o p u l a t i o n , L a b o u r F o r c e a n d E m p l o y m e n t
160
140
120
100
80
60
40
20
0
P o p ulatio n
Lab. F o r.
E m p lo y e d L a b o u r f o r c e
If serious data problems are excluded as a cause, then one of the main reasons for falling labour force
growth rates is reflected in the decline in participation rates due to withdrawal of sections of persons of
working age from the labour force. Educational enrolments for an increasingly younger population of
working age mean that the labour force growth will begin to rise in the near future. This has implications
for trends on unemployment and underemployment in the present situation. These are likely to be magnified
with an increase the growth rate of the labour force in the future.
3.
LABOUR FORCE AND EMPLOYMENT
Definitions of labour utilization
The “economically active population” comprises persons of either sex who furnish the supply of labour
for the production of goods and services, during a specified time reference period. But not all these persons
are currently active (or in the labour force) at any particular point of time. In Pakistan, the currently active
population or labour force comprises of all persons ten years of age and over who fulfil the requirements
for inclusion among employed or unemployed, defined as follows, during the reference period i.e. one week
preceding the date of interview.7
•
The “employed” comprise all persons ten years of age and over who worked at least one hour
during the reference period, and were either “paid employed” or “self-employed”. (Persons holding
permanent jobs, who for any reason had not worked during the reference period are treated as
employed).
7
Pakistan uses the “labour force” approach, to measure employment, unemployment and underemployment. This
approach uses hours of work as the criterion and aims basically at measuring labour utilization. The definitions used in the
recently conducted surveys are given above. The differences in the old (1987-88 and prior) and new (1990-91) concepts may
be seen in Annex 1.
9
•
•
The “unemployed” comprise all persons ten years of age and over who during the reference period
were:
–
“Without work,” i.e. were not in paid employment or self-employment;
–
“Currently available for work,” i.e. were available for paid employment or selfemployment; and
–
“Seeking work,” i.e. had taken specific steps in a specified recent period to seek paid
employment or self-employment.
The underemployed comprise all employed persons who during the reference period were working
less than the “normal” duration on an involuntary basis and were seeking or were available for
additional work. In Pakistan, the underemployment rate is estimated as a ratio of the employed
(who worked less than 35 hours a week) to total labour force. With the help of the available data,
we analyze below the latest employment, unemployment and under-employment situation in
Pakistan.
The self-employed amongst the employed
Employment is divided into two categories in Pakistan: the self-employed and the hired. The self-employed
are only marginally less in number than the hired within the labour force. During 1983-95, the selfemployed, on an average, constituted 44 per cent of the employed work force: 46 per cent in the rural areas
and 37 per cent in the urban areas. The percentage of the self-employed increased from 40.3 in 1982-83
to 47.9 in 1987-88 but was at 42.3 in 1994-95. This percentage increased in the rural areas and declined
in urban areas during the period 1982-83 and 1994-95 (table A10).
In 1987-88, the agricultural sector accounted for 53.6 per cent of the self-employed, followed by trade
(16.8 percent) and manufacturing (10.9 percent). In the rural areas, agriculture accounted for 66.6 per cent
of the self-employed followed by 9.8 per cent in trade. In the urban areas, the wholesale and retail trade
sector accounted for the major share of 41.8 per cent (Table A1.11).
Another distinct feature of the self-employed is that compared to the national average, the share of selfemployed who worked full time was higher (except for women in rural areas). Moreover, the level of
education of the self-employed was also lower than the national average (Table A1.12).
The self-employed are sizeable, significantly agrarian, work long hours and are relatively less literate than
their counterparts in employment. It is important to bear in mind that self-employment in Pakistan is
predominantly in agriculture and more symptomatic of poverty than prosperity.
Underemployment
The underemployment rate is estimated as a ratio of employed who worked less than 35 hours a week to
the total labour force (Table A1.13). There were nearly 4 million persons underemployed in Pakistan in
1994-95.
The proportion of employed persons who worked for less than 35 hours, which had declined from 14 per
cent of the employed work force in 1982-83 to 11.1 per cent in 1987-88, was at 12.2 per cent in 1994-95.
Underemployment was much more prevalent in rural than in urban areas. In 1987-88, it was 2.8 times that
of urban areas. In 1993-94 it was almost double. Unpaid family helpers constituted about half of the
underemployed, followed by the self-employed. This is true in the aggregate as well as in the rural areas.
Underemployment among employers was almost negligible.
10
Within rural areas the share of underemployed declined from 16.3 per cent in 1982-83 to 13.4 per cent in
1987-88, but was at 14 per cent in 1994-95. In contrast, the share of underemployed in urban areas
declined from 7 per cent in 1982-83 to 4.8 per cent in 1987-88, but was at 7.1 per cent in 1994-95
(Table A1.14).
It is also interesting note that in the 1993-94 LFS (when this question was asked) a four-fifths majority of
those who were underemployed, considered their working hours as “normal”. This implies a “normality”
of being permanently underemployed, in an “enclave” of the labour market where most of the
underemployed are not so out of choice (only 2.6 per cent in this group describe their underemployment
as voluntary) and where the severity of underemployment is unlikely to decrease.
Unemployment
In a developing economy characterized by significant poverty, minimal social insurance and welfare
mechanisms, unemployment is probably the least appropriate indicator of labour market conditions. Most
people of working age, who are not in full-time education, need to work to survive. With this proviso in
mind, we will examine unemployment data.
First, it is necessary to clarify a definitional problem. Before 1990-91, the LFS recorded those persons as
unemployed who were without work (i.e. were not in paid employment or self-employment) and were both
currently available and seeking work during the reference period of one week. Those who may have been
available for work but for some reason were not seeking it (i.e. not taken specific steps to seek paid or selfemployment) were not recorded as unemployed. The unemployment rates prior to this period were
therefore recorded at a low figure of about 3 per cent. From 1990-91 onwards, the condition of being
available for work was sufficient to be recorded as unemployed. This resulted in the unemployment rate
in 1990-91 jumping to 6.3 from 3.1 per cent in 1989-90 (Table A1. 15) and implies that comparisons on
unemployment8 are not legitimate across the year 1990-91.
The number of unemployed persons was two million in 1990-91. This figure was one million in 1989-90
and much of the increase occurred because of the change in definition of the term. The overall
unemployment rate declined in 1991-92 and 1992-93 but it went up in 1993-94 and remained at the same
level in 1994-95 and declined again afterwards. There is no real trend which is discernible9. For general
policy purposes, it may not be wrong to assume that currently about two million people are unemployed
in Pakistan. According to data, 63 per cent are men and 37 per cent women. Of the total unemployed in
1994-95, about 60 per cent were in rural areas. However, the unemployment rate (ratio of unemployed
persons 10 years of age and over to labour force) was much higher in urban areas (6.51 per cent in urban
as against 4.22 per cent in rural areas). Available figures for 1984-85 to 1987-88 show that the severity
of unemployment as judged by its duration as well as the percentage of unemployed with previous
experience has been increasing (Table A1.16).
8
This is also true for female participation rates as we shall see below.
9
There is slight decline between the 1970s and 1980s and no pattern after in the 1990s. Comparisons with the 1990s
are, however, suspect for this category.
11
Unemployment rates are higher both for older and younger workers. Whereas the high unemployment rates
for the 10-14 age group may be attributed to restrictions on (child) labour below the age of 14, the high
rates in the 60 plus age group is explained by the non-availability of jobs suiting older workers.10 Within
the unemployed, the share of literates has increased on trend from 42.8 per cent to 48.8 per cent
(Table A1.17).
At the aggregate level the unemployment rate has averaged around 5.0 per cent a year during 1990-91 to
1994-95. Of two million unemployed in Pakistan, nearly half of them are literate and the severity of their
unemployment is likely to be increasing.
Employment and labour force: An overview
Employment growth rates generally increased in the 1970s, and from the end of the 1970s declined on trend
till the late 1980s. In the 1990s, although it is difficult to make a comparative statement, employment
growth is falling on trend.11 The variability in growth rates is partly explained by definitional changes.12
In sum:
•
the gap between the number of persons in the labour force (employed or otherwise) and the
population is likely to widen for a little longer before it starts closing;13
•
the size of the underemployed is around 4 million (12 per cent underemployment rate) and is likely
to have been increasing in recent years; and
•
close as they are in levels compared to the population, the gap between the labour force and the
employed within it as a proportion of the labour force, is wider now it was during the 1970s and
suggests a persisting unemployment problem.
Given that labour force growth is expected to increase in the future, those employment-related problems
that exist now, under falling labour force growth conditions, are likely to worsen.
We now make some further observations on the data available.
4.
CHANGING
TRENDS IN THE RURAL-URBAN DISTRIBUTION OF LABOUR FORCE
In absolute numbers, the labour force in Pakistan has increased from 18.1 million to 35.2 million between
1972 and 1995 (Table A1.3). The male labour force has increased from 16.7 million to 30.5 million and
the female labour force from 1.4 million to 4.7 million. Compared to an average annual increase of 2.7 per
10
See Annex 1: Labour and Employment Statistics
11
Employment levels are generally close to those of the labour force and both have increased steadily over the years.
However, growth rates of employment have both been lower as well as higher than that of the labour force in the past. There
is some pattern. Up to the mid-1970s employment growth rates were higher than labour force growth; from the mid-1970s to
the early 1980s they were lower. In the mid-1980s they were higher again and since the late 1980s they have remained lower
for most years.
12
The 1990-91 Labour Force Survey changed definitions in such a way that unemployment rates as well as female
participation rates increased.
13
12
The education-based withdrawals are likely to swell the labour force with a time lag.
cent in the total labour force between 1972-95, the urban labour force increased by 3.5 per cent per year,
while the rural labour force increased by 2.5 per cent per year in the same period. As a result, the share of
the urban labour force in the total labour force increased from 23.3 per cent in 1971-72 to 27.3 per cent
in 1994-95. This difference in growth rates was largely the result of rural-urban migration. The growth
of the rural labour force in the late 1970s and the first half of the 1980s was also affected (restricted) by
emigration, which is much less important today.
Traditionally, and certainly since 1975 onwards the growth of the urban labour force has been faster than
that of the rural labour force. This was to be expected. However, the reversal of trends in growth rates in
the 1990s (rural labour force growth rates being higher than urban ones)14 suggest that, if no serious data
problem exists, there may be an emerging barrier on internal rural urban migration15 (Table A1.3). This
issue has implications for the size of the labour force in the rural areas, particularly in agriculture, and
needs to be explored.
5.
WHY ARE LABOUR FORCE PARTICIPATION RATES (LFPRS) LOW?
The size of the labour force is determined by the size of the working-age population and its activity or
participation rates 16, adjusted for migration into and out of the country. This population has already been
born; the demographic changes which occur today will affect labour supply with a time lag of about 10
years. The “activity rate” is therefore the key determinant of the currently active population or labour
supply.
We need to explain why the participation rates of labour force are declining in Pakistan. The LFPR peaked
to 31 per cent in 1978-79 and declined to 27.5 per cent in 1994-95. The falling labour force participation
rate has clearly restrained the growth of the domestic labour force (Table A1.4).17 It is worth noting that
rural participation rates are generally higher than urban ones, another reason why when labour force
growth declines it does so less in rural areas. This is also reflected in the fact that while the rates of male
participation in the labour force do not vary so much across the rural and urban divide, and they do so
less over time, the gap between rural and urban participation rates for women is significant and persists
over time. The greater participation in rural areas is due to a greater inclusion of women in what constitutes
the labour force, in spite of the reporting biases on women's household activities in both rural and urban
areas. This feature comes into sharp relief when we consider the size of the excluded labour force in
Pakistan.
We discuss below three tendencies for changes in the LFPRs in Pakistan whose net impact is clearly a
decline. These pertain to education, emigration and gender.
14
For the period 1991-92 to 1996-97 (estimated), the rate of growth of the overall labour force is 2.42 per cent; it
is 2.96 per cent for the rural labour force and 1.08 for the urban labour force.
15
Differences in urban and rural LF growth can be attributed to the net effects of rural-to-urban and urbanto-overseas migration and reverse flows, none of which are precisely known.
16
The crude activity rate, also called the crude labour force participation rate (LFPR), is defined as the ratio of
labour force to the population. The participation rate of the labour force was around 27.5 per cent in 1994-95. This is not only
extremely low but has been declining on trend (Table A1.4).
17
The 1990-91 LFS improved the activity rates for women due to definitional changes.
13
Education and the labour force
High population growth in Pakistan has also been associated with an increasing proportion of population
in the lowest age cohorts (Table A1.5). The proportion of population in the 0-14 years age group increased
from 44.5 per cent in 1981 to 45.8 per cent in 1988 and to 46.3 per cent in 1995, thus raising dependency
ratios and depressing labour force participation rates. In part, age compositions do explain why the overall
participation rates are low. The 10-14 years age group show a decline in participation rates, suggesting a
withdrawal of the young (who are counted as economically active) from the labour force, possibly due to
increased school attendance. 18 The decline in participation rates, in the 15-19 years age group may be
similarly attributed to increasing college enrolment.
Emigration and the labour force
Increasing emigration from the mid-1970s to the mid-1980s had constrained growth in domestic labour.
According to the report of the National Manpower Commission (Government of Pakistan, 1989, p. 101),
during 1978-83, almost 25 per cent of the incremental labour force found employment abroad. This helped
in sustaining employment growth at 2.8 per cent. However, return migration in 1982-87 dominated the
stream of migration and may have played some part in accentuating pressures on the domestic employment
situation (Table A1.6). For the more recent sub-period there is evidence of net out-migration. The net
outflow in 1993-95 period is, however, a much lower percentage of the labour force, in comparison with
the past peak of the 1980s. The size of the labour force today is not subject to pressures return migration
and is unlikely to be seriously constrained by out-migration.
Gender and the labour force
This is an area which requires serious analytical and empirical disentangling.
Due to the way the term ‘labour force’ is defined, a number of persons, particularly women engaged in
household duties, are not included in the term ‘population currently active’ or labour force (table A7). This
reduces the number of labour force as well as the participation rate, a shortcoming that was partly made
up for in Pakistan by adopting a new definition in the 1990-91 LFS, in which women were identified as
employed if they spent time on any of the 14 specified agricultural and non-agricultural activities defined
in the Intentional Standard Industrial Classification, (ISIC).19 This partly redresses the definitional bias.
However, it is interesting to note that in 1994-95 about 59 per cent of the economically active population
were excluded from the labour force. Of these, about 27 per cent were men and 73 per cent were women.
Clearly, the bulk of the ‘excluded labour force’ are women.20
An obvious reason for this in Pakistan is that social perceptions restrict the ‘admission’ of the existence
of female work, by a not too insignificant section of the population. This implies a reporting bias due to
18
This fact has implications for the incidence of child labour. We should expect it decline (Annex 2).
19
Non-inclusion of housewives (home-makers) as well as other categories of persons such as rentiers, thieves
beggars, smugglers, prostitutes, etc., in the labour force has been a matter of debate for a long time. Until the definition of
the term <labour force’ is changed, we have restricted to the bias of the official figures of the labour force. The non-inclusions
are often for ideological or moral reasons.
20
The figures are telling that after accounting for students enrolled in government institutions, about 32.8 million
persons, comprising 2.7 million men and 30.1 million women, were not in the labour force.
14
which female participation rates and employment can be seriously under-reported. Secondly, in Pakistan,
much of the employment data, irrespective of its source, is collected by male investigators interviewing male
respondents.21 Apart from the degree of authenticity of responses, variations in reported employment may also
result from variations in the education, training or supervision of investigators; the periods chosen for the survey;
and the language used in the questionnaire.22 These elements vary from survey to survey and can lead to serious
inconsistencies in the published data.
The definitional changes in LFSs in 1990-91 (apart from increasing the proportion of unemployed in the labour
force) improved women’s participation rates in general. This may be more an effect of a categorical change and
less of an actual improvement in women participation rates, which are still very low. This low rate accounts for
the low overall level of participation of the labour force shows up as a trend decline in participation rates and the
labour force growth over the years. For the 1990s the improvement in coverage of working women is offset by
the withdrawal of the young from the labour force.
6.
ON THE CHANGING
ABILITIES OF THE LABOUR FORCE
The composition of labour force by level of education has witnessed changes in Pakistan (Table A1.8). With the
improvement in the literacy rate, the proportion of the literate labour force has increased from 39.9 per cent in
1990-91 to 43.6 per cent in 1994-95. While the share of literate men in the labour force increased from 37.3 per
cent to 40.1 percent, that of women increased only marginally from 2.57 per cent to 2.67 per cent.23 Clearly, if
one criterion for employability is literacy, then an explanation of low participation rates of women is low literacy,
which needs to be a policy focus.
The literacy rate of the labour force has risen from 35.3 per cent in 1987-88 to 43.2 per cent in 1994-95. Over
this period, the share of degree holders has shown the sharpest rise (from 1.8 per cent to 2.9 per cent), followed
by that of matriculates (from 9.4 per cent to 13.2 per cent). The composition of employed work force by the level
of education has also undergone significant changes (Table A1.9).24
Within the literate labour force, employment growth rates have been positive for all levels of education
except for the holders of degrees in medicine and those with no formal education25. The proportion of
literates in the labour force is also increasing albeit slowly.
21
See Sathar and Kazi (1997).
22
Shah and Sathar (1978).
23
Within the literate labour force, pre-matriculates in 1994-95 accounted for a major share (57 per cent) followed
by matriculates (23 per cent) and those with intermediate degrees (9 per cent). Graduates accounted for about 9 percent of the
literate labour force. Within graduates, about 90 percent hold degrees in subjects other than engineering, medicine and
agriculture. Engineering graduates were 12.3 percent; medical, 4.5 percent; and agricultural graduates, 1.2 percent.
24
The composition of employed work force by sectors shows wide variations. According to the latest LFS (199495), about 74 per cent of the employed labour force in the agriculture sector was illiterate as against 7.8 per cent in finance,
insurance and business services, and 17.1 per cent in the electricity and gas distribution sectors. Next to agriculture, the
illiterate accounted for 69.4 per cent in construction and 58.3 per cent in mining sectors. Within the literate, the most highly
qualified persons were found in finance, services and electricity and gas sectors.
25
The declining share of medical graduates is not easily explained. Perhaps they are included in the “postgraduate”
group, which has registered a growth of about 13.3 per cent per annum.
15
Although literacy is increasing 56 per cent of the labour force are still illiterate and about another 10 per cent
literate only at pre-matriculate levels or with no formal education. Efforts to introduce new technologies and
management techniques in the short-run, essential for the improvement of productivity and efficiency, are likely
to be constrained.
Labour force expectations and the structure of the job market
Although it may be true that economic growth itself is fundamental as a final adjuster of the labour market in the
medium run, it is also arguable that, at least in part, mechanisms of adjustment depend upon the perceptions of
those who bear the burden of adjustment in the labour market, namely the unemployed and the underemployed.
A question was put in the LFS of 1993-94 to those who were not working in the reference week regarding work
expectations. These expectations are indicative of a mismatch with prevailing sectoral, as well as locational,
conditions of employment. This is an interesting finding, which needs some elaboration. In the LFS of 1993-94,
nearly two-thirds of the unemployed expressed the wish for employment with government, a proportion which,
if realized, would be more than twice the current governmental share in employment. Nearly one-fourth of the
unemployed preferred clerical and related jobs. This is mainly the response of the matriculates and
intermediates. On the other hand, only 1 per cent of the unemployed said that they would like to work in the
agricultural sector while nearly half of Pakistan’s employed are still in the occupational category of
agriculturalists and forestry workers. Occupational preferences of the unemployed do partly reflect their
educational background, but the dissonance which is being reflected here is really between the development of
an educational system and the production structure and needs of the economy.
Orientating a future labour force (which will increase in growth and literacy) towards the types of activities the
future holds should be an essential part of the training and skilling efforts being made today. This is an important
challenge for the future of both the labour force and the country.
7.
UPSHOT
Pakistan had a population of around 128.3 million in 1994-95 of whom 85.4 million were above the age of 10.
The labour force size is 35.2 million (29.3 employed; 4.0 underemployed and 2 unemployed). Those who were
outside the labour force, excluding students (17.4 million) were around 32.8 million, 30.1 million of whom were
women. The growth of the labour force has been lower than that of population on trend in the past. Urban labour
forces have also been growing faster than rural ones due to rural-urban migration, although there are some
indicators in the 1990s that internal migration may be halting and trends could be reversing.
The rate of growth of the labour force in Pakistan has been falling in the past but it is expected to rise in the near
future. Unemployment and underemployment trends suggest a worsening or certainly no improvement in the
recent past. This means that the problems associated with those who are not fully employed is likely to increase
when labour force growth picks up. The labour force is also slowly becoming more literate in Pakistan.
Apart from the matters pertaining to restrictions in the growth of population, there are three areas which require
focusing from an employment perspective. These relate to data, participation rates and training.
Data
The coverage of the LFS must improve. This is with respect to the excluded sections of the adult population,
which are dominated by women. Moreover, definitions need to further improve to include home workers, as well
as other categories of persons who may be excluded for non-technical reasons. The Population Census must be
16
conducted without delay. It is the fundamental basis of any serious policy work, quite apart from being a
necessary cross-check on the Labour Force Surveys. A country the size of Pakistan cannot afford to avoid a
Population Census for seventeen years, no matter what the domestic political fall out of this may be. Consistency
exercises must continue to be in built into data collection, as was the case in the 1990-91, whenever definitional
changes take place, so that trends can be readjusted. A consistent series of best-possible estimates of all labour
market indicators in Pakistan needs to be built, which adjusts and reconciles the data available from different
sources.
Participation Rates
Clearly, participation rates have been very low and declining in Pakistan. These need to be improved for the
productive absorption of the labour force in the economy. The issue of female participation rates is a subset of
the general issue. The reason for the increase in the low participation rates for women is not necessarily only
because more women are working but because definitions have improved. The causes for the low participation
rates as well as high incidence of women in those excluded from the labour force need to be ascertained carefully.
The extent to which this is due to social factors, definitional problems, or coverage need to be distinguished
empirically. On a general plane, the low participation rates needs to be improved to effect a more productive use
of labour in the economy.
Training and skills
There must be a conscious attempt made to bring the expectations of the literate labour force which is either not
in employment or likely to come into the labour force in the future, into line with actual possibilities in the job
market. This should be done both at an educational level as well as at the level of training programmes.
Implications for a strategy
From the perspective of a strategy, two issues are important:
•
the labour force growth is expected to increase in the future;
•
problems associated with those who are less than fully employed, are likely to worsen with the expected
rise in labour force growth.
17
CHAPTER TWO
Output Employment and Productivity:
Lessons for an Employment Strategy
1.
A DUAL FOCUS
The magnitude of the employment problem facing Pakistan in the future is considerable. Even if the rate
of growth of the labour force is likely to pick up in the near future, the deteriorating employment situation
is likely to worsen more than present trends anticipate.
There are two related matters for concern: the gap between population and the labour force and a rising
labour force in comparison to the “fully employed” within it. An increasing gap between population and
labour force growth for a given output implies the increasing dependency of a rapidly growing part of the
population on a slowly rising labour force. Under these same conditions, the increase in the gap between
the fully employed and the labour force implies constraints on the earning capacity of the labour force
itself. This has direct and demonstrable implications for poverty.1
One goal of a future employment strategy is therefore to reduce the growth of population. The other, and
what we are concerned with in this report, is to productively increase the participation of the labour force
in the economy. In doing so, the aim is to improve aggregate employment and attack the twin problems of
unemployment and underemployment head on. The next sections take a more detailed view of the
employment situation.
2.
EXAMINING SHARES OF EMPLOYMENT AND OUTPUT
Given the critical situation described above, employment strategies need to be devised in order to face the
employment challenge. The absorption of a larger percentage of population in gainful work, as well as the
reduction of the under employed and unemployed, are important goals.
It would, however, be hazardous to proceed as if all that needs doing is to direct efforts towards an
expansion of sectors with higher employment elasticities and wait for employment to happen. The
precarious nature of estimating elasticities of employment in Pakistan has been discussed elsewhere2. For
the purposes of the present analysis, our position is that elasticity estimates, though useful in the
generation of ball-park projections, are on their own, insufficient for planning an employment strategy.
Moreover, the estimates tend to become more inconclusive the better the methodology used. Elasticities
have generally been low in Pakistan and they have been lower in the high growth period of the 1980s
1
On their criteria of “basket of basic needs”, (Gazdar et al. 1994) find a very drastic decline (18.7 per cent) in
poverty in Pakistan between 1984-85 and 1987-88, which is clearly a period when employment growth outstripped labour force
growth. Their estimates for 1990-91 show a much smaller decline (9.1 per cent), which was a period in which labour force
growth was generally matched by employment growth. Poverty gap measures like the ‘poverty gap’ (PG) and ‘Forster-GreerThorbecke’ (FGT) Index, which take into account the average income of the poor and its distance to the poverty line confirm
this observation more conclusively. From 1984-85 to 1987-88 to 1990-91 the PG declined from .111 to .077 to .071, while the
FGT declined from .038 to .023 to .022 (Table A2.8).
2
18
ILO-SAAT, Arshad Zaman Associates, 1997 (mimeo).
than they were in the relatively lower growth periods of the 1970s and 1990s 3. The increasing trend in
employment elasticities are however, is not a simple index of ascertaining the “labour absorption
capacity”of an economy. We need to look at other indicators implicit in the elasticity measure, in order to
make some judgements on the quality of the labour absorption which the elasticity measure signifies.
Although sector-specific analyses are necessary for producing the details of an employment strategy that
can lead to concrete policies, an aggregative analysis of the sort attempted in this chapter can still provide
a plausible a sectoral prioritization within an economy-wide framework. The following sections examine
the sectoral trends in employment in Pakistan before proceeding to study the indicators of employment
implicit in an elasticity measure: growth in output, employment and labour productivity.
3.
SECTORAL SHARES OF EMPLOYMENT AND OUTPUT
As far as sectoral distribution of output shares are concerned, in the long run agriculture’s share declined
from 39 per cent in 1971 to 24.3 per cent in 1997 (Table A2.2). GDP shares of manufacturing have
increased on trend; they were 14.16 per cent in 1971 and 17.92 per cent in 1997. There are small increases
in other sectors’ GDP shares. The decline has essentially been for agriculture and the gain for most of
the other major sectors. This is to be expected in the process of development.
Sectoral shifts have also taken place in employment shares over time. Once again for agriculture there has
been a long-run trend decline but from the mid-1980s the share has been fluctuating between the 45 per
cent and 55 per cent mark (Table A2.3). It can be argued that although the share of employment has
declined for agriculture, over the longer-run period, it has been fluctuating within a range in the last decade.
On the other hand, contrary to expectation, there has been a declining trend in the share of manufacturing
in employment from 1969-70 (15.57 per cent) to 1993-94 (10.12 per cent), although employment shares
on average rose slightly from the 1970s to the 1980s and then declined in the 1990s. All other sectors which
include construction, trade and the “other” activities category over a longer-run period, from say 1970-71
to 1994-95, have shown an increase in employment shares. It is therefore quite reasonable to argue that
accompanying the longer run decline in employment in agriculture, say from 1969-70 onwards, there have
been increases in employment shares of sectors other than manufacturing.
In the recent and shorter-run period of the 1990s, however, agriculture’s fluctuating share of employment
forms no trend (except that it breaks from the past trend of a declining share of employment), while the
share of manufacturing (and mining) in employment has definitely fallen from 12.54 per cent in 1990-91
to 10.12 per cent in 1993-94.
4.
GROWTH OF EMPLOYMENT AND OUTPUT
Although we need to be aware of the standard limitations of the elasticity measure, it is still worth
examining the trend in employment elasticities, and of output and employment growth for the economy as
a whole over the years. This in conjunction with other measures can help identify general trends. Figure
2.1 below splits the employment elasticity measure into its two components: employment growth and output
growth.
3
They have increased in the 1990s compared to the 1980s.
19
Figure 2.1: Growth of Real GDP & Employment, and
the Output-Elasticity of Employment, 1971-72 to 1996-97
2.00
8.00
1.50
1.00
4.00
0.50
2.00
0.00
-
Elasticity
Growth Rate (%)
6.00
-0.50
-2.00
Fiscal Years Ending June 30
-4.00
-1.00
GDP
Employment
Elasticity
The economy-wide picture shows a few features clearly.
•
GDP growth rates were low in the 1970s, highest in the 1980s and have fallen in the 1990s again.
Excluding the past couple of years, they are nevertheless reasonable growth rates.
•
In relation to GDP growth, employment growth has been low in Pakistan’s economy. In the early
1970s employment growth hit a sustained high level. During the high growth period of the 1980s,
employment growth was very low and since the mid-1980s it has been much more variable.
•
The elasticities of employment have generally followed employment growth, confirming the view
that output growth has been the relatively more stable part of the employment elasticity measure
in Pakistan.
This leaves the matter of the recent volatility in employment growth, which appears seems to be a new
structural feature in the Pakistan economy, as an issue that needs to be explained. Examining sectoral
employment changes over time delineates the sources of this volatility.
5.
SECTORAL EMPLOYMENT ABSORPTION
One question that needs answering in an economy-wide context is: why has the structure of employment
growth become so volatile?3 As a first step, this requires one to explore sectoral trends in employment in
more detail. The Figure below presents data on annual changes in the number of persons employed by
sectors.4
3
The answer as to why GDP growth has declined from the 1980s to the 1990s is complex and requires both a sector
specific view as well as analysis of macroeconomic policies.
4
20
The net change in any year is the difference between the positive change and the negative change.
Figure 2.2. Changes in Employment (000) 1971-96
2.00
1.50
1.00
0.50
-
-0.50
70- 71- 72- 73- 74- 75- 76- 77- 78- 79- 80- 81- 82- 83- 84- 85- 86- 87- 88- 89- 90- 91- 92- 93- 94- 9571 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96
-1.00
-1.50
-2.00
Agriculture
Mining & Manufacturing
Construction
Trade
Others
Elec.Gas& Trans.
-2.50
Although the data presented are not free of problems,5 they do show that:
1.
2.
3.
4.
Three kinds of trends are discernible: first, a period of high and rising labour absorption in the
early 1970s (until 1978-79); second, a period of stable job creation (about 500,000 jobs per year)
from 1979-80 to 1984-85; third, an unstable trend in labour absorption since then, which reached
a high in the 1991-92 period and seems to be on a cyclical downward trend.
Employment in general has definitely become more volatile since the mid-1980s and agriculture
to account for the largest share of changes in employment (positive and negative). Volatility in
employment is thus partly connected to the agricultural sector.
Unlike the early years (the 1970s), manufacturing has not played a major role in labor absorption,
although it has contributed both positively and negatively in specific years (especially 1986-87,
1987-88, and 1992-93). This means that manufacturing is also a contributor to the volatility in
employment.
In recent years (especially since the late 1980s) the wholesale and retail trade sector tends to play
a large role in employment creation. This also true for the residually defined “others” category. A
large part of these sectors are likely to be in the SSE (Small-Scale Enterprise) sector.
5
Especially the significant falls in employment in agriculture in 1990-91 (when there were major floods) and 199495, lesser declines including in “other” sectors in six other years, and the sharp rise in 1986-87, which requires further
investigation.
21
6.
DECOMPOSING OUTPUT GROWTH
The employment swings discussed above and the trends in elasticity observed are consistent with the
decomposition of output growth presented for the 1970s, 1980s and 1990s decades in Table 2.1 below.
Output growth decomposes into two contributing components: employment expansion and labour
productivity and accordingly periodizes the Pakistan economy since the 1970s.6
Table 2.1:
Decomposing output growth, productivity and employment effects
M P @ Nto'M Y
M N @ Pto 'M Y
M N @ M P'M Y
Productivity
Effect
Employment
Effect
1969/70 – 1980/81
0.292
0.615
0.118
1980/81-1990/92
0.578
0.273
0.148
1991/92 – 1994/95
0.400
0.571
0.028
Multiple Effect
Source: National Income Accounts and Labour Force Survey (various years).
The employment effect was strongest in the 1970s after which there was productivity- led growth in the
1980s. The high growth period (1980s) was least driven by employment expansion as a contributor. In the
1990s, there was a shift back towards a growth process which is partly based on increasing employment.
Given that the 1990s are a relatively lower growth period, we need to probe further into the nature of this
employment expansion. In the section following we examine the employment conditions which
charactercized the changes, as reflected in wages and poverty.
7.
WAGES AND POVERTY
Where organized labour is not the largest part of the hired labour force7, and where a multiplicity of
contractual arrangements exist, it is important to analyse not only real wages over time but poverty as well.
Unfortunately, the database on wages is limited in Pakistan and poverty assessments not only differ in
methodology but are also constrained by data sources that are not current. The importance of wages
and poverty indicators necessitates an attempt at their assessment. We start by discussing wage rates
(Table A2.10).
6
The following is a symbolic decomposition of Output change in to: (i) employment effects, (ii) productivity effects,
and (iii) multiple (of employment and productivity ) effects. The basic symbols are:Output = Y; Employment = N; Productivity
= P; Intitial time period = to ; Change over time = M .
P= Y'N
N= Y'P
Y= P @ N
Then, Change in Output is:
M Y = M P @ Nto % M N @ Pto % M N@ M P
Dividing by M Y
M P @ Nto'M Y % M N @ Pto 'M Y % M N@ M P'M Y = 1
The Change in Output decomposes in to:
(i) An employment effect=M N @ Pto 'M Y
(ii)A productivity effect=M P @ Nto'M Y
(iii)A multiple effect = M N@ M P'M Y
7
For a recent review see Amjad and Kemal, 1997, (mimeo) ILO-SAAT.
22
Real Wages
Wages rates are clearly more relevant to that part of the labour force which is hired, a figure previously
mentioned as not much more than half of the employed labour force. About 56 per cent of the employed
labour force is hired., the rest are self-employed. It is, however, not inconceivable that the poorer sections
of the self-employed in Pakistan (particularly in agriculture) also offer themselves on the labour market as
part-time casual workers. 8
The percentage of hired labour which is permanent relative to those on casual contracts is likely to be
small. Much of this organized labour force is either in salaried government jobs or in the organized private
sector of the economy. A smaller proportion is likely to be in the organized industrial workforce.
Consequently, the dominant form of hired labour in Pakistan, in an economy-wide sense, is casual workers,
some who offer themselves on casual wages throughout the year, others who do casual work only as a parttime activity.
There are three wage rates available for the agricultural sector from the 1980s. One for each season (Rabi
and Kharif), and a general casual wage rate. It can be argued that the dominant type of casual labour used
in agriculture is season-specific and not of a general variety, the latter usually representing the casual
labour available in rural areas. The wage rates for two seasons (Rabi and Kharif) in agriculture show an
increase up to the end of 1980s and then a decline in the 1990s. The general and non-seasonally specific
casual wage rates in agriculture also suggest an increasing trend till the end of 1980s and have then
fluctuated. It is clear that overall real wage rates in agriculture increased in the 1980s and are witnessing
a decline in the 1990s (Figure 2.3a).
Real wages of the organized industrial sector, have increased on trend from the 1970s, although there is
no data available for recent years. As suggested earlier, this is likely to be a small proportion of the total
employed labour force ( not exceeding 10 per cent). The category of skilled workers can be seen in real
wages of masons: an increase in real wages in the 1970s, a decline in the early 1980s and an increase on
trend from the late 1980s onwards (Figure 2.3b).
2.3 a: Real Wage Index- Industrial and Skilled
200
150
100
50
Ind u s t r y
8
1996
1994
1992
1990
1988
1986
1984
1982
1980
1978
1976
1974
0
M asons
An indication of this can be gauged from the distribution of job by the organization. In 1993-94 LFS 9.5 per cent
of the employed were the `formal’ employment, the rest were in semi-formal (22.9 per cent), agriculture (47.8 per cent) and
informal (19.8 per cent) employed. It is also the case that in 1993-94 only 33 per cent of the employed were categorized as
`employees’. If we add the semi-formal and informal employed nearly 43 per cent are likely to be “unorganized” workers. This
is the lower-bound since the bulk of hired workers in agriculture are also likely to be of the casual variety, and therefore a part
of the unorganized labour force.
23
Figure 2.3 b: Real Wage Index - Seasonal Agricultulture
140
120
100
80
60
40
20
Rabi(ag)
1994
1992
1990
1988
1986
1984
1982
1980
1978
1976
1974
0
Kharif(ag)
The real wage index of unskilled labourers is based on data of casual workers in construction. It can be
taken as a proxy for non-agricultural urban casual workers, which are likely to dominate the urban smallscale and informal enterprise sector. This also shows a trend increase in the 1970s, and then a decline till
the mid-1980s, which increases briefly during the late 1980s and then shows a slow decline through the
1990s. The pattern is clearer for real wages of unskilled casual labour an increase in the 1970s and a
decline in the 1990s (Figure 2.3c).
Poverty Trends
Trends in poverty are difficult to estimate in Pakistan because research is often based on different poverty
lines and a number of problems also exist with the types of data often available. There is, however, a need
to view the trends in poverty in Pakistan, both rural and urban, from an employment perspective. 9 Malik
(1988) has estimated poverty lines from 1963-64 to 1984-85 on a consistent methodology based on calorie
norm.10 Figure 2.4 shows that poverty increased in Pakistan during the 1960s (although urban poverty
declined). It began declining during the 1970s and this decline continued up to the late 1980s. After the late
1980s (1987-88) there is every likelihood that poverty increased, at least up to 1990-91, after which it has
either increased or remained the same. The 1990s trend is therefore likely to be one of increase. 11 It is true
that the total poverty trend described above is generally reflected in the trends in rural poverty and not
urban poverty. Urban poverty has shown significant declines when total poverty has increased (1960s and
the 1990s). Urban poverty may have started declining again in the 1990s, while rural poverty is probably
either not declining or is increasing. This is of immediate relevance for our impression of wages for the
early 1990s and is quite consistent with the reversal of past urban-rural labour force growth trends in the
1990s.
9
The reason is that employment conditions in Pakistan are reflected in the poverty levels of a society which is
characterized by multiple contractual arrangements (implicit and explicit) and extended family systems.
10
The consumption limit is that of 2250 calories per day. The methodology is from Mujahid (1973) . The same
methodology is used to estimate the series through to the 1990s. The Figure on poverty trends is based on this series. It is a
consistent series.
11
It is true that if a poverty trend is fitted over the longer term then poverty will appear to be declining on trend.
This however is not legitimate, there seems to be some change coming about in the late 1980s. This argument is sometimes
used in order to imply a correspondence between economic reforms and poverty alleviation and is not legitimate.
24
2.3 c: R eal W a g e Index: A g ricultural/R u ral (C asual) Urban Unskilled(C asual)
150
100
50
0
Agriculture
U nskilled Labour
F ig u r e 2 . 4 : P o v e r t y i n P a k i s t a n : H e a d C o u n t s
Total
Rural
Urban
2 p e r . M o v . A v g . ( R u r a l)
2 p e r . M o v . A v g . ( T o t a l)
2 per. Mov. Avg. (Urban)
60
50
%
40
30
20
1 0
0
Poverty, Wages and Growth
It is also useful to make some qualitative assessments about poverty and wages and growth taken together.
For the 1970s, it is fairly clear that poverty declines in both urban and rural areas were matched by a
universal increase in all types of real wage rates for most of the period. Whereas GDP growth was not so
high, the growth that took place was driven by employment expansion. It very clearly demonstrates the
inverse relation between poverty and real wages.12
In the 1980s, when poverty continued to decline but less fast than it did in the 1970s, we have a mixed
picture of real wages. In this situation we need to make judgements on the weight of activities in the
12
One needs to be careful in qualifying this inverse relation. The relevant real wage is important. The correlation
between real wages ( industrial) which have been increasing over time and poverty which on trend in the longer run is
decreasing can be shown to be reflective of the inverse relation. In fact it is not because industrial wage earners are in a
minority in the employed labour force.
25
economy for which the real wage is a proxy. In our view it is the casual wages in agriculture, especially
the seasonal ones and the urban casual unskilled wage rates which would affect most of those offering
themselves on the labour market. General agricultural/rural wage rates (which reflect the rural non- farm
sector as well) showed an increase until the late 1980s; agricultural (seasonal) wages increased on trend
in this period. The wages of the unskilled urban workers declined and increased again. There was an
increase in skilled workers wages and that of the organized industrial sector. On the whole those real wages
which showed a cyclical trend balanced out, while others increased until the late 1980s. The net effect was
an increase in real wages and reduction in poverty. This period was one of high growth which was
dominantly labour-productivity driven. The inverse relation between real wages and poverty is therefore
maintainable for the 1980s.
