revista română de statistică - Romanian Statistical Review

Transcription

Institutul Naţional
de Statistică
Societatea Română
de Statistică
REVISTA ROMÂNĂ DE STATISTICĂ
- SUPLIMENT ROMANIAN STATISTICAL REVIEW
- SUPPLEMENT -
• Scientific research Themes/Studies
• Papers at the National Seminary “Octav Onicescu”
2014 / Nr. 10
Autorii poartă întreaga răspundere pentru conţinutul
materialelor publicate, revista şi Societatea Română
de Statistică fiind exonerate de orice răspundere.
ISSN 2359-8972
TABLE OF CONTENTS
THE BUSINESS ENVIRONMENT AND THE FOREIGN
INVESTMENT............................................................................................. 8
Prof. Constantin ANGHELACHE PhD.
Assoc. prof. Alexandru MANOLE PhD
Lecturer Mădălina ANGHEL PhD
FINANCIAL ENGINEERING INSTRUMENTS FINANCED FROM
EUROPEAN STRUCTURAL AND INVESTMENT FUNDS AND
FINANCIAL PRODUCTS ISSUED BY FINANCIAL INSTITUTIONS
SUPPORTING EUROPEAN PROJECT IMPLEMENTATION:........ 16
Phd Student Daniel Ioan DUMITRESCU
Phd Student Diana Valentina SOARE
THE RISK OF THE FIRM'S MARKETING ......................................... 41
Assoc. Prof. Dan NASTASE PhD
Master Ana Maria Melania PAUN
Master Adrian RADU
MACRO-ECONOMIC ANALYSIS BASED ON ECONOMETRIC
MODELS .................................................................................................... 46
Prof. Constantin ANGHELACHE PhD
Prof. Gabriela Victoria ANGHELACHE PhD
Professor Ioan PARTACHI PhD
Emilia STANCIU PhD Student
Bogdan DRAGOMIR PhD Student
THE DIRECT FOREIGN INVESTMENTS IN ROMANIA BY THE
END OF 2013.............................................................................................. 55
Adina Mihaela DINU PhD Student
USING THE VALUE AT RISK MODEL IN THE PORTFOLIO
MANAGEMENT ....................................................................................... 63
Lecturer Mădălina Gabriela ANGHEL PhD.
Revista Română de Statistică - Supliment nr. 10/2014
3
THE INVESTMENTS EVOLUTION IN ROMANIA ........................... 72
Prof. Dan CRUCERU PhD
DOES CORPORATE GOVERNANCE AFFECT FIRM LIQUIDITY?
EMPIRICAL EVIDENCE FROM ROMANIA ...................................... 79
Floriniţa DUCA PhD Student
THE AUTOCHTONOUS INVESTMENTS AND THE BUSINESS
ENVIRONMENT....................................................................................... 83
Cristina SACALĂ PhD Student
ON MOTIVATION AND MOTIVATION.............................................. 87
Prof. Mircea UDRESCU PhD
GENERAL ASPECTS CONCERNING THE DEVELOPMENT OF
THE NORTH-WEST REGION OF ROMANIA.................................... 92
Assoc. prof. Alexandru MANOLE, PhD.
Assoc. prof. Aurelian DIACONU, PhD.