The 1990s show a decline in real wages of the agricultural seasonally specific wages and a fluctuating
cyclical trend in general agricultural/rural wages. Unskilled urban casual wages have also declined. Poverty
as we know has probably increased and has certainly not declined in the 1990s. This too confirms the
inverse relation between poverty and real wages. It is, however, also evident that the 1990s (like the 1970s)
are not a high growth period such as the 1980s were. Growth in the 1990s is less driven by employment
expansion than was the case in the 1970s.
In general it may be arguable that in Pakistan, although poverty and real wages are related inversely, as
should be the case in an economy in which hired labour constitutes more than half of the employed, both
high and low GDP growth situations have led to the alleviation of poverty. However, in the low growth
scenario the composition of growth needs to be dominated by employment expansion (as opposed to labour
productivity), in order to reduce poverty and improve employment conditions. This is probably not
happening in Pakistan in the 1990s. We can now return to examining the employment indicators implicit
in the elasticity measure which, as we have seen, had increased from the 1980s to 1990s.
8.
ELASTICITY, EMPLOYMENT, LABOUR
OUTPUT: AN INTEGRATED VIEW
PRODUCTIVITY AND
Quite apart from problems of estimation,13 it is the case that employment elasticities implicitly contain
information that may be useful in assessing the employment situation. The overall association of
productivity growth and employment growth in any given period is implicit in the elasticity measure by
definition. It is, however,m partly determined by technological relationships that obtain within sectors,
which are likely to differ across sectors and which are smoothed out or concealed when represented
(implicitly) in an elasticity measure or aggregated at an economy-wide level.
It can be argued that during the development process a negative relationship between labour productivity
growth and employment growth is to be expected, even a strengthening one. This can be consistent with
both employment and productivity increasing at positive rates. Four interesting cases may be defined.
Case 1:
When employment and productivity growth are both sizably positive, and there is the
likelihood of continuing conditions of healthy economic growth which are not employment
unfriendly.
Case 2:
When very low (or negative) growth rates in both employment and productivity occur, it
may be a sign of a potential sectoral slowdown towards stabilization. This is acceptable,
13
ILO-SAAT/Arshad Zaman Associates, 1997 (mimeo).
26
as long as the sector is unlikely to become a natural refuge sector for labour, in times of
overall deceleration of growth.
Case 3:
When there is negative or very low productivity growth and there is sizeable positive
growth in employment, it may be indicative of stagnation in the sector. This is likely to
be accompanied by increasing surplus labour and underemployment and falling real wage
rates. It is important to note that this may be owing not to an unsatisfactory rate of output
growth in the sector but to the employment expansion taking place within it. This is
characteristic of a classic refuge sector.
Case 4:
When there is positive growth in productivity and a negative or very low growth in
employment, it may be indicative of a fundamental technological shift taking place in the
sector.14
We now discuss productivity and employment growth simultaneously, for the major sectors (Tables A2.5
and A2.6). The following observations can be made from examining the data.
1.
A negative association between productivity growth and employment growth is discernible
(Table A2.6). It was weakest in the 1970s and strongest in the 1980s but the intensity of the
measure in the 1990s is still greater than that of the 1970s. What it does show is that the economy
in the 1990s, as a whole, is less able to absorb labour than was the case in the 1970s, although
the situation has altered somewhat compared to the 1980s. It is, however, very important to note
the increase in intensity of this negative relation for agriculture and construction over the same
periods, particularly as sectors are usually associated with high shares of employment.
2.
In the first period (1970s) productivity increased at a low rate, output growth was reasonable, and
high growth in employment took place. In the 1980s, productivity growth was higher than the
1970s, employment growth lower, and output growth very high. In the 1990s productivity growth
has fallen again, employment growth continues near the 1980s rate, while output growth has also
declined. What has happened is that the lower output growth of 1990s is sustaining an
employment growth at a level which was associated with the higher output growth of the 1980s,
which has meant a decline in productivity growth. Employment elasticities, as we know, were
higher in the 1970s, declined in the 1980s and rose again in the 1990s.
3.
In agriculture, productivity growth was negative in the 1970s, increased in the 1980s and has
shown a decline in the 1990s, employment growth has shown gradual decline over the period but
is still positive. 15 Output growth has followed the pattern of productivity growth: it increased
between the first two decades and then declined slightly in the 1990s. It should be noted that
employment and productivity growth rates have all fallen in agriculture over the 1980s and the
1990s while the rate of output growth of the sector improved from the 1970s to the 1980s and,
even in the 1990s when it declined somewhat, it has not been unsatisfactory.16 So output growth,
14
Depending upon the importance of the sector for overall growth, it is entirely possible that such a shift has positive
employment effects on the rest of the economy, even if employment levels are contracting in the sector itself.
15
The relationship between agricultural productivity and poverty is a negative one, Amjad and Kemal, ILO-SAAT,
1997 ( mimeo).
16
It needs to be explicitly recognized that sustained agricultural output and increasing productivity in are necessary
for the economy not only because it produces the main input (cotton) for manufacturing, which goes in to Pakistan’s major
export industry ( textiles), but because it also provides a large portion of the economy’s wage goods. In order for growth to
27
though slightly falling has been reasonable (around 3.4 per cent) and productivity growth has
declined to a lower rate. Employment growth on the other hand has also fallen, although it is still
positive. This does not explain the new volatility in agricultural employment observed earlier.
Further sector-specific investigation is needed. The situation in the agricultural sector in Pakistan
is similar to Case 2 (low-productivity/low employment-growth) described above.
4.
The construction sector’s productivity growth has consistently fallen from the 1970s to the 1980s
and 1990s, when it became negative. Employment growth in this sector has fallen although it has
remained high and positive throughout. Output growth has fallen consistently over the three
periods. Therefore construction seems to be a sector which is likely to be facing a crisis with
increasing employment and negative productivity. This is similar to Case 3 (a stagnating refuge
sector) described above.
5.
In the manufacturing sector, productivity growth was very low (1.3 per cent) in the 1970s, it
increased to a very high rate in the 1980s (7 per cent) and has declined to a middling (4.6 per cent)
rate in the 1990s. Employment growth has very clearly seen a decline from the 1970s, through the
1980s to the 1990s. During the 1990s it has become negative. Output growth in manufacturing
was around 4.7 in the 1970s, it rose to a very high 8.4 per cent in the 1980s and returned to a
lower level of 4.2 per cent in the 1990s. Clearly, manufacturing is a sector where there is prima
facie evidence on a de-linking of output and employment growth. The case of manufacturing is
similar to Case 4 (technological shifts) described above.
6.
There has been a high growth of employment in the retail and trade sector in the 1990s, as well as
the residually defined “other” sector as was observed in the 1970s. Many activities in these sectors
are likely to be located in the non- manufacturing smaller scale and informal sectors.
If the indicative schema and observations made above are to be accepted, then the agricultural sector is
likely to be moving towards low productivity conditions (although from the productivity perspective it is
not as bad as the 1970s) while manufacturing is likely to be undergoing a fundamental technological shift,
in which its growth process is becoming de-linked, at least from direct employment generation.
Construction is likely to have become a sponge or refuge sector, which is simply absorbing labour at
negative productivity levels. There is an increase in employment growth in the retail and trade sector and
the ‘other’ sectors group in the 1990s which is symptomatic of informal and small-scale enterprise sectors
growth. This expansion seems associated with relatively lower levels of GDP growth (1970s and 1990s).
It has also played an active role in labour absorption in the 1990s, as we have seen earlier.
9.
EMPLOYMENT AND OUTPUT GROWTH LINKAGES
It is fairly obvious that the growth of the manufacturing sector has strong growth multiplier effects on the
rest of the economy (Table A2.7iii), but in looking at employment growth rates for different sectors of the
economy we find an interesting set of relationships between employment growth in manufacturing and
employment growth in the rest of the economy. Examining simple correlations between sectoral
employment growth rates (Table A2.7i), it is clear that growth in manufacturing employment is most
strongly related to economy-wide employment growth and, in particular, has positive and relatively stronger
linkage effects on employment growth in most other (non-agricultural) sectors of the economy. This is an
encouraging finding from the point of view of setting up guidelines for an employment strategy.
proceed smoothly agricultural surpluses are critical.
28
The greater the extent to which growth in manufacturing is employment-based, the greater will be its
employment multiplier effects on the rest of the economy. However, promoting employment friendly growth
does have a potential problem that employment elasticities in manufacturing are low and productivity
growth during the 1990s has been associated with a negative employment growth. Hence, the situation in
manufacturing is that output growth cannot be expected to generate much direct employment. This is an
area which requires special focus in a sector-specific analysis, with special attention paid to the distinctions
between the large and small-scale manufacturing sectors.
10.
THE AGENDA FOR AN EMPLOYMENT STRATEGY
The trends in the labour force and employment in Pakistan suggest that with the already low and declining
participation rates of labour in the economy, labour force growth is itself declining. In this situation,
unemployment persists and underemployment is increasing. The indicators of employment conditions, i.e.
real wages and poverty, reflect this worsening in the 1990s. In our view, there are also good reasons to
expect an increase in labour force growth in the near future. This swelling in the labour force growth is also
likely to change the composition of the labour force to a more literate one. In short, the current employment
problems facing the economy are likely to magnify in the near future. The major challenge is to attack the
problems of unemployment and underemployment and to increase aggregate employment significantly as
well.
Apart from controlling population growth, which is an important part of an employment strategy, we need
to look closely at the changing features of employment as a whole and in particular sectors of the economy.
These issues stand out:
1.
An important matter that has emerged concerns growth itself. It is clear from the periodization of
Pakistan’s history that although high growth periods, lead by increases in labour productivity, can
be accompanied by improving wage rates and declining poverty, a low growth period, if it is to
improve wage rates and decrease poverty, cannot be based excessively on labour productivity.
2.
There is a certain volatility to employment patterns observable in recent years at the economy-wide
level. This may reflect widespread shifts in contractual arrangements and is an essential issue to
explore.
3.
The role of agriculture in future employment absorption needs to be very seriously examined. Until
now it has only performed reasonably in terms of growth but appears to have been involved in the
swings in employment absorption in recent years. Rural-urban labour force growth rates may also
be reversing, and this requires special consideration from the point of view of agriculture. Since
poverty is inversely related to productivity in agriculture, a swelling of the labour force in rural
areas, if there is insufficient absorptive capacity in the rural non-farm sector, could put pressure
on the already low and slowly increasing productivity growth rates.
4.
There is a growth and employment linkage between the economy as a whole and the manufacturing
sector.
5.
Manufacturing is not only critical for output growth but its role in employment-generation needs
to be explored. It has clearly faced a crisis of sorts in recent years, but it should be noted that its
output growth, though much lower than the 1980s, has not been all that low in the 1990s,
exclusing the past two years. Manufacturing is critical for growth and growth is crucial for
productive employment. However, the crisis is in employment within manufacturing. For an
employment strategy, both a ‘revival of output growth’ of manufacturing as a whole and the
29
location of its employment crisis need to be assessed. The manner in which employment linkages
are affected between manufacturing and other sectors is also important to assess. In short, the
revival of growth and the nature of low employment elasticities must be the critical focus of an
employment review of manufacturing.
6.
There is a need to examine the growth of the small-scale enterprise sector and its employment
absorption which not only covers manufacturing but other labour intensive-sectors of the economy.
The necessary focus is on the nature of growth and the potential in it for employment-generation.
Taking into account the caution required for greater employment absorption in agriculture and the
apparent limits to employment growth in manufacturing, it is clear that those sectors of the
economy covered by the SSE sector become critical from the perspective of an employment
strategy.
30
CHAPTER THREE
The Agricultural Sector
1.
INTRODUCTION
Agriculture in Pakistan has had reasonable output growth in the past.1 At the aggregate level, its growth
was showing signs of decline from the 1980s to the 1990s.2 On the other hand, employment growth in the
sector continued to be positive though it also declined on trend in the 1990s. The sector could be moving
towards a situation where it may be forced to absorb large sections of the labour force, possibly
unemployable in other sectors that face a slow-down in output growth. This possibility is also reflected
in labour absorption in the sector, which showed that it was the main sector ‘adjusting’ to employment
fluctuations in the economy. Part of the reason for this is external to the sector. When the overall economy
faces a slowdown, its largest employer (even if its sectoral employment share is declining over the longer
run) is likely to experience a swelling in its labour force relative to the output it produces. In the present
chapter, we explore these external causes of change as well as what may have happened to the structure
of output and employment within the agricultural sector.
2.
THE SPECIAL NATURE OF EMPLOYMENT AND OUTPUT IN AGRICULTURE
Some points need to be noted about employment and output that are specific to agriculture and necessary
for interpreting the trends in Pakistan.
Measurement of employment
Employment in agriculture is family-based and also uses hired labour both on a casual/part-time and well
as a permanent basis. In other words, employment in agriculture is non-homogenous3 and does not directly
depend on the labour market for all its supply of labour. Seasonal demand for agricultural labour means
that those employed, can be expected to be “underemployed” at least some of the time. The notion of fulltime work; the role of the labour market in the supply of labour and the aggregation of different types of
workers into the employed category are less straightforward in the agricultural sector.
The special nature of output
The determinants of agriculture output are also different from those of output in other sectors. In
agriculture, output is partly dependent on external uncertainty, this means that weather is an important
determinant of output, especially at low levels of output. Therefore, whenever there are conditions of an
immanent collapse of output, labour which has already been employed, appears less productive
1
Although it has expectedly been lower than overall rates of growth.
2
See Chapter1 Annex Table A1.5.
3
The assumption that is implicitly made is on the duration of work-time and effort associated with a unit of labour.
The quantitative difference between family labour and hired permanent labour which are both full-time is that the former
requires supervision while the latter does not. Therefore aggregating the two may not be strictly appropriate. But there is an
even more fundamental and qualitative difference between a ‘unit’ of family labour and permanent labour on the one hand,
and casual labour on the other. No assumptions on comparability can be made on time and effort between these two units,
yet employment figures do a headcount of all labour. Non-homogeneity in agricultural labour can lead to a fallacy of
aggregation.
31
(productivity declines). Agricultural output collapses are less often failures of demand and are more supplyside determined. Clearly then the measure of labour productivity in such a situation is not so much a proxy
of the contribution of labour assuming employment is counted properly) to production but reflects the overdetermining influence of other external causes that influence output.
Thus, we need to be cautious in using ‘employment’ and ‘output’ categories in themselves or in standard
measurements, when analyzing the agricultural sector. We now select two features of this discussion,
external uncertainty with output and casual labour use in employment, to posit a combined effect which
may be of special relevance in Pakistan.
A combined effect
The degree of external risk in agriculture is also sensitive to the technological features of the production
process. The HYV technical input package, in use in Pakistan, which is based on robust varieties of seeds,
also requires the use of complementary inputs,4 the application of which is subject to serious time
constraints.5 It can be argued that the widespread use of the package, though growth- enhancing on
average could also increase the sensitivity of the production process to this external uncertainty. If this
is the case then it should be reflected not only in an increasing level of output on average but also in relative
output instability post-adoption.
One response to increased external risk (due to the profitable technological package and uncertainty), is
that land-owning employers move towards flexible arrangements with labour, to reduce a part of their
wage-cost risk due to the vagaries of weather. The use of casual labour,6 particularly during labour
demand peaks, can generate this flexibility.
It also means that the greater the proportion of casual labour in the agricultural labour force, the more
closely the employment growth trend in agriculture is likely to follow the output growth trend, because it
is precisely the casual labour component of the labour force that becomes its variable part.
This would also imply that in conditions of economy-wide low growth, levels of surplus labour in the
agrarian economy will be high and underemployment and poverty due to the changes in the composition
of the labour force and its casualisation will become increasingly visible.
4
The application of complementary inputs (seeds, fertilizers, pesticides, irrigation, labour) may also be costly as
everyone does not have equal access to the capital market.
5
6
See e.g. Sen (1980).
There are other reasons for the increased use of casual labour: (a) the profitability considerations of land owners
in a situation where potentially higher yields prevail; and (b) their need to expand production on wage labour and reduce share
tenancy (in which output sharing parameters are considered to be norm-determined and inflexible). The problems with
permanent labour are supervision costs and underemployment due to seasonality. This suggests casual labour use as a solution.
Increasing landlessness also tends to provide a pool for such labour.
32
3.
OUTPUT AND EMPLOYMENT GROWTH RATES IN PAKISTAN’S AGRICULTURE
The growth of output in agriculture has been positive and increasing (tables A3.1 and A3.2, A3.3) in
Pakistan. The sector has by and large under-performed GDP growth but its growth rate is reasonable.
Figure 3.1 shows that the pattern of output and employment growth has been fluctuating much more since
the mid-1980s. Although it is quite true that output growth was much more stable in the 1970s, which
meant stable employment growth and stable elasticities, it is likely that the fluctuations apparent from the
mid-1980s have contributing factors other than external uncertainty.
Figure 3.1: Agriculture
Grow th of Real Value-Added & Employm e n t ,
and the Output-Elasticity of Employment
1 5 .0
5.0
4.0
1 0 .0
2.0
5 .0
1.0
-
0.0
Elasticity
Growth Rate (%)
3.0
-1.0
- 5 .0
Fis c a l Y e a r En d i n g J u n e 3 0
-2.0
-10.0
-3.0
V alue added
Employment
Elasticity
These patterns may have something to do with the changing nature of both output and employment. For
output, the country-wide use of the HYV technological package by the 1980s (tables A3.3a and 3.3b)
meant that its sensitivity to the timing of inputs, as well as external weather conditions with respect to that
timing, became more accentuated. This may explain the increasing amplitude of movements in output
growth over the years as shown in Figure 3.1.7
Because family labour and permanent labour are a constant part of the employed labour force in
agriculture, the changes that may result from output booms and slumps are likely to be due to changes in
the employment of the casual labour force. We therefore need to examine changes in the composition of
the labour force (table A3.4). According to Agricultural Census data agricultural “employment” witnessed
a 0.62 per cent annual growth in the 1980s. This excludes casual labour use, which is known to have
increased phenomenally in the same period (see table A3.5)8. Permanent hired labour use has altered but
7
Agricultural output growth was been 2.1 per cent for the 1970s; 3.9 per cent for 1980s and 3.3 per cent for the
1990s (See Chapter Two, A3, table A3).
8
Labour force survey figures are therefore more appropriate for capturing total employment growth rates The data
on casual labour use in agriculture are available on the incidence of farms using casual labour in the Agricultural Census. This
show s 60 per cent and 48 per cent increases in casual labour over the decade of the 1970s and the 1980s respectively.
33
the weight of permanent hired labour in the census figures of permanent agricultural employment is not
large enough to warrant comment (2.7 per cent).
4.
AGRICULTURAL EMPLOYMENT AND TOTAL EMPLOYMENT
Throughout the 1970s the rate of growth of economy-wide employment has been, on a trend, higher than
that of agricultural employment. The LFS figures are, as suggested earlier, likely to capture employment
in agriculture data, which includes casual labour (table A3.5) and are therefore preferable, at least in terms
of coverage, to the Agricultural Census (AC) figures. Both figures for the 1980s (AC and LFS) are,
however, lower than the overall growth rate of employment. Since the mid-1980s (which is also the peak
period of growth after which a gradual decline sets in), there is no longer a discernible pattern; agricultural
employment growth has been higher as well as lower from the overall rate of employment growth (table
A3.2). There is also a changing pattern of rural-urban migration, with rural Pakistan increasingly retaining
more of the labour force (table A3.6).9 It is worth noting that for the second half of the 1980s decade,10
there is a greater increase in growth of ‘agricultural employment’ than is the case in the first half
(table A3.4).11 Consequently, there are signs of a swelling in the size of the agricultural labour force.
5.
DECOMPOSING THE SOURCES OF OUTPUT GROWTH
In the 1970s output growth was not too high (2.0 per cent) but it was positive and so was employment
(2.1 per cent). This trend altered in the 1980s, when output growth on average was higher (3.9 per cent),
and employment growth remained a little lower (1.9 per cent) but switched to an increased use of casual
labour. In the 1990s output growth continues at a slightly lower rate (3.3 per cent) and employment growth
is also low (1.6 per cent) but both output and employment growth patterns are more volatile (table A3.2).
We now come to the decomposition of growth exercise, which looks at the contribution of labour
productivity and employment expansion to output growth, bearing in mind the qualifications made earlier
regarding output, employment and productivity in agriculture. Basically, employment expansion-based
growth dominated in the 1970s, shifting to productivity-dominated growth in the 1980s, and shifting back
to employment expansion based growth in the 1990s, though it is now ‘shared’ with labour productivity.
In the 1970s, a more stable period of lower output growth, the employment expansion effect dominated
the productivity effect for several reasons . The nineteen seventies were a period when the green revolution,
although significant, had not spread nationwide (table A3.7a). The popular belief that effective land reform
may come about in Pakistan encouraged landed agriculturists with significant holdings to stay in sector.
This was also reflected in a spate of land resumptions, a decline in absenteeism and the expansion of
9
Growth rates of the labour force have been positive and declining since 1989-90.The percentage drop in the rural
labour force growth rate from 1989-90 to 1994-95 was -10.1 per cent ; the drop in the urban labour force growth rate for the
period was -39.9 per cent; and the overall drop in the growth rate of the labour force as a whole was -20.2 per cent.
10
Note this period corresponds to what is the slump in employment of the small-scale enterprises (SSE) sector of
which rural employment is very significant.
11
We have already observed the phenomenon of relative decline in the rural urban labour force growth rates in the
chapter on labour force.
34
cultivable land cultivation. Also, growth in other sectors is this period was low. A combination of these
conditions may explain the dominance of the employment effect.12
Table 1:
Decomposing output growth , productivity and employment effects -agriculture
Year
Productivity Effect
Employment Effect
Multiple Effect
1969/70 - 1980/81
0.063
0.918
0.018
1980/81 - 1991/92
0.664
0.236
0.100
1991/92 - 1994/95
0.361
0.623
0.040
The 1980s story is slightly different. Labour productivity dominated contributions to output growth (which
was also higher than in the 1970s). Reasons include the less costly expansion of land frontier (already done
in the 1970s); the widespread use of a HYV input package (Table A3.7 a and A3.7 b), and greater
tractorisation in parts of the country other than the Punjab, where the green revolution had become
widespread earlier. The possibility of land reform had also receded from the agenda of the then military
regime. But equally significantly, the decline in the employment contribution to growth in the 1980s may
be due to higher growth in other sectors of the economy. Sectors that were drawing productive labour out
of agriculture particularly manufacturing. It is worth noting that SSE manufacturing, which has a large
rural component, was witnessing employment and output growth at least up to the mid-1980s.
The 1990s reverted to an employment expansion based effect (at levels of agricultural output growth
similar to the 1980s but more volatile on an annual basis) and may reflect a deceleration of growth in other
sectors, particularly manufacturing. There is nonetheless a significant contribution of labour productivity
in this period as well.
Employment expansion in the presence of as large a casual labour force as exists in Pakistan in the 1990s
says little about the quantum of labour used or its returns. It is worth recalling that the composition of the
agricultural labour force has changed in the 1990s compared with the 1980s, and volatility of output in
the sector is reflected more in employment growth than previously it is also likely to have generated a
precariousness in the livelihoods of those now employed as ‘casual labour’ in the agricultural sector.
6.
UNEMPLOYMENT AND UNDEREMPLOYMENT
Agricultural employment is a dominant part of rural employment. Trends of unemployment and
underemployment in the rural areas reflect labour market conditions in the agricultural sector. However,
unemployment, in a developing country context, in particular in agriculture, is not a good indicator of
labour market conditions. In the absence of social welfare and insurance, the unemployed are generally
available for work in any sector, and often do work to survive. Underemployment is therefore a better
indicator of conditions in the labour market. The trends in unemployment and underemployment are
examined below.
12
See Mahmood (1993), Hussain (1980), Majid (1995).
35
The data (table A3.8) show that unemployment increased on trend in the 1980s, from 1979-80 to 198788. It is not legitimate to observe trends on unemployment without qualification across the year 1990-91
when LFS data is used, as in this year definitional changes took place which particularly affected the
unemployed. The data show that unemployment was increasing on trend in rural Pakistan during the 1980s
and was showing a trend decline in the 1990s.13
The case for rural underemployment is also mixed. It shows a decline from early to mid-1980s and an
increasing trend through the second half of the 1980s and the 1990s.14 What is clear is that the rural
underemployment rate is high in Pakistan.
By 1993-94 about 20 per cent of the rural labour force was either not working or only partially working
in rural areas, consistent with a fluctuating pattern of growth in output and employment, which as we
argued is increasingly based on the use of casual labour.15 An agricultural sector with low levels of
productivity, coexisting with other sectors with limited employment absorption capacities, is likely to have
a large reserve army of the underemployed with a high degree of underemployment.
If non-farm employment growth (which is the rural part of the SSE sector) had started slowing down since
mid-1980s, then it can be assumed that the bulk of labour absorption in the 1990s would be in the
agricultural sector, possibly as underemployment and casual labour.16
7.
LABOUR DEMAND
It has been suggested above that, owing to the non-homogenous nature of the employed, increasing levels
of employment (numbers of employed) may not translate into increasing use of labour (amount of labour).
Consequently we need to look at the requirements of labour and the many factors which affect them. In the
short-run they are best reflected in estimations based on cropping patterns.
Cropping patterns and profitability
Driven by profitability considerations, there has been an increase in the cultivation of crops with a higher
labour input in Pakistan. This is clearly a trend across the 1980s and 1990s (table A3.9 ). These changes
in cropping patterns which require more labour are also consistent with trends in rates of profits of
individual crops (table A3.10 ).
There are two ways to respond to increases in labour requirements. One is by actually increasing labour
inputs to meet those requirements. The other is by capital-labour substitutions which may reduce those
13
Between 1990-91 and 1991-92 there is continuity, a drop in 1993-94 , continuity in 1993-94 and then an increase
again to 1994-95. The general trend across the 1980s and 1990s may be of an increase, it is unlikely to be of a decline.
14
It is arguable that underemployment in the 1980s was lower than what it was in the 1990s, which fits in with
the picture of economy-wide high growth 1980s, continuing rural-urban migration and increases in the SSE manufacturing
sectors employment in the first half of the decade and a possible decline in the second.
15
A given level of underemployed in the labour force is likely to understate the degree of underemployment more,
the greater the proportion of casual labour in the labour force.
16
Although the share of rural non-farm employment in rural areas on trend has increased since the 1980s
(table A3.11), agriculture was around 62 per cent of rural employment and has shown a fluctuating pattern of employment
shares from 1991-92 to 1993-94.
36
requirements. Increasing labour inputs can be done by hiring additional labour or by increasing the use of
existing labour (either family or hired or both).
Size and productivity: Increasing family labour use
Changes in average sizes of farms may have automatically led to the internalization of some of these
increased labour requirements due to changing cropping patterns. The changes in farm size over the
intercensal period have increased the incidence of small farms in Pakistan. It can be argued from research
on the farm size–productivity relationship in Pakistan, that an inverse relation between farm size and labour
input exists (table A3.12 ).17 So the fall in farm size due to the sub-division of holdings18 over time would
increase the potential availability of labour inputs, especially family labour inputs.
It is also the case that small farms have higher total productivities and greater cropping intensities than
larger ones, whereas they may have lower individual-crop yields than large farms ( Mahmood, 1997b,
mimeo).
This means that small farms maximize returns through their choice of cropping patterns and greater use
of labour. This response to the increasing requirements of labour is one that automatically comes about
when productivity led cropping pattern changes made possible by the new technology take place over time.
Large farms still have to contend with the hiring-in of extra labour, much of which is likely to be of a
casual variety.
Mechanization: Reducing labour requirements
The second way to respond to increasing labour requirements is mechanization 19. Some economy- wide
evidence exists here as well. Farm area exclusively using bullock power has declined over the 1980s. On
the other hand, farm area using a mix of bullocks and tractors as well as tractors exclusively has increased.
It is clear that the effect of tractor use is the displacement of labour (table A3.13).
Tenurial shifts: Creating an available labour pool
Changes in land tenure which have taken place in Pakistan in the last two decades (a decline in tenancy)
may or may not have increased productivity. Evidence is mixed and depends on the existence of
disincentives in tenancy compared with owner-farming as well as on who is resuming the tenanted land.
It is likely that over time disincentives in tenancy have become marginal and insignificant, at least in the
Sindh province in Pakistan where the bulk of tenancy exists (Majid, 1994). Reduction in tenancy releases
labour into the labour market as landless labour, which needs to get absorbed. Tenancy has also clearly
declined in Pakistan (table A3.14).
8.
WAGES AND POVERTY
17
The relationship is slightly exaggerated because of the casual-worker factor, as larger farms are likely to use
casual labour which does not figure in the calculations. In general the relationship is supposed to be the most robust for the
relation between size and of productive factors.
18
Or due to the resumption of land from owner-cum-tenants.
19
There are limits to activities within agriculture which can feasibly be mechanized. Mechanization is especially
difficult for peak period labour activities, which is where the demand of labour is concentrated.
37
Results from a recent study (Gazdar, Howe and Zaidi, World Bank, 1994) shows that in rural areas,
households headed by tenants and agricultural labourers have a very high incidence of poverty
(table A3.15).20 These workers are at the bottom end of the range of human capital and physical assets
categories. This suggests that casual workers constitute one of the poorest sections of the agricultural
labour force and, given that tenancy has declined and casual labour increased, these workers are likely to
be a growing section of the rural poor.
We have already discussed wage and poverty trends in Chapter Two, but a restatement is in order in the
agricultural context. Nominal wage data are available on seasonal agricultural casual workers
(table A3.16). Although real wages of agricultural workers improved up to the mid- 1980s, during the
1990s they have probably declined. The wage data again corroborates our expectations about the
continuing slow-down of the rural non-farm employment growth since the late-1980s and the swelling of
the casual labour force in agriculture. The assumption here is on the nature of the labour market and its
extent of isolation. In our view the agricultural casual labour market does function in rural Pakistan; in
an overall sense the wage rates are a signal of supply and demand conditions and there is some evidence
to support this view. 21 Recent poverty studies in Pakistan also tend to show a decline in rural poverty from
1969-70 up to 1987-88. There is an increase in rural poverty after 1987-88 up to 1990-91, according to
one study (Malik, 1996) and a slight decline according to another (Gazdar et. al., 1994), owing to
differences in assumptions made to calculate poverty lines (Kemal and Amjad, 1997). However, it can be
claimed with some degree of certainty that the declining trend in rural poverty either reversed or witnessed
a severe slowdown in 1987-88 to 1990-91, the latest data period available. In our view the increase in
rural poverty seems to be a more plausible result.
9.
UPSHOT
Agricultural output growth rates were reasonable in the 1980s and 1990s. Employment growth and
productivity growth have declined commensurately, leaving a more or less constant elasticity of
employment (.48). However, the low employment–low productivity growth situation is sensitive to growth
conditions in the rest of the economy and the sector needs to be protected on this count. An overview of the
employment situation in agriculture suggests that over the 1970s, 1980s and 1990s, profitability-driven
cropping pattern changes based on the new technological package may have increased labour requirements
in the sector. The changing distribution of operated holdings, mechanization and tenurial shifts may have
partially adapted to, as well as reduced, these increases. The rest of the adjustment has had to be borne
by the new hired casual labour force, the size of which is increasing. The nature of this labour force is
reflected in the extent of rural underemployment, wage rates and poverty. While underemployment is
sizable (around 20 per cent including the unemployed) it has shown signs of an increasing trend since the
late 1980s. The returns to casual labour suggest that both the levels of real wages and the size of the nonpoor in the rural economy of Pakistan have either stagnated or declined in the last period for which
information exists (1987-88 to 1990-91 for poverty and up to 1994-95 for wages).
20
21
As do non-agricultural casual workers and self-employed workers with assets less than Rs 1000.
There is a negative relationship over time between the average ( seasonal average) real agricultural wage rates
and the rural participation rate (-.69), which suggests that, imperfect as it may be, the casual labour market does operate, in
some basic sense as a conventional market. This is of course not a good thing in itself. Normally labour markets where wage
also performs a signaling function are downwardly rigid at levels reasonably above the poverty line. This may not be the case
for the agricultural casual labour market.
38
These changes have been accompanied by what can be seen as structural change in the agricultural sector.
This change is manifest both at the level of the production and labour process on the one hand and the
supply of agricultural labour on the other. Both these changes are noteworthy from a policy point of view.
First, on the production and the labour process. What is significant about the growth of output and
employment in the agricultural sector in Pakistan, is not so much their rates of growth, but the changing
composition of the labour force on the one hand and the increased variability in the pattern of its
production over time, on the other. There is much greater volatility in agricultural output since the mid1980s, connected to the widespread assimilation of technical changes in the rural economy and now
embedded in the production process. This translates into a fluctuating trend in the employed labour force,
with the increasing casual labour component on the receiving end of the adjustments to this volatility in
output.
The second matter concerns the expanding and impoverished pool of labour reserve from which this casual
labour springs. Landlessness and near-landlessness as a consequence of declining tenancy and the
subdivision of holdings is one element in this. The other may be a return labour flow into the agricultural
sector because of low growth in other sectors of the economy, especially the rural SSE sector. These
tendencies are likely to exacerbate the size of the labour reserve in rural areas, which then has to ‘forcibly’
get ‘absorbed’ in agriculture as a last resort.
An effective policy focus to promote future growth and employment in the agricultural sector needs to have
a dual aim: the dampening of the relationship between the volatility of output and the livelihoods of the
workforce; and making the livelihoods of casual labour within this workforce more sustainable.
39
CHAPTER FOUR
The Manufacturing Sector
1.
INTRODUCTION
In Chapter Two, we concluded that at an aggregate level an employment strategy in Pakistan has to have
the manufacturing sector as a critical focus. The argument was based on two observations. First, that given
the problems with the elasticity measure, at least a simultaneous examination of employment and labour
productivity growth was needed. Second, that cross-sectoral employment linkages also seemed to be
important. It was consequently argued that despite the fact that there was limited room within the
manufacturing sector to generate employment directly, if manufacturing growth could be employmentbased, it would have positive employment effects on the rest of the economy.
Within manufacturing, a distinction can be made between “small-” vs. “large-scale” manufacturing.1 This
section looks at manufacturing as a whole and then focuses on large-scale sector. In a separate chapter
(Chapter Five) devoted to the Small-Scale Enterprise Sector (SSE), we look at small-scale manufacturing.
2.
ELASTICITY, EMPLOYMENT AND OUTPUT GROWTH
Figure 4.1 gives a visual plot of employment elasticity, as well as employment and output growth rates,
in the manufacturing sector over the years in Pakistan. Plotting growth rates of employment and output is
useful for an overview and we can start with the same point we made at the economy-wide level about the
limitations of elasticity measures taken on their own. A stable and very low elasticity has accompanied
fairly diverse output and employment growth patterns in manufacturing over the years in Pakistan. What
can be claimed with some degree of confidence is that elasticity of employment is low2 in manufacturing,
and this at least seems to be a structural feature of the sector. The latest period of the 1990s in Pakistan
is showing a decline in both output and employment growth and this is a seriously worrying matter for the
sector3. The reason for this low elasticity of employment in Pakistan’s manufacturing sector is therefore
a critical policy question.
1
For statistical purposes, manufacturing and mining are added together in Pakistan. Large-scale industries (defined
as consisting of registered factories employing more than five persons) are equivalent by definition to industries covered by
the census of manufacturing industries. The census covers all factories registered under section 2(j) and 5(l) of the Factories
Act 1934, as amended from time to time. Effectively, until 1967 this meant a coverage of all registered factories which
employed ten or more persons, and since October 1972, five or more persons.
2
Estimates depend on the estimation method and time frame. We have already shown that employment elasticities
in manufacturing have been declining on trend.
3
It is because of the rates of these relative declines in employment and output growth in very recent years of the
1990s that elasticity seems to be increasing now.
40
15.0
15.0
10.0
10.0
5 .0
5.0
-
0.0
-5.0
-5.0
-10.0
-10.0
-15.0
-15.0
V alue added
3.
Elasticity
Growth Rate (%)
Figure 4. 1
Grow th of Real Value-Added & Employment,
and the Output-Elasticity of Employment:Manufacturing &Mining
Employment
Elasticity
DECOMPOSING OUTPUT GROWTH IN THE MANUFACTURING SECTOR
Having observed the trend of output and employment growth, we will now conduct a ‘decomposition of
growth’ exercise for the manufacturing sector.4 We will first examine how the contributions of labour
productivity and employment relate to output growth, and second, whether any trend can be observed in
these contributions.
In the first period of the 1970s, although growth itself was uneven (higher in the first half, lower in
the second) it was roughly equally divided between productivity and employment. The next period
of 1980-81 to 1991-92, the period of consistent high output growth, was based dominantly on the
productivity effect (about 81 per cent) while the contribution of employment to growth was low
(8 per cent). Clearly, a shift was already taking place in this period of high growth of the
manufacturing economy. The last period of the 1990s is one of low and declining growth, especially
in the recent years, and the contribution of employment to output growth has been negative. The entire
growth process now seems to be based on labour productivity.5 This trend makes the task of boosting
and restructuring the industrial sector, from an employment perspective, somewhat difficult. We need
to bear in mind the cross-sectoral employment linkage caveat made in the Chapter Two, to emphasize
the role of manufacturing.
4
Although such a decomposition is very useful for the periodization of employment growth in a sector in an
economy and does not make restrictive assumptions on the nature of production functions, it does stop short of deconstructing
labour productivity itself.
5
We examine the sources of labour productivity increases later.
41
Table 4.1:
Decomposing output growth: productivity and
employment effects – manufacturing
Year
Productivity Effect
Employment Effect
Multiple Effect
1969/70 – 1980/81
0.460
0.419
0.120
1980/81 – 1991/92
0.816
0.089
0.094
1991/92 – 1994/95
1.868
-0.680
-0.188
4.
OUTPUT AND EMPLOYMENT IN THE MANUFACTURING SECTOR
A low elasticity of employment has been observed in the manufacturing sector in Pakistan. Progressively
over the last two decades growth in manufacturing has become more labour-productivity driven (than
employment-expansion driven) and in the 1990s it seems to have been de-linked from employment
expansion altogether. This picture is quite consistent with the low and declining elasticities of employment
already observed. The sources of this growth need to be further explored.
While the share of manufacturing in GDP has increased from 15.1 per cent to 18.2 per cent, its share in
employment declined from 13.54 per cent to 10.12 per cent. The rate of growth of value added in the
manufacturing sector as a whole has been declining on a trend in Pakistan, over the Plan periods since
1982-83. This is true for manufacturing as a whole as well for large-scale manufacturing. In particular,
large-scale manufacturing has experienced a serious slowdown from 1994 onwards and growth was
negative in 1996-97. The 1980s were the high growth period of the manufacturing sector in Pakistan.
There has been a clear decline, on trend, in the growth of output ever since6.
Table 4.2: Growth rates of manufacturing output over the sixth, seventh and eighth plan periods
Period
1982-83 to 1987-88
1987-88 to 1992-93
1992-93 to 1996-97
1992-93
1993-94
1994-95
1995-96
1996-97
Total
8.2
5.9
3.8
5.4
5.5
3.6
4.4
1.8
Large-scale
8.1
4.9
1.7
4.1
4.3
1.5
2.2
-1.4
Source: Based on Economic Survey (1996-97 and previous issues).
6
Data produced in the Pakistan Economic Surveys show consistently higher total growth rates than growth rates
of the large-scale sector, the implication being that small-scale sector growth in manufacturing is very high. We will return
to this important matter in another section. But this qualification has a bearing on the official figures for manufacturing taken
as a whole.
42
Manufacturing comprises both the small-scale and large-scale sectors in Pakistan. The small-scale sector
dominates employment in it, while the large-scale sector dominates output. Table 4.3 shows that although
output growth has taken place in the manufacturing sector in both its small and large-scale sections,
employment began to decline in the small-scale sector in the mid-1980s. There seems to be some constraint
that the small-scale sector begins to face at this time. In other words, the de-linking of employment from
growth which was taking place in the manufacturing sector in the 1980s, may have been due to the
overwhelming weight of the declining employment in the small-scale manufacturing sector and not
because of the large-scale sector as such. The picture after 1990-91 is constructed on the basis of
National Income Accounts (NIA) and the labour force surveys (LFS), and there is not much that can be
said about the large-scale and small-scale manufacturing sector separately here, except that overall growth
of the sector has fallen further, and there has been a negative employment growth. It would seem that at
least the same trend with respect to the small-scale sector employment can be assumed.
Table 4.3:
Output and employment in manufacturing
Output
Period
Total
Large
Scale
Small
Scale
Employment
(Mill. nos.)
Share of
manufacturing
sector in total
employment
Employment in
Largescale
manufac.
Smallscale
manufac.
Growth
rate of
total
employment
1982/83
45.60
33.80
11.70
3.50
13.54
0.465
3.04
0.30
1983/84
49.20
36.50
12.70
3.61
13.69
0.476
3.13
3.10
1984/85
53.20
39.40
13.80
3.73
13.84
0.493
3.24
3.30
1985/86
57.20
42.20
15.00
3.62
13.40
0.507
3.11
2.30
1986/87
61.50
45.30
16.20
4.08
14.23
0.532
3.55
12.70
1987/88
67.60
50.00
17.60
3.72
12.84
0.515
3.21
-8.20
1988/89
70.30
51.20
19.10
3.84
12.84
-
-
3.20
1989/90
74.30
53.70
20.70
3.96
12.84
-
-
3.10
1990/91
79.00
56.60
22.40
3.70
12.38
0.623
3.08
1991/92
85.30
61.00
24.30
3.88
12.53
-
-
4.90
1992/93
89.90
63.60
26.30
3.53
11.00
-
-
-10.00
1993/94
94.70
66.20
28.50
3.34
10.12
-
-
-4.20
1994/95
98.20
67.30
30.90
3.49
10.50
-
-
3.30
Sources:
-6.60
Economic Survey, 1996-97; Labour Force Surveys; Censuses of Manufacturing Industries;
Censuses of Small-scale and Household Establishments.
43
5.
THE LARGE-SCALE SECTOR: MAIN FEATURES
Large-scale manufacturing in Pakistan is dominated by the so-called “Big Four” industries – sugar, textiles
(cotton yarn and cloth), cement, and fertilizers while accounting for only 6.9 per cent of the units in the
sector in 1991, consisted of 37.6 per cent of net output, 40.2 per cent of exports, 35.0 per cent of
employment and 43.2 per cent of the capital stock employed in large-scale manufacturing.7 Unlike its
contribution to output and exports, the large-scale sector’s contribution to employment has been moderate,
even in periods of rapid growth. On the whole, manufacturing industries in Pakistan, have failed to create
sufficient employment: employment levels were almost the same in 1994-95 as they were in1982-83.
During 1980-95, when total employment grew by 2.3 per cent per year, employment in large-scale
manufacturing increased at only 1.8 per cent per year.8 Over the same period (1980-95), large-scale
industry absorbed only 1.4 percent of the additional employment in the economy.9 Slow job creation in
large-scale manufacturing was accompanied by a substantial rise in capital intensity and labour
productivity in the period 10, as assets employed per worker increased from Rs. 50,000 in 1980-81 to Rs.
192,000 in 1990-91. As a result, the labour content in output and the share of wages in value added
dropped in most industries (table A4.3). It is therefore quite clear that labour productivity as well as
capital intensity have risen on trend in the large-scale manufacturing sector in Pakistan (table A4.6).
It has also been suggested above that, despite the slowdown of overall growth, employment and output
growth have not moved in opposite directions in the large-scale sector until very recently, whereas they
showed signs of this in the small-scale sector as early as the mid-1980s. The share of large-scale
manufacturing employment has been around 17 per cent of manufacturing employment in 1990-91, while
its output share was around 70 per cent in the same year.
From an employment point of view the separation of large from small-scale as well as the distinctness of
the high-growth 1980s and low-growth 1990s are important facts. The centrepiece of an employment
strategy within manufacturing is the small-scale sector, which is larger in weight and has been facing
problems since the mid-1980s, In contrast the primary focus of the revival of growth is relevant to the
large-scale sector where the bulk of manufacturing output is produced and where employment is still
growing, albeit slowly. It is this sector’s growth which is likely to have positive linkages with other sectors,
including activities in the manufacturing as well as non-manufacturing small-scale sector. Since we are
discussing the large-scale sector in the present section, this difference must be kept in mind.
7
Of the four, textiles account for the major share of output, employment and exports.
8
As a result, the sector has always accounted for less than 2.5 per cent of total employment (in 1990-91, 2.1 per
cent), although its share has varied between 6-8 per cent of urban employment, and between 3-6 per cent of non-agricultural
employment.
9
During the 1984-90 sub-period however employment in large-scale manufacturing grew by 3.9 per cent per year,
with textiles and food processing accounting for 48.8 per cent and 15.5 per cent of the growth respectively.
10
The increase in labour productivity in the 1980s was spread unevenly across sectors. The largest gains were in
petroleum refining, while textiles, paper and board, and drugs and pharmaceuticals also registered significant gains. Capital
intensity measures can be seen in table A4.2.
44
6.
AN EXAMINATION OF PRODUCTIVITY IN THE LARGE-SCALE
MANUFACTURING SECTOR
Apart from describing some specific features of the manufacturing sector in Pakistan, the discussion above
highlighted that the growth process in the large-scale manufacturing sector is characterized by a low
employment elasticity and that if it is decomposed over time, labour productivity dominate employment
expansion as the source of growth. We also saw that both labour productivity and capital intensity have
increased in the large-scale manufacturing sector.
We now attempt to examine the determinants of labour productivity as well as employment over time in
a more systematic way. There are two basic sources of increases in labour productivity. First, there can
be an autonomous increase, arising from better management, skill upgrades (possibly via training), longer
working hours and greater effective effort. Productivity gains that result from better management and skill
upgrades are desirable. These are likely to show up over time.
Second, productivity can increase from increases in the use of machinery and non-labour inputs. This
would largely be reflected as the effect of capital intensity.11
The question to ask at this stage is: given that labour productivity has shown an increase over time, what
is the extent to which it has been driven by changes in the composition of capital (the capital-labour ratio)
and to what extent is it due to autonomous increases in productivity? Since it is expected that in the course
of development the composition of capital effect is dominant, we are interested in knowing whether
autonomous increases in productivity have any potential in manufacturing in Pakistan.
A regression analysis conducted for the period 1980-97 (see table A4.4), which focuses on the
determinants of labour productivity and employment in large-scale manufacturing, suggests that labour
productivity in Pakistan has been influenced by changes in capital intensity (i.e., the capital-labour ratio)
as well as increases in ‘autonomous’ productivity. The capital intensity effect on productivity clearly
dominates in manufacturing.
Labour productivity and capital intensity have a significant positive relationship (for equations in which
it used), and this is according to expectation. The level of value added in manufacturing also has a positive
relationship with labour productivity (it is significant in two specifications out of three) which suggests
that high value added production is associated with high labour productivity, which is also expected. The
positive relation also holds true for the time variable (statistically significant in two equations), which can
be seen as a proxy for skills development, learning or ‘autonomous’ increases in productivity.12 So there
are some grounds to expect a potential for autonomous productivity increases in Pakistan.
Employment on the other hand is significantly and positively associated with value added (in two out of
three equations). The capital-labour ratio, the measure of capital intensity, is significantly and negatively
related to employment. The time variable simply shows a negative sign showing the growth rate trend.
Three matters are deducible from this analysis which have strategic implications. First, that increasing
capital intensity which increases labour productivity also has a negative effect on employment. Second,
that higher value added production, though positively related to labour productivity and capital intensity,
is likely also to have a direct beneficial impact on employment. This means that the promotion of high
11
Aggregate productivity can also increase if labour flows into sectors with higher levels of labour productivity,
in other words through the expansion of high productivity sectors, although this is subject to demand constraints.
12
Actually, the time and value added seem to be correlated.
45
value added production has two possible effects on employment, through capital intensity it is likely to
reduce employment, but through the overall positive association between increase valued added production
and employment it is likely to increase employment.
Third, and most importantly, we know from the analysis that autonomous increases in productivity are not
unknown in Pakistan. This is a significant finding and can provide a basis for an employment-friendly
investment plan.
7.
THE STRUCTURE OF LARGE-SCALE MANUFACTURING IN THE 1980S AND 1990S
We now try to differentiate the two periods of the 1980s and 1990s. We know that one was a low-growth
period and the other a high-growth period. We also know that the overall trend is of increasing labour
productivity and capital intensity in the sector. A decomposition of total factor productivity is useful in this
context. 13 The increase in productivity in the large-scale manufacturing sector shows that the increase in
total factor productivity from 1982-83 to 1996-97 has been slight, and has been declining, on trend, since
1992-93. Labour productivity, as we know, has shown an increase on trend, (except for the decline for
1996-97). Capital productivity shows an increase up to 1992-93 and then shows declines. Therefore, it
is really both capital and labour productivity which increased in the 1980s boom. In contrast, while labour
productivity continued to increase, capital productivity showed a decline in the lower growth 1990s. This
is a crucial difference. 14
Table 4.4:
Productivity in large-scale manufacturing (1980-81=100)
Labour productivity
Capital productivity
Total factor productivity
1982-83
122.5
110.1
101.2
1987-88
166.9
136.3
102.5
1992-93
205.2
155.8
103.0
1994-95
208.9
148.9
102.7
1995-96
211.9
143.1
102.4
1996-97
201.7
135.6
102.4
Source: DRI/PIDE Study on Technology 1997.
The output and employment growth policy in manufacturing needed in Pakistan is intrinsically tied to the
labour productivity-led growth process which the country began to witness in the 1980s. The causes for
13
Total Factor Productivity is decomposable into Labour and Capital Productivity. Decomposition is based on
assumptions made on the production function.
14
Declining capital productivity also suggests that a substitution between labour and capital is likely to have begun
in the 1990s. Sectoral decompositions of total factor productivity can be seen in table A4.5.
46
increases in labour productivity are critical to assess. We have done this across the two periods fairly
systematically in the regression analysis above, which suggested that while the capital intensity effect
dominated, autonomous productivity increases were not unknown. For a periodized decomposition of total
factor productivities we found that the difference between the 1980s and 1990s was located in capital, not
labour productivity. The 1980s saw an increase in the latter, the 1990s a decline. We now attempt an
assessment for the 1980s and 1990s separately and at a sectorally more disaggregated level.
The high-growth 1980s
The 1980s were a high-growth period, particularly for the period 1982-82 to 1987-88, after which a decline
set in. Indicators of capital intensity for parts covering the period also tend to confirm that capital intensity
increased in this period. This process has continued between the high-growth 1980s and the low-growth
1990s (table A4.2), but for different reasons. It is reasonable to argue that if growth is positive, as it was
in the 1980s, and capital intensity also increases, as was also the case in 1980s, then labour productivity
(value added per unit of labour) is also likely to rise. This is the case for the evidence we have for the 1980s
(table A4.6). So the increasing capital intensity argument behind the high labour productivity is further
corroborated for the 1980s.
There are some other indicators which explain the 1980s story a little more. Data on investment for the
1980s suggest that it remained around a 3 per cent proportion of GDP from 1983-88 and increased to
4.7 per cent by 1992-93 (table A4.7). This is not only consistent with the capital intensity argument made
above, but it also shows that it was the increase in value of capital stock as well as employment increases
which characterized growth in the 1980s. Labour productivity driven growth in the 1980s, was due to
increasing overall capital intensity and the number of persons employed, which was being sustained by
a relatively stable investment pattern.
Alterations in the composition of investment began in the 1980s. There are falls (table A4.8) during 198283 to 1988-89 in the shares of the chemicals sector and the cement sector, while there are increases in the
textiles and food sectors. So it would appear from investment patterns that while the overall intensity of
capital seemed to be increasing, a sectoral shift was also taking place in the 1980s to less-capital intensive
sectors. We need to examine the capital intensities of sub-sectoral shifts to explain this.
During the period 1980-81 to 1990-91, in the large-scale sector, the share of food products declined from
24.3 per cent to 14.2 per cent (table A4.9). This is interesting because food was not a highly capital
intensive sector, and although the share in value added of the food sector was declining, investment in it
was increasing;15 the share of textiles increased from 24.3 per cent to 26 per cent and textiles on the whole
are even less capital-intensive than food. It is also clear that both food and textiles are on the middle to
lower end of the capital intensity scale in the large-scale sector taken as a whole. The chemical sectors
share increased from 13.2 per cent in 1980-81 to 23.5 per cent in 1985-86 and then declined to 14.9 per
cent in 1987-88 and further to 13 per cent by 1990-91. Industrial chemicals constitute the larger part of
this sector and are very capital- intensive. Investment figures reported earlier which show a decline for the
chemical sector after 1985-86 tend to suggests that there was over-capitalization in the sector in the early
1980s.16 These are the only significant changes in the period; the rest of the sectors are mostly not major
15
This is partly due to the fact that food figures include the sugar sector and while the rest of the food sector was
in decline, there was investment in the sugar industry. Moreover food production was moving towards lower value added
activities and thus losing its share in total value added.
16
The causes for over-capitalization in chemicals (as well as cement) may have something to do with lending
criteria. It has been shown above that despite the slowdown in the manufacturing economy some investment is still taking
place. Given that there is under-utilized capacity in an industry, it is pertinent to ask what causes investment based increases
47
and generally tend to fluctuate with respect to their value added shares in smaller margins. It appears that
the net result of sectoral shifts has been an increase in capital intensity and this needs to be explained.
There are two factors at work here. Although the major sectoral changes (as well as investment patterns)
suggest production may have been moving towards relatively less capital-intensive sectors in the 1980s,
it is also the case that 16 out of 24 sub-sectors have individually experienced an increase in capital intensity
even in the period 1987-88 to 1990-91 (table A4.2). Furthermore, while the food sector’s (the major loser)
capital intensity, contrary to the trend actually declined in the period , the capital intensity of the textile
sector (the main gainer) increased. Capital intensity of the chemicals sector also declined during the late
1980s.
It can be argued that taking into account overall increases in capital intensity across the manufacturing
sector, and the specific changes in the capital intensity of the main losers and gainers, the sub-sectoral shifts
in the 1980s are likely to have accompanied increasing capital intensity on the whole. Although,
counterfactually speaking, had the shifts in the major sectors not taken place the capital intensity would
have increased even more.17
Finally, data on capital-output ratios is also available. An increasing capital output ratio suggests that the
value of capital stock in relation to the value of output is rising. Assuming stable prices, this is consistent
with either an increase in capital stock or a decline in production. A decline in production, which would
tend to raise the capital- output ratio, is consistent with a crisis of demand and excess capacity building
in industry. Therefore rising capital-output ratios are consistent with building excess capacity. Falling
capital-output ratios suggest the opposite. The latter was the case in Pakistan during the 1980s (table
A4.3). To the extent, excess capacity that it existed was being used up in the 1980s. It was a relative
increase in output despite the increases in capital stock which characterized the capital intensive–labour
productivity driven growth of the Pakistan economy in the 1980s.18
We now return to the issue of the low elasticity of the manufacturing economy. It is arguable that the
1980s high-growth period’s low elasticity of employment and shifting source of growth (from being
unequally shared between employment and labour productivity to being labour productivity driven) is
consistent not only with an increasing capital intensity in general across the large-scale sector, but also a
compositional shift to relatively less capital intensive sub-sectors within manufacturing.
By the end of the 1980s, a slowdown in growth began to take place. What were the characteristics of this
slowdown and what were its causes?
The 1990s: A period of low growth
of capacity when it is under utilized to start with? Clearly this is what is also partly responsible for the observed increasing
capital intensity in an industry. There are two sides to the issue in Pakistan. One is simply that new entrants in a free market
structure can enter the industry (unless it is a monopoly) even if there is excess capacity in it. The matter clearly turns on the
gains as well as profitability of the enterprise for the individual investor and pricing of capital. This is discussed later.
17
In a situation of positive growth, if capital flows into sectors which have higher levels of labour
productivity(which produce more value added per employed person), then aggregate labour productivity would increase.
These high productivity sectors could be correlated to higher capital intensity sectors. It is therefore not plausible to argue that
sectoral flows were mainly causing a general increase in capital intensity in manufacturing in Pakistan.
18
Investment financing and the use of capital are related directly to capacity utilization. It can be argued that one
of the reasons for the recent lower levels of productivity in Pakistan is the under-utilization of capacity. Increases in capacity
utilization in the sector would therefore tend to increase productivity (and reduce domestic resource costs).
48
During the 1990s growth has moved from positive to negative. We cannot say much about employment
levels because of data constraints. With increasing flexibility in labour markets, it is likely that employment
may have declined, and contractual changes occurred.19
Even if growth is declining and turns negative (output increases less and less and then declines) a capital
intensity rise (which reduces employment in relation to capital) will show up as an increase in labour
productivity (the production of output or value added per unit of labour) but this will be for different
reasons than in a high growth situation. Capital intensity can rise for two reasons: an increase in capital
stock and a decline in employment. In a period of zero or negative growth, a rise in capital intensity is
likely to be due to a decline in employment as opposed to an increase in capital stock.20 This means that
if labour productivity increases it does so because the rate of fall of output (value added) is less than the
rate of fall of employment. The issue really turns on how flexible the labour market is. If the number of
employed decline, and output declines as well, an increase in labour productivity is as possible as a decline
is. It depends on the respective rates of decline. It is not clear whether Pakistan is already in this situation,
but it may be close to it.
Consequently, the same indicators of increasing capital intensity and increasing labour productivity can
characterize two very different situations. It is fairly clear from the data that growth in the 1990s slowed
down (table 4.2). Declining and low as it was it is equally clear that growth was even more dominantly
based on labour productivity increases than employment expansion than in the 1980s. What was the
sectoral basis of this rising labour productivity?
Investment declined in the sector from 4.7 per cent of GDP to 2.7 per cent from 1992-93 to by 1996-97.
It is, however, still likely that capital intensity in the sector increased, from the foregoing discussion and
the data at our disposal. The 1990s also indicate only slight changes in the composition of output (table
A4.10). 21 By and large, shares of output show variations of a small margin for the main sectors. The
1990-91 pattern of industrial composition continues. The only sector which shows any serious increase
is the textile sector. The relatively more capital-intensive sectors reveal a trend decline within a small
margin.
It is, however, very clear that unlike the 1980s, there is an excess capacity build-up in some of the major
sectors of the economy (table A4.11). We have information for 1990-91 when capacity utilization was
around 60 per cent. Recent trends based on Planning Division estimates suggest a declining trend in
selected sub-sectors. In the recent period from 1992-93 to 1995-96, capacity utilization has declined on
trend in the spinning, sugar, and cement sectors. It has remained stagnant in weaving and increased only
in fertilizers. This clearly suggests an overall decline.
It can be argued that the 1990s picture is characterized partly by a failure of demand in the large-scale
manufacturing sector. The low level and declining growth of output and employment, declining investments
and the build-up of excess capacity all point to this failure. The increase in capital intensity (like the
increasing labour productivity in the 1990s) which characterizes the growth process, needs to be matched
19
Estimates of contract workers vary. They increased from 4.9 per cent (1980-81) to 6.3 per cent (1987-88) of the
total industrial labour force (Shahid Associates, 1989). It is very likely that this process has continued through the 1990s.
20
Some investment is likely to occur, to replace existing capital in a low-growth situation and may itself raise the
capital–labour ratio.
21
As previously mentioned, the Census of Manufacturing Industries (CMI) data are unfortunately unavailable for
periods after 1990-91. Physical production data collected by the Federal Bureau of Statistics are used for estimating value
added for the large-scale sector after 1990-91.
49
with declining capital productivity and is therefore more indicative of shrinking employment than an
increasing capital stock and value of output.
What is responsible for the slowdown in growth? Apart from the general failure of demand argument, there
are two broad answers to this question. One relates to macroeconomic policies and the other to the
investment climate.
From the macroeconomic perspective, Pakistan has pursued deflationary policies since the beginning of
the reforms in 1988. This is supposed to have short-run consequences for growth, which are not
inconsistent with what can be discerned for the 1990s. Among other issues this also includes the
withdrawal of the public sector in the economy under depressed demand conditions.22
Since the decline in investment is also for the more recent years, it may partly be due to the unstable
conditions of production and investment (i.e., the law and order situation) in both Karachi and the Punjab,
which have clearly deteriorated in the recent past.
8.
TOWARDS A POLICY OUTLINE
The challenge for the manufacturing sector in Pakistan is considerable. A concerted effort is needed
towards increasing the low elasticity of employment as well as output growth. This effort needs to focus
on reviving demand and improving the social climate for investment, on increasing the utilization of
existing capacity and promoting growth in sectors with a potential for autonomous productivity increases.
Criteria of sectoral choices in an employment-friendly investment plan
Some of the above findings can assist in the formulation of an employment-friendly investment plan for the
future. It is therefore recommended that in the selection of activities to be promoted, the following factors
must be borne in mind when developing the criteria for sectoral choice:
•
•
•
•
sectors should have some potential for autonomous productivity growth;
sectors should have some employment-generating capacity;
sectors should be producing sufficient value added (such that the capital intensity/negative
employment effect is offset by the expansion-high value added/positive employment effect); and
there should be a separate assessment of demand conditions in such sub-sectors and those which
seem relatively unconstrained must be promoted.
The mechanism of sectoral promotion should be affected through two means. First, via the banking
system, which should try to guide investment. Sub-sectors fulfilling composite measures based on the above
criteria need to be identified and a system of incentives offered through the financial system to realize the
desired flows into these sub-sectors.
Fiscal expansion and demand
22
The point is general, but one that is often missed. An adjustment and reform period is likely to depress demand
and an overall slowdown in growth and investment is to be expected. This affects the investment climate. If the adjustment
process is also accompanied by the withdrawal of public sector from the economy, it is more than likely that the private sector
would not, due to the altered investment climate, immediately step into public-sector shoes. Even if the theory is right, this
move is likely to take place after a substantial lag. In the case of Pakistan it is arguable that there has been a failure in the
sequencing of reforms which may have affected growth.
50
Given that part of the problem may be in government pursual of deflationary policies under the reforms,
which has led to a decline in demand for manufactured goods, it may be worth examining the worth of
expansionary fiscal policies, to revive demand. To the extent that capacity is under-utilized (investment
requirements become less) and the manufacturing sector is not primarily export-based, the case may have
some merit.23
The budget deficit and working capital
A critical factor in freeing affordable resources for the manufacturing sector is the degree to which the
government budgetary deficit falls and the government borrows a smaller amount of money from the
banking sector. Capacity utilization and employment can increase without substantial increases in
investment. There is a clear link between the budget reform government and the relief of working capital
constraints in manufacturing. This is, however, not inconsistent with the selective fiscal expansion
suggested above.24
Promotion of sub-sectors through tariff rationalizations
In order to revive growth in manufacturing, the profitability issue needs to be addressed directly. This
entails a serious examination of the structure of tariff rationalizations and the matter is likely to be
critical. The development of the manufacturing sector has become somewhat lop-sided over the years, as
production has moved against high value added products. If corrected this may benefit the sector as a
whole. Tariff rationalization can result in improvements in the relative profitability of the chemicals and
engineering sectors (the sectors falling behind) and arrest the trend in the overall composition of
investment and output in the large-scale sector. This is important to do for the general health of the largescale manufacturing sector, even though it may be true that some parts of these non-traditional sectors may
comprise relatively capital intensive activities.
Capital pricing and directing new investment
Another issue concerns investment itself and the price of capital. It is questionable if capital is priced in
relation to its opportunity cost. If capital were priced at its opportunity cost with prudential regulations,
then the true costs of investment would be transparent to investors and lenders. This is clearly not the case
in Pakistan, and the crisis of bad loans that the financial sector is facing is testimony to this fact. Arguably
the weakest link in the financial sector reforms which have taken place in Pakistan, it also highlights
something that is fairly obvious but often ignored, namely that in many instances market-based reform must
be complemented by institutional reform in order to be effective.
23
The idea is to decrease unproductive as opposed to productive expenditure of government.
24
In fact one of the failures of sequencing of economic reforms in Pakistan has been to go ahead with financial
liberalization before a budget reform.
51
The co-ordination of capital flows
Unlike the earlier period, when credit plans were coordinated by government to put sectoral ceilings on
bank lending, direct leverage for credit allocation is no longer used by government and credit is controlled
indirectly through discount rates, open-market operations and liquidity requirements. It is, however, still
possible for banks to collude with respect to sectoral lending priorities, as they have a significant interest
in the setting up of new plants and improving the overall use of capital. Banks therefore clearly have a
stake in the provision of capital which is invested and there is much that can be done in this area.
The revival of sick industries
There is another important issue which needs to be assessed concerning capacity utilization and the
performance of the manufacturing sector in Pakistan . A large number of industrial units have closed down
over the last few years and a considerable number are operating below capacity; as many as 2,533
industrial units are closed and another 1,252 units are running losses (Report of Committee on Sick Mills,
1996). The units have become ‘sick’ for several reasons which need to be distinguished. The checklist
includes: over-capitalization of different industrial units; over-capacity in the unit’s industry as a whole;
inappropriate site selection; inappropriate choice of technology, lack of working capital; and basic
mismanagement. Units operating below capacity could also be facing a slackness in demand, energy
constraints via load shedding, or the non-availability of complementary inputs. Solutions vary according
to the dominant cause of the sickness of unit and these must be identified in a fair amount of detail for a
serious attempt at devising revival strategies. In general, the question is whether anything can be done to
increase the utilization of capacity in the present circumstances.
Tax policy and flow of goods
As indicated above, in recent years Pakistan has been pursuing deflationary policies in the context of
economic reforms, with a direct influence on the decline in demand for manufactured goods. The increase
in sales tax and regulatory duties on raw materials and intermediate inputs has at the same time made
domestic manufacturing less competitive against smuggled goods. It is therefore important to assess the
effect of government taxation efforts on competition, in the presence of leaky borders. There may be
something which can be done here.
Energy pricing
Load shedding has been a constraint to industrial growth in the past in Pakistan. It is expected to be
overcome because of increased capacity, although the whole matter of an inefficient energy distribution
system still needs to be addressed. Whatever the determinants and cost parameters associated with the
growth of the energy sector, it is fairly clear the issue of energy prices will be critical for the growth
process. Higher energy prices may still constrain the utilization of capacity. Consequently, a critical factor
in the increase in the utilization of capacity in manufacturing is the degree to which energy prices increase
in the economy.
9.
UPSHOT
We have attempted to explain the trends of employment and growth in the manufacturing sector in Pakistan
over the 1980s and 1990s. There are some features of this review which need to be highlighted.
A low employment elasticity is a structural feature of the manufacturing sector in Pakistan. We find that
trends in growth rates suggest a decline. The 1980s were a high growth period while the 1990s are
characterized by low growth. Growth in manufacturing since the 1980s has been driven by labour
52
productivity as opposed to employment expansion; the last period in which employment expansion took
place was the (low growth) period of 1970s. It can be argued that output growth began de-linking itself
from employment in the 1980s and became de-linked from employment expansion altogether in the 1990s.
Part of the explanation of this feature lies in the distinction between the small and large-scale sectors in
manufacturing in Pakistan. It is the small-scale manufacturing sector employment which declined in the
mid 1980s, while its output grew. In the large-scale sector both employment and output growth have been
positive in the 1980s and most of the 1990s. In other words, the de-linking of employment from output
growth which was taking place in the manufacturing sector in the 1980s and which was established in the
1990s, may have been due to the overwhelming weight of declining employment in the small-scale
manufacturing sector and not because of the large-scale sector as such.
A policy implication of the above is that employment growth needs to be promoted in the small-scale
manufacturing sector, while output growth needs to be revived and the low elasticity of employment
increased in the large-scale sector. Therefore the centrepiece of an ‘employment generation’ strategy
within manufacturing should be the small-scale sector, which is larger in weight (around 83 per cent). In
contrast, the primary focus of a ‘revival of growth’ strategy is the large-scale sector where the bulk of
manufacturing output (around 70 per cent) is produced. It is this sector’s growth which is likely to have
positive linkages with other sectors, including the activities in small-scale manufacturing as well as smallscale non-manufacturing.
Examining labour productivity, the engine of growth in the sector, it is fairly clear that labour productivity
in Pakistan’s large-scale sector has been dominantly due to increasing capital intensity, but it is worth
noting that autonomous increases in productivity are not unknown. The labour-productivity led growth is
not alarming in itself since such increases are expected over time. The periods of high growth in the 1980s
and low growth in the 1990s need to be differentiated on other grounds. While both periods are
characterized by increasing capital intensity and labour productivity in large-scale manufacturing,
investment trends in the 1980s are stable and positive while in the 1990s they are declining, just as excess
capacity is declining in the 1980s and is increasing in the 1990s. The examination of total factor
productivities sums up the situation well. These increased in the 1980s and declined in the 1990s. The
difference was not in labour productivities which rose in both periods, but in capital productivities which
increased in the 1980s and declined in the 1990s.
The challenge for the manufacturing sector in Pakistan is considerable. A concerted effort needs to be made
towards increasing the low elasticity of employment as well as reviving growth. From our analysis it is
clear that a crisis of demand may be in the process of setting in the large-scale manufacturing sector. The
causes are complex and multiple but two issues can be singled out which may explain the slowdown of the
1990s. One concerns the investment climate in Pakistan which has not only deteriorated but spread from
the 1980s to 1990s; the second relates to post-reform deflationary policies adopted by the government (and
their sequencing) in the late 1980s and 1990s, (which were accompanied by privatization and public-sector
retrenchments). These are likely to have dampened demand and the supply of working capital for the
manufacturing sector.
A multifaceted policy initiative is required in order to revive growth in the large-scale manufacturing sector.
This effort in the large-scale sector needs to focus on reviving demand and improving the social climate
for investment, on increasing the utilization of existing capacity and promoting growth in sectors which
also have a potential for autonomous productivity increases. Some policies consistent with these aims
have been suggested.
53
CHAPTER FIVE
The Small-Scale Enterprise Sector
1.
INFORMATION AND DATA
There is a serious limitation of information on the Small-scale Enterprise Sector (SSE) in Pakistan and
wide discrepancies exist between data available from different sources. Our earlier discussion suggests that
this sector is of critical importance with respect to employment, especially its manufacturing component.
Manufacturing employment growth as a whole has linkages with employment in other sectors of the
economy. The structure of employment in manufacturing is such that the bulk of the manufacturing sector’s
employed persons are located in the SSE sector. Thus, it is the SSE manufacturing sector which has
employment absorption potential. In this chapter, we look at the SSE sector as a whole but with particular
emphasis on SSE manufacturing.
As the data on the sector in Pakistan is often incomplete, irregular, and varying in definitions, the task of
producing an ‘overview’ is difficult. In making this attempt, we rely on National Income Accounts, the
Labour Force Surveys, each of the major surveys done for the SSE sector in Pakistan, as well as some
important micro studies done with the SSE as a focus.
2.
DEFINITIONS
Small-scale Enterprises are defined in this section as firms using less than 10 workers. However, different
definitions are used in Pakistan for varying purposes. The definition intended for statistical use and data
generation has undergone a change from being asset value (Rs. 2 million or less in 1976-77) based to being
labour (less than 10 workers) based.
Definitions which are not for classification purposes but entail ‘policy support’ to the SSEs in the form of
loans and tax relief, differ widely according to the assessing authority and are almost always capital based.
For example, the State Bank of Pakistan, the central government as well as provincial governments, each
involved in lending decisions related to the sector, have different cut-off capital values which ‘constitute’
for them, the SSE sector.
3.
ESTIMATES OF OUTPUT AND EMPLOYMENT IN SSE MANUFACTURING
Partial estimates of the output and employment of the sector based on National Income Accounts (NIA)
and Labour Force Surveys (LFS) are reported in the Economic Surveys (ES). They suggest that the SSE’s
output share in manufacturing is around 30per cent while its employment share is nearly 83 per cent (tables
A5.1 and A5.2). These figures have already been encountered in our general discussion on manufacturing.
Data reported in the Economic Survey (ES), however, calculate the size of the small-scale sector as a
residual. In short, according to this data we have a very high share of employment within manufacturing
which goes to the SSE. Another characteristic of the SSE sector is its allegedly high growth rate of output.
The combination of its high employment absorption capacities and as its high growth rate makes this sector
an appropriate focus from an employment perspective.
54
Levels of employment and growth rates, as reported in the Economic Survey, are shown in tables A5.3 and
A5.4. Our alternative sources of information are mentioned.1 On the basis of a thorough review of much
the information available on the SSE sector in Pakistan (Appendix 1) in the major surveys, we present our
synthesis of employment output and growth in the sector below:
4.
The decline in SSE manufacturing employment in the mid-1980s discernible from the Economic
Surveys is plausible and the pattern is likely to continue. Since comparing alternative surveys over
time is not feasible, the trend is likely to have continued, especially since we do know that overall
GDP growth declined and has not since picked up in the 1990s. Employment growth in SSE
manufacturing is likely to have therefore declined on trend, if it has not been negative during the
post-1991 period.
5.
The level of employment in SSE manufacturing is likely to be lower than the three million ball
park figure (in 1988) based on LFSs. How much lower is a matter of guess work, it may be as low
as even half that figure, but its level does not alter our view on the trend of employment growth.
6.
The growth of output of SSE manufacturing, estimated for the sector in NIA is likely to be very
seriously lower than what is reported in the Economic Surveys. Instead of averaging around the
8 per cent mark, it was probably closer to 4.3 per cent in the 1976-77 to 1983-84 period and 4.7
per cent for the 1983-84 to the 1988 period; and a much lower 2.6 per cent from 1983-84 to 199293. Therefore the 1980s figure is closer to 4-5 per cent and the 1990s figure is much lower.
7.
The SSE manufacturing value added or employment shares are unlikely to exceed a quarter of
total value added and employment in the sector. Within sub-sectors in manufacturing it is textiles,
food, wood products and fabricated metals which dominate both value added and employment.
Textiles in turn are dominated by weaving and the carpet industry, which also have dynamic export
linkages.
Apart from our findings on the size and growth of the sector synthesized above, mean incomes are also
found to be lower in SSE manufacturing than in the large-scale sector. As its growth is unlikely to be as
high as is assumed in the data reported in the ES, we need to emphasize both the revival of growth and
employment generation in any strategy for the sector.
We have based our synthesis on a careful assessment of the numbers available from different sources.
There are some implications:
1
The major surveys are: The Small Household and Manufacturing Industries (SHMI) 1983-84, 1988; The Census
of Establishments 1987-88, The Household Integrated Economic Survey (HIES) 1987-88, 1990-91; The Integrated Survey of
Service and Manufacturing Industries-Small, (ISSMI-Small), 1992. There are three micro studies based on sample surveys
which are comprehensive in their coverage of many important structural characteristics of the SSE and are of interest to us.
These will be referred to by name in the text. The largest survey of 1417 firms is also the most recent, conducted in 1992, by
Kemal and Mehmood [Kemal A.R. and Mahmood Z., 1993]. The second largest survey of 806 firms was conducted in the mid80s by Cohen and Havinga, [Cohen S.I. and Havinga I., 1988]. The third largest of these surveys is of 328 firms conducted in
1989 by Nadvi, [Nadvi K., 1990]. Two other surveys have larger samples, but their results are more limited in terms of our
characteristics. One is a survey by Burki in collaboration with the Freidrich Ebert Stiftung (FES), of 2,030 apprentices and
their masters (Ustaads and their Shagirds), [Burki A.A., 1989]. The other is a survey of 600 rural firms conducted in the late
1980s by Aftab, [Aftab K., 1990]. In addition there are two assessments of the role of the Panjab Small Industries Corporation
and its established industrial estates by the Panjab Economic Research Institute (PERI) [PERI, 1985, 1988]. Finally there are
a large number of purposely partial sector coverage studies on women and children in the SSE sector; two policy studies by
Frerks, Thomas, and Thomson, [Frerks G.E., Thomas H. and Thomson L.B.M., 1989], and the World Bank, [World Bank,
1991].
55
First, there are sufficient grounds for re-examining the growth rates assumed for the SSE manufacturing
sector in the National Income Accounts. A much more detailed investigation is necessary, but the
background research done for this report has taken a first step in this direction.2
Second, these qualifications do not alter the thrust of our employment strategy for the manufacturing sector
as a whole, or the SSE component of it. Employment is still much higher in SSE manufacturing than largescale manufacturing. The trend of an arrested or declining employment growth evidenced in the mid-1980s
is still likely to be valid.
Third, the focus of a strategy for the SSE manufacturing sector is employment expansion through growth,
as this is where many of the employment linkage effects discernible for `manufacturing’ at the aggregate
level may be forged into the rest of the economy.
4.
CHARACTERISTICS OF THE SSE SECTOR
The size of the rest of the SSE sector compared with its manufacturing component is likely to be much
larger both in terms of value added and employment. It could employ anywhere from four to six and a half
million persons. In our view, the figure is a closer to the former than the latter. In Annex 5.1, we examine
the basic sectoral profile of the SSE sector which can be gauged from the large-scale surveys done in
Pakistan during the 1980s and 1990s. It is worth noting that trade and services are the largest sub-sectors
in SSE manufacturing, which may employ up to 70 per cent of the persons working in the sector.
There are a large number of micro sample surveys of the SSE in Pakistan. We focus on four of the
important micro analyses. These are: Kemal and Mehmood (Kemal A.R. and Mahmood Z., 1993; Cohen
and Havinga, (Cohen S.I. and Havinga I., 1988); Nadvi, (Nadvi K., 1990), and Aftab (Aftab K., 1990)
from now on referred to by the authors’ names. Our objective is both to get some answers to questions of
policy relevance and to qualify the estimates of what we already know about the broad attributes of the
sector from the data in major surveys. We focus on two important areas: the demand and output of the SSE
firm; and its productivity and returns. The larger survey: ISSMI-Small, 1992-93, is mainly used as the
benchmark.
The SSE firm: Subcontracting and demand
ISSMI-Small for 1992-93 shows that the SSE sector was not ‘fully integrated’ into the large-scale sector,
with no firms solely reliant on sub-contracting. SSE sector firms also seemed to be transient, the vintage
of over one-third of the firms being the 1990s.
We can try and qualify this with reference to other studies. For the four sub-sectors it examines, Kemal
and Mehmood’s study finds that sub-contracting is predominant (63 per cent of firms) in manufacturing
only. Cohen and Havinga differentiate between substantially self-sufficient firms (SS) and firms linked
to the modern sector (ML). They find (almost by definition), the ML firms rely more on hired labour with
outward sources of inputs and outward sources of demand such as wholesalers, middlemen and
government. Aftab’s survey, distinguishing between household and small-scale firms, finds sub-contracting
to be very low in rural areas. Nadvi distinguishing between household firms (HH) and larger firms which
he calls small-scale (SC) finds a high incidence of household firms tied into sub-contracting. This appears
like a ‘putting out’ system where suppliers are the main entrepreneurs and households the main labourers.
2
56
ILO-SAAT, Mahmood, M., 1997 (mimeo).
This sub-contracting is unlikely to be a phenomenon exclusive to a large number of SSE firms, although
in manufacturing it is likely to exist non-exclusively in a significant degree for many SSEs. It is also likely
to rely on household enterprises and have a higher urban incidence.
This clarifies a point made for the manufacturing sector in the overall employment strategy, where we
viewed the growth of manufacturing sector employment as critical for employment growth elsewhere in the
economy because of linkage effects. It is now clear that there is a growth-based linkage between the largescale manufacturing sector and the small-scale manufacturing sector through sub-contracting. Since the
bulk of manufacturing employment is in the SSE manufacturing sector, it is arguable that a decline in
growth of the large-scale sector and loss of incomes (as in the 1990s) could adversely affect the demand
side for goods produced in the SSE manufacturing sector. Consequently the growth of the large-scale sector
would tend to revive these sub-contracting links and increase effective demand for the SSE manufacturing
sector. It is through this revival that employment linkages with other sub-sectors (particularly with trade
and services) could be realized.
Labour use in the SSEs
The ISSMI-Small data shows (table A5.13), that 94 per cent of SSE firms were individual proprietorships.
About 41 per cent of firms hired one employee, another 35 per cent employed two persons and another 20
to 30 per cent employed between three and four persons.
Kemal and Mehmood find firms rely for about 50 per cent of labour force on family labour, with 37 per
cent self-employment and 13 per cent family help. The other 50 per cent of the labour force is hired,
consisting of 38 per cent employees and 12 per cent apprentices. They also find a higher working week for
all types of SSE labour compared with the large-scale sector. Cohen and Havinga find their self-sufficient
‘SS’ firms relying more on family labour while Nadvi finds what he terms household ‘HH’ firms relying
more on family labour.