NEW CONCEPTS AND SUCCESSFUL ENTREPRENEURIAL
MODELS .................................................................................................. 101
Associate Professor Sorin Gabriel GRESOI PhD
POPULATION INCOMES ..................................................................... 110
Andreea Gabriela BALTAC, PhD Student
Georgeta LIXANDRU BARDAŞU, PhD Student
MULTIPLE LINEAR REGRESSION MODEL USED IN ECONOMIC
ANALYSES .............................................................................................. 120
Lecturer Mădălina Gabriela ANGHEL PhD
Ligia PRODAN PhD Student
Marius POPOVICI PhD Student
4
ROUTES AND TRENDS OF ROMANIAN CORE ECONOMIC
VARIABLES ............................................................................................ 129
Lecturer Oana Simona HUDEA (CARAMAN) PhD
EVOLUTION OF THE POPULATION EXPENDITURE IN 2013 ... 138
Zoica NICOLA, PhD Student
Alexandru URSACHE, PhD Student
AN OVERVIEW OF THE CONSTRUCTION MATERIALS
MANUFACTURE SECTOR AT SIX YEARS AFTER THE START
OF ECONOMIC CRISIS IN ROMANIA ............................................. 146
Lecturer Adrian ANICA-POPA PhD
THE INFLUENCE OF ATMOSPHERIC METHANE ON HUMAN
HEALTH................................................................................................... 155
Assistant Cristina STIRBU PhD Student
NEGOTIATION TEAM – A BRIEF TECHNICAL OVERVIEW..... 163
Assoc. prof. Dragoş Gabriel MECU PhD
5
6
7
The Business Environment and the Foreign
Investment
Prof. Constantin ANGHELACHE PhD.
Academy of Economic Studies, Bucharest
„Artifex” University of Bucharest
Assoc. prof. Alexandru MANOLE PhD
Lecturer Mădălina ANGHEL PhD
Abstract
The basic element at the basis of this temperate development of certain
foreign investment is given by the fact that the legislation was not clear and
encouraging enough for all those wishing to come and invest in our country. The
foreign investment in Romania recorded a particular diminishing for the period
2008-2009, mainly because the way the crisis affected the economy of our country
and the lack of confidence from the investors as regards the anti-crisis program
considered by the Executive. The direct foreign investments are representing a
significant opportunity for the development of the Romanian economy. The
investors directed their participation mainly towards branches such as the
manufacturing industry, energy, the financial intermediations and insurances
sector, the real estate sector. However, a strategic desideratum of our country
economy consists of the consolidation of the foreign investment in the productive
sectors, which can support the durable development, in time, of the economic
situation of Romania.
Key words: development, foreign investment, economy, consolidation,
environment.
1. General aspects
A crucial issue for the economies in transition tending to consolidate their
presence on the market consists of the drawing foreign capital.
Since 1990 up to date, leave apart slight exceptions, the direct investment
with foreign capital participation in our country was recording a positive rhythm.
This development has been influenced and sustained by several factors such as: the
existence of an investment market in our country, the industrial restructuration, the
development of the multiple services industry, the legislative framework
attractiveness offering warranties to the foreign investors and many other factors.
It may be that, if comparing it with the situation recorded by other
countries, our country is not recording an overall evolution particularly stimulating
or significant.
8
The basic element at the basis of this temperate development of certain
foreign investment is given by the fact that the legislation was not clear and
encouraging enough for all those wishing to come and invest in our country.
This is a specific feature of the entire period as from 1990 until now.
The foreign investment in Romania recorded a particular diminishing for
the period 2008-2009, mainly because the way the crisis affected the economy of
our country and the lack of confidence from the investors as regards the anti-crisis
program considered by the Executive.
Entries of commercial companies with foreign participation to the subscribed
social capital
Mil. euro
1991
817,9
2000
648,6
2009
3512,6
1992
443,1
2001
1190,9
2010
3914,4
1993
322,9
2002
833,8
2011
3329,4
1994
681,4
2003
996,2
2012
2856,4
1995
183,7
2004
2343,7
1996
443,3
2005
2434,5
1997
278,1
2006
2417,2
1998
583,9
2007
2389,3
1999
729,9
2008
3984,4
The years 2010-2012 were in fact insignificant at this chapter. The figures
are modest and refer, mainly, to completions or increases of capital, required by the
crisis effects.
Until the year 2008, 0ne of the encouraging factors of the increase of the
direct foreign investment in our country has been given by the privatization of
certain sectors of the national economy, the drawing of the foreign capital by
already existing commercial companies as well as the setting up of new companies
with foreign capital (which, unfortunately is not valid for the period 2009-2013).