Kemal and Mehmood find a high incidence of skilled labour in this sector, which is also confirmed for ML
firms by Cohen and Havinga. There is a clear tendency for the SSE to rely significantly on family and
household labour, which is used quite intensively.
Capital stock ratios
ISSMI–Small shows a low capital base for the SSE sector. However, two types of firms can be
distinguished, particularly in the manufacturing sector (tables A5.14 and A5.15). Firms with 5 persons or
less had a capital-labour ratio which is around Rs 20,000. Those with more employment (excluding one
size category) had a capital-labour ratio which jumps a scalar of 1.5 to 2. These ‘capital-starved’ firms of
less than five persons comprised 83 per cent of manufacturing units. In general, just under a quarter of
firms have assets between Rs 1,000 and 10,000, while 84 per cent of firms have assets of a value less than
100,000.
Kemal and Mehmood find a lower capital-output ratio for the sector compared with the large-scale sector,
consistent with its low capital intensity. On labour productivity, Cohen and Havinga find that their ML
firms have a higher labour productivity compared with their SS firms. Capacity utilization, however, varies
in their ML firms and suggests unstable demand, which shows up as low capital-productivity.
The capital intensities in all the micro surveys vary according to expectation. Nadvi’s SC firms and Cohen
and Havinga’s ML firms have higher capital-labour ratios than their household or self-sufficient
57
counterparts. The Kemal and Mahmood comparison of the SSE to large-scale sector shows the capitallabour ratio in the SSE to be nearly half that of the large-scale sector.
Capital intensity is low in the SSE sector is low, although firms can be differentiated on two grounds: those
which have external linkages are also more capital intensive; those which are capital starved, employ less
than five persons and are in a majority in manufacturing. This also implies that it is precisely the capitalstarved firm employing a lower number of persons per unit that is likely to be part of a refuge sector
within the SSE sector.
Credit
The low capital base in the SSE sector can be explained by low access to the formal credit market. The
SHMI 1988 data on credit is available for the manufacturing sector (table A5.16). From a total investment
of Rs 1.7 billion in 1988 over 91 per cent came from private savings, 9 per cent from the informal credit
market and 1 per cent from the formal credit market. This is consistent with the World Bank findings which
estimate around 2 per cent of the loans flowing to the SSE from the formal sector (World Bank, 1991).
HIES 1990-91 (table A5.11) also has data on loan access and its impact on the SSE sector. Of the
4.4 million units of the SSE, 26 per cent had taken loans from both formal and informal sources. The
proportion was highest for manufacturing (35 per cent) and lowest for hotels (19 per cent). Formal market
commercial loans were however limited to only 1.5 per cent of the total units, the highest being in trade (2.4
per cent). Some impact of these formal and informal loans on income or employment of these units can
be seen. The average monthly income of an SSE without any loan is Rs. 2086; of an SSE with only an
informal sector loan is Rs. 1796; and of an SSE with a formal sector loan is Rs. 2627. Similarly, in firms
with zero-borrowing average employment is 1.53 persons; firms with only informal loans have a similar
employment level of 1.51; but SSEs with formal sector loans employ 2.06 persons on an average. Formal
sector credit can have a significant impact on the employment and income of SSEs.
The informal credit market is the main external source of funds for the SSE sector. A report by the World
Bank (World Bank, 1991) identifies different forms of urban informal credit mechanisms operating in the
sector, although these are likely to be relevant in both urban and rural contexts.3 The access to a formal
credit market is therefore weak, especially for household-based firms, although it is clear that the links with
it are beneficial for the SSE sector.
Incomes
The returns to self-employment in the SSE sector, which are returns to both capital and labour, are four
times greater than the hired wage rate in the SSE sector.4 The hired labour wage is also significantly lower
than the large-scale sector wage in Kemal and Mehmood’s study. Cohen and Havinga find that their ML
firms compared with their SS firms have 66 per cent higher income. They also find income inequalities
between owners and labour to be higher for ML firms than SS firms.
3
These mechanisms of informal credit include: high interest rate supplier’s credit which varies with the repayment
period (up to 15 per cent per month ); buyer’s advance with high implicit interest rates (up to 16 per cent per month); the
‘parchi’ system based on discounted cash sales and IOUs; and what is known as the ‘Committee system’, which is based on
a central fund with lots drawn for lump-sum withdrawals by members of the group who, on winning, exclude themselves from
subsequent draws. Remittances, funds taken from relatives, and ‘own savings’ are also sources of capital. Moneylenders are
the most unpopular form of borrowing for the SSEs in Pakistan.
4
The general results of the self-employed being `poor’ encountered earlier in Chapter One is therefore largely due
to the agricultural sector.
58
It is appears that returns to both capital and labour for owners and labour are generally low in the SSE
sector compared with the large-scale sector. There is demand based differentiation within the SSE sector
between modern sector linked (ML) and self-contained/self-sufficient(SS) firms. External linkage in the
ML firms is likely to improve their incomes.
5.
OVERVIEW
These indicators show the SSE sector as partly a refuge sector, inflated by low productivity employment
absorption in agriculture on the one hand and a small registered formal sector on the other. They also
show it to be partly integrated into the mainstream economy where its market demand is based on growing
export niches in textiles, in metal fabrication, and a growing domestic demand for consumption and capital
goods. In particular the analysis of the sector finds:
•
The output growth rate of the SSE manufacturing sector is not as high as the official 8 per cent
per annum, and may be between a half to a quarter of this for the last decade. The size of the entire
SSE sector is large, with employment estimated to be around 4.4 million persons.
•
The largest sub-sectors are trade and services which account for 60 per cent of the employment
in the SSE sector. Manufacturing accounts for around 26 per cent of the employment, (and, within
manufacturing, textiles account for 12 per cent of total employment), followed by catering with
11 per cent and fabricated metals and food processing (3 per cent each).
•
Within the manufacturing sector as a whole (i.e., large-scale and SSE), the SSE employs the bulk
of the labour force. The share of the SSE sector in manufacturing value added is around 33 per
cent. However its share of capital assets is a much lower. This gives the SSE sector a capitallabour ratio which is lower than the large-scale sectors. The estimates of the difference are wide,
ranging from a factor of 2 to 17. As a result of its low (and depreciating) capital and technology
base, the SSE sector has a capital-output ratio which is considerably lower than the large-scale
sector’s (probably by a factor of 10).
•
The SSE manufacturing sector does however display a rich dualism within itself. Some of its
enterprises appear more integrated into the mainstream economy, act entrepreneurially, are based
on hired labour, have better access to the formal credit market, have higher capital assets, a higher
productivity, and better returns. Other enterprises are more involuted, appear to be recipients of
a ‘putting-out’ system, are based more on family labour, are more reliant on the informal credit
market, have lower capital assets, lower productivity, and lower returns.
6.
THE SUPPLY AND DEMAND FOR SSE GOODS AND SERVICES
We now examine some supply and demand side issues that have policy implications for the SSE sector.
Our objective is to explore some potential sources of promoting the employment and output growth of the
sector.
Changes in purchasing power of social groups and demand
It is worth investigating this issue of demand. We know from the foregoing that if our dualism hypothesis
is correct, then the dynamic part of the SSE is more linked into the structures of demand in the economy
than its involuted part. Demand for the sector can be articulated through cross-sectoral linkages (sub-
59
contracting) as well as through changes in the purchasing power of consumer groups. Further this demand
for the sector’s output can be directly policy-induced, as well as a result of wider changes in the economy.
The latter are often expressed through changes in the purchasing power of social groups.
Remittances
An increase in the purchasing power of a significant group in the economy can lead to an increase in
demand of the SSE and large-scale sectors. Remittances have clearly had an impact on the purchasing
power of families of the migrants. Pakistan has had a history of migration during the 1970s and 1980s to
the Gulf states. Many of the migrants have originated from rural areas of the country. The migration-based
remittances from the Gulf arguably had a demand-boosting effect on the SSE (Hamid, 1983). However
now that migration is not a major phenomenon in Pakistan, it is unlikely that the demand effect on SSE
goods would further increase from this source. Historically speaking, it is likely that (and especially to the
extent that this migration was rural) there was an initial boost to SSE consumption goods demand from
remittances but with increases and stabilization in the wealth of recipients this should have been slowly
shared with demand for goods from the large-scale sector.
The green revolution and differentiation of the peasantry
A possible new source of purchasing power is the differentiation of a largely self-subsisting peasantry
producing their own consumption goods, into landless wage labour demanding both capital goods as well
as consumption goods to supplement their incomes. There has been increasing landlessness in the
agricultural sector in the past two decades (Mahmood, 1993). The increased demand from these lower
income groups will tend to be largely from the SSE sector. The assumption here is of course that landless
labourers’ share of consumption goods (and capital goods) from SSE production is greater than the
respective share of landlords and large owner operators.
An effect of remittance and landlessness should be evidenced in the growth of consumption goods in the
SSE, (especially in the food, textiles, and wood sub-sectors) over the 1970s and 1980s.5 Since both outmigration and the remittance effects are now likely to be small, the landlessness effect should be what is
of relevance. It is important to note that although it has the same effect on the SSE sector, the landlessness
effect is not unambiguously a result of increasing prosperity, as is the case with the remittance effect.
The income and technical change effect of the green revolution
Another source of increasing purchasing power in Pakistan has been the profitability-enhancing, inputintensive green revolution in agriculture. The High Yielding Variety (HYV) inputs and accompanying
mechanization increased demand for capital goods from higher income groups such as large farmers and
landlords. The resultant profitability should have increased the demand for consumption goods from both
the SSE and the large-scale sector. It would seem that these income groups, after some time in which
capital and wealth are accumulated, tend to switch expenditure to the products from the large-scale sector.
Depreciation of exchange rates
A drop in the real exchange rate can increase the demand for SSE goods. The exchange rate depreciation
has been in effect in Pakistan for the past two decades. The idea is that more expensive imports of capital
5
These effects should result in a relatively greater growth of the capital goods sector in the later 1980s to account
for a lag in the accelerator of demand for consumption feeding the demand for capital goods.
60
and consumer goods, mainly in the large-scale sector can increase the demand for the domestic products
of the SSE sector.6
7.
SOME INFERENCES
If survey data SHMI for three points in time is assessed (See table A5.9), we can infer the following:
–
The food sector's share in value added, assets, employment, and the number of units has increased
between 1976/77 and 1988, as expected. The data show that the textile and leather sectors have
not increased their share over this period.7 The share of the weaving sector increases in terms of
value added, assets, employment, and the number of units. This supports our hypothesis about
consumption goods produced by the SSE sector and is consistent with the landlessness and
remittance effects improving the purchasing power of the poorer sections of society with respect
to the SSE.
–
It is also clear that while the fabricated metal sector decreases its share over time, the share of
agricultural machinery increases marginally, while the textile machinery sector is born.8 All the
variables (unit numbers, asset values, employment and value added) for these sub-sectors increase.
This supports the posited income and technical change effects of the green revolution.
–
The CE 1987/88 data (table A5.17) gives the vintage of firms for three periods: pre-1970, 1970
to 1979, and 1980 to 1988. It shows that at least 70 per cent of the SSE firms in manufacturing
have a post-1980 vintage. This may reflect the short life of SSEs or a recent growth spurt.
However, at least in relative terms, the food, textiles, and wood sub-sectors have the highest
proportion of vintages for the 1970s. The metals, fabricated metals, and chemicals sub-sectors
have the highest proportion of vintages for the 1980s, which is also consistent with our hypotheses.
The above discussion suggests that many factors may work simultaneously to affect the demand of SSE
sector and that these may not always work in the same direction. For example, the remittance effect is
likely to favour the SSE more in the initial period. The differentiation of the peasantry (through
landlessness) associated with the green revolution, would largely affect the SSE sector positively. Both
these effects are likely to feed into the capital goods sector with a lag. On the other hand, the income and
technical change effects of green revolution may be biased in favour of the large-scale sector.
8.
POLICY AREAS
6
The impact of devaluation can be ambiguous, as seen in the analytical model by Mahmood (Mahmood, ILO-SAAT,
1997). As imports drop, both the large-scale and the SSE sector can gain, depending upon the demand factors and how the
landlessness and remittance effects are balanced by the technical change effect. That is, the share of the SSE sector relative
to the share of the large-scale sector in the production of consumption goods can increase, decrease, or remain constant.
Similarly, the share of the SSE sector relative to the large-scale sector in the production of capital goods can increase, decrease,
or remain constant.
7
This is probably due to the exogenously given demand for carpets whose share drops over time.
8
The technical change effect does not feed through to the SSE sector fabricated metals in general, although it must
be contributing to the increase in share of agricultural and textile machines.
61
Government policy, as a whole, towards the SSE sector is likely to fall into two categories, committed and
omitted. Committed policy is GOP attempts to help the SSE sector. Omitted policy is default policy, the
actual impact of all its macro policy for non-SSE and SSE sectors, on the SSE sector.
There are three areas in which policy of the government can be strengthened.
Credit policy
The SSE sector gets an estimated 2 per cent to 4 per cent of its credit from the formal sector, despite all
the institutional schemes - this is committed policy. However, more recent data sources like ISSMI-Small
show that formal market credit for the SSE sector may be higher, or may have increased by 1992/93 to
about 19 per cent of the units. Omitted policy is the high volume of concessionary credit mainly flowing
to the large-scale sector, which results in a disincentive to invest in the SSE sector. The net result of both
committed and omitted policy is the low levels of investment and depreciating capital base seen for the SSE
sector in manufacturing.
The provincial government credit programmes are based on subsidized mark-ups below the market rate,
and along with the GOP programmes have low recovery ratios. Subsidized credit is not viable in the long
run: it contributes to low recovery ratios and is not as important a condition for growth as access to credit.
The low recovery ratios reflect bad programme management, remote relationships with the clientele, the
latter's shortfalls in working capital and weak investment planning.
Tax policy
The SSE sector gets fiscal incentives through tax holidays for rural and under-developed areas, and
reduction in import duties and excise taxes on industrial estates. Being less import-intensive than the largescale sector, customs rebates do not affect the SSE significantly. The impact of tax holidays, and reduced
excise taxes on industrial estates also has the impact of industrial relocation rather than generating new net
investment. This is the impact of committed policy. Omitted policy is that the SSE sector has to comply
with 57 tax and regulation ordinances. Withholding taxes on 19 income sources and a turnover tax have
been added to these since 1992/93. This raises the cost of `formalization’ of the SSE sector and acts as a
disincentive. Increases in indirect taxes passed on to the consumer reduce the demand for SSE products.
A reduction in import duties through liberalization increase cheaper competitive imports for the products
of the SSE sector.
Infrastructure policy
Of the infrastructural support programme, the industrial estates programme is relatively ineffective, and
the skilling centres programme is nascent and small in comparison to its target groups.
9.
A STRATEGIC POLICY COROLLARY AND SOME SPECIFIC MEASURES
If the SSE sector is partly a refuge sector, then survival compulsions will force some SSEs to subsist in
conditions of high financial and fiscal distortions. However, within the sequencing of decision making in
the production process, the cost of the input (distorted or otherwise) will often be a secondary issue,
preceded by the first choice of what and how to produce. This first choice is based upon technology and
skilling. Moreover, technology skilling and an increase in the knowledge base can reduce the high financial
and fiscal costs caused by policy distortions.
62
Given the dichotomous nature of the SSE sector with capital, productivity, profitability and employment
(definitionally) rising discretely for enterprises employing above five workers, the provision of skilling and
credit needs to be oriented towards the different nature of these two types of enterprise. Enterprises
employing below five workers can be characterized as refuge labour and the principal constraint on their
expansion, given their SSE-internal demand, is that they are credit- starved.
Enterprises employing above five workers can be characterized as refuge capital and the principal
constraint on their expansions given their non SSE/external demand is that they are skill-starved to increase
their demand. In fact, the appropriate characteristic for each of these two types of SSE enterprises is that
they are differentiated by their principal constraint. Enterprises, employing below five workers have a
primary supply constraint-credit. Enterprises employing above five workers share a primary demand
constraint - they need to increase demand, which can only be done by increasing their skill and product
levels.9
This analysis implies that policy should direct relatively more credit towards the enterprises employing
below five workers and relatively more skilling towards the enterprises employing above five workers.
Conversely, in the first stage, the refuge labour sub-sector will not be able to absorb skilling and the refuge
capital sector will not have a primary credit constraint relative to their demand and production levels. What
good future policy must be predicated upon is a thorough study of the poor/informal/SSE sector which
identifies its heterogeneity more precisely in terms of the sector’s own perceived needs and constraints.
What is needed is a participatory appraisal (PRA) methodology applied to a conventional empirical survey
and analysis of the SSE sector.
Some specific policy measures which are likely to enhance employment and growth in the SSE sector are:
•
Elimination of subsidies in credit programmes and increasing credit lines through SSE targeted
institutions.
•
A major source of effective domestic demand, as seen in East Asia, is agrarian reform. Extending
ownership rights or making tenancy rights effective will boost the demand for SSE products.
If expansion of social infrastructure, education, health, water supply, sanitation, and shelter are
decentralized down to the sub-district level, their domestic and SSE component will increase.
Further, if community programs are associated with this expansion of social infrastructure, then
decentralization reaches the village level and the domestic and SSE component will increase even
more.
•
•
10.
The probability of export market niching increases with the skill base. This skill base should be
expanded through dedicated institutions.
UPSHOT
The main point to note from the above review is that growth rates for SSE manufacturing may not be as
high as the 8 per cent estimated by the National Income Accounts, since survey-based estimates suggest
about half this growth rate. This does not mean that the emphasis on the SSE sector for employment is
misplaced. However, nor is it as great a panacea for resolving the employment problem as its growth
estimates suggest, and we may need to direct policy as much on growth as on employment generation.
9
Institutional support programmes, even internationally like the Grameen Bank’s credit programme in Bangladesh,
tend not to discriminate sufficiently between the heterogenous segments of their poor/informal/small-scale clientele.
63
Consequently, there is little ground from a policy perspective to be complacent about SSE growth rates.
Manufacturing is around a quarter of the SSE sector in terms of employment and is much the majority in
employment for the manufacturing sector taken as a whole.
This review of existing major surveys, apart from bringing in a perspective on the growth rate problem,
also allows us to disaggregate the macro estimates derived for the SSE sector. The macro estimate we settle
on, shows the SSE sector employing approximately four and a half million workers. Characteristics
indicate the SSE to be in substantial part a refuge sector based on a spillover of surplus labour
unabsorbable in other sectors. The review also shows that trade and services account for the bulk of the
SSE sector. The SSE sector is also likely to be underinvested.
Examining small micro analyses, this ‘aggregate’ view of the SSE sector can be disaggregated. There are
some important findings. The first is that the SSE may not be one large refuge sector, but instead is
characterized by a classic dualism. The micro surveys suggest that one part of the SSE sector may
comprise firms more integrated into the mainstream economy, while the other part comprises of firms that
are more involuted. The more integrated firms are characterized by stronger demand and input linkages,
entrepreneurial decision making, better access to the formal credit market, more use of hired labour, higher
capital intensity, higher capital and labour productivity, and higher returns. The SSE displays a rich
dualism in structural characteristics.
A critical and operational result of this dualism is to have a ‘different’ policy focus on SSEs with less or
more than five persons employed. This has implications for specific policies. Targeting and improving
formal credit access and skills, simplifying tax and regulation ordinances affecting the SSE sector are
crucial supply-side measures in general, but the focus of targeting credit must be on the capital-starved,
self-contained smaller-sized firms while the concentration of training must be on skill starved, external
demand linked, larger sized ones. On the demand, side the aim should be to promote export market niches
with a skills base, to have a decentralized expansion of social infrastructure and conduct agrarian reform
which at least makes tenancy rights more effective. These would be useful measures for the promotion of
the SSE sector in Pakistan.
On a broader policy note, it should be recalled that the argument made in this report is that the growth of
manufacturing-sector employment is critical for employment growth elsewhere in the economy because of
cross-sectoral linkage effects. These are connected to the two types of demand linkages for the SSE
manufacturing sector identified in this chapter. One sort of SSE demand linkage which has been identified
is an internal one for the manufacturing sector, i.e. the sub-contracting one, which links modern-sector
manufacturing firms to SSE manufacturing. The second type of link is that which is based on direct
consumer demand, which pertains to changes occurring in the purchasing power of social groups. These
are likely to have cross- sectoral implications for other sectors. Promoting both these links is important.
Since the bulk of manufacturing employment is in the SSE manufacturing sector, it is arguable that a
decline in growth of the large-scale sector and loss of incomes (as witnessed in the 1990s) could have
adversely affected the demand side for goods produced in the SSE manufacturing sector (the subcontracting effect). Consequently, the growth of the large-scale sector could revive these subcontracting
links and increase effective demand for goods in the SSE manufacturing sector. It is through such a revival
as well as the promotion of direct consumer demand through the suggested policy measures, that
employment linkages with other sub-sectors (particularly with trade and services) could be realized.
64
CHAPTER SIX
Outline of an Employment Strategy
1. ELEMENTS OF AN EMPLOYMENT STRATEGY
This chapter marshals the main features of the employment strategy proposed in this report. As a
preliminary, it must be stated that an effective employment strategy requires as its basis reliable
information. There is a need to develop a consistent data series on the labour force and other indicators of
employment conditions in Pakistan based on existing information. In this respect, the urgency of publishing
the full the Population Census is of prime importance.
The employment strategy, as we have outlined it, has two areas of focus. The first concerns general goals
pertaining to the labour force and employment. The second concerns sectoral strategies which provide the
means of achieving these goals.
On labour force and employment
For the labour force, we have found that its size with respect to the population of working age is small. This
is clearly reflected in low participation rates. The rate of growth of the labour force has also been falling
over recent years and, though it has been lower than that of population , it is likely that this labour force
growth will pick up in the near future due to the re-absorption of the young who have opted out of it due
to education, as well as the increasing participation of women in the economy. The problems observed today
with respect to those sections of the labour force `not fully employed will be magnified in the years to come.
In other words, the widening gap between the labour force and the fully employed labour force observable
over the medium-run past suggests that, small as it is, the unemployment problem is likely to persist and
underemployment that has of late been increasing on trend, will continue to do so. The 16 per cent of the
present labour force (the unemployed and underemployed) who are 'not fully employed' are therefore likely
to increase even if the present trend of a declining labour force growth were to continue. If we expect an
increase in the growth rate of the labour force for the reasons cited above, then the situation is likely to
become worse. This is the core problem of an employment strategy.
There is a need not only to eliminate the persisting gap between the labour force and the fully employed
but to significantly increase the growth of aggregate employment in the economy as well.
There are two general implications of the above goal that this report emphasizes:
•
Preparing the labour force for the future: Since one of the reasons for the decline in the labour
force growth has been the withdrawals of an increasingly younger population due to educational
enrolment, the literacy levels in the labour force though presently low and increasing, will further
increase. The withdrawal of a younger labour force because of education today, will be mean a
swelling in the ranks of the educated labour force tomorrow. This will pose a serious employment
concern in the years to come. The prospect has implications for planning an educational, training
and skilling strategy commensurate with the abilities of a more literate labour force and the needs
of the economy of the future.
•
Improving the productive participation of women in the economy: The other feature of the labour
force and employment trends worth emphasizing is the low participation rates for women. There
can be various reasons for this, and those related to data quality and information gathering need
improvement. Nevertheless, female participation rates are very low in Pakistan, and there is need
to find out why and increase them. If this means yet another factor which increases ‘the growth
rate’ of the labour force, then there is all the more reason to address the issue of productive
65
absorption of labour from the demand side.
On sectoral strategies
The report argues that an employment strategy for the future needs to be sector-specific. It has to look to
sectors other than agriculture for increasing productive employment and focus on the manufacturing and
the small-scale enterprise sector for employment growth. The main points of the argument are presented
below.
The overview of the employment situation in agriculture suggests that over the 1970s, 1980s and 1990s,
profitability-driven cropping pattern changes based on the new technological package may have increased
labour requirements in the sector. The changing distribution of operated holdings, mechanization and
tenurial shifts may have partially adapted to, as well as reduced, these increases. The rest of the adjustment
has had to be borne by the new hired casual labour force, the size of which is increasing. The nature of this
labour force is reflected in the extent of rural underemployment, wage rates and poverty. While
underemployment is sizeable (around 20 per cent including the unemployed) it has shown signs of an
increasing trend since the late 1980s. The returns to casual labour suggest that both the levels of real wages
and the size of the non-poor in the agrarian economy of Pakistan have either stagnated or declined in the
last period for which information exists (1987-88 to 1990-91 for poverty and up to 1994-95 for wages).
At the aggregate level of analysis, it can be said that although agricultural growth performance has not been
unsatisfactory, an employment strategy for the future has to look to sectors other than agriculture for
increasing productive employment because of low and declining rates of productivity growth in the sector
and the already massive share of employment it supports. The main focus in agriculture should be to
increase agricultural productivity, which will also mean a reduction in rural poverty, a critical indicator of
rural employment conditions in agriculture.
The structural change in the agricultural sector is manifest at the level of both the production and labour
process on the one hand and the supply of agricultural labour on the other. Both these changes are
noteworthy from a policy point of view.
First, on the production and the labour process. What is significant about the growth of output and
employment in the agricultural sector in Pakistan, is not so much their rates of growth, but the changing
composition of the labour force on the one hand and the increased variability in the pattern of its production
over time, on the other. There is much greater volatility in agricultural output since the mid-1980s which
is connected to the widespread assimilation of technical changes in the rural economy, now embedded in
the production process. This translates into a fluctuating trend in the employed labour force, with the
increasing casual labour component on the receiving end of the adjustments to this volatility in output.
The second matter concerns the expanding and impoverished pool of labour reserve from which this casual
labour springs. Landlessness and near landlessness as a consequence of declining tenancy and the
sub„¼division of holdings is one element. The other may be a return labour flow into the agricultural sector
because of low growth in other sectors of the economy, especially the rural SSE sector. These tendencies
are likely to exacerbate the size of the labour reserve in rural areas, which then has to forcibly get absorbed
in agriculture as a last resort.
A policy focus which promotes growth and employment in the agricultural sector in the future therefore
needs to have as a dual aim:
•
the dampening of the relationship between the volatility of output and the livelihoods of the
workforce; and
•
making the livelihoods of casual labour within this workforce more sustainable.
66
The whole area of provisions of micro credit in rural areas to reduce the enforced dependence of a
growing labour force on the sector and related efforts for the promotion of productive rural non-farm
employment, are of immediate relevance. On the other hand autonomous expansion of employment if it is
to take place in as large a sector as agriculture, needs to be integrated with poverty alleviation
programmes.
The active focus of an employment strategy must move towards manufacturing. Manufacturing output
growth is not only strongly related to the growth of output in other sectors but to economy-wide employment
growth. In particular, it does have positive and relatively stronger linkage effects on employment growth
in most other (non-agricultural) sectors of the economy. Therefore, the greater the extent to which growth
in manufacturing is employment based, the greater will be its employment multiplier effects on the rest of
the economy. Promoting employment-friendly growth through manufacturing does have a potential problem:
employment elasticities in it are low and productivity growth during the 1990s has been associated with a
negative employment growth. The situation in manufacturing therefore, at least on the face of it, has the
problem that output growth cannot be expected to generate much direct employment. This requires us to
make critical distinction between the large-scale and small-scale manufacturing sectors.
The report argues that the manufacturing sector has a role to play in the revival of employment growth just
as it has a role to play in output growth, despite popular perceptions regarding its jobless-growth
characteristics. It has to be a lead sector from the point of view of future employment generation through
its multiplier effects. We find that trends in output growth rates suggest a decline. The 1980s were a high
growth period while the 1990s are characterized by low growth. Growth in manufacturing since the 1980s
has been driven by labour productivity as opposed to employment expansion, the last period in which
employment expansion took place was the (low growth) period of the1970s. It can be argued that output
growth began de-linking itself from employment in the 1980s and became de-linked from employment
expansion altogether in the 1990s. Part of the explanation lies in the distinction between small and large
scale sectors in manufacturing in Pakistan. It is the small-scale manufacturing sector employment which
declined in the mid 1980s while its output grew. In the large-scale sector both employment and output
growth have been positive in the 1980s and most of the 1990s. In other words, the de-linking of employment
from output growth which was taking place in the manufacturing sector in the 1980s and which was
established in the 1990s, may have been due to the overwhelming weight of the declining employment in
the small-scale manufacturing sector and not because of the large-scale sector as such.
An implication of the above is that employment growth needs to be promoted in the small-scale
manufacturing sector, while output growth needs to be revived and the low elasticity of employment
increased in large-scale-scale sector. Therefore the centrepiece of an employment generation strategy
within manufacturing should be the small-scale sector, which is larger in weight (around 83 per cent). In
contrast the primary focus of a revival of growth strategy is the large-scale sector where the bulk of
manufacturing output (around 70 per cent) is produced. It is this sectors growth which is likely to have
positive linkages with other sectors including activities in small-scale manufacturing as well as small-scale
non„manufacturing. The challenge for the manufacturing sector in Pakistan is considerable. A concerted
effort needs to be made towards increasing the low elasticity of employment as well as reviving growth.
From the analyses in this report it is also clear that a crisis of demand may be in the process of setting in
the large„scale manufacturing sector. The causes of this are complex and multiple but two issues need to
be singled out which may go some way towards explaining the slowdown of the 1990s. One concerns the
investment climate which has not only deteriorated but spread (from Karachi to the Punjab) in Pakistan
from the 1980s to 1990s. The second aspect is related to post-reform deflationary policies adopted by the
government in the late 1980s and 1990s, (which were accompanied by privatization and public-sector
retrenchments). These are likely to have dampened demand for the manufacturing sector.
A multifaceted policy initiative is required in order to revive growth in the large-scale manufacturing sector.
67
This effort in the large-scale sector needs to focus on reviving demand and improving the social climate for
investment, on increasing the utilization of existing capacity; and promoting growth in sectors which also
have a potential for autonomous productivity increases. Policies in many areas consistent with these aims
have been suggested in this report. These include suggestions on:
•
Criteria of sectoral choices in an employment friendly investment plan
•
Fiscal expansion and demand
•
The Budget deficit and working capital
•
Promotion of sub-sectors through tariff rationalizations
•
Capital pricing and directing new investment
•
The co-ordination of capital flows
•
The revival of sick industries
•
Taxation and flow of goods
•
Energy pricing
The report further argues that the sector which may still have potential for direct employment generation
is the SSE sector, there are likely to be labour„intensive activities. Dynamic sub-sectors need to be
identified in the SSE sector and practical selection criteria for support need to be developed.
For the SSE sector, a central point to note from our analysis is that growth rates for SSE manufacturing
may not be as high as 8 per cent, as estimated by the National Income Accounts, since survey based
estimates suggest about half this growth rate. This does not of course mean that the emphasis on the SSE
sector for employment is misplaced. However, nor is it as great a panacea for resolving the employment
problem as may be imagined and we may need to direct policy as much on growth as on employment
generation. It is therefore arguable that there is little ground from a policy perspective to be complacent
about SSE growth rates. Manufacturing is around a quarter of the SSE sector in terms of employment and
is much the majority in employment for the manufacturing sector taken as a whole. Since the bulk of
manufacturing employment is in the SSE manufacturing sector, it is arguable that a decline in growth of
the large„scale sector and loss of incomes (as witnessed in the 1990s) could have adversely affected the
demand side for goods produced in the SSE manufacturing sector (the sub„contracting effect).
Consequently, the growth of the large„scale sector could revive these sub„contracting links and increase
effective demand for goods in the SSE manufacturing sector. It is through such a revival as well as the
promotion of direct consumer demand, that employment linkages with other sub-sectors (particularly with
trade and services) could be realized.
The review of existing major surveys, apart from bringing in a perspective on the growth rate problem, also
allows us to disaggregate the macro estimates derived for the SSE sector. The macro estimate we settle on,
shows the SSE sector employing approximately four and a half million workers. Characteristics indicate
the SSE to be in substantial part a refuge sector based on a spillover of surplus labour unabsorbable in
other sectors. The review also shows that trade and services account for the bulk of the SSE sector. The
SSE sector is also likely to be underinvested.
This ‘aggregate’ view of the SSE sector has been ‘disaggregated’ in this report by an assessment of the
important micro surveys on the subject. There are some relevant findings. The first is that the SSE may not
be one large refuge sector, but is instead characterized by a classic dualism. The micro surveys suggest that
68
one part of the SSE sector may comprise firms more integrated in to the mainstream economy, while the
other part comprises of firms that are more involuted. The more integrated firms are characterized by
stronger demand and input linkages, entrepreneurial decision making, better access to the formal credit
market, more use of hired labour, higher capital intensity, higher capital and labour productivity and higher
returns. The SSE displays a rich dualism in structural characteristics.
A critical and operational result of this dualism is to have a different policy focus on with less or more than
five persons employed. This has implications for specific policies. Improving formal credit access and skills,
simplifying tax and regulation ordinances affecting the SSE sector are crucial supply-side measures in
general, but the focus of targeting credit must be on the capital starved, self-contained smaller sized firms
while the concentration of training demand should be on skill-starved, external demand linked larger sized
enterprises.
Government policy, as a whole, towards the SSE sector is likely to fall into two categories, committed and
omitted. Committed policy is the States attempts to help the SSE sector. Omitted policy is default policy,
the actual impact of all its macro policy, on the SSE sector. In particular, some areas in which government
policy can be strengthened with respect to the SSE have been emphasized in this report. These relate to
credit, taxation, infrastructure, training and demand creation. Some the specific policies advocated in this
report concern:
•
Refocusing committed and omitted credit policy through the elimination of subsidies in credit
programmes and increasing credit lines through SSE targeted institutions.
•
Restructuring omitted and committed taxation policies.
•
Decentralization of infrastructural programmes
•
Tying of skills and export markets
•
Creating effective demand for SSE products
On the whole employment strategy for the future in Pakistan must aim to eliminate the gap between the
‘labour force’ and ‘the fully employed’ within it. It must act not only by attacking unemployment and
underemployment head-on but by adopting policies that simultaneously and significantly increase aggregate
employment. The strategy must function at a sectoral basis. This report argues that an employment growth
strategy for the future must be built with three aims:
•
the growth of output and employment in the manufacturing sector
•
the limitation of increased labour absorption in agriculture
•
the promotion of dynamic sub„sectors within the small-scale enterprise sector
The overarching objective of these aims is to revive growth in such a way that its employment multiplier
effects in the economy are significant and there is minimum downward pressure on productivity in
agriculture. The positive focus of the strategy is based on manufacturing and the small-scale enterprise
sector. In the view taken by this report, this triadic approach constitutes the way towards an improved
employment situation in Pakistan.
69
APPENDIX
The Economic Reforms Context of Growth and Employment
1. The periodisation of growth and status of macro-economic policies
This appendix attempts to provide a macro-economic and growth context to the issue of employment in
Pakistan. A serious study of macro-economic policies and their effects on the different parts of the real
economy is a more complex and detailed exercise, which is beyond the scope of the present report. It is
however, the view taken here, that a perspective on macroeconomic policies and growth is a necessary
starting point for an analysis of the employment situation in Pakistan today. In fact, in a dynamic sense,
it may be necessary to take in to account the macro policy regime, for a revival of growth that entails
employment expansion.
The link between macroeconomic policies followed by the government on the one hand and employment
on the other, is mediated by the level and pattern of growth. In Pakistan the links between macro policies
and growth, at least until recently, have involved both economic and non economic aspects. Examining
trends over the longer historical period we find, that although macroeconomic policies undoubtedly
influenced growth, the periodisation of growth itself into high and low phases, introduces factors that are
beyond economic policy itself.
To emphasize the point about non-economic factors, and as a useful perspective on Pakistan’s growth
process, Table 7.1 attempts a periodisation of its economic and political history simultaneously. There are
many ways in which periods can be distinguished. Of the many demarcation criteria for periods of
development in Pakistan, the timing of the flow of foreign aid; the forms of political governments; the two
martial law periods (1958-73 and 1977-85); and legal-institutional watersheds such as the three
constitutions (1956, 1962, and 1973) are important markers. Another criterion, which is more economic
policy related is the set of eight Five-Year Plans – especially the Second Plan (1965-70) and to a much
lesser extent the Sixth Plan (1982-87) – which lay out strategies and policy frameworks. Since the role
of macroeconomic policies has acquired centre stage in policy debates in the economic reforming Pakistan
of today, the periodisation is also given according to both pre and post-economic reform periods. In
addition our focus within this classification is the set of macro economic policies of the early period of
reforms and the more recent years.
A brief description of the longer historical period is in order, as a starting point..The first two periods in
the Table 1.1 correspond to a Pakistan which includes what is now Bangladesh (1947-71), while the last
three periods (1971-97) correspond to the present boundaries of Pakistan1. Under pre-1971 Pakistan, four
phases can be identified: 1947-53, was characterized by reconstruction and self-reliant development; 195358 was occupied with the preparation of the First Five-Year Plan (1955-60), achieved with considerable
external assistance; 1958-65 were the “miracle” years of aid reliant development; and 1965-71 can be seen
as a period of disintegration, leading to the independence of the eastern wing of the country as a separate
nation State.
In the contemporary period (1971-97), three political phases can be readily identified. In the first, 1971-77,
an elected government sought to re-orient the path of growth that Pakistan had embarked upon in the 1960s,
and ushered in a period of greater state intervention in the economy characterized by widespread
nationalizations. In the next period, 1977-88, a military government which replaced the elected
1
70
For a detailed discussion, See ILO-SAAT/ Arshad Zaman Associates (1997).
government, undid the nationalizations of the first period. In the present phase, 1988-98 , democratic
governments returned to the country and the economy was re-oriented towards private-sector-led growth.
This period is also characterized by economic reforms which the government is now in the process of
implementing and which are the focus of this Appendix..
Table 1.1:Growth and structural change,
1950-97
1950-58a
1958-71a
1971-77
Population
2.5
2.8
3.2
3.1
3.0
Real GNP (mp) per capita
0.9
4.2
3.3
3.0
1.1
Consumer prices
2.3
3.2
17.4b
7.5
10.4
3.3
1.8
19.8
6.2
4.3
12.1
4.8
2.2
2.3
6.6
3.9
9.4
4.8
3.9
4.0
..
..
..
1.6
0.8
3.6
3.0
1.8
3.0
2.4
2.0
1.7
2.1
1.0
- 0.9
51.8
41.2
36.6
22.9
22.4
6.1
11.9
10.3
11.6
11.1
..
..
-8.6
-8.5
-6.3
-4.9
-3.2
-7.8
-5.0
-4.8
Current account deficit on the BOP (-)
..
..
-7.0
-4.4
-7.1
M&LT external debt (DOD US$ billion)
(as % of GNP)
..
..
..
..
8.3
52.6
20.0
49.9
30.0
46.6
..
(..)
0.1
(2.3)
0.4
(1.9)
0.5
(0.9)
2.5
(2.5)
1977-88
1988-97
Growth rates (% p.a. by OLS method)
Real GDP (fc)
Value added in agriculture
Value added in LS manufacturing
Employment
In agriculture
In large-scale manufacturing
Structure (% GDP, end period)
Agriculture
Large-scale manufacturing
Overall budget deficit (-)
Trade deficit (-)
Liquid external reserves (US$ billion)
(as months of merchandise imports)
Notes:
All growth rates have been calculated by fitting an ordinary least squares (OLS) trend.
.. not available.
a
(West) Pakistan only.
b
Only 11.1% (OLS, or 9.5% simple average), if 1971-72 and 1973-74 (when imported inflation was an
extraordinarily high) are excluded.
Source: Economic Surveys, Annual, and Federal Bureau of Statistics. See ILO-SAAT/Arshad Zaman Associates (1997).
The non-economic correlates of macro-economic policies and growth
In general it can be argued that in Pakistan, the degree of causality between macro policies and growth is
weak and it may be difficult explicitly inferring outcomes from the policy. The argument for the
71
importance of non-economic policy factors is straight forward. Two overdetermining correlates of the
phases of growth (high/low) in Pakistan are:
•
the timing of flows of external assistance (economic and military aid) which the State has received
over time; and
•
the performance of the agricultural sector.
It is noteworthy that both correlates are subject to external influences which are governed in part by non
economic considerations. In the case of external flows, there is a whole set of international geo-strategic
considerations as well as the nature of government, which may be of relevance. In the case of agricultural
performance, there is clearly a feature of external natural uncertainty at work. It can be argued that
throughout the almost 50-year period the volume of external assistance received (on which reliable data
is easier to acquire on the economic side) and the performance of the agricultural sector have been the
proximate determinants of economic performance. If this is indeed the case, it leads to a peculiar difficulty
in attempting any serious analysis of the impact of development strategies and macro-policies on economic
outcomes.
This knowledge of crucial external determinants at the policy level has implications for institutional
behaviour. It has meant that economic strategy and policy statements have been, at least in some measure,
motivated by a concern for maximizing foreign assistance. In particular, the nature of this relation between
‘stated growth strategy’ and ‘access to capital’ has had two specific effects on policy making in Pakistan.
One concerns state action and the other the robustness of policy itself. First, it has made plans of action
by government, subject to ad hoc executive decisions, which are not transparent. Second, and at the
analytical level, the link between ‘strategy’ and ‘outcome’, when it has been invoked, has often been a
fortuitous one, even though plan and programme reviews submitted by government to donors have on
occasion sought to establish such links.
However, in the present phase , it is precisely the adoption of specific macro-policies themselves that have
arguably come to play an influencing role in the timing of external flows. It is therefore important to assess
if these policies have performed the role that they were supposed to, given their raison d’etre.
In any periodization of the political economy of Pakistan, therefore, broader conditions for the sources and
flow of foreign assistance must constitute an important criterion of demarcation. This slightly cross-cuts
our classification of decades, the 1970s , 1980s and 1990s phases chosen for the analysis of the labour
force and sectors of the economy.
Given the external determinants of past growth and their impact on the nature of the decision making
process in Pakistan, two important symptoms of what can be termed the problem of growth and
development in Pakistan become easier to understand.
Two symptoms of the problem of growth
There are two important symptoms of the problem of growth and development in Pakistan, which need to
be singled out for the purpose of our discussion. First, the country’s economic performance has been such
that growth and structural change have not improved the lives of a majority of the population by anywhere
72
near what that growth process could have achieved. Growth has been insensitive to distribution.2 A
second symptom of the problem of Pakistan’s growth has been the government’s inability to establish a
sustainable pattern of public finance, historically relying first on foreign grants, then loans, supplemented
by domestic non-bank borrowing, and of late, even by borrowing from short-term private sources. As a
result, Pakistan faces a profile of high increasing future debt service payments. These two symptoms are
also mutually reinforcing. A growth process insensitive to distribution is complemented by the
unwillingness or the inability of the State to tax the better-off sections of society (which, in part, is what
makes the public finance structure narrow and precarious).
Assessing the policy-growth linkage
The employment situation in Pakistan, both in general and at a sectoral level, has been discussed in this
report. One central concern in this assessment pertains to the 1990s overall slowdown of growth after the
1980s boom and, in particular, the crisis of growth in the manufacturing sector. In our view, this
constitutes a critical matter to address, for any future employment revival strategy. Here we attempt a
macro policy based explanation of what happened to growth in the 1980s and 1990s.
Notwithstanding the problems in choosing the right periodization and the matter of external determinants
of growth, an basic assessment of the association between growth and macro-economic policies is at both
an aggregate as well as a thematic level is attempted below.
The aggregate assessment gauges the impact of macro policies taken together during a pre-selected period
( i.e. the reform period). The same assessment also to distinguishes between sub-periods within the reform
period. The thematic assessment on the other hand, gauges results of each type of macro policy area (e.g.
trade, fiscal or monetary policy). The latter can also be phased in terms of the pre given periodization (e.g.
trade policy in the reform period) or can move across periods (e.g. trade policy from the 1970s onwards).
Particular reform policies undertaken by government are distinct insofar as they pertain to different areas
of the macroeconomy as well as their implementation over different time periods. Finally, since the
expected effects of macro policies on growth depend, in part, on the interaction between the individual
policies themselves, it is important to look out for sequencing of reform policies as well.
The aggregate overview
For the aggregate overview, the reform policies can be taken as the ‘package’ and the reform period as
starting from when the first reform initiatives were taken up, to the present. However, in order ask the
larger question on the ‘effect of reforms’, we first need to identify some core objectives of the reforms and
then select the appropriate indicators of their performance. We list below what can be termed the three
core objectives of the economic reforms:
•
One objective is that of sustainable growth, if the reform package ‘as a whole’ works it should be
reflected in a healthy growth process which is sustainable.
•
A second objective is to achieve price stability
•
A third objective is balance of payments viability.
2
The argument which can be developed here can be based on two points. The first point is that a long history of
non-democratic periods of government entrenches State structures that are less pressured to be distribution-sensitive. Secondly,
a history of excessive reliance on external flows of funds erodes the institutional incentives to develop a progressive taxation
system to be applied on civil society in order to finance economic development.
73
Figure 1 presents trends in major macroeconomic variables since 1971, along with a demarcation of the
periods identified (for data on period averages, see Table 7.1 above).3 We have separated the reform from
the pre-reform period. Moreover, the reform period has been divided into two sub-periods. It is the case
that one phase of the sub-division can be associated with the part of the 1980s in which manufacturing
growth occurred. In terms of a reform history, the first reform period marks the first extended fund facility
(EFF, 1980-83) obtained for debt rescheduling from the International Monetary Fund (IMF) by Pakistan.
In 1982, the World Bank (WB) also extended a structural adjustment loan (SAL) to complement the IMF’s
EFF,4 which was later abandoned and then followed by two sectoral adjustment loans (SECALS). The
third period (from 1988 to the present) has been characterized throughout by intermittent long-term
arrangements with the IMF.5
The indicator on economic growth
The data represented in Figure 1 suggests that there has been a downward drift in the rate of economic
growth, on average at least since the mid-1980s. Therefore, for the initial part of the 1980s, it can be
argued that reforms, to whatever extent they were occurring at the time, did not harm growth and may have
enhanced it. In fact, if we recall the data on large scale manufacturing in Chapter Four, the bulk of the high
growth during the 1980s was in 1982-83 and 1987-88 (the growth rate in this period was 8.2 per cent).
Since the reforms affected large scale manufacturing more directly than other sectors, a growth-enhancing
relationship can be posited for this period.6 By the same logic, the next period is one of economic
slowdown and declining growth, which can be associated with the nature of reforms undertaken in that
second phase.7
3
Because annual data is presented we can do different periodizations. We have also stated on the x-axis a
classification based on reforms and forms of government.
4
The SAL broke down eventually because of differences between the government and the lender. Accordingly, it
was followed by sectoral adjustment loans (SECALs) in energy (1985) and export development (1986). The latter was a
compromise option, as the government was not prepared to accept the trade liberalization measures being proposed by the WB
for a trade sector loan at the time.
5
The government has presently negotiated a US$1.6 billion extended structural adjustment facility (ESAF) and EFF,
with a first tranche of US$200-250 million.
6
It is of course possible to argue that the reforms undertaken in this period were ‘soft’, and this freedom of not
being forced in to taking ‘hard’ options was due the political and diplomatic relationships that Pakistan enjoyed internationally
at the time.
7
We will see later, in a thematic assessment, that exchange rate reforms and import liberalization (non-tarrif barrier
removal) were the focus of the first period and financial sector liberalization and tariff reforms the added focus of the second.
74
Figure 1: Growth, Inflation, Unemployment Rate, Budget Deficit & the Current
Account Deficit on the Balance of Payments
State Capitalism /
Reform
Reform Period II /
Elected
Period I /
Elected Governments
Government
Military Government
35
1st
EFF
10
30
20
6
15
4
10
1996
1994
1992
1990
1988
1986
1984
1980
1978
0
1976
0
1974
5
1972
2
per cent
25
8
1982
Deficit (% of GDP)
12
Fiscal Years Ending June 30
Budget Deficit
BOP Deficit
Grow th
Inflation
Unemployment Rate
The indicator on price stability in the economy
There has been a secular upward drift in the rate of inflation, during the later reform years. Inflation fell
below 5 per cent in 1987, but has been rising sharply since then. It is the second reform period which is
associated with rising prices. It is to be noted that these trends on performance indicators appear to be
independent of the size of the budget or the balance of payments deficits - although, naturally, it is
counterfactually arguable that higher deficits would have led to higher inflation and lower growth.
Indicator on external balance
On the count of the balance of payments situation, Pakistan continues to seek extraordinary external
finance despite over ten years of adjustment programmes, as figure 7.1 shows.
Indicators on labour market conditions
It is useful to review the results in Chapter Two, of the indicators of labour market conditions in Pakistan.
Although improvement here may not be an explicit reform objective, labour market conditions have been
affected in the period and are a central concern for the ILO. The rate of unemployment rose after 1975,
stabilized (at around 5 per cent) from 1979 to 1990 and, given comparability problems, is unlikely to have
declined since then. We have, however, seen in detail (in Chapter One) the underemployment situation as
well, which is a better indicator of employment conditions and, in our assessment, this situation is not
improving. Indicators on poverty and wages (in Chapter Two), which are probably even more
comprehensive signals of labour market conditions in countries where formal labour markets are limited
in scale and scope, show a deterioration in the 1990s.
The overall assessment of the reform experience in Pakistan, taken across sub-periods, therefore requires
circumspection. It is clear from the above evidence that adjustment programmes may not have been able
75
to achieve at least three of their main aims: (i) sustainable growth; (ii) price stability; and (iii) balance of
payments viability – in the sense that at the end of the programme there would be no need for further
extraordinary external financing. In addition, labour market indicators of employment conditions have
deteriorated in the recent period. However, on balance, it also seems clear that it is the second period of
adjustment that has been characterized by falling growth, rising inflation and worsening employment
conditions, while in the first period the economy had performed better.
On the evidence of these indicators, we need to look more closely at the type and nature of reforms being
undertaken in the first period, largely covering the 1980s and those in the second period (from the late
1980s to the present). This is a periodic demarcation which is suggested by the distinctness of the indicators
of achievement in the two periods and brings us directly to the thematic analysis referred to above, the
focus of the next section.
7.
A THEMATIC ASSESSMENT
On the sequencing of reforms and the reform policies
Why have the achievements of the reform package been so modest in Pakistan? One argument is that the
sequencing of reform policies is as critical as their content, and that there has been improper sequencing
of reforms in Pakistan. There is ample evidence from both IMF/WB studies and from independent research
that macroeconomic stability - which in Pakistan also means budgetary stability is an essential precondition
for the success of economic liberalization.8
Unfortunately, in the face of binding political constraints to budget and institutional reform (especially
when democratically elected governments are in power) international lending and financial agencies,
possibly facing their own operational exigencies, have gone ahead with such “reforms” as the government
could agree to. This may have occurred even though the sequencing conditions considered important for
the success of these reforms may not have been met.
There is much to be said about sequencing, although it must be emphasized that the argument invoking
a sequencing failure is agnostic on the validity or appropriateness of the individual policies whose
sequencing is in question. These must be assessed on their own merit. In other words, correct sequencing
is only a necessary condition for reform success; the individual reforms must also be suitable for the
country involved. This is important to bear in mind because of a tendency in policy debate to use
“sequencing failure” as a reason to ignore the assessment of individual reform measures.
Having noted the important issue of sequencing, which will be illustrated by example later, we now
examine three thematic areas of intervention by government which circumscribe the main reform agenda.
These pertain to fiscal policy, monetary policy and the trade regime.
8
76
See Thomas et. al., 1991.
Fiscal Policy
Fiscal policy can be seen as a set of measures taken by the State, that are concerned with income and
expenditure of government. On the income side, there is direct revenue generation (taxation) and deficit
financing; the expenditure side is self-evident. In the absence of a formal model, we use the likely key static
first-round effects of the impact of fiscal policy on economic growth as described in the following
processes:
•
government revenues reduce disposable income and hence private savings, private investment and
growth. The effect on growth is therefore likely to be negative;
•
deficit financing, which absorbs a large share of private savings and raises interest rates, reduces
investment and growth (among other effects). Thus the growth effect is also likely to be negative;
•
government expenditures can lead to domestic income redistribution, incremental demand for goods
and services and capital formation, all of which should have a likely net positive impact on
investment and growth, depending on the level and composition of government expenditure. So the
growth effect is likely to be positive.
In principle, the tax-revenue effect and the deficit financing effect are negative and the expenditure effect
is positive. Consequently, in principle, as long as fiscal policy is also redistributive, the expenditure effect
can be made to dominate the expected negative tax and deficit-financing effects. It should be recalled that
in the opening section we noted two symptoms of the weakness of the growth process in Pakistan: namely
that it was insensitive to distribution and relied on a narrow base of public finance. This combination is
clearly not conducive to a growth-enhancing fiscal policy thrust.
Government revenues in Pakistan have remained at around 17 per cent of GDP for a very long time - the
higher budget targets for the present years are unlikely to be attained. Also, the direct impact of the
revenue-effect on disposable incomes and saving has not been onerous. The bulk of tax revenues, however,
arise from indirect taxes, mainly import duties; their effects on industrial incentives will be examined
further in our discussion of trade policy. Over the last decade, sales tax (mainly as a surcharge on import
duties) and excise duties (collected mainly from a few items) have grown. On balance, however, the average
burden of taxation has been moderate, although the incidence of salaried tax-payers already in the tax net
had become quite high. This has been corrected in the 1997-98 budget.
The major impact of the budget on investment and growth, however, has come from expenditures and their
non-revenue financing. First, the accumulated burden of inadequate taxation has led to an unsustainable
rise in the debt burden so that, over the decade, debt service payments have been growing, at a rate of
nearly 20 per cent per year.
As a result of the rising burden of debt service payment and government expenditure on defence,
development and civil administration have been severely curtailed. Clearly the restriction on development
expenditure is not without social costs, particularly when indicators of labour market conditions are also
worsening. The decline in public investment has arguably had both a direct impact on capital formation
and an indirect one on conditions of work through inadequate provision of public goods (especially the
physical and social infrastructure). Also, as the government has sought to mobilize increasingly higher
amounts of money from the capital markets, interest rates have risen and private investment incentives have
deteriorated.
77
Table 2:
Indicators of fiscal policy, 1980-97
1979-80
1987-88
1994-95
1995-96a
1996-97b
Structure (as % of GDP)
Revenues
16.4
17.3
16.9
17.5
18.7
Expenditures
23.3
26.7
22.8
23.9
22.7
Debt service
4.6
6.8
8.7
8.7
9.3
Foreign
3.4
3.2
4.4
4.1
4.5
Domestic
1.2
3.6
4.3
4.6
4.8
Defence
5.4
7.0
5.6
5.5
5.2
Development
9.3
6.9
4.4
4.3
4.2
Administration, etc.
4.0
6.0
4.1
5.4
4.0
6.3
8.5
5.6
6.3
4.0
3.3
6.6
4.0
5.1
3.3
Non-Bank
0.6
4.5
2.6
2.7
2.5
Banking System
2.7
2.1
1.4
2.4
0.8
3.0
1.9
1.6
1.2
0.7
Public Debtc
..
73.9
79.0
79.3
..
External debtc
..
33.0
36.5
37.3
..
Domestic debt
..
40.9
42.5
41.9
..
17.5
7.7
29.4
21.9
..
Overall deficit
Domestic financing (Net)
External financing (Net)
Memorandum (as % of GNP):
External liquidity (as % of imports)
Notes:
Consolidated federal and provincial government budget figures, as presented by the Ministry of
Finance in their Economic Survey. In the past few years, these figures have differed from those
presented by the State Bank of Pakistan (SBP) in its Annual Report. The overall deficit is the difference
between revenues and expenditures plus the surplus of autonomous bodies (not shown).
.. not available.
a
Provisional actuals.
b
Budget estimates.
c
Outstanding and disbursed.
Source: Economic Survey 1996-97, Statistical Supplements, and SBP Annual Reports.See ILO-SAAT/Arshad
Zaman Associates (1997).
78
25
2500
20
2000
15
1500
10
1000
5
500
0
0
1991
1992
1993
1994
1995
Fiscal Years Ending June 30
LT Debt
LT Debt Service
US$ million
US$ billion
Figure 2 External Debt & Debt Service
1996
ST Debt
ST Debt Service
Thus, the pattern of government expenditure has become less growth-enhancing and has relied for its
income more on non-revenue-based deficit finance. The net impact of the government’s fiscal operations
especially in the 1990s, has therefore been to contribute to macroeconomic instability and lower the rate
of investment and growth.
Monetary Policy
Monetary policy primarily affects investment and growth through its impact on incentives to save, invest
and produce. It does so mainly by ensuring that credit is available, at as low interest rates as possible, in
a stable macroeconomic environment. Until February 1994, when the State Bank of Pakistan Act, 1956
was amended to give the State Bank greater autonomy, monetary policy in Pakistan was conducted largely
to accommodate the financial requirements of government.9 It is still too early to predict the impact of this
new autonomy on the government’s future conduct. Although early signs suggest possible areas of conflict
between an elected government’s need to facilitate its own access to capital and a central bank’s
responsibility to have a broader economy-wide stability as an objective10 . In the past, however, the role
of monetary policy per se had been minor, as the State Bank’s intervention in financial markets had
consisted mainly of the direct regulation of credit, in support of the government’s economic objectives.
9
The State Bank of Pakistan Order 1948 was succeeded by the State Bank of Pakistan Ordinance of 6 July 1955
(converted to an Act of 18 April 1956).
10
According to Hasan (1997, p. 10): “…reliance on credit controls has not disappeared completely although formal
credit controls no longer exist. In practice, formal controls have been replaced by equally effective jawboning [i.e. making firm
‘suggestions’ which are carried out for fear of offending the authorities] when a bank’s credit expansion gets out of line in the
opinion of the authorities.”
79
There have been three major landmarks in the history of credit regulation in Pakistan11. More recently, in
1990-91, under a Financial Sector Adjustment Loan (FSAL) from the World Bank and technical assistance
from the IMF, a transition from instruments of direct control over credit to indirect influence of monetary
aggregates (mainly through open-market operations) was effected.12
Whether it had other costs or not, there should be little controversy in assuming that the direction of credit
flows to priority sectors led to an improved fulfilment of the government’s priorities: promoting investment
and growth, and partly meeting its distributional objectives. At the same time, there is considerable
evidence that without prior budget reform, financial – sector reform can be seriously counterproductive.
In the context of Pakistan, this essentially translates into putting in place legislative constraints to fiscal
indiscipline. It is reasonable to argue that financial-sector liberalization was premature. Whatever impact
it had on the efficiency of the banking sector,13 the rise in interest rates that followed had disastrous
consequences for the budget,14 and may have led to a crowding-out of genuine private investment.
The idea that, by confronting government with higher interest rates, the government’s recourse to non-bank
domestic borrowing would be curtailed, was flawed from the start. In the event, after the switchover to
market-based instruments, recourse to domestic non-bank borrowing - after turning negative in the year
of the switchover, 1991-92 - rose rapidly, and at higher rates of interest (Figure 7.3).
The common-sense view was that without putting in place effective constraints on budgetary indiscipline,
financial sector liberalization would lead to higher interest rates and hence a rise in the government deficit.15
On the basis (presumably) of a judgement that budget deficits could be controlled, the financial sector
liberalization was supported through substantial loans. Surprisingly, and on a priori reasoning, it was
held that the higher interest cost on market-based government borrowing (estimated at Rs 3.2 billion over
the nine-year period 1985-86 to 1996-97) would be offset by lower
11
First, there was the Credit Inquiry Commission of 1959 and the Credit Inquiry Committee of 1962 , that provided
the State Bank of Pakistan (SBP) with clear directions to micro-manage the process of credit distribution - to primary-producing
sectors, and small and medium-scale enterprises – through the establishment of new institutions. Second, under the banking
reforms introduced in May 1972, elaborate institutions, consisting of the National Credit Consultative Committee (NCCC) and
its sub-committees, were set up to ensure that the credit needs of specific sub-sectors were met.
12
As distinct from monetary policy, the financial sector in Pakistan was affected by three major developments in
the banking sector. First, the establishment of United Bank Limited (UBL) in 1959 introduced the culture of aggressive deposit
mobilization in commercial banking in Pakistan. Second, the nationalization of banks on 1 January 1974 inaugurated an
eventful era of government control over banks. This era came to a close in 1991 when the government partially disinvested
two nationalized banks, and granted licenses to 10 new private banks, while 6 investment banks (licensed earlier in 1989)
started operations.
13
Serious questions can be raised about the contribution to higher profits of inadequacies in banking supervision
and regulation and the lack of competition in the banking sector.
14
High interest rates have also inhibited private investment, although there have been other non-economic reasons
for this as well.
15
In an important report, the World Bank (1987, vol. 2, pp. 6-7) also stressed the need for “careful sequencing” of
reforms – identifying price stability and the maintenance of external balance, through deficit reduction, exchange rate action,
and conservative monetary policies, as pre-requisites for the success of trade reform, financial sector reform and deregulation
– and warned that “financial sector reform will not be successful unless accompanied by reduction in the budget deficit.”
80
short-term rates on national saving schemes and greater dividends and taxes from increased earnings of
the banking sector (estimated at Rs 14.5 billion):16
‘‘Overall, the government would gain Rs 17 billion, over a nine year period, (US$100
million equivalent per year) if it pursued the proposed strategy as against following the
existing financing pattern.” (Underlining in original)
These expectations did not materialize. First, budget deficits did not decline progressively from 8.7 per cent
of GDP in 1986-87 to 4.2 per cent in 1996-97, leading to much larger borrowing requirements than had
been anticipated. Second, the rise in interest rates on domestic public debt envisaged - from 11.2 per cent
in the base case to 11.67 per cent in the recommended (staged introduction of market-based borrowing)
case – proved unrealistic. Both the interest cost and the stock of government domestic debt rose much
faster, as figure 7.3 shows.17 Finally, the assumption that government would be able to “earn an additional
Rs 14.5 billion through higher earnings of SBP/NCB [State Bank of Pakistan/Nationalized Commercial
Banks]” proved to be incorrect.18
Consequently, monetary policy as far as it brought in financial sector liberalization, led to an interactive
sequencing problem with respect to fiscal policy, and this has been an important cause of macroeconomic
instability, the drying up of investment and the slowdown in growth.
14
12
10
8
6
4
2
0
Rs billion
1000
800
600
400
200
1996
1995
1994
1993
1992
1991
1990
1989
1988
1987
0
% per year
Figure 3 Domestic Debt: Interest Rate & Stock Outstanding
Fiscal Year Ending June 30
Outstanding Debt
16
Interest Rate
World Bank 1987, vol. 1, p. 27.
17
Figure 3 is based on data provided by State Bank of Pakistan (1996, p. 91). The interest rate is estimated as the
ratio of interest payments to the stock of debt outstanding at the end of the previous year.
18
This was compounded by the fact of an early disinvestment of some of the banks and the losses absorbed by the
State Bank on the provision of forward exchange cover [i.e forward selling of foreign exchange at a fixed rate].
81
Trade and exchange rate liberalization
The second area where the government undertook reforms, pending meaningful action on the budget, was
that of external finances. These involved exchange rate depreciation, trade liberalization (i.e. reduction of
non-tariff barriers) and tariff reforms (i.e. reduction - and the lowering of dispersion – of import duties).
These matters need to be assessed separately.
Exchange Rate Reforms (1982- )
In February 1982, as part of the first Extended Fund Facility (EFF), Pakistan de-linked the rupee from the
US dollar, and initiated the current regime of the managed float.19 The immediate motivation for
devaluation or depreciation of the rupee has always been to shore up foreign exchange reserves, even
though of late the action is sometimes justified as having a beneficial long-term impact on resource
allocation.
There is, however, some controversy about the efficacy of exchange rate action in Pakistan’s
circumstances. First, it can be argued that unless there is prior action to curtail excess demand arising from
the budget – demand for debt service or military expenditures which are insensitive to the exchange rate
– a lowering of the exchange rate merely exacerbates budgetary pressures without alleviating the root cause
of macroeconomic instability. Second, given that the demand for Pakistan’s major exports (cotton and
cotton-based textiles and garments) is relatively price-inelastic, a depreciation of the rupee does not lead
to a rise in export receipts. Finally, and more generally, structural rigidities in factor markets inhibit a
reallocation of resources (from non-tradeables to tradeables), which are necessary to realize the fuller
efficiency gains from currency depreciation. Figure 4 presents the basic data on nominal and real
(consumer price index deflated) exchange rates and the trade and current account deficits on the balance
of payments (as ratios of GDP).
Despite the heavy nominal depreciation of the rupee, in real terms the rate of exchange has remained fairly
constant. On the “before-and-after” assessment, it would seem on balance that exchange rate depreciation
has not had any appreciable impact on external deficits. On a “counterfactual” reading, however, it can be
maintained that had the nominal value of the rupee been maintained at a higher level the deficits would have
been larger. There is probably some positive impact of currency devalution on the the deficit.
Basically, the argument for devaluation resulting in a feedback mechanism for an export boom has not
materialized. This argument assumes a structure of exports which is essentially different from Pakistan’s.
Clearly, exchange rate reforms were not sufficiently drastic to alter the structure of incentives in production
and ensure a smooth transition between tradeable and non-tradeable production in the economy. The
budgetary effect of exchange rates has been adverse and is mainly felt through price-insensitive items such
as defense and debt repayments.
19
In historical terms, the exchange control system inherited at independence in 1947 was modified by two major
external developments in the initial years (1947-55): the devaluation of the British pound, and consequently of a number of
sterling area currencies, in 1949; and the Korean War boom and following slump of the early 1950s. Pakistan first devalued
the rupee in 1955, and following setbacks in exchange and trade liberalization (pursued during 1959-65) once again in 1972.
82
0
5
10
15
20
25
30
35
40
45
12
% of GDP (mp)
10
8
6
4
2
1997
1996
1995
1994
1993
1992
1991
1990
1989
1988
1987
1986
1985
1984
1983
1982
1981
0
Exchange Rates (Rs/US$)
Figure 4. Exchange Rate (Rs/US$) & External Deficits (% of GDP)
Fiscal Years Ending June 30
Trade Deficit
Nominal Exchange Rate
Linear (Current Account Deficit)
Current Account Deficit
Real Exchange Rate
Trade liberalization (1983- )
Non-tariff barriers
Traditionally, non-tariff barriers (NTBs) were used in Pakistan to curb imports in the face of acute
shortages of foreign exchange. In time, they were justified on grounds of industrial promotion, even though
their adverse impact on government revenues (and efficiency of resource use) was recognized. Until 198283, only those goods could be imported which were on the “free” list (for which imports were allowed,
subject to quantitative restrictions (QRs), after obtaining an import license) or the “tied” list (which
regulated mainly public-sector imports from specified sources).
Under the first EFF, the government agreed to a radical change in its import policy. In 1980, 406 of 435
products on the free list were subject to QRs. As part of its agreement with the IMF, by 1983 the
government had reduced these QRs to 5, and by 1985 no product was subject to QRs. Even more
significantly, the 1983 import policy replaced the free and tied lists with a “negative” list (and a
transitional, “restricted” or “conditional” list),20 leaving all items not on the two lists to be freely
importable. Initially, the negative (and the conditional) list was quite large. Over the years, however, and
especially since 1988, these lists have been narrowed parallel with successive IMF agreements.21 In recent
years, the import licensing requirement has also been removed so that an importer can open a letter of credit
with a bank and import any of the importable goods.
20
The restricted list was a revised version of the tied list and sought to protect Pakistan’s trade commitments under
a variety of bilateral agreements.
21
The bulk of the reduction took place in 1987-88 and the next three years, respectively: 136, 169, 70 and 97 items
were removed from the negative list, and 10, 51, 20 and 43 items, from the restricted list.
83
What has been the impact of the removal of NTBs? While increased efficiency of resource use is hard to
document, trade liberalization has certainly led to an increase in government revenues from import
duties on previously banned imports. This gain however, has been at the expense of increased imports, and
the loss of an instrument of strategic intervention in trade policy.
Tariff reforms (1990- )
One major thrust of the adjustment programmes in the second period has been the reduction of import
tariffs and the elimination of export duties. The purported objective is a reduction in effective protection
rates (EPRs), and in the dispersion of EPRs.
Figure 5 is a visual representation of the share of customs tariff line items in the (most favored nation,
MFN) statutory tariff rates in (fiscal years ending June 30) 1982, 1990, 1993, 1996 and 1998.22 In addition
to the tariff slabs represented in Figure 7.5, the coverage of specific tariffs fell from 4.1 per cent in 1982,
to 2.3 per cent in 1990, but rose to 2.6 per cent in 1993 (to meet revenue needs), before falling again to 1.3
per cent in 1996 and 1.2 per cent in 1998. As a result of these changes, in the same four years, the average
rate of import tariffs fell from 79.2 per cent, to 59.8 per cent, to 58.2 per cent, to 44.3 per cent, while the
dispersion in these rates was reduced from 49.8 per cent, to 33.9 per cent, to 24.6 per cent, to 23.1 per cent
(and the coefficient of variation from 62.9 per cent in 1982 to 51.3 per cent in 1996). In addition to tariff
reductions, adjustment programmes have sought to reduce (and eliminate) the numerous exemptions and
concessions provided to specific commodities, plants, industries, and even importers.
Figure 5. Tariff Reform, 1982-98
% of lines
60
1982
40
1993
20
1998
0
Free
15
25
35
45
60
75
85
120
160
200
300
M FN Statutory Import Tariffs (%)
On the export side and unlike the matter of reduction of import tariffs, there is greater unanimity of views
among economists that a good case exists for imposing export duties where the exporting country enjoys
some degree of monopoly power in the export market. Even when this is not so, there is a case for collective
action by developing countries. This is a fairly credible position to take. 23
22
Data up to 1996 are from Arshad Zaman Associates (Pvt.) Ltd. (1997, p. 63), data for 1998 are estimated from
Government of Pakistan, Import Policy Order 1997-98, Ministry of Commerce, 1997.
23
John Williamson (1991, p. 74). (Williamson is now the Chief Economist, South Asia Region, World Bank.)
writes: “Every economist knows that for a country with monopoly power in world trade, equalization of domestic resource costs
would require an ‘optimum tariff,’ but the relevance of this principle for developing countries is denied on the grounds that
they do not possess any significant monopoly power. Although that is true for individual countries, it is not true for developing
countries collectively (most notably beverages). A common export tax on those commodities, by enabling low-income countries
84
The government has eliminated all export duties, despite the fact that Pakistan enjoys considerable
monopoly power in 8 export items (at the Standard International Trade Classification, SITC, 3-digit level)
which account for 52.6 per cent of its 1990-91 merchandise exports (see Table 7.3 below). Clearly, there
is a case on both revenue and trade policy grounds for reconsidering the government’s policy of eliminating
export taxes on these items.
Table 3:
Pakistan’s major exports, among 70 leading commodity exports of developing
Countries at the SITC revision 2, group (3-digit) level
As percentage of
SITC (Revision 2) Code
World
1990-91
Value
Country
Developing
World
Commodity Group
Rank
(US$ ‘000)
Total
Countries
Total
263
Cotton
1
560,626
8.17
13.25
6.58
611
Leather
6
244,339
3.56
7.30
2.71
651
Textile yarn
2
1,222,853
17.81
13.57
4.99
653
Woven man-made FIB fabric
7
429,189
6.25
3.93
1.75
655
Knitted or crochetted fabric
9
50,357
0.73
1.39
0.69
658
Textile articles NES
2
632,691
9.22
12.96
6.83
848
Headgear
clothing
8
340,379
4.96
5.07
3.40
894
Toys, sporting goods, etc.
10
132,111
1.92
1.27
0.58
Source:
non-textile
United Nations, Handbook of International Trade Statistics, 1994, New York: United Nations.
See ILO-SAAT/Arshad Zaman Associates (1997).
What has been the overall impact of trade liberalization and tariff reforms on growth and employment?
First, there has been a fall in government revenues – even though it has been compensated by a
diversification of the structure of government revenues. Second, there has been a rise in import payments
due to cheaper imports. Third, a reduction in protection to industry has affected industrial output and
employment adversely. On the exports side, there is a case to be made for an unnecessary loss of duties
on certain critical items, which are a much needed source of revenue.
9.
UPSHOT
Whereas international circumstances of resource flows (a critical correlate of growth phases in Pakistan)
have changed over time, macro policies remain an important consideration in the present period of
economic reform, precisely because the adoption of these policies have become a correlate of the timing
to redistribute income toward themselves at the expense of the rich, seems to me worthy of encouragement rather than the
reverse.”
85
of the resource flows themselves. This is apparent especially in the successive reform that the country has
gone through.
First, there is a question to be raised on the appropriateness of some reform policies to Pakistani
conditions. This is especially so for those pertaining to the trade regime. Second, there has also been a clear
sequencing problem in the implementation of some reform policies that have adversely affected the stability
of the macroeconomic environment and, therefore, growth. This adverse impact on the economy has worked
largely through the budget itself, from its direct and indirect impact on macroeconomic stability, to the
investment climate and then ultimately to growth and employment. With budget reforms politically
infeasible, what happened in Pakistan in practice was that, in return for balance of payments support, such
“reforms” as could be carried out were carried out. The sequence in which some of these policies were
implemented was insensitive to the institutional and structural realities of the country’s political economy.
We can also demarcate the basic differences in the policies of the two sub-periods of reform, the second
of which was the more difficult one as by that time Pakistan was arguably weakened in its geo-strategic
position due to changed international circumstances.
In the first instance (which began with EFF 1980-83) the major movement was on exchange rates and
import liberalization, along with disinvestment, deregulation, and privatization. Clearly, as stated, these
were also times when resources flowed into Pakistan easily. It can nevertheless be argued that
disinvestment, deregulation and privatization had an initial beneficial effect on the private sector and the
industrial growth climate of the time.
Over time, and by the second phase of reforms not only did the direct effect of fiscal contraction in
productive public investment lead to a decline in capital formation, but the government’s revenue base
persisted in remaining very narrow. Its continued non-revenue-based financing of expenditure in the
changed, financially liberated internal capital market environment, led to a very serious crisis of domestic
debt in this second reform period. This crisis, apart from starving the private sector for resources, has
contributed to the macroeconomic instability facing the country today.
On the monetary policy front, it is again the interaction of the liberated financial sector’s soaring interest
rates and government’s propensity to borrow which has been the most explosive.
Exchange rate reforms, due to the structure of exportable items produced in Pakistan, may also not have
had the desired effect of substantially boosting Pakistani exports, for which demand in general is relatively
price inelastic. On the other hand, the devaluations have put serious pressures on the budget, owing to the
price-insensitive ‘necessary’ expenditures embedded in it.
Trade reform has increased government revenues on import duties, but imports have also increased, and
exports have not picked up. There is a gradual loss of revenue, associated with the removal of tariffs. The
removal of all export duties, on the other hand, may not have been necessary, and has been done in some
haste.
With hindsight, it seems that in the absence of prior budget reforms, both tariff reform and financial sector
liberalization may have been premature, but in particular it was the financial-sector reforms in the second
reform sub-period which are likely to have significantly contributed to the present crisis of growth.
What can be said about the macroeconomic policies and employment? Clearly, some links have been
established between the macroeconomic policies adopted and the slowdown of growth in the 1990s. It has
86
also been argued separately in this report that the employment problem can best be addressed with a growth
revival strategy. This is the subject of the rest of the rest of the report.
There are a few policy lessons that need to be further explored and constitute areas in which follow-up
work is urgent.
•
First an attempt must be made to minimize sources of macroeconomic instability that arise from the
actions of government itself.
•
Second, trade policy has to be reassessed in the light of maximizing gains for the country given its
production structure, as opposed to hoping that market signals on their own will transform and
diversify the production structure. There is obvious room here for expanding the revenue base for
government without adversely impacting output.
•
The focus of government expenditure should be on growth-enhancing and demand-generating
activities that have a strong re-distributive side.
•
Lastly and most critically, a central aim of the government should be to produce and develop a new
breed of employment-friendly alternative adjustment programmes. These must examine the
feasibility of expansionary macroeconomic policies in Pakistan and be used as working documents
for negotiation with donors, carrying explicit improvements on social indicators as part of their short
and medium-run goals.
87
ANNEXES
88
CHAPTER ONE
ANNEX 1.1: SOURCES OF DATA ON LABOUR AND HUMAN RESOURCES
Agencies
Type of Data
Federal Bureau of
Statistics (FBS)
Labour force surveys, censuses of manufacturing industries, household income
and expenditure surveys, Inquiry on Labour Welfare, Establishments
Inquiry, wage rates of unskilled agricultural workers, labour productivity
indices in selected industries, wage rate survey of manufacturing
establishments, wage rates of construction workers in cities, and many adhoc
inquiries, surveys, etc.
Population Census
Organization (Decennial)
Conducted in 1951, 1961, 1972 and 1981.
Agriculture Census Org.
(Decennial)
Agriculture Census: 1962, 1972, 1980, 1990. Mostly data on family
Org. (Decennial) : members and use of hired labour family workers.
Provincial Bureau of
Statistics (Punjab & Sindh)
Employment and wages in manufacturing sector, teaching staff, health
personnel, number of posts by Basic Scales in the Budget, number of persons
migrated abroad.
Ministry of Industries
Category-wise employment, salaries and wages Annual Report of Public
Sector Industries.
Management Services
Division
Census of Federal Government Civil Servants (Triennial).
Year Book of Information
(Railways)
Annual data
employment.
Registrar Pakistan Medical
Council
Data on medical and para-medical personnel registered.
Registrar Pakistan
Engineering council
Data on engineers registered with the council.
Annual Reports of
Corporate Bodies
These reports provide information on employment, wages and salaries and
social security benefits etc.
Economic Advisers Wing,
Ministry of Finance
Economic Survey and Annual Reports (now discontinued) of Public Sector
Corporations.
Research Institutions
Data generated through research, and special surveys and studies on
employment, poverty alleviation, human resource development and wages.
PC-I of Projects
PC-I of Development Projects(Part-C)contains information on labour
requirements by major occupation groups.
on persons employed by Departments and total cost of
A cursory glance of the list of agencies and the types of data generated by them would give an impression
that labour market information system in Pakistan is well developed and integrated and that most of the
information required for policy formulation and research is available. However, this is not the case and the
real problem emerges when one attempts to use and analyze the data. Official statistics suffer from serious
definitional and measurement problems and also render the inter-temporal comparison difficult. Specialized
89
studies exist but are usually too limited in coverage to be representative. Some comments on the available
data are given below:
•
Decennial population censuses constitute a major source of information on population and civilian
labour force. An inter-temporal comparison of the censuses data can neither be made between
censuses themselves nor with other surveys, as surveys are not undertaken in the census year. For
example, unlike the 1961 census where total enumeration was used to obtain data on employment,
in subsequent censuses data on employment was obtained through sample surveys. The last census
was conducted in 1981.
•
Agriculture censuses conducted every ten years, provide data on the use of hired labour, family
workers, and economically inactive family members. The coverage of data is confined to
employment in agriculture and livestock activities. The rural agriculture employment estimated on
the basis of agriculture census differ widely from data obtained through other sources in number
as well as in concept. The characteristics of employed persons are restricted to the total number
of hired labour and family members sub-divided in full time and part time workers.
•
Labour force surveys carried out by the Federal Bureau of Statistics since July, 1963, constitute
the most commonly used major source of information on labour force and employment. The
survey is based on a representative sample. However, the labour force participation and
unemployment rates obtained through these surveys do not show any significant changes over the
period.
Pakistan has been using the “labour force approach” recommended by the ILO to define economically
active, employment and unemployment. The sample size and inadequacy of the concepts used, may have
influenced the quality and size of data generated through these surveys. Moreover, the Federal Bureau of
Statistics have also been changing the concepts. The 1990-91 round is based on new questionnaire
developed in the light of ILO recommendations made at 13th International conference of Labour
Statisticians in 1982. A comparative picture of old and new definition of labour force concepts is given
in table A1.2.
For example, the share of agriculture, animal husbandry, forestry and fishing in employed work-force
jumped from 14.2 per cent in 1987-88 to 46.6 per cent in 1990-91, while that of production and related
workers dropped from 58.4 per cent to 26 percent. Similarly the crude participation rate in 1990-91
improved to 27.97 (both sexes) under new concept from 27.19 under the old concept, of female increased
from 7.61 to 8.23, while that of male increased to 46.36 from 45.45. Similarly the age specific activity
rate derived from new concepts were also higher than derived from old concept. Usually the data has a time
lag of 3 years. The summary results of LFS(1994-95) were released in April 1997. The data for mining
and manufacturing (both large and small-scale) is reported in combined form and as such can not be cross
checked with CMIs data.
The Census of Manufacturing Industries (CMI) conducted annually, provides information on employment
and employment cost by major groups of industries in large scale. The data is reported in aggregate form
and is usually available three to four years after the collection. Similarly the data collected by other
agencies shown in the annex, is restricted to a particular activity or profession and are collected for meeting
the internal requirements of the management concerned. Except the LFS, the coverage of statistics collected
by other agencies is restricted to aggregate number and wage bill and that too in areas of vested interest.