In 2013 the foreign capital contributed to the setting up of a number of
6624 companies, the subscribed value as contribution amounting 2,355,803.7
thousand euro.
Nevertheless, the years when the foreign capital investment recorded
higher increases are the years when important sectors of the national economy have
been privatized.
However, the process of analysis as to the efficiency of all those
privatizations with foreign capital should focus on detecting whether the normal
procedures meant to protect the national interest and to get a maximum of
profitableness out of these privatizations.
The flow of the direct foreign investment
The ISD net flow for the year 2012 recorded the level of 2,138 million euro
and is structured as follows:
• Net participations of the direct foreign investors to the capital of direct
foreign investment from Romania, amounting 795 million euro (37.2%
out of the IDS net flow). The net participations to capital are resulting
9
from the diminishing of the capital participations, amounting 2,676
million euro, by the net loss, amounting
1, 881 million euro.
• The net loss resulted by deducting, out of the ISD companies profit
recorded in 2012, amounting 4, 691 million euro, the dividends
distributed for the year 2012, counting for 2,212 million euro, followed
by diminishing this value with the losses recorded by the ISD
companies in 2012, amounting 4,360 million euro.
• The net credit received by the companies with direct foreign
investment directly from the direct foreign investors, including within
the group, amounted 1,343 million euro, counting for 62.8% from the
ISD net flow.
Out of the data concerning the ISD net flow and its components
(participations to capital, reinvested profit/net loss and the net credit from the
investors), distributed on activity domains, there are relevant conclusions to
underline.
For the majority of the economic activity domains, where the ISD hold a
significant weight, there are increases of the participation to capital as to the ISD
companies, which means a continuation of the investment process during the year
2012.
The domains recording the most significant increases of capital have been
the industry (1, 072 million euro), in which frame, the manufacturing industry (529
million euro) and the energy (497 million euro) are leaders; other domains
recording significant capital investment have been financial intermediations and
insurances (646 million euro), as well as constructions and real estate transactions
(295 million euro).
The main economic domains where the losses exceeded the profits have
been financial intermediations and insurances (376 million euro profit, 1, 015
million euro loss) and constructions and real estate transactions (255 million euro
profit, 747 million euro loss).
Through the distribution for the year 2012 of significant amounts as
dividends within the above mentioned domains, the net loss gets deeper (profit
minus distributed dividends, minus losses). Thus, dividends amounting 134 million
euro have been distributed in the domain of financial intermediations and
insurances and 158 million euro in constructions and real estate transactions.
A number of domains have taken the advantage of important financings,
through net credits mother-daughter, respectively: the manufacturing (606 million
euro), energy (173 million euro), trade (423 million euro), constructions and real
estate transactions (213 million euro).
As far as the industry is concerned, although significant losses have been
recorded (1,491 million euro) and dividends amounting 960 million euro have been
distributed, by the recorded capital participations level (1,072 million euro), the net
credits (862 million euro) received and the achieved profit (2,345 million euro), it
10
benefited of a net flow if ISD amounting 1,828 million euro, representing 85.5 %
from the ISD net flow for the year 2012.
2. The distribution of the direct foreign investment by branches
From the point of view of the distribution of the ISD by economic branches
(according to CAEN Rev. 2), they have been concentrated mainly in the
manufacturing industry (31.3 % of total). In the frame of this industry, the best
represented branches are the crude processing, manufacturing of chemicals, rubber
and plastics (6.7% of the total ISD), the conveyance means industry (5.4%),
metallurgy (4.9%), foodstuff, beverage and tobacco (3.7%) and cement, glass and
ceramics (2.8 %).
Out of the above situation we can conclude that the direct foreign
investment in the production activity are not counting for too much within this
structure, which would be vital and imply further consolidations if considering the
integration with the European Union.