The national requirement is best served by the LFS(s), though LFS also need improvement in concept, size,
and timely releases.
90
Comparative statement showing old and new definition of labour force concepts
Contents
Old definition
New Definition
1.
Labour Force
It includes all noninstitutional civilian population
10 years of age and above who
are found employed or
unemployed during the
reference week preceding the
date of inter view.
The “Labour Force” or “currently Active
population” consists of all persons 10 years of
age: and above who are either “employed” or
“unemployed” during the reference period i.e. one
week preceding the date of interview.
2.
Employed
Persons
It includes all persons: who,
during the reference week,
were either working for pay or
profit in cash or kind, including
unpaid family helpers (who
had worked for any period of
time during the reference
week)or had a job but did not
work
The “employed” comprises all persons of 10 years
age & above who worked at least one hour during
the reference week in the following
categories:
(i) Paid employment (1) “at work” persons who
during the reference week, performed some
work for wage or salary, in cash or in kind;
(2)”with a job but not at work”: persons
who, having already worked in their present
job, were temporarily not at work during
reference week due to some reasons such as
absence, leave, illness: and strike etc. but had
a formal attachment to their job;
(ii) Self-employment (1) “at work”: persons
who, during the reference week, performed
some work for profit or family again, in cash
or in kind (2) “with an enterprise but not at
work” persons with an enterprise, which may
be a business enterprise, a farm or a service
undertaking, who temporarily not at work
during reference week for some specific
reasons such as absence, leave, illness &
strike etc.
3.
Unemployed
Persons
Include all persons who, during
the reference week were either
looking for work, or not
looking for work because of
illness, or not looking for work
believing job not avail- able or
temporarily or indefinitely laid
off, or waiting to report to new
job or willing to work if job is
provided, or apprentice with no
guaranteed job or have some
usual occupation but were
doing nothing during the
reference period.
The “unemployed” comprises all persons of 10
years of age and above who during the reference
week were either:
(i) “available for work” i.e. were available
for paid employment or self-employment; or
(ii) “seeking work “ had taken specific steps in a
specified recent period to seek paid
employment or self-employment. It also
includes persons who were not available for
work during the reference week due to certain
reasons such as illness, will take a job within
a month, temporary laid off and apprentice
and not will to work.
91
Annex 1.2:
Youth employment and child labour
The exploitation of child labour is one of the most odious aspects of global labour markets. In most
developing countries, it has not been possible to put an end to child labour (including child prostitution
inspired by the tourist industry) despite the fact that almost all these countries have satisfactory legislation
in this respect. The abolition of child labour and more generally the protection of children and young
persons against work of a character or condition unsuitable to their age have been a serious concern to the
government and social activists in Pakistan, especially during the last decade or so.
The Census of Population and Labour Force Surveys are the two main sources of manpower statistics but
they do not provide information about child labour. In the absence of information, there are various
guesstimates of varying credibility. According to the summary results of 1994-95 LFS, 1.7 million children
in the age group of 10-14 years constituted 5.07 per cent of the employed persons. The total population in
the age group 10-14 was 16.5 million or 12.9 per cent of total population.
The Child Labour Survey (CLS) conducted in 1996 by the Federal Bureau of Statistics in collaboration
with the Ministry of Manpower & Overseas Pakistanis and under the auspices of the International
Programme on Elimination of Child Labour (IPEC), revealed that among 40 million children aged 5-14
years, 3.3 million (8.3 per cent) were economically active. Out of the total, 2.4 million (73 per cent) were
boys and 0.9 million (27 per cent) were girls. The absolute size of male child labour in the age group of
10-14 years was 2.1 millions while that of female child labour in the same age group was found to be 0.6
million. Child labour in rural areas was about eight times higher than in urban areas, due mainly to a large
proportion of unpaid family helpers.
The data also revealed that about 33.2 per cent of the total children employed in the labour market, were
literate from the formal system of education. Of the boys workers about 40.3 per cent were pre-matric
while only 11.2 per cent of the female child workers were pre-matric. Similarly about 41 per cent of the
total child workers in urban areas as against 32 per cent in rural areas were pre-matric.
As regard the major industrial groups, about 67 per cent of the children were engaged in agriculture,
followed by 11 per cent in manufacturing. The wholesale and retail trade and services (community, social
and personal services) sectors absorbed 9 per cent and 8 per cent of the employed children, respectively.
By occupation, the survey revealed that about 71 per cent of 3.3 million employed children were engaged
in unskilled occupations relating to agriculture, fisheries, sales and services. Craft and related trade
activities were the next major occupational groups which absorbed about 19 per cent of the working
children. Only 0.31 per cent child workers were found working as plant and machine operators. Children
as service and sales workers constituted 9.24 per cent of the working community.
Besides the Child Labour Survey and Labour Force Surveys, studies on the pattern of child labour in a few
cities have also been conducted. According to these studies most of the children are working in
manufacturing, transport and services sectors. In the manufacturing sector they are generally found in food
processing, textiles, footwear, printing, publishing, brick-making, carpet-weaving and sports goods.
The Labour Force Surveys show that the age-specific activity rate for the age group 10-14 years is
declining as shown below:
92
93
Table 1:
Percentage share of children age 10-14 years
1982-83
1987-88
1990-91
1994-95
18.8
18.7
18.1
19.3
4.0
3.1
2.5
2.2
21.5
16.6
13.6
11.6
8.4
6.7
5.5
5.1
10.0
9.9
9.9
10.4
3.3
2.6
1.9
1.7
33.0
26.6
19.3
16.6
7.6
6.4
5.0
4.4
Share in population
8.8
8.8
8.2
8.9
Share in Labour Force
0.7
0.5
0.6
0.5
Participation rate
8.3
5.5
6.8
5.7
14.1
9.6
9.4
9.7
Total
Share in population
Share in Labour Force
Participation rate
Share in employed force
Males
Share in population
Share in Labour Force
Participation rate
Share in employed force
Females
Share in employed force
Source: Labour Force Surveys.
Both the age-specific participation rate and the share of children in total employed force are declining,
mainly due to higher enrolment at primary and high schools level. Children constitute 6.2 per cent of work
force in rural areas compared to 2.9 per cent in urban areas. The size of child labour revealed by CLS and
LFS (1994-95) is compared below:
Table 2:
Child labour (million)
Age group (10-14)
Total
Male
Female
CLS (1996)
2.7
2.1
0.6
LFS (1994-95)
1.9
1.5
0.5
Source: CLS and LFS.
94
There is not much detailed work done which explores the relationship between the level of family income
and the incidence of child labour, or on other social-economic compulsions that force children to work in
hazardous environments. Although it can be argued that part of the problem certainly derives from
insufficient enforcement of legislation. The major causes for the existence of child labour include poverty,
lack of proper educational facilities, large size of informal economy and the socio-economic background
of the parents. As such it is a complex issue which does not yield to simplistic analyses. Employers in the
informal sector prefer to hire child workers because there is no law specifying the rights of child workers
with respect to minimum wages, maximum work hours and social security benefits. Children also help as
unpaid workers in family-owned and managed business.
The existence of child labour is a worrisome aspect of the condition of the poor in Pakistan. All countries
have enacted suitable legislation for the protection of children against exploitation, abolition of child labour
and against work unsuitable to their age or sex. Articles 11 (3) of the Constitution of the Islamic Republic
of Pakistan states that “no child below the age of fourteen years shall be engaged in any factory or mine
or any other hazardous employment.” Article 37(a) provides that the state shall “remove illiteracy and
provide free and compulsory secondary education within a minimum period.” Article 37(c) says that the
state shall “ensure that children and women are not employed in vocations unsuitable to their age or sex.”
The above provisions of Pakistan Constitution clearly show the concern of Pakistan regarding child labour.
Pakistan is a signatory to the Declaration of the Rights of the Child adopted by the UN General Assembly
in 1959. The legislation enacted and enforced in the country for the protection of children include:
• The Mines Act, 1923.
• Factories Act, 1934.
• The Employment of Children Act, 1938.
• West Pakistan Shops and Establishment Ordinance, 1969.
Most recently the government has set up a National Commission on child welfare in response to UN
Convention on the Rights of Children. As a consequence, the Employment of Children Act, 1991 has also
been enacted to promote the cause of working children. The government has also enacted the Bonded
Labour System (Abolition) Act, 1992, Pakistan, through a Memorandum of Understanding signed in 1994
with the ILO, has joined the International Programme for Elimination of Child Labour (IPEC), which aims
at gradual elimination of child labour. A National Steering Committee has been set up to supervise the
programme and a child labour unit has been established in the Ministry of Labour and Manpower to
monitor the administration of IPEC.
95
ANNEX 1.3: TABLES
Table A1.1:
Growth of population and labour force (% per annum)
Growth of labour force
Growth of
population
Period
1972-75
1975-79
1979-83
1983-88
1988-91
1991-95
Average(1972-95)
Total
Rural
Urban
2.9
4.4
2.4
2.1
2.1
2.6
2.7
3.1
3.9
2.0
1.7
0.9
3.4
2.5
2.2
6.3
3.6
3.3
5.1
0.5
3.5
3.2
3.0
3.1
3.1
3.1
3.0
3.1
Source: Population censuses and labour force surveys.
Table A1.2:
Census data on population, labour force and employment
Growth rate (% p.a.)b
Numbers (in ‘000 or %)
1951
Population (‘000)
Urban
Under 10 Years of Age
Over 10 Years of Age
Rural
Under 10 Years of Age
Over 10 Years of Age
Labour Force (‘000)
Urban
Rural
Employment (‘000)
Urban
Rural
Unemployment Rate (%)
Urban
Rural
Notes:
c
a
33,817
6,019
..
..
27,797
..
..
10,370
..
..
..
..
..
..
..
..
1961a
1972
1981
42,978 a
9,654
2,956
6,698
33,324
11,156
22,168
13,880
2,872
11,008
13,640
2,790
10,850
1.73
3.06
1.63
65,321
16,594
4,942
11,652
48,727
17,462
31,265
19,520
5,128
14,392
18,550
4,814
13,736
4.97
6.12
4.56
84,254
23,841
7,131
16,710
60,413
19,274
41,139
25,780
7,254
18,526
24,700
7,009
17,691
4.19
3.37
3.37
19511961
19611972
19721981
2.4a
4.8
..
..
1.8
..
..
3
..
..
..
..
..
3.7a
4.8
4.5
4.9
3.3
3.9
3
3
5.1
2.3
2.7
4.8
2.1
3.1
4.4
4.4
4.4
2.6
1.2
3.3
3.3
4.2
3
3.4
4.5
3
Official figures for 1961 are adjusted by 7.5 per cent, for under enumeration. This gives a 1961
population of 46.2 million, and hence inter-censal growth rates of 3.21 per cent for 1951-61 and 3.02 per
cent for 1961-72.
b
In calculating average annual population growth rates, the month in which the census was carried out
is taken into account (February 1951, March 1961, October 1972, and March 1981).
Civilian labour force only.
96
Table A1.3:
Population, labour force and employment, 1990-97
Fiscal Years Ending June
30:
1990
1991
1992
1993
1994
1996
1997
110.4
113.8
117.3
120.8
124.5
128
131.6
135.3
32.7
35.8
37.0
36.9
36.2
36.9
37.9
39.0
Under 10 Years of Age
10.1
11.6
12.6
11.5
11.0
10.8
11.3
11.5
Over 10 Years of Age
22.6
24.2
24.4
25.4
25.2
26.1
26.8
27.5
77.7
77.9
80.4
83.9
88.3
91.1
93.7
96.3
Under 10 Years of Age
26.7
28.4
27.9
29.9
30.9
32.0
32.9
63.8
Over 10 Years of Age
51.0
49.5
52.4
54.1
57.4
59.2
60.8
62.5
31.8
31.8
33.0
33.7
34.7
35.2
36.1
37.2
Urban
8.6
9.5
9.7
9.5
9.3
9.6
9.9
10.2
Rural
23.2
22.4
23.3
24.1
25.4
25.5
26.2
27.0
30.8
29.8
31.0
32.1
33.0
33.3
34.2
35.2
Urban
8.2
8.7
9.0
9.0
8.7
9.0
9.2
9.5
Rural
22.6
21.2
22.0
23.1
24.3
24.3
25.0
25.7
3.1
6.3
5.9
4.7
4.8
5.4
5.4
5.4
Urban
4.6
8.2
7.0
5.9
6.5
6.9
6.9
6.9
Rural
2.6
5.5
5.4
4.3
4.2
4.8
4.8
4.8
Population (‘000)
Urban
Rural
Labour Force (‘000)
Employment (‘000)
Unemployment Rate (%)
1995
Source: Labour Force Surveys, cited in Government of Pakistan (1997, Statistical Appendix, pp. 19-20). Figures
for 1996 and 1997 are estimates by the Economic Adviser’s Wing, Ministry of Finance, based on the
1994-95 labour force survey. (See Annex 4, Table 1.3.)
97
Table A1.4:
Crude labour force participation rates
Total labour force
Year
Total
Male
1971-72
29.9
51.9
1974-75
29.5
1978-79
Rural labour force
Female
Total
Male
5.3
31.0
53.3
52.1
4.3
30.8
31.0
52.3
7.9
1982-83
30.2
51.5
1984-85
29.6
1985-86
Female
Urban labour force
Total
Male
Female
5.6
26.5
53.2
2.6
52.1
5.1
26.5
48.0
2.4
32.6
53.1
9.7
27.1
47.3
3.7
7.2
31.8
53.1
8.9
26.3
47.7
3
51.7
5.8
30.7
52.7
7.1
27.1
49.4
2.8
28.7
50.0
6.0
29.9
51.2
7.5
25.8
47.1
2.4
1986-87
29.4
49.5
7.9
30.8
50.7
9.8
26.3
47.0
3.5
1987-88
28.8
49.4
6.8
29.9
50.2
8.2
26.3
47.5
3.4
1990-91
28
46.4
8.2
28.7
46.9
9.4
26.4
45.1
5.8
1991-92
28.1
46.1
9.2
29.0
46.5
10.7
26.1
45.1
5.5
1992-93
27.9
45.9
8.6
28.8
46.3
10.1
25.8
45.0
5.0
1993-94
27.9
45.7
8.9
28.7
45.9
10.5
25.8
45.4
4.9
1994-95
27.5
45.9
7.6
28.0
46.0
8.7
26.1
45.7
4.9
Source: Labour Force Surveys.
Table A1.5:
Age specific participation rates
Age group
1982-83
1987-88
1994-95
36446
21.5
16.6
11.5
15-19
40.3
36.4
32.3
20-24
50.8
48.3
47.9
25 & above
52.0
53.0
52.8
Source: Labour Force Surveys.
98
Table A1.6:
Out and return migration for different years
Emigration
BOI
Per Year
(000)
Return
Migration
Per Year
(000)
Net Out
Migration
1977-81
659715
132
98176
19
561539
112
1982-87
592279
98642
448107
50169-9
98
642448
107
-50169
-9
1988-92
642494
128
450000
90
192494
60
1993-95
394633
131
213008
71
181625
60
Period
Sources:
1
2
3
Per Year
(000)
ILO-SAAT/ M. Irfan , 1997.
1977-81 (Iqbal & Khan) 1981
1982-87 and 1993-95 (Bureau of Emigration) based on Airport Surveys.
1988-92 (M. Irfan’s ,estimation on the basis of the estimated flows of preceding and the following periods.
Table A1.7:
Persons included and excluded from the labour force, 1994-95 (million)
Total
Population
Male
Female
128.3
66.3
61.8
Age 10 years and above
85.4
44.2
41.2
Labour Force
35.2
30.5
4.7
Fully Employed
29.3
27
2.4
Underemployed
4
2.3
1.7
Unemployed
1.9
1.2
0.7
50.2
13.7
36.5
Students
17.4
11.0
6.4
Others
32.8
2.7
30.1
Outside Labour Force
Source: Labour Force Survey, 1994-95.
99
Table A1.8:
Composition of labour force by sex and level of education
1990-91
Total
1994-95
Growth (% p.a.)
M
F
Total
M
F
Total
M
F
Total
31.8
27.30
4.5
35.20
30.5
4.7
2.6
2.8
1.1
Illiterate
19.11
15.43
3.68
19.86
16.10
3.76
1.0
1.1
0.5
Literate
12.69
11.87
0.82
15.34
14.40
0.94
4.8
4.9
3.5
Literate
100
100
100
100
4.8
4.9
3.6
No formal education
100
100
3.95
3.60
9.01
2.89
2.67
6.31
-3.0
-2.6
-5.2
Pre-Matriculate
60.68
61.70
45.95
57.37
58.60
37.84
3.4
3.6
-1.1
Matriculate
20.91
20.61
24.32
22.59
22.36
25.23
6.9
7.1
4.7
Intermediate
7.20
7.08
9.01
8.51
8.24
12.61
9.3
9.0
12.6
Engineering Degree
1.05
1.06
0.90
1.06
1.01
1.80
5.2
3.6
24.8
Medical Degree
0.52
0.43
0.90
0.39
0.36
0.90
-2.4
-2.7
0
Agriculture Degree
0.06
0.06
-
0.11
0.12
0.00
20.7
20.7
0
Other Degree
4.30
4.10
7.21
5.17
4.80
10.81
9.7
9.1
14.7
Post-Graduate
1.39
1.30
2.70
1.89
1.78
3.60
13.3
13.5
11.5
Source: Based on Labour Force Surveys.
100
Table A1.9:
Percentage Distribution of Employed by Sex and Level of Literacy
1987-88
Total
M
1990-91
F
Total
M
1994-95
F
Total
M
F
Total
100
88.35
11.65 100
87.40
12.60 100
87.85
12.15
Illiterate
64.67
54.51
10.16
60.40
49.90
10.50
56.80
46.98
9.82
Literate
35.3
33.8
1.49
39.6
37.5
2.1
43.2
40.9
2.33
-
-
-
1.54
1.36
0.18
1.28
1.11
0.17
35.33
33.84
1.49
38.06
36.13
1.92
31.92
39.76
2.16
K.G Nursery
0.06
0.06
-
0.41
0.39
0.02
0.18
0.17
0.01
K.G but below Prim.
3.49
3.36
0.10
3.54
3.38
0.16
3.01
2.92
0.10
Primary but below
middle
12.26
11.81
0.46
12.81
12.29
0.52
13.30
12.72
0.58
Middle but below
Matric
7.39
7.24
0.15
7.50
7.24
0.26
8.50
8.31
0.18
Matric but below inter
7.14
6.80
0.34
8.09
7.60
0.49
9.60
9.03
0.57
Inter but below degree
2.20
2.06
0.14
2.81
2.63
0.18
3.63
3.35
0.28
Degree in Engineering
-
-
-
0.41
0.40
0.02
0.43
0.39
0.04
1.84
1.64
0.20
0.20
0.17
0.03
0.17
0.15
0.02
-
-
-
0.03
0.03
-
0.04
0.04
-
Degree in other subj.
0.80
0.69
0.11
1.70
1.53
0.17
2.25
1.96
0.29
Post Graduate
0.19
0.18
0.01
0.56
0.48
0.08
0.81
0.71
0.09
No Formal education
Formal education
Degree in Medicine
Degree in Agriculture
Source: Labour Force Surveys.
101
Table A1.10:
Rural-urban share of self-employed (%)
1982-83
1987-88
1994-95
Average
Total
40.3
47.9
42.3
43.6
Rural
41.7
51
45.2
46.1
Urban
36.1
39.5
34.3
36.6
Table A1.11: Distribution of self-employed by sectors
1982-83
1987-88
Sectors
T
R
T
R
Agriculture
54.3
67.5
7.6
53.6
66.6
7.2
Manufacturing
13.6
11.1
22.1
10.9
8.7
19.1
Trade
19.6
12.4
45.1
16.8
9.8
41.8
Transport
3.3
2.2
6.8
8.3
3.4
8.2
Services
6.6
4.8
12.8
6.0
4.1
12.8
Others
2.6
2.0
5.6
4.4
7.4
10.9
100.0
100.0
100.0
100.0
100.0
Total
U
U
100
Source: Labour Force Surveys.
Table A1.12:
Share of full-time (over 35 hours) and educated workers
among the self-employed, 1994-95
Share of full-time workers
(%)
National
Total
Male
Female
Self-employed
Total
Male
Female
Middle
and below
Matric but
below Degree
Degree and
above
Pakistan
Rural
Urban
87.8
92
57.7
86.0
90.8
55.8
92.9
95.0
67.5
62.6
28.5
8.9
91.9
93.2
59.4
90.9
92.4
51.1
95.1
95.9
71.0
74.4
22.1
3.5
Source: Labour Force Surveys.
102
Share of educated workers
(%)
Table A1.13:
Underemployment among the employed (%)
1982-83
Status
1987-88
1993-94
Total
Rural
Urban
Total
Rural
Urban
Total
Rural
Employer
0.2
0.3
0
0.2
0.2
0.1
0.1
0.1
0.2
Self-Employed
3.8
4.2
2.8
3.5
4.1
1.9
3.4
4.1
1.7
Unpaid Family
Helpers
7.4
9.2
1.7
6.1
7.9
1.2
5.7
7.2
1.3
Employees
2.6
2.6
2.5
1.3
1.2
1.6
3.0
2.6
3.9
11.1
13.4
4.8
12.2
Total
14
16.3
7
Urban
14
7.1
Source: Labour Force Surveys
Table A1.14:
Underemployment rates in rural and urban areas
1982-83
1987-88
1993-94
T
R
U
T
R
U
T
R
U
Labour Force (mill.)
26.9
20.0
6.9
29.9
21.9
8.1
35.2
25.6
9.6
Employed (mill.)
25.8
19.3
6.5
29.0
21.3
7.7
33.3
24.4
8.9
Underemployed
3.6
3.1
0.5
3.2
2.9
0.4
4.1
3.4
0.6
13.4
15.5
7.2
10.7
13.2
4.9
11.6
13.3
6.3
Underemployment Rate
Source: Calculated from Labour Force Survey Data.
103
Table A1.15:
Number of unemployed and unemployment rates
Unemployed labour force (million)
Unemployment rate
Year
Total
Rural
Urban
Total
Rural
Urban
1986-87
0.90
0.55
0.35
3.05
2.50
4.51
1987-88
0.94
0.57
0.37
3.13
2.60
4.58
1988-89
0.97
0.59
0.38
3.13
2.60
4.58
1989-90
1.00
0.60
0.40
3.13
2.60
4.58
1990-91
2.00
1.23
0.77
6.28
5.48
8.19
1991-92
1.93
1.26
0.67
5.85
5.40
6.97
1992-93
1.60
1.03
0.57
4.74
4.29
5.88
1993-94
1.68
1.04
0.64
4.84
4.22
6.31
1994-95(E)
1.73
1.06
0.68
4.84
4.22
6.51
Source: Federal Bureau of Statistics.
Table A1.16:
Duration of unemployment
Duration of unemployment
Year
1984-85
1985-86
1986-87
1987-88
Nature of
experience
Total
w.past.exp.
without p.exp.
Total
w.p.exp.
without p.exp.
Total
w.p.exp.
without p.exp.
Total
w.p.exp.
without p.exp.
Total
100.0
41.9
58.1
100.0
41.4
58.6
100.0
43.6
56.4
100.0
44.3
55.7
Less than 1
month
1-6 months
46.4
14.7
31.7
23.0
16.4
6.7
28.7
15.0
13.6
22.7
14.9
7.7
Source: LFS.FBS Economic Survey of Pakistan 1995-96
Note: w.p.exp= with past experience; without p.exp.= without past experience.
104
18.5
11.6
6.9
37.2
12.6
24.6
35.9
12.7
23.1
36.9
16.9
20.1
6 months and
over
35.1
15.6
19.5
39.8
12.5
27.3
35.5
15.9
19.6
40.4
12.5
28.0
Table A1.17:
Percentage distribution of educated unemployed
1982-83
Total
M
1987-88
F
Total
1993-94
M
F
Total
M
F
Total
100
-
- 100
96.7
3.3
100
68.1
31.9
Illiterate
57.2
-
- 51.0
48.9
2.1
51.2
27.1
24.2
Literate
42.8
-
- 49.0
47.8
1.3
48.8
41.0
7.7
Pre-matric
27.9
-
- 29.6
29.3
0.3
24.1
21.3
2.7
Matric
10.5
-
- 12.6
12.1
0.5
14.2
11.5
2.7
Inter
2.4
-
- 4.2
4.1
0
4.6
3.5
1.1
Degree. Of which
1.2
-
- 2.1
1.8
0.4
3.4
3.0
0.4
Professional
-
-
-
-
-
0.6
0.6
0.1
Post Graduates
0.5
-
- 0.5
0.5
0.1
0.9
0.7
0.2
No formal education
-
-
-
-
-
1.6
1.0
0.6
-
-
Source: Labour Force Surveys.
105
CHAPTER TWO
ANNEX 2:
TABLES
Table A2.1a:
Growth rates of population labour force and employed labour force in Pakistan
Year
106
Growth (Pop)
Growth (LF)
Growth (Emp)
1973
3.01
1.28
0.98
1974
4.03
3.54
3.72
1975
3.05
2.60
2.70
1976
3.06
2.58
2.73
1977
3.06
4.36
3.84
1978
3.06
4.36
3.84
1979
3.05
4.36
3.84
1980
3.05
4.39
3.92
1981
3.07
2.37
2.24
1982
3.05
2.31
2.28
1983
3.10
2.42
2.31
1984
3.10
2.44
2.30
1985
3.10
2.01
2.13
1986
3.10
2.00
2.12
1987
3.10
0.18
0.22
1988
3.10
5.53
6.22
1989
3.10
1.11
1.01
1990
3.10
3.14
3.14
1991
3.10
3.08
3.08
1992
3.10
0.03
-3.21
1993
3.10
3.58
4.06
1994
3.00
2.12
3.35
1995
3.00
3.03
2.90
1996
2.86
1.33
0.76
1997
2.83
2.82
2.83
1998
2.77
2.79
2.78
Table A2.1b:
Year
Levels of population, labour force and employed labour force in Pakistan
Population
Labour force
Employed labour
force
1971
61.49
18.70
18.37
1972
63.34
18.94
18.55
1973
65.89
19.61
19.24
1974
67.90
20.12
19.76
1975
69.98
20.64
20.30
1976
72.12
21.54
21.08
1977
74.33
22.48
21.89
1978
76.60
23.46
22.73
1979
78.94
24.49
23.62
1980
81.36
25.07
24.15
1981
83.84
25.65
24.70
1982
86.44
26.27
25.27
1983
89.12
26.91
25.85
1984
91.88
27.45
26.40
1985
94.73
28.00
26.96
1986
97.67
28.05
27.02
1987
100.70
29.60
28.70
1988
103.82
29.93
28.99
1989
107.04
30.87
29.90
1990
110.36
31.82
30.82
1991
113.78
31.83
29.83
1992
117.31
32.97
31.04
1993
120.83
33.67
32.08
1994
124.45
34.69
33.01
1995
128.01
35.15
33.26
1996
131.63
36.14
34.20
1997
135.28
37.15
35.15
107
108
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
39.04
39.48
37.58
36.44
34.33
34.74
34.63
33.03
32.26
32.02
30.83
30.01
29.34
26.86
27.41
27.30
26.64
25.71
26.22
25.83
25.68
26.11
24.18
24.34
24.65
24.81
24.24
14.55
14.40
14.63
14.50
14.03
13.76
13.68
13.99
14.34
14.76
15.53
16.42
16.42
17.02
16.94
17.19
17.47
18.07
17.92
18.13
18.27
18.29
18.83
18.98
18.66
18.64
18.41
0.39
0.39
0.37
0.38
0.37
0.35
0.40
0.38
0.37
0.39
0.42
0.44
0.41
0.40
0.42
0.48
0.49
0.53
0.51
0.54
0.56
0.53
0.54
0.54
0.49
0.50
0.50
Mining
Mining and
manufacturing
Year
Agriculture
GDP ( at factor cost) sectoral shares
Table A2.2:
14.16
14.01
14.26
14.12
13.66
13.42
13.28
13.61
13.96
14.37
15.11
15.98
16.02
16.62
16.52
16.71
16.98
17.55
17.40
17.59
17.71
17.76
18.30
18.44
18.17
18.14
17.92
Manufacturing
11.15
10.85
11.09
10.94
10.37
9.99
9.71
9.97
10.19
10.53
11.08
11.91
11.89
12.32
12.23
12.34
12.50
12.98
12.69
12.70
12.69
12.71
12.94
12.89
12.45
12.21
11.68
Maunfacturing
large scale
3.57
2.92
3.16
3.25
3.69
4.26
4.11
4.13
4.13
4.28
4.67
4.59
4.18
4.06
4.09
4.10
4.36
4.30
4.19
4.13
4.14
4.07
4.21
4.10
3.93
3.88
3.86
Construction
1.67
1.72
1.87
2.05
1.76
1.77
1.99
2.01
2.09
2.18
2.39
2.26
2.26
2.46
2.33
2.44
2.54
2.78
3.00
3.29
3.46
3.50
3.64
3.59
3.99
3.82
4.14
Electicity
and gas
8.55
8.56
9.31
9.07
9.12
8.93
8.84
9.36
9.58
9.53
9.65
9.72
9.83
10.23
10.16
10.02
10.16
10.19
9.34
9.51
9.58
9.82
10.24
10.16
10.05
9.67
9.86
Transport
14.70
14.69
14.54
15.42
15.30
15.07
14.61
14.90
15.03
15.05
15.06
15.36
15.60
15.69
16.12
16.18
16.20
16.59
16.66
16.49
16.45
16.39
16.50
16.23
16.14
16.38
16.32
Trade
Table A2.3:
Distribution of the employed by sector
Period
Agriculture
Manufacturing
and mining
Construction Electricity
Transport Trade Others
distribution
and gas
1969-70
57.03
15.57
3.93
0.41
4.73
9.89
8.44
1970-71
57.58
15.25
3.60
0.25
4.88
10.89
7.56
1971-72
57.32
12.92
3.41
0.37
4.84
9.89
11.25
1972-73
56.47
13.20
3.66
0.41
4.85
10.27
11.15
1973-74
55.62
13.49
3.92
0.45
4.86
10.67
10.99
1974-75
54.80
13.78
4.20
0.49
4.87
11.09
10.77
1975-76
54.25
13.99
4.37
0.54
4.83
11.09
10.92
1976-77
53.71
14.21
4.55
0.60
4.80
11.09
11.04
1977-78
53.71
14.44
4.73
0.67
4.76
11.08
11.15
1978-79
52.65
14.66
4.92
0.74
4.73
11.08
11.22
1979-80
52.67
14.37
4.89
0.82
4.69
11.29
11.26
1980-81
52.69
14.09
4.86
0.91
4.66
11.50
11.28
1981-82
52.71
13.81
4.83
1.02
4.62
11.72
11.29
1982-83
52.73
13.54
4.80
1.13
4.59
11.94
11.27
1983-84
51.63
13.69
5.18
0.88
4.89
11.74
11.99
1984-85
50.56
13.84
5.60
0.69
5.20
11.54
12.57
1985-86
54.01
13.40
5.24
0.52
4.42
11.40
11.01
1986-87
49.24
14.23
6.01
0.73
5.25
12.05
12.50
1987-88
51.15
12.84
6.38
0.59
4.89
11.93
12.22
1988-89
51.15
12.84
6.38
0.59
4.89
11.93
12.22
1989-90
51.15
12.84
6.38
0.59
4.89
11.93
12.22
1990-91
47.45
12.38
6.62
0.83
5.24
13.24
15.22
1991-92
48.27
12.53
6.33
0.79
5.51
13.10
13.48
1992-93
47.54
10.89
6.94
0.85
5.52
13.31
14.95
1993-94
50.04
10.12
6.50
0.87
4.95
12.78
15.56
Source: Labour Force Surveys.
109
Table A2.4:
Decomposing output growth, productivity and employment effects
Nto (DP)
DY
Productivity
Effect
Pto (DN)
DY
Employment
Effect
DP (DN)
DY
Multiple Effect
1969/70 – 1980/81
Agriculture
Manufacturing
Construction
Transport
Trade
Other
TOTAL
0.063
0.460
0.178
0.416
0.045
0.145
0.292
0.918
0.419
0.695
0.431
0.927
0.731
0.615
0.018
0.120
0.127
0.153
0.028
0.124
0.118
1980/81-1990/92
Agriculture
Manufacturing
Construction
Transport
Trade
Other
TOTAL
0.664
0.816
0.041
0.334
0.425
0.339
0.578
0.236
0.089
0.932
0.501
0.390
0.491
0.273
0.100
0.094
0.026
0.163
0.184
0.170
0.148
0.361
1.868
-1.250
1.090
-0.599
-0.089
0.400
0.623
-0.680
2.522
-0.077
1.710
1.107
0.571
0.0140
-0.188
-0.272
-0.013
-0.110
-0.018
0.028
1991/92 – 1994/95
Agriculture
Manufacturing
Construction
Transport
Trade
Other
TOTAL
Source: National Income Accounts and Labour Force Survey (various years).
Note: P = Productivity; N = Employment; Y = Output; D = Change; to = original time period.
110
Table A2.5:
Employment, output and productivity growth rates (OLS estimates)
1970s
1980s
1990s
Total (GDP)
1.50
3.90
1.80
Agriculture
-0.10
2.00
1.70
Manufacturing
1.30
7.00
4.60
Construction
0.90
-0.30
-2.20
Transport
2.50
3.40
3.20
Trade
0.50
4.70
-0.90
Total
3.20
2.40
2.40
Agriculture
2.10
1.90
1.60
Manufacturing
3.00
1.40
-0.40
Construction
7.00
6.00
4.90
12.80
-3.90
2.40
Transport
3.00
3.20
0.50
Trade
4.40
2.80
5.00
Others
6.40
3.50
4.30
Total (GDP)
4.70
6.30
4.20
Agriculture
2.00
3.90
3.30
Manufacturing
4.30
8.40
4.20
Construction
7.90
5.70
2.70
Electricity and gas
8.50
9.90
7.40
Transport
5.50
6.60
3.70
Trade
4.90
7.50
4.10
Others
6.40
3.50
4.30
Total (GDP)
0.68
0.38
0.57
Agriculture
1.05
0.49
0.48
Manufacturing
0.70
0.17
-0.10
Construction
0.89
1.05
1.81
Electricity and gas
1.51
-0.39
0.32
Transport
0.55
0.48
0.14
Trade
0.90
0.37
1.22
Productivity
Employment
Electricity and gas
Output
Elasticity
Note:
The estimates are based on Ordinary Least Squares Regression Coefficients.
111
Table A2.6:
Corelation coefficents productivity and employment growth
Sectors
cor (1970-96)
All
Agriculture
Manufacturing and mining
Construction
Electricity and gas
Transport
Trade
cor (1970s)
-0.71
-0.72
-0.89
-0.41
-0.91
-0.84
-0.80
-0.25
-0.13
-0.86
0.42
-0.61
0.041
-0.67
cor (1980s)
cor (1990s)
-0.81
-0.49
-0.93
-0.72
-0.95
-0.93
-0.86
-0.43
-0.66
-0.96
-0.95
-0.87
-0.83
-0.92
Table A2.7:
(i) Correlation matrix between sectoral employment growth rates 1971-97
All
Agriculture Manufacturing Construction
Electricity
and gas
Transport
All
1
Agriculture
0.42
1
Manufacturing
0.62
-0.07
1
Construction
0.49
-0.37
0.56
1
Electricity
and gas
0.14
-0.46
0.04
0.12
1
Transport
0.50
-0.49
0.59
0.69
0.46
1
Trade
0.17
-0.53
0.61
0.63
0.27
0.50
Trade
1
(ii) Correlation matrix between sectoral productivity growth rates 1971-97
All
Agriculture Manufacturing Construction
Electricity
and gas
Transport
All
1
Agriculture
0.56
1
Manufacturing
0.45
-0.08
1
Construction
0.35
-0.04
0.06
1
Electricity and
gas
0.28
-0.20
0.16
0.04
1
Transport
0.44
-0.33
0.56
0.43
0.43
1
Trade
0.39
-0.13
0.56
0.07
0.32
0.41
112
Trade
1
(iii) Correlation matrix between sectoral output growth rates 1971-97
All
Agriculture Manufacturing Construction
Electricity
and gas
Transport
All
1
Agriculture
0.58
1
Manufacturing
0.76
0.17
Construction
0.34
-0.04
0.25
1
Electricity
and gas
0.15
0.04
0.26
-0.10
Transport
0.54
-0.13
0.62
0.28
0.14
1
Trade
0.88
0.40
0.63
0.22
0.12
0.39
Table A2.8:
Trade
1
1
1
Poverty GAP (P1) & Foster-Greer-Thorbecke index (P2)
1984-85, 1987-88,1990-91
Gazdar et.al (1994) Basket of Basic Needs
All Pakistan
(P1)
(P2)
1984-85
0.111
0.038
1987-88
0.077
0.023
1990-91
0.071
0.022
Source: Gazdar, et.al. (1994) and Malik, S. (1996).
113
Table A2.9:
Growth rates of output productivity and employment
Year
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
114
Output
growth
2.3
6.8
7.5
3.9
3.3
2.8
7.8
5.6
7.4
6.0
7.6
6.8
4.0
8.7
6.4
5.8
6.4
4.8
4.6
5.6
7.7
2.3
4.5
5.2
4.6
3.1
Productivity
growth
1.3
3.0
4.6
1.1
-0.6
-1.0
3.8
1.6
5.0
3.7
5.1
4.4
1.8
6.5
6.1
-0.4
5.4
1.6
1.5
9.1
3.5
-1.0
1.6
4.4
1.7
0.3
Employment
growth
1.0
3.7
2.7
2.7
3.8
3.8
3.8
3.9
2.2
2.3
2.3
2.3
2.1
2.1
0.2
6.2
1.0
3.1
3.1
-3.2
4.1
3.4
2.9
0.8
2.8
2.8
Table A2. 10: Real Wage Trends in Selected Sectors 1971 to 1996 (Index base year 1984)
Constructionc1
Manufacturing
Year
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
Note:
Large
scaleal
58
----58
68
72
78
81
81
83
95
100
104
113
123
132
--138
------
Small
scale and
householdbl
-----161
-------100
---138
---------
Labour
---84
83
91
94
98
115
111
116
104
103
100
97
100
103
107
103
104
101
104
103
99
99
96
Carpenters
---85
86
92
100
98
114
113
113
104
104
100
97
98
101
104
103
103
100
98
100
97
96
96
Masons
---91
90
103
108
105
111
110
110
104
105
100
110
111
114
116
116
118
121
117
124
119
121
127
Agriculture
rural casual
workersdl
-------------100
102
107
110
110
108
111
110
116
105
121
113
114
Rabi
-------------100
104
108
118
109
117
129
118
118
107
116
---
Kharif
-------------100
102
104
105
114
115
127
118
116
112
111
---
Money wages deflated by the consumer price index.
al – Economic survey 1986-87, 1990-91, 1996-97.
bl – Census of Small & Household Manufacturing Industries 1976-77, 1983-84, 1988.
cl – Economic survey 1986-87, 1996-97, average of Karachi, Lahore, Quetta, Peshawar wages. Data
pertains to month of November each year.
dl – Monthly Statistical Bullein Jan. 1997, Jan.1992 & Nov. 1988.
115
CHAPTER THREE
ANNEX 3:
TABLES
Table A3.1:
Selected indicators of employment and output for the economy and agriculture
GDP
GDP
(AG)
POP
LF
1971
14.80
5.80
61.49
18.70
18.37
10.58
0.54
1972
15.1
6.0
63.34
18.94
18.55
10.63
0.57
1973
16.1
6.1
65.89
19.61
19.24
10.82
0.57
1974
17.3
6.3
67.90
20.12
19.76
10.99
0.58
1975
18.0
6.2
69.98
20.64
20.30
11.12
0.55
1976
18.6
6.5
72.12
21.54
21.08
11.44
0.57
1977
19.1
6.6
74.33
22.48
21.89
11.76
0.57
1978
20.6
6.8
76.60
23.46
22.73
12.09
0.57
1979
21.8
7.0
78.94
24.49
23.62
12.43
0.57
1980
23.4
7.5
81.36
25.07
24.15
12.72
0.59
1981
24.8
7.6
83.84
25.65
24.70
13.01
0.59
1982
26.7
8.0
86.44
26.27
25.27
13.32
0.60
1983
28.5
8.4
89.12
26.91
25.85
13.63
0.61
1984
29.6
8.0
91.88
27.45
26.40
13.63
0.59
1985
32.2
8.8
94.73
28.00
26.96
13.63
0.64
1986
34.2
9.3
97.67
28.05
27.02
14.60
0.63
1987
36.2
9.6
100.70
29.60
28.70
14.13
0.69
1988
38.5
9.9
103.82
29.93
28.99
14.83
0.67
1989
40.4
10.6
107.04
30.87
29.90
15.29
0.70
1990
42.20
10.9
110.36
31.82
30.82
15.77
0.70
1991
44.60
11.5
113.78
31.83
29.83
14.15
0.80
1992
48.00
12.5
117.31
32.97
31.04
14.98
0.83
1993
49.10
11.9
120.83
33.67
32.08
15.25
0.78
1994
51.40
12.5
124.45
34.69
33.01
16.52
0.75
1995
54.1
13.3
128.01
35.15
33.26
15.56
0.85
1996
56.5
14.0
131.63
36.14
34.20
16.00
0.88
1997
58.3
14.1
135.28
37.15
35.15
16.45
0.85
Year
Note:
EMP
PRDY (AG)
GDP = Gross domestic product; VA = Value added; POP = Population; LF = Labour force;
EMP = Employment; PRDY = Productivity
Source: Labour Force Survey and Natural Income Accounts, various years.
116
Force
Emp (AG)
Table A3.2:
Selected growth indicators of employment and output
for the economy and agriculture
YEAR
VA
EMP
EMP(AG)
1973
1.67
3.72
1.79
1974
4.18
2.70
1.57
2.12
2.73
1.18
1976
4.47
3.84
2.88
1977
2.53
3.84
2.80
1978
2.82
3.84
2.81
1979
3.10
3.92
2.81
1980
6.61
2.24
2.33
1981
2.06
2.28
2.28
1982
4.72
2.31
2.38
1983
4.40
2.30
2.33
1984
-4.82
2.13
0.00
1985
10.92
2.12
0.00
1986
5.95
0.22
7.12
1987
3.25
6.22
-3.22
1988
2.73
1.01
4.95
1989
6.87
3.14
3.10
1990
3.03
3.08
3.14
1991
4.96
3.21
- 10.27
1992
9.50
4.06
5.87
5.29
3.35
1.80
1994
5.23
2.90
8.33
1995
6.57
0.76
1996
5.27
2.83
1975
1993
-
-
-
-
5.81
2.83
VA = Value added; EMP = Employment
Source: Labour Force Survey and Natural Income Accounts, various years.
117
Table A3.3a:
Output levels and trends in agriculture from 1979-80 to 1994-95
Description
1979-80
1984-85
1989-90
1994-95
A. Value added at constant factor cost of 1959-60 (Rs. billion) for:
(vii)
Agricultural sector
15.83
18.60
23.26
28.21
(viii)
Crop sector
11.20
12.75
15.29
17.74
(ix)
Livestock sector
4.42
5.85
7.51
9.41
B. Output (mil tonnes) of:
•
Wheat
10.59
11.70
14.72
17.00
•
Cotton
0.73
1.01
1.46
1.48
•
Sugarcane
27.50
32.14
35.49
47.12
C. Annual growth rates (% ) over preceeding five years
1. Agricultural sector
-
3.28
4.57
3.93
2. Crop sector
-
2.63
3.70
3.02
3. Livestock sector
-
4.77
6.12
5.70
4. Wheat output
-
2.01
4.12
3.49
5. Cotton output
-
6.71
7.65
0.27
6. Sugarcane output
-
3.12
2.00
12.89
7. Rice output
-
1.19
-0.61
1.39
Source: Calculation based on data in Pakistan (1997).
Table A3.3b:
Use of Agricultural Inputs for Cultivated Acre 1969-70,1979-80,
1984-85, 1989-90 and 1994-95
Acreage input (kgs) per cultivated acre of:
Year
Fertilizer nutrients
(1)
(2)
Improved
seed
distributed
Pesticides
Number of
tractors per
100 Acres
(3)
(4)
(5)
1969-70
16.00
0.83
0.10
0.17
-
1979-80
51.62
3.01
0.22
0.48
-
1984-85
-
60.81
4.19
0.77
0.76
1989-90
-
90.26
2.90
0.50
-
1994-95
101.53
3.57
1.01
1.17
-
Source: Columns 2-4 from Pakistan (1996 and 1997) and Col. 5 from United Consultants (Private) Limited (1989)
and Agricultural Census Organization (1997) Pakistan 1994 Census of Agricultural Machinery. Lahore:
Statistics Division, Government of Pakistan
118
Table A3.4:
Growth rates of employment in agriculture from alternative sources at mid and end
points of the decades since 1969-70
Annual growth rate during:
Source and description
1969-70 to 1979-80
1979-80 to 1989-90
1989-90 to 1994-95
A. Agricultural Census Data
1. Family labour
3.14
0.59
-
2. Permanent hired labour
-3.44
2.33
-
3. Total permanent labour
2.94
0.62
-
2.30
2.17
(2.96)
2.40
1. Cropping pattern change
0.75
0.34
0.74
2. Crop land increase
1.70
1.11
0.62
3. Per acre labour input increase
0.13
0.75
0.19
4. Total
2.58
2.20
(2.61)
1.55
B. Labour Force Surveys*
1. Labour force employed in
agriculture
C. Labour input changes due to:
Note: Figures in parentheses refer to growth rates during 1984-85 to 1989-90.
*
Growth rates based on labour force survey data reported in Pakistan (1997) Table 1.10.
Source: For A. Pakistan (1975, 1983 and 1993, for B, C-1 and C-2 Pakistan 1984 and 1997) and for C-3 PERI
(n.d.).
Table A3.5:
Farms using casual labour and number of permanent hired workers as percentage of
total permanent labour working in agriculture during 1972, 1980 and 1990
Description
Number (‘000) during the agricultural
census of:
1972
1980
1990
A. Total number of farms
3,762
4,070
5,071
1. Farms using casual labour
1,102
1,753
2,557
2. Percentage using casual labour
29.29
43.07
50.42
3. Growth rate of farms using casual labour
5.64
3.85
4. Percentage change of farms using casual labour
59.10
95.90
B. Total permanent labour (family + permanent
labour)
13,366
16,853
17,943
C. Permanent hired labour
512
387
487
D. C as percentage of B
3.83
2.30
2.71
Source: Pakistan (1975, 1983 and 1993).
119
Table A3.6:
Population and labour force estimates and trends according
to Labour Force Survey Data
Population
Areas and year
Number
(mn)
Growth
rate (%)
Crude
activity rate
(%)
Labour force
Number
(mn)
Growth
rate (%)
A. Rural areas
1979-80
58.34
-
31.03
18.10
-
1984-85
68.30
3.20
30.65
20.93
2.98
1989-90
77.71
2.62
29.90
23.23
2.08
1994-95
91.12
3.24
28.00
25.51
1.89
1979-80
23.02
-
27.17
6.25
-
1984-85
26.43
2.80
27.07
7.16
2.58
1989-90
32.66
4.32
26.28
8.59
3.88
1994-95
36.89
2.47
26.12
9.64
2.33
1979-80
81.36
-
29.95
24.35
-
1984-85
94.73
3.09
29.59
28.09
2.89
1989-90
110.36
3.10
28.99
31.82
2.52
1994-95
128.01
3.01
27.35
35.15
2.01
B. Urban areas
C. All Areas
Source: Labour Force Survey data given in Pakistan (1997).
120
Table A3.7a:
Use of agricultural inputs per cultivated acre 1969-70, 1979-80,
1984-85, 1989-90 and 1994-95
Acreage input (kgs) per cultivated acre of:
Year
Fertilizer
nutrients
Improved seed
distributed
Pesticides
Number of
tractors per 100
Acres
(2)
(3)
(4)
(5)
(1)
1969-70
16.00
0.83
0.10
0.166
1979-80
51.62
3.01
0.22
0.476
1984-85
60.81
4.19
0.77
0.763
1989-90
90.26
2.90
0.50
-
1994-95
101.53
3.57
1.01
1.173
Source: Columns 2-4 from Pakistan (1996 and 1997) and Col. 5 from United Consultants (Private) Limited (1989)
and Agricultural Census Organization (1997) Pakistan 1994 Census of Agricultural Machinery. Lahore:
Statistics Division, Government of Pakistan.
Table A3.7b:
Area under high yielding varieties (HYVs) of wheat, rice and cotton
since 1979-80
Agricultural
crops and area
Area (million acres) under the crop during:
1979-80
1984-85
1989-90
1994-95
17.11
17.94
19.38
20.19
Rice
5.03
4.94
5.21
5.25
Cotton
4.99
5.54
6.42
6.56
13.81
16.18
17.99
18.93
Rice
4.31
4.33
4.81
4.97
Cotton
4.61
5.22
6.20
6.35
A. Total area under:
Wheat
B. Area under HYV’s of:
Wheat
C. HYV areas as % of total area
Wheat
71.30
90.19
92.83
93.76
Rice
85.69
87.65
92.32
94.67
Cotton
92.38
94.22
96.57
96.80
Source: Pakistan (1996).
121
Table A3.8:
Rates of rural unemployment and underemployment in Pakistan and provinces
Percentage of labour force (%)
Period
Pakistan
Baluchistan
NWPF
Punjab
Sindh
A. Rate of unemployment
1979-80
2.33
2.96
2.00
2.54
1.64
1982-83
3.19
3.07
7.53
3.43
0.40
1984-85
2.95
1.03
3.53
3.43
1.28
1985-86
3.12
3.19
5.71
3.27
0.80
1986-87
2.50
0.64
3.83
2.82
0.63
1987-88
2.60
0.44
4.57
2.80
0.67
1990-91
5.47
4.09
5.48
6.46
2.19
1991-92
5.40
2.73
5.51
6.21
2.85
1992-93
4.28
2.24
5.50
4.82
1.98
1993-94
4.22
1.58
5.23
4.61
2.36
1994-95
4.80
4.09
7.10
4.86
2.28
B. Underemployment (working less than 35 hours per week)
1982-83
16.24
4.96
9.28
17.65
17.51
1984-85
11.64
8.64
10.76
11.68
12.92
1985-86
12.00
6.46
12.33
11.90
13.49
1986-87
12.68
1.19
15.23
13.80
9.44
1987-88
13.27
3.62
20.41
14.58
4.96
1990-91
14.83
11.63
19.43
18.45
9.90
1991-92
16.51
11.39
18.78
18.62
7.75
1992-93
15.02
14.12
21.05
15.91
7.75
1993-94
15.26
13.87
20.29
14.69
10.94
Note: Underemployment rates for 1979-80 and 1994-95 are not available.
Source: Pakistan (1984, n.d. and 1997).
122
Table A3.9:
Cropping pattern and average labour input per crop acre for various years and
provinces
Percentage (%) area under:
Geographical area
and year
Wheat
Rice
Cotton
Sugarcane
Fruits and
vegetables
Other
crops
A. Pakistan
40.7
34.7
47.1
169.5
74.6
20.0
1979-80
36.0
10.6
10.8
3.7
2.3
36.6
1984-85
36.6
10.0
11.2
4.6
3.1
34.5
1989-90
36.5
9.8
12.1
4.0
3.4
34.2
1994-95
36.9
9.6
12.0
4.6
4.1
33.8
1979-80
38.1
9.1
11.4
3.8
2.0
35.6
1984-85
37.9
8.2
11.5
4.6
2.9
34.9
1989-90
37.9
8.5
13.6
3.3
3.1
33.6
1994-95
37.7
8.6
14.3
4.2
3.4
31.8
1979-80
26.3
19.2
15.3
3.3
2.3
33.6
1984-85
22.7
18.5
18.0
4.8
2.7
28.3
1989-90
27.7
17.6
14.9
6.7
3.2
29.9
1994-95
30.3
17.1
11.7
7.1
3.7
30.1
1979-80
39.8
3.7
-
4.7
2.6
49.2
1984-85
40.7
3.6
-
5.2
2.1
48.4
1989-90
41.4
3.0
-
4.9
3.5
47.2
1994-95
41.0
2.9
-
4.8
3.8
47.5
1979-80
45.2
9.5
-
-
9.5
35.8
1984-85
43.8
18.8
-
-
10.9
26.5
1989-90
42.9
15.7
-
-
12.9
28.5
1994-95
37.4
13.3
-
-
17.6
31.8
Labour input
(Man-days per acres)
B. Punjab
C. Sindh
D. NWFP
E. Baluchistan
Source: Pakistan (1996) for crop shares and Chaudhry (1982) for labour input.
123
Table A3.10:
Rate of profit in Pakistan's agriculture: 1982-83 to 1991-92
Commodity and
province
Rate of profit (percentage) during:
1982-83 1983-84 1984-85 1985-86 1986-87 1987-88 1988-89 1989-90 1990-91 1991-92
1. Wheat
Punjab
-1.70
-12.57
-3.71
6.67
0.38
0.98
7.46
15.11
16.55
10.32
Sindh
-1.70
8.29
5.74
17.47
11.11
11.79
6.38
16.08
15.70
11.71
2. Rice coarse
Punjab
-
-11.23
-14.39
-8.01
-11.49
-12.59
-8.84
-5.96
-4.76
-18.11
Sindh
-
-11.23
27.60
26.13
31.56
22.22
8.70
12.82
5.01
0.00
Punjab
-
-
14.20
13.26
26.77
24.11
23.43
23.87
15.53
10.20
Sindh
-
-
16.09
15.14
35.80
32.78
35.37
35.92
32.35
25.95
Punjab
-
9.77
5.43
4.43
19.58
11.56
10.11
13.47
13.11
11.69
Sindh
-
-
-
-
65.50
16.30
15.50
18.30
14.30
11.40
2.35
2.38
6.92
31.45
21.18
22.75
7.99
7.90
3. Sugarcane
4. Seed cotton
5. Rice basmati
Punjab
-
-5.51
Source: Afzal et al (1992 and 1993).
Table A3.11:
Relative shares of agricultural and non-agricultural sectors
in rural employment since 1979-80
Years
Employment rural
labour force
Percentage of
employment in
agriculture
1979-80
100.00
68.76
31.24
1982-83
100.00
67.69
32.31
1984-85
100.00
66.69
33.31
1985-86
100.00
70.94
29.06
1986-87
100.00
65.24
34.76
1987-88
100.00
67.49
32.51
1990-91
100.00
63.74
36.26
1991-92
100.00
63.26
36.74
1992-93
100.00
63.76
36.24
1993-94
100.00
64.76
35.24
1994-95
100.00
61.94
38.06
Source: Population Census 1981, Pakistan (1997) and Various Labour Force Surveys.
124
Share of
non-agricultural
sector
Table A3.12:
Area and permanent (hired and family) labour input per acre by farm size
for 1979-80 and 1989-90
Area and permanent labour input during:
1979-80
Farm size
Area
(%)
1989-90
Labour (manyears)
Area
(%)
Labour
(man-years)
All sizes
100.00
0.2820
100.00
0.2898
Under 1.0 acre
0.19
4.2559
0.39
3.9914
1.0 - 2.5 acres
1.75
1.5215
3.28
1.3842
2.5 - 5.0 acres
5.10
0.5941
7.56
0.7128
5.0 - 7.5 acres
8.54
0.5342
10.31
0.4654
7.5 - 12.5 acres
18.76
0.3619
17.32
0.3097
12.5 - 25.0 acres
24.67
0.2477
21.58
0.2007
25.0 - 50.0 acres
17.81
0.1528
15.83
0.1200
50.0 - 150.0 acres
14.68
0.0786
13.64
0.0633
150.0 acres and above
8.50
0.0309
10.09
0.2610
Source: Pakistan (1983 and 1993).
Table A3.13:
Proportionate area and labour input (man-hours per crop acre)
under various technological packages
Bullocks
only
Description
Bullock-cumtractor
Tractor
only
A. Percentage area
1979-80
57.67
29.45
12.88
1989-90
17.69
30.33
52.98
Family and permanently hired
184
141
110
Casual labour
42
85
70
B. Labour input
Source: Pakistan (1983 and 1993) and United Consultants (1989).
125
Table A3.14:
Changing patterns of land tenure between 1979-80 and 1989-90
Number of farms (‘000) and
operational farm area (million acres)
Census years and
tenurial classes
Number of farms
Number
Operational farm area
Percentage
Area
Percentage
A. 1980 Agricultural Census
1. All farms
4,070
100.00
47.09
100.00
2. Owner farms
2,227
54.72
24.53
52.09
3. Owner cum tenant
789
19.38
12.40
26.33
4. Tenant fars
1,054
25.90
10.16
21.58
1. All farms
5,071
100.00
47.32
100.00
2. Owner farms
3,491
68.84
30.73
64.94
3. Owner cum tenant
626
12.35
8.98
18.98
4. Tenant farms
954
18.81
7.61
16.08
B. 1990 Agricultural Census
Source: Pakistan (1983 and 1993).
126
Table A3.15:
Employment profile of household heads and incidence of poverty, 1991
Urban
Proportion
of sample
(%)
Incidence
of poverty
(%)
Rural
Poor
(%)
Proportion
of sample
(%)
Incidence
of poverty
(%)
Poor
(%)
63.60
35.10
64.70
Tenant
36.60
30.20
32.00
Agricultural Labourer
13.60
43.80
17.30
7.00
56.00
11.40
Agriculture
By land ownership
Other Agriculture
43.80
28.40
39.60
17.90
29.80
15.50
White collar
14.20
22.1
10.00
6.50
26.30
5.00
Skilled/Semi-skilled
20.10
28.1
18.00
6.60
22.10
4.20
Casual/Manual
9.50
38.3
11.60
4.80
45.10
6.30
Self-Employed
Out-side Agriculture
36.30
34.00
39.30
15.20
36.30
16.00
9.30
51.20
15.20
4.30
46.30
5.80
Rs. 1,000 – 10,000
12.40
34.5
13.60
6.00
39.20
6.80
Rs. 10,000 or more
14.60
22.2
10.30
4.80
24.50
3.40
19.90
33.7
21.40
3.40
41.10
4.10
100.00
31.40
100.00
100.00
34.50
100.00
Non-Agriculture Wage Earners
By type of job
By value of assets
Rs. 1,000 or less
Other
Overall
Source: Gazdar, Howe and Zaidi (1994).1
1
The table is based on data from the 1991 Pakistan Integrated Household Survey. The identification of households
was sequential, with priority given to the identification of agricultural households in rural areas, followed by wage earners
outside agriculture and self-employed outside agriculture. Agricultural households were identified from their land ownership
or operation status, ownership of other agricultural assets such as livestock, and reporting of earnings from agricultural labour.
Of the remainder, if the household head reported any positive wage income and his/her occupation as employment, the
household was classified as a non-agricultural wage earner. The residual households were classified as self-employed if the
household head reported any positive income from self-employment, and as “other” if they could not be classified under any
of the above categories, or were non-earners or unemployed. The category “other agriculture” includes those who did not report
land ownership or operation, but did own other agricultural assets such as livestock. The poverty line used is Rs 296 per capita
per month in 1991/92 rural prices.
127
128
15.28
15.56
137.57
15.00
15.00
131.83
Kharif
Rabi
CPI
142.52
15.85
15.85
1986-87
151.49
16.07
17.38
1987-88
167.23
17.46
15.97
1988-89
177.33
17.63
17.21
1989-90
Source: Monthly Statistical Bulletin (various issues), cited in
M. Irfan: Employment and Wages in Pakistan: Recent Evidence,
1985-86
199.78
19.32
18.85
1990-91
220.69
18.01
17.35
1991-92
Real wages for agriculture workers (average in Rs. per day)
1984-85
Table A3.16:
242.73
17.69
17.26
1992-93
269.98
17.10
15.68
1993-94
305.12
17.01
17.01
1994-95
CHAPTER FOUR
ANNEX 4:
TABLES
Table A4.1:
Capital stock ratios in large-scale manufacturing, 1990-91 (Rs million or %)
Gross output
Per unit
Per
worker
Capital
per
worker
Net
output
per
worker
Net output
% of
Gross
output
Capital
stock
Consumer goods
77.80
0.49
0.158
0.130
34.2
82
Food, geverages and tobacco
80.20
0.78
0.182
0.224
28.9
123
423.30
0.50
0.256
0.203
40.7
7
76.90
0.38
0.156
0.100
25.3
62
236.70
0.39
0.188
0.109
28.0
58
73.40
0.58
0.104
0.126
21.8
121
104.60
1.30
0.228
0.239
18.4
105
57.80
1.88
0.066
0.108
5.8
164
168.20
1.13
0.477
0.379
33.4
79
902.50
1.13
0.605
0.431
38.3
71
10122.30
13.50
0.809
0.960
7.1
119
Other cons-related inter. goods
63.80
0.68
0.146
0.184
26.8
125
Intermediate goods (invest.)
72.20
0.49
0.437
0.166
34.0
38
Non-metallic mineral products
99.60
0.57
0.436
0.261
46.2
60
582.90
0.86
0.655
0.428
49.8
65
Of which: Sugar
Textiles, garments and footwear
Of which: Cotton yarn and cloth
Other consumer goods
Intermediate goods (cons.)
Cotton ginning
Industrial chemicals
Of which: Fertilizers
Petroleum refining
Of which: Cement
129
Gross output
Per unit
Iron and steel
Per
worker
Capital
per
worker
Net
output
per
worker
Net output
% of
Gross
output
Capital
stock
116.90
0.50
0.537
0.134
27.0
25
Other inv-related inter. goods
15.40
0.28
0.084
0.062
22.3
75
Capital goods
49.70
0.53
0.125
0.131
24.7
105
Machinery (including electrical)
44.20
0.49
0.128
0.143
29.4
112
111.80
0.78
0.141
0.142
18.3
101
15.40
0.25
0.084
0.056
22.0
67
78.20
0.60
0.202
0.149
24.8
74
307.40
0.47
0.249
0.160
34.2
64
Transport equipment
Other capital goods
Total or average
Memo: “Big Four” a
Note: a “Big Four” refers to sugar, textiles (cotton yarn and cloth), cement and fertilizers.
Source: Censuses of Manufacturing Industries.
Table A4.2:
Ratio of fixed assets to employment
K/L ratio
Major Industry
1988-87
1990-91
Food
183,045
177,905
Beverages
132,167
228,000
Tobacco
32,333
85,833
Textiles
93,327
151,172
Wearing apparels
39,417
46,050
Leather and products
49,833
104,733
-
-
303,000
203,333
-
-
153,222
207,875
Printing and publishing
60,583
121,000
Drugs and pharmaceutical products
86,267
120,889
453,000
449,000
80,364
110,889
Ginning, pressing and bailing
Wood and products
Furniture and fixture
Paper and products
Industrial chemicals
Other chemical products
130
Petroleum refining
1,176,500
984,000
Petroleum and coal products
77,000
92,500
Rubber products
94,875
103,875
Plastic products
95,000
133,200
Non-metallic mineral products
331,036
443,000
Iron and steel basic industries
612,667
546,614
67,000
76,417
Non-electrical goods
101,947
95,960
Electrical machinery
74,250
152,684
Transport equipment
70,913
135,947
Measuring, photographic, optical goods
62,000
43,500
86,319,000
14,962,250
-
-
Fabricated metal products
Sports and athletic goods
Others
131
Table A4.3:
Capital output ratios wage – value added ratios
Capital output ratios
198081
Wage – value added ratios
198485
198788
199091
198081
198485
198788
199091
All industries
1.7
1.89
1.421
1.350
0.417
0.355
0.253
0.285
Food manufacturing
1.3
1.34
0.746
1.169
0.229
0.273
0.207
0.251
Beverage industries
1.4
2.13
0.776
1.103
0.374
0.510
0.159
0.184
Tobacco manufacturing
0.4
0.75
0.056
0.079
0.325
0.313
0.031
0.032
Textile
1.8
1.70
1.538
1.576
0.551
0.373
0.290
0.322
Wearing apparel
0.8
1.14
0.665
1.086
0.313
0.694
0.398
0.754
Leather and leather products
0.7
0.53
4.203
1.891
0.181
0.217
0.991
0.452
Foot-wear except rubber or plastic
0.3
0.88
0.633
1.404
0.338
0.323
0.480
0.870
Ginning and bailing of fibres
0.5
0.76
0.623
0.435
0.183
0.266
0.347
0.325
Furniture and fixtures, not metal
0.8
5.12
3.192
1.022
0.387
0.373
0.449
0.347
Other paper products
1.6
2.11
1.959
1.491
0.535
0.440
0.319
0.229
Printing and publishing
2.1
1.57
1.388
0.420
0.558
0.506
0.606
0.166
Drugs and pharmaceutical products
0.4
1.14
0.875
0.798
0.236
0.385
0.478
0.479
Industrial chemicals
4.2
2.10
1.725
1.259
0.332
0.269
0.224
0.220
Other chemical products
1.0
0.55
0.501
0.497
0.395
0.233
0.194
0.217
4.59
0.508
0.843 na
0.183
0.043
0.116
Petroleum refining
na
Rubber products
0.6
1.66
1.558
0.972
0.345
0.489
0.433
0.388
Plastic products
2.4
1.43
1.484
0.095
0.784
0.362
0.424
0.376
Pottery, china and earthenware
2.2
2.42
1.415
3.011
0.538
0.478
0.411
0.424
Other non-metallic mineral products
7.9
1.81
1.492 na
0.938
0.303
0.156
7.622
Glass and glass products
2.3
4.49
2.010
1.609 na
0.604
0.344
5.740
Iron and steel
1.0
1.40
5.784
4.019
0.863 na
0.422
0.543
Non-ferrous metal basic industries
1.4
1.12
0.470
2.662
0.756
0.403
0.722
0.676
Metal products, machinery,
equipment
1.8
1.10
1.036
0.955
0.595
0.419
0.418
0.381
Non-electrical machinery
1.0
1.09
1.888
1.049
0.458
0.518
0.538
0.530
Transport-equipment
2.3
1.17
1.730
0.988 -na
0.319
0.676
0.414
132
Table A3.4:
log V/L =
Determinants of labour productivity and employment in Pakistan
OLS Regression results
0.89 + 0.85 log K/L + 0.05t
R2 = 0.99
(0.41)
(3.84)
(12.32)
log V/L =
-0.48 +
(0.16)
0.81 log K/L + 1.74 log V+
(3.41)
(0.69)
log V/L =
-6.68 +
(3.30)
0.78 log K/L + 0.79 log V
(2.79)
(10.02)
log V/L =
-1.15 + 0.99 log v
(2.50) (23.85)
log L = 6.99
- 0.58 log K/L (2.41) (-1.96)
0.01 t
(1.80)
log L = 0.48
+ 0.83 log V
(-.20) (3.30)
-
0.81 log K/L
(3.41)
Log L =
6.68 + 0.21 log V
(3.30) (2.67)
-
0.78 log K/L
(2.78)
Log L =
1.15 + 0.013Log V
(2.50) (0.31)
0.040t
(2.56)
-
0.04 t
(2.l56)
D.W. 1.20
R2 = .99
D.W. = 1.09
R2 = .98
D.W. = 0.53
R2 = .97
D.W. 1.15
R2 = 0.22
D.W. 0.49
R2 = .57
D.W. 1.09
R2 = .36
D.W. = 1.5
R2 = 0.06
D.W. = 1.15
where: V = Value added in manufacturing
K = Capital stock in manufacturing
L = Labour in manufacturing
t = time trend
Table A4.5:
Productivity in different manufacturing industries in 1990-91 (Base=1982-83)
Labour productivity
Food
Capital productivity
Total factor
productivity
84.3
76.7
98.3
Textiles
257.1
151.3
103.1
Leather
57.2
53.2
94.9
Drugs and pharmaceutical
124.7
70.0
97.6
Industrial chemicals
139.4
196.0
104.2
Plastic products
109.1
106.0
100.2
Electrical machinery
175.0
103.9
100.7
Transport equipment
145.0
72.9
99.3
72.6
61.3
96.6
Cement
Source: DRI/PIDE Technology Study (1977).
133
Table A4.6:
Labour productivity and capital intensity manufacturing (Rs. Mn)
Labour productivity
(Value added/employment)
Capital intensity
(Value of fixed assets /employment)
1984-85
1985-86
1986-87
1987-88
1990-91
0.104
0.109
0.127
0.144
0.178
0.099
0.123
0.166
0.168
0.192
Source: Economic Survey 1995-96.
Table A4.7:
Investment in manufacturing industries
Investment in manufacturing
as percentage of GDP
Share of private
investment in total
manufacturing
Private
Public
Total
1982-83
1.7
1.3
3.0
57.0
1983-84
2.9
1.2
3.1
60.0
1984-85
2.0
0.8
2.7
72.1
1985-86
2.2
0.8
3.0
72.6
1986-87
2.6
0.4
2.9
87.1
1987-88
2.5
0.4
2.9
86.5
1988-89
2.9
0.4
3.4
87.2
1989-90
3.3
0.5
3.7
88.0
1990-91
3.3
0.5
3.8
87.6
1991-92
4.3
0.5
4.8
89.8
1992-93
4.2
0.5
4.7
89.1
1993-94
4.2
0.5
4.7
87.7
1994-95
2.2
0.5
2.7
80.8
1995-96
2.3
0.6
2.9
80.9
1996-97
2.1
0.6
2.7
77.4
Source: Based on data obtained from Economic Survey, 1996-97 and previous issues.
134
Table A4.8:
Composition of total investment in the manufacturing sector
Percentage share in investment
1982-83
1988-89
1992-93
Food, tobacco and beverages
14.30
18.90
26.40
Textiles
16.09
41.00
29.30
Leather, footwear and leather goods
1.50
3.70
2.30
Rubber and rubber products
3.60
0.80
1.20
Pulp and paper
5.50
4.30
4.60
Chemicals, pharmaceuticals and fertilizers
27.60
7.30
10.10
Cement and other non-metallic minerals
products
12.80
4.90
2.90
Basic metals
2.30
1.20
1.80
Metal products other than machinery
and transport equipment
2.50
1.10
1.30
Machinery other than electrical
2.40
1.10
1.30
Electrical machinery, appliances and fittings
3.20
3.20
2.70
Transport equipment
2.20
2.50
3.40
Services and miscellaneous industries
5.10
9.10
13.60
Source: National Accounts, 1988/89, and unpublished data from Federal Bureau of Statistics.
135
Table A4.9:
Composition of industrial output in Pakistan
Industries
Percentage share in value added
at factor cost
1980-81
1985-86
1987-88
1990-91
24.21
15.69
15.49
14.24
1
Food Industries
2
Beverage Industries
0.90
1.52
0.61
1.27
3
Tobacco Manufacturing
3.00
2.87
5.38
7.49
4
Manufacturing of textiles
24.32
19.85
21.43
25.97
5
Manufacturing of wearing apparel except footwear
1.42
1.55
1.96
1.03
6
Manufacturing of leather and leather products,
leather substitutes and fur except wearing apparel
1.62
2.34
1.60
0.73
7
Manufacturing of footwear except vulcanized
molded rubber of plastic footwear
1.29
0.29
0.99
0.38
8
Ginning, pressing and baling of fibres
4.65
2.60
1.25
1.23
9
Manufacturing of wood and cork products
except furniture
0.43
0.48
0.61
0.26
10
Manufacturing of paper and paper products
2.06
1.26
1.32
1.69
11
Printing publishing and allied industries
1.15
1.54
1.33
2.57
12
Manufacturing of drugs and pharmaceutical
products
5.35
5.72
3.46
3.46
13
Manufacturing of Industrial chemicals
5.88
14.18
8.35
7.25
14
Manufacturing of other chemical products
1.99
3.62
3.11
2.31
15
Manufacturing of rubber products
1.26
1.86
0.70
0.86
16
Manufacturing of plastic products n.e.c.
0.24
0.75
0.51
0.55
17
Manufacturing of pottery, china and earthenware
0.32
0.32
0.42
0.25
18
Manufacturing of non-metallic mineral products
2.36
4.86
6.02
7.69
19
Iron and steel basic industries
6.61
5.32
8.26
6.34
20
Non-ferrous metal basic industries
0.06
0.02
0.02
0.03
21
Manufacturing of fabricated metal products
except machinery and equipment
1.30
1.10
0.93
0.80
22
Manufacturing of machinery except electrical
2.59
3.26
2.09
2.46
23
Manufacturing of electrical machinery apparatus,
appliances and supplies
4.25
4.06
3.53
4.21
24
Manufacturing of transport equipment
2.49
3.36
4.62
2.86
25
Manufacturing of scientific, precision and
measuring instruments and equipment
0.29
0.17
0.40
0.14
26
Manufacturing of photographic and optical goods
0.04
0.03
-
-
27
Manufacturing of sports and athletic goods
0.10
0.17
0.25
0.32
28
Other manufacturing industries
0.36
0.29
5.00
1.27
Source: Census of Manufacturing Industries, 1980-81, 1985-86, 1987-88 and 1990-91.
136
Table A4.10:
Industrial production – large-scale (percentage share)
Item
Food, beverage and
tobacco
1988-89 1989-90 1990-91 1991-92 1992-93 1994-95 1995-96 1996-97
26.14
25.58
24.25
25.52
27.06
28.65
28.53
26.10
18.89
18.76
18.83
19.57
19.59
21.68
20.73
18.34
Beverages
5.55
2.18
4.03
4.68
6.15
5.60
6.62
6.10
Cigarettes
1.70
1.64
1.30
1.27
1.32
1.37
1.18
1.66
24.75
26.46
26.03
27.48
26.78
26.05
26.07
28.32
16.13
18.11
17.17
17.50
19.62
19.93
20.03
21.39
Jute goods
1.36
1.22
1.22
1.16
1.04
0.79
0.67
0.69
Leather
1.84
1.83
1.73
1.58
1.39
1.29
1.23
1.15
Cotton (ginned)
5.41
5.30
5.91
7.24
4.73
4.04
4.14
5.09
Paper and board
2.29
2.16
1.87
1.99
2.75
2.69
2.99
2.84
19.16
18.52
18.79
17.70
17.88
18.57
17.22
18.67
7.04
7.16
7.52
7.60
7.56
7.07
6.32
6.50
11.26
10.54
10.39
9.41
9.74
10.88
10.24
11.44
0.86
0.82
0.88
0.69
0.59
0.62
0.66
0.74
Petroleum products
7.13
7.17
8.02
7.40
6.56
6.43
5.60
6.02
Non-metallic mineral
products
2.70
2.72
2.82
2.71
2.59
2.42
2.37
2.68
Basic metal industries
6.78
6.49
7.22
6.65
6.44
7.02
5.73
5.60
Metal products,
machinery
11.06
10.90
11.00
10.54
9.94
8.18
11.50
9.77
Metal products
0.29
0.29
0.25
0.28
0.29
0.23
0.24
0.27
Machinery
1.33
1.05
0.78
0.56
0.84
0.52
0.47
0.44
Electrical machinery
4.98
4.85
5.15
4.85
4.57
4.55
4.75
5.02
Transport equipment
4.46
4.75
4.82
4.85
4.24
2.88
6.04
4.04
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
Food
Textile, apparel and
leather
Textiles
Pharmaceuticals,
chemicals and rubber
Pharmaceuticals
Chemicals
Rubber
TOTAL
Source: Unpublished National Accounts Data.
137
Table A4.11:
Capacity utilization in major industries
1992-93
1993-94
1994-95
1995-96
Spinning
80.30
71.90
72.10
61.50
Weaving
42.90
42.90
35.70
42.90
-
50.70
44.70
47.30
Fertilizer
87.70
93.50
92.40
100.60
Cement
104.80
99.60
95.40
96.60
99.10
102.20
95.40
69.50
Jute Goods
Sugar
Source: Planning and Development Division.
138
CHAPTER FIVE
ANNEX 5.12: THE SMALL-SCALE ENTERPRISE
SECTOR IN MAIN DATA SOURCES
The data sources include National Income Accounts, Labour Force Surveys, the Economic Survey as well
as major surveys done for this sector in Pakistan. These major surveys are: the Small Household and
Manufacturing Industries (SHMI) 1983-84, 1988; the Census of Establishments 1987-88, the Household
Integrated Economic Survey (HIES) 1987-88, 1990-91; the Integrated Survey of Service and Manufacturing
Industries-Small, (ISSMI-Small), 1992.
Partial estimates of the output of the sector based on National Income Accounts (NIA) (table A5.1), suggest
that its output share in manufacturing is around 30 per cent while its employment share is nearly 83 per cent
(table A2). NIA, however calculate the size of the small-scale sector as a residual. In short, according to
NIA we have a disproportionately high share of employment within manufacturing which goes to the SSE.
Another characteristic of the SSE sector is its allegedly high growth rate. The combination of high
employment absorption capacities and its supposedly high growth rate make this sector a focus of attention
from an employment perspective.
Rates of growth
It is therefore important to estimate the growth rate of the sector as correctly as is possible, even if it is only
in manufacturing. However, serious problems arise. Of the two methods of calculating growth rates of the
SSE in Pakistan, one is based on National Income Accounts (NIA) and the other on inter-survey data on
the SSE. National Income Accounts essentially calculate the growth rate between two residual categories
(the estimate of the sector’s size is itself based on a residual); these calculations give a high growth rate for
the sector. Inter-survey data on the other hand give a much lower rate of growth, although they have some
problems of definition and comparability.
On NIA data, during the period 1980-81 to 1992-93, the manufacturing sector as a whole grew by 7.3 per
cent, the large-scale sector is supposed to have grown by 7.1 per cent. This gives a residual growth rate of
the SSE of 8.1 per cent (see table A5.3). If the period is extended up to 1996-97, the growth rate of the SSE
become even higher at nearly 10 per cent. NIA data over the long run show, that during the 1950s and 1960s
the large-scale sector was the leading sector in manufacturing. In the 1970s a reversal took place when the
growth of the large-scale sector dropped (to around 4 per cent) and that of the small sector increased (to
nearly 8 per cent)3. Over the 1980s , the period of high growth of the economy both sectors registered a
growth of around 8 per cent. Since 1987-88, the trend in large-scale manufacturing growth is one of decline.
However, a constant rate of growth of 8.4 per cent is estimated for the SSE for each subsequent year, up
to 1997. This suggests that the estimate is likely to be ‘projection based’ and does not have a direct
empirical basis (see table A5.4).
The growth of the SSE in manufacturing from the alternative survey sources give different growth figures.
There are two sources here. First we have the Survey of Small Household-based Manufacturing Industries
2
See ILO-SAAT, Mahmood, M., 1997, mimeo for details.
3
This is sometimes attributed to the effect of the first PPP governments’ nationalization of some large-scale
industries.
139
(SHMI) surveys for 1976-77, 1983-84 and 1988. Growth rates can be calculated from these, subject to
modifications, due to differences in definitions and coverage of the SSEs in the three surveys, in order to
make the basis of calculations consistent. There is also a fourth Integrated Survey of Service and
Manufacturing Industries –Small (ISSMI-Small) for 1992-934 .
An input-output table for Pakistan has been used to make the SHMIs of 1976-77 and 1983-84 comparable
(table A5.5) . This gives a growth rate of SSE between 1976-77 and 1983-84 of 4.4 per cent. Making
the SHMIs of 1983-84 and 1988 comparable, a growth rate of 4.7 per cent is estimated. The final
comparison is between the SHMI 1983-84 and ISSMI-Small 1992-93.5 This gives an even lower growth
rate of 2.6 per cent.
Thus, NIA-based growth rates for the SSE sector in manufacturing are high, at around 8 per cent for the
1970s, 1980s and the 1990s. In contrast inter-survey growth rates for the 1970s and 1980s are much lower
at 4.5 per cent and, for the last decade, up to 1992-93, even lower at 2.6 per cent. Even if we take an
equivocal view on the data sources for the calculation of growth rates the SSE sector in manufacturing
cannot be considered to have had unambiguously high growth rates during the 1970s, 1980s and 1990s.
The likelihood is that growth rates were considerably lower, especially in the past decade. We now examine
the profile of SSEs as it is revealed in the major surveys.
Broad characteristics
The SHMI
In 1988 there were 258,000 SSE units in manufacturing. They had fixed assets of Rs.5.6 billion; employed
.6 million persons and produced a value added of Rs 9.9 billion.
4
The differences between the SHMI surveys and ISSMI-Small in definitions and coverage are the following: SHMI
1976/77: (a) Surveyed establishments; (b) With an investment of less than Rs. 2 million; (c) In urban areas only. SHMI
1983/84: (a) Surveyed establishments; (b) Which were not registered; (c) In both urban and rural areas. SHMI 1988: (a)
Conducted a census of establishments; (b) Employing less than 10 workers; (c) In both urban and rural areas. ISSMI-Small
1992/93: (a) Surveyed establishments; (b) Which were neither listed on the stock exchange, nor registered with the
Government, nor Government sponsored; (c) In both urban and rural areas.