Anyhow, the development such as is a positive fact.
Besides industry, the other activities which have drawn significant ISD are
the financial intermediations and insurance (representing 18.5 % of the total ISD),
the trade (11.4%), constructions and real estate transactions (9.2%), information
technology and communications (4.8%).
Repartition on main economic activities of
FDI balance on December 31st, 2012
Value (mil euro)
TOTAL, of which
Industry
Extractive industry
Processing industry, of which
- Food,beverages and tobacco
- Cement, glass, ceramics
- Manufacture of wood products,
including furniture
- Manufacture of computers, other
electronic, optical and electrical
products
- Machineries, tools and
equipments
- Metallurgy
- Transportation means
- Processing of oil, chemical
59.126
27.455
3.225
18.509
2.160
1.684
1.090
Weight in total
FDI
100,0
46,5
5,5
31,3
3,7
2,8
1,8
1.051
1,8
1.144
1,9
2.899
3.173
3.962
4,9
5,4
6,7
11
Value (mil euro)
products, rubber and plastic
materials
- Textiles, confections and leather
- Other branches of processing
industry
Electrical energy, gases and water
Professional, scientific, technical and
administrative activities, support services
Agriculture, silviculture and fishing
Trade
Constructions and real estate transactions
Hotels and restaurants
Financial intermediaries and insurance
Information & communications
technology
Transportation
Other activities
Weight in total
FDI
834
542
1,4
0,9
5.721
2.843
9,7
4,7
1.402
6.714
5.466
348
10.914
2.854
2,4
11,4
9,2
0,6
18,5
4,8
876
254
1,5
0,4
To note that the corporal and non-corporal immobilizations, recording a
sold of 27,412 million euro by the end of the year 2012, are representing 46.4 % of
the total sold od ISD which leads to a significant degree of stability of the foreign
investment.
The economic activities where the ISD are found as corporal and noncorporal immobilizations at a significant level are the following:
- industry (27.7% of the total ISD, while in this frame the manufacturing
industry counts for 17.9 % of the total ISD);
- trade (5.9%) as well as
- constructions and real estate transactions (4.8%).
Repartition on main economic activities of
Balance for tangible and intangible assets on December 31st, 2012
TOTAL, of which
Industry
Extractive industry
12
TANGIBLE AND INTANGIBLE
ASSETS
Value (mil
Weight in total
euro)
FDI
27.412
46,4
16.456
27,7
2.802
4,7
Processing industry, of which
- Food,beverages and tobacco
- Cement, glass, ceramics
- Manufacture of wood products,
including furniture
- Manufacture of computers, other
electronic, optical and electrical
products
- Machineries, tools and equipments
- Metallurgy
- Transportation means
- Processing of oil, chemical
products, rubber and plastic
materials
- Textiles, confections and leather
- Other branches of processing
industry
Electrical energy, gases and water
Professional, scientific, technical and
administrative activities, support services
Agriculture, silviculture and fishing
Trade
Constructions and real estate transactions
Financial intermediaries and insurance
Information & communications technology
Transportation
Other activities
TANGIBLE AND INTANGIBLE
ASSETS
Value (mil
Weight in total
euro)
FDI
10.638
17,9
1.412
2,4
1.126
1,9
785
1,3
474
0,8
586
1.787
1.859
1.834
1,0
3,0
3,1
3,1
451
324
0,8
0,5
3.016
567
5,1
1,0
658
3.463
2.816
283
1.309
1.276
471
113
1,1
5,9
4,8
0,5
2,2
2,2
0,8
0,2
From the territorial point of view it is obvious that the ISD have been
directed mainly towards the development region BUCUREŞTI-ILFOV (60.6%),
the next to count as beneficiaries of ISD being the following development regions:
CENTER (7.8%), WEST (7.6%), SOUTH-MUNTENIA (7.2%) and SOUTHEAST (5.5%).
13
Distribution of the FDI balance on development regions,
on December 31st, 2012
TOTAL, of which
- Bucharest Ilfov
- Center
- West
- South Muntenia
- South East
- North West
- South West Oltenia
- North East
Value (mil
euro)
59.126
35.859
4.625
4.510
4.230
3.253
2.814
2.068
1.767
Weight in total
FDI
100,0
60,6
7,8
7,6
7,2
5,5
4,8
3,5
3,0
The first 4 countries classified upon the weight held in the ISD sold by
December 31st 2012 are the following: Holland (22.4% of the ISD sold), Austria
(18.5%), Germany (11%) and France (8.9 %), an unchanged hierarchy since the
year 2009.
Distribution of the FDI balance, on December 31st 2012, by countries
of origin (TOP 10)
Value (mil euro)
TOTAL, of which
Netherlands
Austria
Germany
France
Italy
Cyprus
Greece
Switzerland
USA
Luxembourg
59.126
13.229
10.920
6.499
5.272
2.930
2.687
2.529
2.194
1.809
1.368
Weight in total
FDI
100,0
22,4
18,5
11,0
8,9
5,0
4,5
4,3
3,7
3,1
2,3
Thus, the first four countries are holding a weight of 60.8%, the other six
countries included in the hierarchy are holding 22.9%, while the “rest of the world”
contributed with 16.3% to the sold of the direct foreign investment.
14
3. Conclusions
The direct foreign investments are representing a significant opportunity
for the development of the Romanian economy. The investors directed their
participation mainly towards branches such as the manufacturing industry, energy,
the financial intermediations and insurances sector, the real estate sector. However,
a strategic desideratum of our country economy consists of the consolidation of the
foreign investment in the productive sectors, which can support the durable
development, in time, of the economic situation of Romania.
References
Anghelache, C., Anghel, M. (2014) – „Modelare economică. Concepte, teorie şi
studii de caz”, Editura Economică, Bucureşti
Anghelache C. et. al. (2014) – „Romanian International Trade Evolution”,
Romanian Statistical Review, Supplement no. 7/2014, pp. 17-24
Anghelache, C. (2013) – „România 2013. Starea economică sub povara efectelor
crizei”, Editura Economică, Bucureşti
Anghelache C.; Manole A. (2012) – „Romania's Foreign Trade by the End of
2011”, Metalurgia International, nr. 5/2012, pp. 140-144, ISSN 1582-2214,
Editura Ştiinţifică F.M.R., revistă citată în bazele de date internaţionale Scopus,
Ebsco, Thomson Scientific Master Journal List, Sci Search
Anghelache C.; Fetcu (Stoica) A.E. (2012) – „Investments and Service's
Production”, Metalurgia International, nr. 5/2012, pp. 131-134, ISSN 15822214 Editura Ştiinţifică F.M.R., revistă citată în bazele de date internaţionale
Scopus, Ebsco, Thomson Scientific Master Journal List, Sci Search
15
Financial Engineering Instruments Financed from
European Structural and Investment Funds and
Financial Products issued by Financial Institutions
supporting European Project Implementation:
Phd Student Daniel Ioan DUMITRESCU
Phd Student Diana Valentina SOARE
Abstract
At European level, the European Court of Auditors, in the Special Report
No. April 2011 "The audit of the SME Guarantee" and Special Report no. 2 of
2012 "Financial instruments financed by the ERDF to support SMEs", established
that where equity instruments and debt instruments, the leverage obtained was not
a significant one and it was even lower than the reference levels used as a base
instead. Instead, guarantee instruments provides the best way to multiply public
funds in the revolving system.