5
To make the SHMIs for 1976/77 and 1983/84 comparable and to calculate the growth rate, Table A5.5 carries out
a procedure detailed in Input Output Table for Pakistan, 1993. In essence the procedure is the following: for the SHMI 1983/84,
it takes the Gross Value Added (GVA) revised downwards for 6 industries with estimation errors, per urban labourer. It then
estimates the labour force in manufacturing for 1983/84 and subtracts the large-scale sectors share given in the Census of
Manufacturing industries (CMI) for 1983/84. This gives an SSE labour force for both rural and urban areas. Then SSE
employment multiplied by SSE GVA per labourer gives a total SSE GVA of Rs 12.8 billion. For the SHMI 1976/77 it follows
a similar procedure to give a total SSE GVA of Rs 5.6 billion. These values for 1976/77 and 1983/84 are then indexed by
wholesale prices. This procedure gives a growth rate for the inter-survey period of 1976/77 - 1983/84 of 4.4 per cent in Table
A5.5. We have followed an additional procedure given in SHMI 1988, which makes urban SHMI 1983/84 comparable to urban
SHMI 1988 [SHMI, 1988]. This involves subtracting units employing more than 10 workers from urban SHMI 1983/84. This
procedure gives a growth rate for the inter-survey period of 1983/84 and 1988 of 4.7 per cent in Table A5.6.
The growth rates for value added per unit of labour are given in Table A5.7. Finally in Table A5.8 we have calculated
growth rates for value added in the SSE sector for the most recent period possible, 1983/84 to 1992/93. This involves a
comparison between the SHMI 1983/84, and the most recently conducted Integrated Survey of Service and Manufacturing
Industries Small (ISSMI-Small) for 1992/93. There is some justification for making this comparison because, as the above
definitions show, both the SHMI 1983/84 and ISSMI Small 1992/93 surveyed the unregistered sector. In Table A5.8 we have
compared SHMI 1983/84 which is for manufacturing only, with ISSMI-Small 1992/93 for manufacturing. This gives an even
lower growth rate for the SSE sector between 1983/84 and 1992/93 of 2.6 per cent p.a.
140
The value added per worker (labour productivity) of the sector was Rs. 18,000 in urban areas and
Rs. 11,000 in rural areas (table A5.7). In contrast, large-scale sector labour productivity is 10 times
greater on average. The capital-labour ratio, i.e. the capital intensity, for the SSE is around Rs. 9,000. The
large-scale sectors value of capital per worker is Rs. 202,000 (not provided in a table here), which is greater
by a factor of 22 in comparison to the SSE (table A5.9). The capital output ratio of the SSE is 1.8, which
is also lower than 3.0 for large-scale sector. Clearly, both in terms of capital intensity and labour
productivity the SSE sector is much lower than the large-scale sector.
In terms of value of assets the predominant SSE sub-sectors are food (31 per cent); followed by textiles (24
per cent); wood products (17 per cent) and fabricated metals (15 per cent). In employment, textiles have the
largest share (42 per cent) followed by food (16 per cent); wood products (15 per cent) and fabricated metals
(14 per cent). Textile again have the highest share in value added at 36 per cent, followed by food (18 per
cent) and fabricated metals and wood with a 15 per cent share.
The significant industries within each major sub-sector can be determined on the basis of value added. In
textiles, the largest industries are weaving (11 per cent share in total SSE manufacturing value added
(TVA)) and carpets (7 per cent of TVA). In the second largest sub-sector, which is food products, the
largest industry is wheat milling (8 per cent of TVA) and rice (2 per cent of TVA). In the third largest subsector of fabricated metals, the major industry is metal products (8 per cent of TVA) followed by nonelectrical machines (3 per cent of TVA). In the fourth largest sub-sector, wood products, the most
significant industry is furniture (6 per cent of TVA).
If we rank the industries on their own, weaving is the largest, followed by metal products, wheat milling,
jewelry (a category on its own), furniture and non-electrical machinery.
The Census of Establishments (CE) 1987-88 and the Household Integrated
Economic Survey 1990-91 (HIES)
The SHMI of an SSE employment of .63 million workers and 258,000 units is also partial as it excludes
non-manufacturing sector. This SHMI estimate, however, is complemented well by a survey of income for
the same year, the Census of Establishments (CE) 1987-88. The two together allow an estimate of the entire
SSE sector.
The CE estimates of non-farm establishments using less than 10 workers are around 1.8 million, which
employ 3.1 million workers. The share of manufacturing in employment from this data source is 0.65 million
which is consistent with the SHMI data set, this is also the case with the sectoral compositions.
The total picture therefore gives an employment size of 2.45 million workers in non-manufacturing
employment in 1987-88 (table A5.10). The largest share of employment is in trade (42 per cent of SSE
employment), followed by services (28 per cent), textiles (9 per cent), catering (7 per cent), finance (2 per
cent), transport (1 per cent), and fabricated metals and wood (around 3 per cent) each. The urban-rural
employment split of the SSE is 69 per cent and 31 per cent respectively, although the ranking of the subsectors within them is the same.
The rural urban split is 31 to 69 per cent in favour of rural and the ranking of sub-sectors is the same for
both.
141
Serious discrepancy in the manufacturing sector estimates
We need to note a very significant discrepancy between the employment estimates based on the SHMI and
CE of 1987-88 and the Labour Force Surveys( LFS). The SHMI and CE data estimate the SSE employment
in manufacturing to be roughly around 0.7 million. The LFS estimates the total employment in
manufacturing in 1987-88 to be 4.1 million, of which the SSE’s share is 3 million and the large-scale
manufacturing sectors share is .6 million.6 In other words the lower bound for SSE manufacturing
employment is .7 million (SHMI and CE data) and the upper bound is 3 million (LFS data) for the year
1987-88. This poses a serious problem and we need to have some alternative estimates, to achieve
perspective on the size of employment in the sector.
The Household Integrated Economic Survey (HIES) 1987–88 and 1990-91
The HIES 1990-91 gives a fairly good and recent estimate of the entire SSE (tables A5.10 an A5.11). The
variable in the HIES is the number of units, 4.5 million in 1990-91. Trade is still the largest sub-sector (2.1
million units) followed by services (1.3 million), manufacturing (0.8 million) and catering (0.2 million). For
all the units in the sector taken together and applying a constant ratio of employment per unit (1.72) the total
employment for 1991 comes to 7.7 million persons. On the same assumption, manufacturing employment
comes to 1.37 million, somewhere between the SHMI/CE estimate and the LFS estimate.
A striking characteristic brought out by the HIES 1990-91 is that of the 4.5 million units, 1.1 million are
mobile, 0.5 from trade and another 0.5 from services.
A third important characteristic is that rural units are greater than urban ones. Of the 4.5 million, 2.5 million
are in rural areas and 2 million in urban areas7. This is in contrast to the SHMI/CE estimates which
suggest that the number of urban units to be higher in 1987-88, some three year prior to the date of the
HIES.
Fourthly, mean income is clearly lower than that in the large-scale sector.
Our estimates of the SSE from the above discussion suggest that this sector could be employing between
3.1 and 7.7 million persons. Its mean income is lower than that in the large-scale sector and to that extent
it is to a refuge sector. Manufacturing is a quarter of this sector in terms of value added, while trade and
services account for around 70 per cent. Manufacturing in the SSE has a low capital-labour ratio and
therefore a much lower labour productivity compared to the large-scale sector.
ISSMI-Small 1992-93
We have a wide range of size of employment in the sector, which we need to narrow down. Estimates based
on Integrated Survey of Service an Manufacturing Industries-Small 1992-93 (ISSMI) allow for this
possibility (tables A5.12-15). In 1992-93 the SSE comprised 1.9 million units which is consistent with the
1.8 units figure of the CE 1990-91 and much lower than the HIES 1990-91 figure of 4.5 million.
Employment according to ISSMI is 4.4 million which lies between the lower bound given by CE of 3.1
6
LFS 4.1 million in the manufacturing sector should be equaled by [CMI Large-scale = 0.6m] + [SHMI Smallscale ] in 1988 but is not. Therefore, as a second-best estimate we can take SSE as a residue = [(4.1m) - (CMI's 0.6m)] = 3.7m.
But this may be on the high side since CMI 0.6m is underestimated due to non-registration.
7
The density of units per 1,000 population is 55 for urban, 33 for rural areas and 40 for the whole sector. This
suggests that the proliferation of the SSE sector is some function of population, even if it is not strictly proportional.
142
million and the upper bound of 7.7 million projected with HIES 1990-91. Of the value added contribution
of Rs. 226 billion, the share of manufacturing is 26 billion, which is 17 per cent of the value added in the
entire manufacturing sector according to ISSMI –Small and ISSMI- Large. The mean wage in the SSE is
Rs 4000, which lies between that of a semiskilled and skilled worker. Capital stock data for ISSMI-Small
are comparable to SHMI 1988 estimates shown above. Trade is ranked as the largest sub-sector on asset
values, employment and value added. This is followed by services, textiles, food, hotels and metal
fabrication. This is also in keeping with the SHMI 1988 data.
Therefore ISSMI-Small is not only consistent in many respects with other major surveys, it also arrives at
a plausible middling figure for employment in the SSE sector which lies between the wide range of figures
we get from different sources.
143
ANNEX 5.2: TABLES
Table A5.1:
Estimated share of the small-scale sector in manufacturing 1992/93
GDP at current
factor cost
1990/91
(Rs. Million)
%
908,374
100.00
%
1991/92
(Rs. Million)
%
1,077,943
100.00
%
1992/93
(Rs. Million)
%
1,200,129
100.00
%
1996/97
(Rs. Million)
%
%
2,245,904
100.00
Total
manufacturing
158,840
112,204
Small-scale
46,636
17.49
12.35
5.13
100.00
70.64
29.36
186,832
130,252
56,580
17.33
12.08
5.25
100.00
69.72
30.28
207,273
142,206
65,267
17.27
1185.00
5.44
100.00
68.61
31.49
378,647
256,164
122,483
16.86
11.40
5.45
100.00
67.65
32.36
Source: Calculated from the Economic Survey 1996-97.
144
Large-scale
145
100.00
1,838,000
100.00
80.50
19.50
% of
Manufacturing
25,220,000
(13.44)
3,389,044
(10.70)
2,699,044
690,000
(2.74)
1982-83
100.00
79.60
20.40
% of
Manufacturing
ILO/ARTEP, employment and structural change in Pakistan, Bangkok, 1983 and labour force surveys, CMI 1990-91.
21,840,000
(13.640)
2,978,928
(10.98)
2,398,928
580,000
(2.66)
1977-78
Source:
18,270,000
100.00
79.00
21.00
% of
Manufacturing
(a) Residual of total and large-scale manufacturing sector.
(b) Domestic employed labour force.
(c) For 1987-88 based on CMI and NMC Survey of large-scale manufacturing.
13,517,000
Total labour
(12.51)
2,286,150
(9.89)
1,806,150
480,000
(2.63)
1971-72
Note:
(13.60)
Manufacturing
Total
81.70
1,501,000
(11.10)
Small-Scale
(a)
Manufacturing
18.30
% of
Manufacturing
337,000
(2.49)
1960
Employment in the manufacturing sector
Large-Scale
Manufacturing
Table A5.2:
29,600,000
(14.00)
4,143,900a
(11.57)
3,423,900
720,000c
(2.43)
1987-88
100.00
82.60
17.40
% of
Manufacturing
29,828,000
3,647,964
3,024,584
623,380
1990-91
100.00
12.23
10.14
2.09
% of
Manufacturing
100.00
82.90
17.10
% of
Manufacturing
146
580,000
(19.47)
1,501,452
(50.40)
897,476
(30.13)
480,000
(21.00)
1,295,814
(56.68)
51,366
(22.32)
Small-scale rural
Small-scale urban
(I)
(II)
Breakdown of Small-scale based on labour force survey.
All Large-scale assumed in urban areas.
% in brackets.
1,473,625
(35.56)
1,950,275
(47.06)
720,000
(17.37)
4,143,900
(100.00)
1987-88
Source: ILO/ARTEP, employment and structural change in Pakistan, Bangkok, 1983 and labour force surveys, CMI 1990-91.
Note:
Large-scale
Total manufacturing
2,978,928
(100.00)
1977-78
2,286,150
(100.00)
1971-72
Table A5.2b: Employment in manufacturing, urban/rural
1,315,440
(36.10)
1709,144
(46.90)
623,380
(17.10)
3,647,964
(100.00)
1990-91
Table A5.3:
Growth rates in manufacturing (constant factor cost 1980/81, Rs million)
Value added
Total
manufacturing
Large-scale
1980-81
37,446
27,451
9,995
26.70
1992-93
89,889
63,577
26,312
29.10
Growth rate (%)
1980/81-1992/93
1996-97
7.30
7.10
104,381
Growth rate (%)
1980/81-1996-97
Small-scale
68,051
8.50
8.10
33,330
7.60
10.00
Small-scale
(%) share
31.90
-
Source: Calculated from the Economic Survey 1996-97.
Table A5.4:
Real growth in the manufacturing sector (% per annum)
Small-scale
manufacturing
Large-scale
manufacturing
1950-60
2.30
15.40
7.70
1960-70
2.90
13.90
9.90
1970-80
7.90
3.90
4.80
1980-89
8.40
8.30
8.40
1950-86
5.00
10.00
7.50
1986-87
8.40
7.20
7.50
1987-88
8.40
10.60
10.00
1988-89
8.40
2.40
4.00
1989-90
8.40
4.70
5.70
1990-91
8.40
5.40
6.30
1991-92
8.40
7.90
8.10
1992-93
8.40
4.10
5.40
1993-94
8.40
4.30
5.50
1994-95
8.40
1.50
3.60
1995-96
8.40
2.60
4.40
1996-97
8.40
-1.40
1.80
Period
Total manufacturing
sector
Source: Economic Surveys.
147
Table A5.5:
Growth of SSE based on inter survey 1976/77 - 1983/84 growth rates
(Rs. million)
I.
1983/84
SHMI - Urban GVA (published)
8377.4 million
Correction for 6 industries
1518.0 million
SHMI Urban GVA revised
6895.4 million
Employment SHMI Urban
555,497
Urban SHMI GVA/L
Rs. 12,413
II. 1983/84 Estimates
Employed labour force in manufacturing
Pakistan
by Pop. Census 1981
Urban
1.996
LFS % PA 1980/81-1983/84
Rural
1.041
0.955
2.071
1.08
0.991
-0.665
-0.484
-0.181
1.406 million
0.596
0.81
Rs. 12,413
Rs. 6,669
7,410 million
5,398 million
1.23%
Manuf. est. labour force 1983/84
Manuf. LSE (cm1 1983/84)
Manuf. SSE
GVA/L in SSE
SSE GVA 1983/84
Rs. 12,808 million
III. 1976/77 Estimates
Employed labour force in manuf.
Pakistan
by pop. Census 1981
Urban
1.996 million
LFS % PA 1976/77 - 1980/81
Rural
1.041
0.955
2.85%
Manuf. Est. L Force 1976/77
1.784
0.931
0.853
Manuf. LSE (CM1 1976/77)
-0.616
-0.462
-0.154
1168
0.469
0.699
Rs. 6,629
Rs. 3,561
3104
2,490
Manuf. SSE
GVA/L in SSE
SSE GVA 1976/77
Rs. 5,594 million
IV. WPI 1976/77 (1975/76 = 100)
=
112.4
WPI 1983/84 (1975/76 = 100)
=
190.8
V. GVA SSE ave. PA growth rate 1976/77 1983/84
=
Source: Input Output Table 1993.
148
4.4%
Table A5.6:
Inter survey growth in value added: Pakistan, 1976/77-1988
Value added (Rs.million)
Current
1976-77
(Rs. 1975/76) Constant
5,594
% Growth Rate
4,977
4.3a
1983-84
12,808
6,713
5,250
2,752
(URBAN)
1983-84
4.7b
1988
Notes:
7,736
a
b
326
From the Input Output Table 1993. SHMI 1976/77 made comparable to 1983/84.
From the SHMI 1988. SHMI 1983/84 made comparable to 1988.
Table A5.7:
Inter survey growth in value added/labourer Value added/labourer (Rs.)
URBAN
Years
(Rs.)
Current
1976-77
6,629
(Rs.
1975/76)
Constant
RURAL
Growth
Rate
5,898
(Rs.)
Current
(Rs.
1975/76)
Constant
3,561
3,168
1.40
1983-84
12,413
6,506
1.40
6,669
3,495
4.80
1988
18,359
7,893
Growth
Rate
6.60
10,566
4,543
Source: Calculated from Input Output Table 1993, SHMI 1988.
Table A5.8:
Year
SSE manufacturing: Inter survey growth rates in value added 1983-84 - 1992/93
Current
GVA
(Rs. Million)
WPI
Constant
GVA
(Rs. Million)
1983/84
12,808.00
100.00
12,808.00
1992/93
25,768.00
159.41
16,206.00
Real
Growth
Rate in
GVA
2.6% PA
Source: Calculated from SMM1 1983/84 and ISSMI 1992/93.
149
150
955
100.0
22.4
9.3
3.1
3.5
29.6
8.5
2.5
11.5
2.4
2.7
0.9
4.4
0.7
2.0
22.6
8.4
9.3
1.1
5.2
2.0
1.3
4.8
3.6
0.8
Fixed
Assets
(Rs.m)
380
100.0
11.1
2.4
0.3
1.1
41.6
5.5
19.2
10.0
4.2
2.9
1.6
10.0
1.6
7.4
16.1
7.9
4.5
0.5
2.6
0.8
0.8
7.4
5.8
0.8
Employ
ment
(000)
1976/77
URBAN
Source: Calculated from SHMI: 1976/77, 1983/84, 1988.
8
7
5
4
3
2
1
108,642
100.0
9.2
3.5
0.2
1.2
43.0
6.4
9.1
13.5
6.7
2.8
1.6
3.5
2.0
0.5
16.9
8.3
4.9
0.7
3.0
0.8
0.6
10.2
8.8
0.4
No of
Units
SSE sectoral shares
Total value
Total
Food, beverages tobacco
Wheat milling
Rice milling
Oil extraction
Textiles, leather
Weaving
Carpets
Wood & products
Furniture
Chemicals, rubber
Plastic products
Minerals (non-iron)
Pottery
Bricks
Fabricated metal
Metal products
Non electric machines
Agricultural
Machining
Textiles
Basic metals
Iron foundries
Other
Jewelry
Sports goods
Table A5.9:
10
100.0
11.4
3.0
0.4
2.4
41.4
7.8
7.3
10.4
4.4
3.6
2.0
7.4
1.0
5.1
17.9
8.2
5.0
0.9
2.7
0.9
0.8
7.1
5.7
0.9
Value
Added
(Rs.m)
426,457
100.0
20.3
9.4
0.9
0.9
35.0
2.9
9.3
13.9
5.9
1.0
0.4
4.1
2.4
0.7
159.0
12.1
3.1
1.2
1.1
0.1
0.2
0.1
9.4
7.7
0.5
No of Units
6,736
100.0
44.5
5.5
18.9
1.0
17.3
5.9
1.2
12.5
2.4
1.3
0.4
4.0
0.4
1.3
14.2
6.6
5.9
2.4
1.8
0.3
0.5
0.3
5.6
4.3
0.4
Fixed
Assets
(Rs.m)
946
100.0
22.0
7.5
1.7
0.6
35.3
4.4
10.7
12.9
5.2
1.3
0.5
6.7
1.9
2.4
14.5
10.1
3.2
1.2
1.1
0.2
0.3
0.2
7.1
5.3
0.5
Employ
ment
(000)
1983/84
RURAL AND URBAN
9,369
100.0
20.2
7.9
3.2
0.9
32.0
7.0
1.8
12.7
4.8
1.9
0.8
8.7
1.1
4.7
15.4
8.8
4.2
1.8
1.3
0.2
0.4
0.3
8.7
6.7
0.6
Value
Added
(Rs.m)
257,557
100.0
18.9
13.4
0.5
0.6
39.2
6.2
13.5
15.1
7.0
1.7
0.9
2.7
1.4
0.3
12.4
7.7
2.2
0.8
0.6
0.2
0.3
0.1
9.7
7.1
1.3
No of Units
5,597
100.0
30.8
19.7
1.4
1.2
24.4
12.5
1.5
17.2
4.0
2.5
1.0
2.8
0.5
0.5
14.7
7.1
4.4
1.5
1.0
0.4
0.7
0.3
6.9
5.8
0.3
Fixed
Assets
(Rs.m)
627
100.0
15.9
8.9
0.5
0.5
41.6
8.8
14.2
15.0
6.5
2.2
1.3
3.2
1.3
0.6
13.7
8.0
2.6
0.8
0.6
0.3
0.5
0.3
7.8
5.3
1.3
Employ
ment
(000)
1988
RURAL AND URBAN
9,903
100.0
18.0
8.0
1.6
1.0
35.6
11.3
6.8
14.6
5.9
3.6
1.6
3.7
0.7
1.2
14.9
8.2
3.3
1.4
0.8
0.3
0.7
0.3
8.9
6.7
0.9
Value Added
(Rs.m)
151
20.2
57.8
844.8
10.4
24.5
543.0
Source: HIES 1987/88.
1.3
1.7
1,285.6
206.4
0.9
0.5
899.0
99.4
Utilities
Construction
Trade
Catering
Transport, storage
communication
Finance
Services
99.7
16.7
22.9
4.1
86.1
50.3
41.9
5.1
7.8
1.3
31.6
26.0
Wood products
Chemicals
Minerals
Metals
Fabric metals
Others industries
3,068.7
650.6
107.9
262.8
1,845.0
268.0
52.6
102.0
Employment
Total
Manufacturing
Food beverage
Textiles, leather
No. Units
Total
23.5
314.0
9.6
0.9
0.4
555.7
68.0
29.0
4.7
4.3
1.2
26.7
19.3
1,132.8
160.7
16.2
59.3
No.
Units
Rural
Total
Urban
55.8
573.0
18.7
1.3
1.6
882.9
152.0
74.4
15.8
12.3
3.9
76.2
38.9
2,119.6
434.2
45.9
166.9
1.0
228.5
0.8
0.1
343.1
31.4
13.7
0.4
3.5
0.1
4.9
6.7
712.2
107.2
36.5
42.3
2.0
271.9
1.4
0.1
402.9
54.4
25.3
1.0
10.7
0.2
9.8
11.5
949.1
216.4
62.0
95.9
1.3
29.4
0.6
0.0
0.0
48.7
5.4
2.3
0.3
0.4
0.1
1.7
1.4
100.0
14.5
2.9
5.5
1.9
27.5
0.7
0.0
0.0
41.9
6.7
3.2
0.5
0.7
0.1
2.8
1.6
100.0
21.2
3.5
8.6
1.3
17.0
0.5
0.0
0.0
30.1
3.7
1.6
0.3
0.2
0.1
1.4
1.0
61.4
8.7
0.9
3.2
1.8
18.7
0.6
0.0
0.0
28.8
5.0
2.4
0.5
0.4
0.1
2.5
1.3
69.1
14.1
1.5
5.4
0.1
12.4
0.0
0.0
18.6
1.7
0.7
0.0
0.2
0.0
0.3
0.4
38.6
5.8
2.0
2.3
0.1
8.9
0.0
0.0
13.1
1.8
0.8
0.0
0.3
0.0
0.3
0.4
30.9
7.1
2.0
3.1
Employment
Rural
EmployEmployEmployEmployNo. Units
No. Units
No. Units
No. Units
ment
ment
ment
ment
Urban
Table A5.10: HIES 87/87 i.e. SSE in manufacturing and other sectors estimate of establishments with less than 10 workers (‘000)
Table A5.11:
HIES, Non agricultural micro enterprises, 1990/91 (number and %)
Total
Manuf.
Trade
Hotels
Services
and others
Total
Manuf.
100.0
18.2
Trade
Hotels
Services
47.6
4.6
29.4
No. All Units
4,475
818
2,134
207
1,316
Fixed
3,367
777
1,610
166
814
75.2
17.3
35.9
3.7
18.1
Mobile
1,108
41
524
40
502
24.7
0.9
11.7
0.9
11.2
Urban
1,962
321
925
123
593
43.8
7.1
20.6
2.7
13.2
Rural
2,513
496
1,209
84
723
56.1
11.0
27.0
1.8
16.1
Average monthly income (Rs)
All Units
2,025
1,706
2,254
2,213
1,821
Urban
2,481
2,243
2,743
2,416
2,214
Rural
1,668
1,358
1,881
1,916
1,498
Density (Units/1000 Pop)
All Units
39.6
7.2
18.9
1.8
11.6
Urban
54.5
8.9
25.7
3.4
16.5
Rural
32.6
6.5
15.7
1.1
9.4
% Income share from SSE:
All Units
61
54.4
63.8
79.7
57.6
Urban
63
55.9
65.9
78.7
59.6
Rural
58.8
52.8
61.5
81.6
55.4
% Share of SSE's with all loans
All Loans
26.0
34.7
22.4
18.9
27.4
Urban
22.6
26.2
19.6
23.5
25.1
Rural
28.7
40.2
24.6
12.1
29.4
% Share of SSE's with commercial loans only
All Units
1.5
0.9
2.4
0.0
0.7
Urban
1.6
0.6
2.1
0.0
1.6
Rural
1.5
1.1
2.6
0.0
0.0
Average outstanding loan (Rs) Commercial only
All Units
74,046
200,000
64,510
Urban
51,711
18,937
18,987
Rural
90,967
200,000
73,051
152
54,323
12,007
16,474
Total
Manuf.
Trade
Hotels
Services
and others
Total
Manuf.
Trade
Hotels
Services
Average outstanding loan (Rs) Non-commercial only
All Units
12,953
12,340
14,233
9,725
12,269
Urban
17,611
18,937
18,987
12,007
16,474
Rural
10,129
9,432
11,425
3,572
9,467
Average income of (Rs/pm) SSE without any loans
All Units
2,086
1,738
2,326
2,238
1,837
Urban
2,567
2,327
2,854
2,443
2,243
Rural
1,677
1,268
1,895
1,979
1,484
Average income of (Rs/pm) SSE with only commercial loans
All Units
2,627
3,067
2,435
3,240
Urban
2,537
1,406
2,279
3,240
Rural
2,724
3,725
2,559
Average income of (Rs/pm) SSE with only non-commercial loans
All Units
1,796
1,607
1,950
2,103
1,724
Urban
2,148
2,022
2,288
2,330
2,026
Rural
1,588
1,432
1,752
1,461
1,531
Average employment of SSE without any loan
All Units
1.5
1.9
1.4
2.0
1.4
Urban
1.8
2.4
1.6
2.5
1.5
Rural
1.3
1.6
1.3
1.3
1.4
Average employment of SSE with only commercial loan
All Units
2.1
5.4
1.8
0.0
1.3
Urban
1.9
6.0
1.9
0.0
1.3
Rural
2.2
5.2
1.7
0.0
0.0
Average employment of SSE with only non commercial loan
All Units
1.5
2.1
1.3
1.5
1.3
Urban
1.5
2.0
1.4
1.6
1.3
Rural
1.5
2.1
1.2
1.2
1.3
Source: HIES (1990/91).
153
152
153
9
Paper
Services
Source:
ISSM1, 1992/93.
1,868
39
546
Finance
All Sectors
2
134
Hotels
Transport
35
778
Trade
Metal Products
Other
1
45
Metals
6
49
Wood
13
158
Textiles
Minerals
54
Chemicals
369
Food
No
Units
(000)
118,037
35,518
3,561
195
2,496
47,108
1,391
4,989
142
1,047
1,030
973
4,906
8,637
6,041
29,159
(K)
Asset
Value
(M.Rs)
4,368
(Million)
1,115,040
99,847
8,424
477,146
1,523,855
74,055
147,278
4,039
62,541
22,589
31,429
131,504
520,530
149,634
1,143,602
(L)
Employment
4,095
3,912
9,925
3,561
2,808
2,694
1,701
6,688
8,666
10,521
8,455
8,304
4,905
6,782
4,170
6,171
Mean
Wage
(Rs)
Small and medium sector characteristics (ISSMI) 1992-93
Manufacturing
Table A5.12:
226,010
19,126
3,257
168
6,384
171,246
2,168
3,605
96
2,586
692
809
2,897
9,777
3,195
25,829
(Y)
Profits or
Value
Added
(Mrs)
27,023
31,854
35,664
23,214
5,232
30,931
18,797
33,938
35,500
16,887
46,818
31,387
37,306
16,592
40,543
25,510
K/L
(Rs)
51,742
17,153
32,619
20,000
13,383
112,439
29,297
24,523
24,000
27,001
20,726
10,124
28,477
18,801
21,442
22,597
Y/L
(Rs)
1.91
0.54
0.91
0.86
2.56
3.64
1.56
0.72
0.68
2.47
0.67
0.83
0.59
1.13
0.53
0.89
Y/K
100.00
29.23
2.09
0.10
7.33
41.65
1.87
2.41
0.05
0.70
0.32
0.48
2.62
8.46
2.89
19.75
No
Units
100.00
30.09
3.02
0.17
2.11
39.91
1.18
4.23
0.12
0.89
0.87
0.82
4.16
7.32
5.12
24.70
Asset
Value
100.00
25.52
2.29
0.19
10.92
34.89
1.70
3.37
0.09
1.43
0.52
0.71
3.01
11.92
3.42
26.18
Employment
Percentage
Value Added
100.00
8.46
1.44
0.07
2.82
75.77
0.96
1.60
0.04
1.14
0.31
0.36
1.28
4.33
1.41
11.43
154
0
546
Finance
Services
Source: ISSM1 (1992-93).
2
Transport
134
1
Metals
Hotels
13
Minerals
778
6
Chemicals
Trade
9
Paper
35
49
Wood
Other
158
Textiles
45
54
Food
Metal products
369
1,829
Total
29
0
0
7
42
2
2
0
1
0
0
3
8
3
20
100
%
377
0
2
93
618
20
34
1
5
5
9
29
66
19
188
1,279
Urban
29
0
0
7
48
2
3
0
0
0
1
2
5
1
15
100
%
No. of Units
169
0
0
41
169
15
11
0
9
1
0
20
92
34
181
550
Rural
31
0
0
7
3
3
2
0
2
0
0
4
17
6
33
100
%
486
0
2
127
687
339
1,719
Individual
proprietorship
89
0
100
95
88
92
94
%
23
0
0
7
42
30
112
Partnership
Type of Firm
4
0
0
5
12
8
6
%
Estimates of the medium and small-scale non-agricultural sector 1992-93, (ISSM1) (000)
Manufacturing
All sectors
Table A5.13:
101
750
1
115
647
2
95
354
3-4
51
101
5-9
No. of Employees
8
17
> 10
Table A5.14:
SSE Sector characteristics (ISSMI, 1992/93) (000)
Characteristics
Vintage
90's
All sectors
Manufacturing
551
205
Late 80's
113
Early 80's
93
Late 70's
58
Early 70's
21
60's
45
50's
12
Pre 1947
4
Period Worked
1,279
Full Year
1,264
Type of Work
1,868
Subcontracting Only
Asset Size (Rs.)
> 1000
1 - < 10,000
0
369
85
106
10,000 - < 50,000
73
50,000 - < 100,000
44
100,000 - <500,000
51
>500,000
11
Obtaining loans
Outstanding Value
23
Rs.2,286M
Sources: Private
32
Landlord/Shopkeeper
22
Commercial Bank/Institution
18
Provincial Government
6
Source: ISSM1 (1992-93).
155
156
7
1
362
36456
>25
<10
Source: ISSM1 (1992/93).
51
5-9
115
2
95
101
1
3-4
369
All Manufacturing
No of.
Units
(000)
24,733
692
3,734
11,299
6,252
5,183
1,996
29,159
Asset Value
(M. Rs.)
1,007,551
47,850
88,201
331,414
325,640
238,328
112,167
1,143,602
Employment
5,433
8,333
13,409
10,042
5,025
1,819
723
6,170
Mean
Wage (Rs.)
Small and medium sector characteristics by size, (ISSM1), 1992/93
Employment size
(persons engaged)
Table A5.15:
21,614
1,194
2,960
8,889
6,453
3,789
2,481
25,768
Profit or
Value
Added
(M.Rs.)
0.060
1.800
0.400
0.200
0.070
0.030
0.020
0.060
Profit/
Unit
(M.Rs.)
0.874
1.730
0.790
0.790
1.030
0.730
1.240
0.880
Profit/
Capital
0.021
0.025
0.034
0.027
0.020
0.016
0.022
0.023
Profit/
Labour
(M.Rs.)
24,536
14,416
42,432
34,135
19,178
21,777
17,821
25,510
K/l (rs.)
157
566.5
Plant
364.8
569.2
247.1
55.5
88.5
11.0
252.9
108.3
Food, Beverage,
tobacco
Textiles, leather
Wood and products
Chemicals, rubber
Minerals (non iron)
Basic metals
Fabricated metals
Others
All industries
629.8
Weaving
97.5
235.4
10.6
84.6
52.7
234.1
486.3
335.3
519.4
28.3
100.0
8.6
539.4
259.5
182.5
1,536.4
From
Savings
90.5
Total Investment
30.6
Other fixed assets
9.0
269.8
Buildings
Transport
191.7
1,697.3
Total
Investment
(Rs. M)
Credit for the SSE sector
Land
All industries
Table A5.16:
8.5
10.4
16.7
0.4
3.9
2.6
11.2
80.5
18.7
100.8
1.3
0.4
24.1
9.9
8.2
144.7
Individuals
1.0
0.5
0.8
0.0
0.0
0.1
1.5
2.4
10.7
9.7
1.0
0.0
2.9
1.5
1.1
16.1
Total
0.3
0.5
0.1
0.8
0.9
9.8
7.7
1.0
1.9
1.2
0.7
12.5
Pakistani
Banks
Shares
0.1
0.1
0.1
Foreign
Banks
0.2
0.1
0.3
0.2
0.4
0.6
Coop Banks
Loans from financial institutions
0.1
0.6
1.3
0.5
1.5
0.5
0.3
0.4
2.6
Non-Banks
Institutions
0.1
0.1
0.1
0.1
0.3
0.3
Joint
Investment
Table A5.17:
Vintage of industries
No. of Units (000)
Total
units
Total
Pre1970
19701979
% of Units
19801988
Total
units
Pre1970
19701979
19801988
1,844.9
263.1
256.4
1,325.4
100
14.3
13.9
71.8
Manufacturing
267.9
27.1
37.9
202.9
100
10.1
14.1
75.7
Food, beverages
52.6
6.4
10.5
35.7
100
12.2
20.0
67.9
Textile, leather
101.6
9.7
14.0
77.9
100
9.5
13.8
76.7
41.9
3.4
5.3
33.2
100
8.1
12.6
79.2
Chemicals
5.1
0.2
0.4
4.5
100
3.9
7.8
88.2
Minerals
7.8
2.2
1.4
4.2
100
28.2
17.9
53.8
Metals
1.3
0.1
0.1
1.1
100
7.7
7.7
84.6
Fabric metals
31.6
2.2
2.9
26.5
100
7.0
9.2
83.9
Other industries
26.0
2.9
3.3
19.8
100
11.2
12.7
76.2
Utilities
0.9
0.1
0.2
0.6
100
11.1
22.2
66.7
Constructions
0.5
0.0
0.1
0.4
100
0.0
0.2
0.8
898.7
80.5
134.2
684.0
100
9.0
14.9
76.1
Catering
99.4
7.7
12.5
79.2
100
7.7
12.5
79.2
Transport, storage
10.4
0.8
1.5
8.1
100
7.7
14.4
77.9
Finance
24.5
2.1
4.4
18.0
100
8.6
18.0
73.5
Services
542.5
144.7
65.5
332.3
100
26.7
12.1
61.3
Wood
Trade
Source: HIES (1987/88).
158
159
Total value
Food, beverage, tobacco
Wheat milling
Rice milling
Oil expelling
Textiles, leather
Weavingstan
Carpets
Wood and products
Furniture
Chemicals, rubber
Plastic products
Minerals (non-metal)
Pottery
Bricks
Fabricated metal
Metal products
Non electric machines
Agricultural
Machining
Textiles
Basic metals
Iron found-aries
Other
Jewelry
Sports goods share
108.6
10,042.0
3,793.0
201.0
1,317.0
46,709.0
6,965.0
9,833.0
14,643.0
7,284.0
3,070.0
1,688.0
3,832.0
2,123.0
589.0
18,395.0
9,060.0
5,305.0
771.0
3,312.0
851.0
628.0
11,100.0
9,611.0
480.0
No. Units
955.2
213.6
88.8
29.6
33.9
282.4
81.6
23.6
110.2
22.6
26.1
8.7
41.8
6.6
19.2
216.2
80.7
17.0
10.8
49.4
19.3
12.2
45.6
34.1
7.3
Fixed
Assets
(Rs.M.)
380.0
42.0
9.0
1.0
4.0
1,586.0
21.0
73.0
38.0
162.0
11.0
6.0
38.0
6.0
28.0
61.0
30.0
13,222.0
2.0
10.0
3.0
3.0
28.0
22.0
3.0
Employment
(000)
1976/77
SHMI Pakistan (rural and urban)
2,599.6
296.5
76.7
9.5
62.4
10,766.0
202.8
190.0
269.1
113.6
94.0
51.2
191.5
25.4
131.3
465.3
212.4
30.0
24.4
69.5
23.1
19.7
183.3
148.4
24.0
Value
Added
(Rs.M.)
426,457.0
86,774.0
40,149.0
39.8
3,751.0
149,088.0
12,466.0
39,861.0
59,186.0
25.0
4,450.0
1,844.0
17,807.0
10,432.0
3,022.0
67,927.0
51,530.0
5,758.0
5,196.0
4,913.0
575.0
928.0
500.0
40,297.0
32,830.0
229.4
No. Units
6,736.2
3,000.5
372.9
1,271.4
67.1
1,165.5
398.3
81.8
841.8
160.8
88.0
26.7
272.5
29.9
85.8
958.2
441.7
16.0
161.9
121.6
18.3
35.2
17.0
374.4
287.5
30.2
Fixed
Assets
(Rs.M.)
946.0
208.0
71.0
167.0
6.6
334.0
42.0
101.0
122.0
492.0
12.0
5.0
63.0
18.0
23.0
137.0
96.0
324.7
11.0
10.0
2.0
3.0
2.0
67.0
50.0
5.0
Employment
(000)
1983/1984
9,368.9
1,894.2
739.1
308.4
82.3
2,993.8
659.6
171.6
1,187.8
446.2
179.5
74.5
813.5
107.5
441.5
1,440.2
823.7
248.0
165.1
117.5
21.3
41.3
23.5
818.7
627.0
53.1
Value
Added
(Rs.M.)
257.6
48.8
34,389.0
1,169.0
1,444.0
100,867.0
16,082.0
34,705.0
38,897.0
17,957.0
4,282.0
2,228.0
7,012.0
3,713.0
673.0
31,903.0
19,848.0
391.4
2,057.0
1,528.0
569.0
813.0
384.0
25,015.0
18,159.0
3,359.0
No. Units
Note:
The absolute values of the 3 surveys are not comparable because of differing definitions of Small-scale Mnufacturing for each.
Source: SHMI, (1976/77, 1983/84, 1988).
8
7
6
5
4
3
2
1
Table A5.18:
5,597.0
1,728.2
1,100.6
79.0
68.1
1,363.7
700.7
85.9
962.9
224.7
139.5
57.8
155.0
27.8
26.1
822.8
397.6
400.6
81.2
54.1
20.6
37.6
18.4
387.4
324.9
17.7
Fixed
Assets
(Rs.M.)
627.0
100.0
56.0
3.5
3.5
261.0
55.0
89.0
94.0
415.0
14.0
8.0
20.0
8.3
4.0
86.0
50.0
131.2
5.0
4.0
2.0
3.0
2.0
49.0
33.0
8.0
Employment
(000)
1987/1988
9,902.8
1,784.6
789.2
155.4
96.3
3,523.4
1,118.3
676.9
1,445.6
583.3
355.5
160.1
369.5
64.7
119.6
1,477.9
815.9
88.5
134.2
75.1
27.6
69.0
32.8
877.4
662.8
85.7
Value
Added
(Rs.m)
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