Key words: analysis, instrument, financial, leverage, loan
In the Multiannual Financial Budget 2007 -2013 were used three types of
financial instruments: equity, loans and guarantees. These three categories of
instruments were eligible for ERDF co-financing, but must comply with national
and EU rules on eligibility (eg, transfer of business, capital, state aid). In the case
of equity and loans, income generated from the sale of equity securities or,
respectively, of debt service are re-bound for funding of other financial instruments
designed for other SMEs; it is therevolving effect. For collateral, the money is
spent only if defaults entry. If that does not occur into default, may proceed to issue
the amounts contributed when it considers the underlying contractual conditions .
To achieve the analysis of financial instruments, the European Court of Auditors
calculated using the formula:
Leverage = Grants to final recipients / Public Contributions
(calculated as the sum of the contribution of the EU and Member States'
contributions).
Leverage:
For the examples above, the Court calculates leverage as follows:
16
Grants to final recipients / Public Contributions
Following the calculation of the Court, the above presented schematically
how leverage works for each main category of financial instrument and, in the
context of the ERDF, the way in which you understand leverage. For example, a
1.00 coefficient of leverage means not at all attracted funding from private sources.
In August 2011, the Commission changed the concept of the multiplier effect,
which corresponds to the following formula:
Grants to final recipients / EU contribution
The numerator coefficient of leverage applied by the Court is identical to
the number coefficient multiplier effect of the Commission. Regarding the
denominator, the Court makes the amount of public funding from all sources, while
it took into account only the contribution from the EU.
APPLICABLE FORM TOOLS LEVERAGE, EQUITY, LOANS AND
GUARANTEES:
Coefficient of leverage for participation in the capital:
Funding available for SMEs: 40 M / Financing of the operational program: 10M
Leverage factor = 4
17
Coefficient of leverage for loans:
Funding available for SMEs: 18 M / Financing of the operational program: 3M
Leverage factor = 6
Coefficient of leverage for guarantees:
Funding available for SMEs: 120 M / Financing of the operational program: 6 M
Leverage factor = 20.
18
Presentation of the main financial instrument of the Multiannual
Financial Framework 2007 - 2013:
In Romania, the European Investment Fund has been appointed the sole
administrator of the JEREMIE program. POSCCE financed JEREMIE program,
Priority Axis 1 "An innovative and eco-efficient production" DMI 1.2 "SME access
to finance" in 2013 was supplemented JEREMIE program in Romania budget of
100 million Euro to 150 million Euro.
Financial intermediaries1 were only credit institutions and NBFIs. Thus,
following the procedure for awarding the JEREMIE funds organized by EIF, these
commercial banks have become financial intermediaries:
• Romanian Commercial Bank;
• Raiffeissen Bank;
• Unicredit Tiriac Bank;
• BT;
• ProCredit Bank;
• Libra Internet Banking.
1
Mădălina Gabriela ANGHEL, Pocan Ovidiu – Modele de estimare a rentabilităţii şi
riscului unui titlu financiar, Revista Română de Statistică – Supliment „Criza economică efect, cauze, perspective”, nr. 3, 2009, pg. 337 – 340, ISSN 1018 – 046x CNCSIS
Categoria B revistă indexată în bazele de date internaţionale DOAJ, Index COPERNICUS,
EBSCO, ICAAP Revista Română de Statistică - Supliment nr. 10/2014
19
Partial evaluation of the JEREMIE program in Romania:
Situation on 24 November 2011:
• In October 2011 there were reallocated from operations 17,500,000 Euro venture
operations Guarantee (from 63 million euros to 80 million euros);
• loans were granted to 110 SMEs worth about 10 million euros (credits not
guarantees);
Situation 31.12.2011:
• Guarantee Fund in the amount of EUR 80 million was spent by the three banks
participating at EIF auction:
• BCR (ERSTE BANK) – 42.500.000 Eur;
• Raiffeisen – 20.500.000 Eur;
• Unicredit Tiriac Bank – 17.500.000 Eur);
• At the end of 2011 were given 142 guarantees totaling EUR 11.66 million.
The situation on 09 July 2012:
• JEREMIE Holding Fund (worth EUR 100 million) is structured as follows:
• a. Guarantee funds: EUR 80 million;
• b. Venture capital funds: EUR 17.5 million;
• c. Fund reserve: 2,500,000 EUR.
• In late May 2012, BCR, Raiffeissen and Unicredit were awarded a total of
approximately 400 loans totaling 32 million Euro (credits not guarantees);
• AMPOSCCE increased in the 2013 the budget of 50 million euros JEREMIE
program, an operation that was performed by supracontractare not reallocation;
• Catalyst Romania 3TS Fund was founded with participation of the European
Investment Fund of EUR 10 million JEREMIE Romania and other amounts from
BTAM - BT Asset Management. The fund will have a total capital of 30 million
Euro and will invest amounts between 2,000,000 and 2,000,000 Euros Euros in
SMEs in the ICT sector, media and internet. The life of the fund is 10 years, with
an investment period of 2-5 years for the companies concerned. The Fund is
managed by a local team of 3TS Capytal Partners.
• Catalyst Romania 3TS Fund invested in Intelligo Media, owner and developer
portal AvocatNet www.superlege.ro;
The situation in June 2014:
Since June 2014, the JEREMIE Holding Fund portfolio had the following
instruments:
• Guarantee Instrument Portfolio: Implemented through agreements with BCR,
UniCredit and Raiffeisen; instrument has received an allocation of EUR 62
millions euro, set to lead to a total portfolio of new loans for SMEs 310 million
through specific leveraged portfolio first loss "first loss portofollio". Warranty is
20
free for SMEs (de minimis aid). In June 2014, the instrument was absorbed at a
rate of 83%, with a portfolio of 2,300 loans for investment or working capital
totaling 258 million euros expected. Guarantee Instrument JEREMIE portfolio will
be absorbed 100% in December 2014.
• Catalyst 3TS Fund Romania: With an allocation of up to EUR 17.5 million (EUR
10.5m of which employees effective June 2014), supplemented by private
participation 30%, for 2014, the Fund announced 3TS Catalyst Romania
investment in developer solutions Simartis phone. JEREMIE venture capital fund
investment period will end in 2015 and thereafter will only further investment in
existing portfolio.
• Risk sharing loan portfolio (interest subsidy) risk-sharing loan portfolio (interest
subsidy) launched in 2014, implemented through BRD, BCR, Banca Transilvania,
ProCredit Bank and the Savings Bank, with a total budget of 65 EUR million,
resulting in a target portfolio of new loans for SMEs 130 million. SMEs benefit
from a 50% interest rates (de minimis aid), and the losses are covered under the
pari passu principle - the bank and JEREMIE Holding Fund. This tool will be
implemented by the end of 2015.
• In terms of resources revolving JEREMIE Holding Fund, which will be available
after 2015 and will be used for instruments SME decision on tools that will be
funded will be made by the Government Romania, taking into account the need to
ensure consistency and also taking into account the needs of the market at the time.
It is recalled that these resources will be managed by the EIF in 2020.
Effective delivery of two financial instruments used guarantee
Multiannual Financial Framework 2007 - 2013:
Multiannual Financial Framework 2007 - 2013 has provided financial
engineering instruments for managing data as European financial institutions, such
as the JEREMIE program, funded POSCCE Priority Axis 1 Key Area of
Intervention 1.2 "SME Access to Finance" and the financial institutions national,
such as financial Engineering Measure 2.4 of the Operational Programme for
Fisheries.
JEREMIE holding fund managed by the European Investment Fund:
JEREMIE Holding Fund is the largest financial instrument used during
2007 - 2013 in Romania. Although it was approved in 2008, it was not available
until 2011, when the European Investment Fund, appointed administrator of the
program, organized an auction with three credit institutions, Romanian
Commercial Bank, Raiffeisen Bank and UniCredit Tiriac Bank Romania became
financial intermediaries in financial instrument portfolio as collateral. Thus, based
on the budget allocated 68 million euros, according Partnership Agreement 20142020, the three commercial banks were guaranteed loans totaling more than 160
million Euro, so a degree of European money multiplier (effect coefficient
leverage) 2.4.
21
Credit Guarantee Scheme for eligible beneficiaries POP managed
FNGCIMM:
During the same period, FNGCIMM was appointed after the auction
organized by the Ministry of Agriculture and Rural Development, manager of bank
credit guarantee scheme for eligible beneficiaries of POP, with a budget of 14
million Euro. By the end of 2013, FNGCIMM, guaranteed loans 8 commercial
banks totaling approximately 34 million Euro, so a degree of European money
multiplier (leverage factor) of 2.4.
Although the degree of European money multiplier is similar to note that
by the end of 2014, when the JEREMIE program, SMEs that benefited from the
financial engineering products to customers were limited to three commercial
banks (BCR, Raiffeisen Bank, Unicredit Tiriac Bank), while for the Fisheries
Operational Programme - Measure of Financial Engineering, customers have
access to eight commercial banks from the 27 partner banks FNGCIMM.
In 2014 the National Credit Guarantee Fund for Small and Medium began
to implement national programs to ensure, with a total annual budget of more than
2 billion (approx. EUR 455 million). Under the program, SMEs can obtain credit
for working capital loans of up to EUR 5 million (EUR 1.13m) for a maturity of up
to three years at an interest rate limited to ROBOR 3M + 3.5% (currently up to
5.7%). Loans are funded up to a 50% guarantee fee is 1.99%. As the architecture of
these guarantee schemes differ from the guarantee instrument for the Jeremie
program, they can coexist in the future.
Financial instruments in the Partnership Agreement 2014 - 2020:
Change the rules of the rules (2007-2013 to 2014-2020):
1 Financial instruments may be used in any operational program for any of the
thematic objectives, where they can prove the efficiency and effectiveness;
2 They can be used in combination with other forms of support, particularly grants,
allowing the design of support schemes well adapted to meet the specific needs of
the Member State;
3 The proposal to use such a tool will be made only on the basis of ex-ante analysis
to identify any market failure or sub-optimal investment situations, needs
investment and the added value it can bring to the financial instrument;
4 will be set clear rules for financial management;
5 Report on progress in implementing simplified.
Characteristics of Financial Instruments:
• In the MFF 2014-2020, the European Commission proposed an extension
and consolidation of the use of financial instruments that effective and
sustainable alternative complementing traditional financing based on
grants;
• target the potential economic viability of projects with financial
instruments provides support investments through loans, guarantees, equity
22
investments and other risk-bearing mechanisms, which can be combined
with interest rate subsidies or contributions guarantee fee within the same
operation;
• Financial instruments contribute to the mobilization of public and private
co-investment further to address market failures in accordance with the
priorities of Europe 2020 and cohesion policy;
• structures implementing them involve an additional financial expertise and
know-how - bank, which contribute to the efficiency and effectiveness of
public resource allocation;
• Moreover, these tools provide a variety of incentives to improve
performance, including greater fiscal discipline in the projects supported;
Given the experience of the Multiannual Financial Budget 2007 - 2013,
financial institutions - banks will have an important role in management of
financial instruments for SMEs, large enterprises, local authorities and NGOs.
Advantages of financial instruments:
• helps to multiply the available resources and increase impact of their
programs through FESI;
• due to the revolving nature increases both the efficiency and the
effectiveness of interventions and impact public policies due to continuity
use of funds throughout the implementation cycle of FESI;
• reduces dependence on eligible projects grants / subsidies provided by the
EU;
• facilitates the involvement of the private financial sector (credit guarantee
institutions specialized banks) in order to achieve public policy objectives;
• allows access to a wide range of financial instruments for implementing
public policies through private financial sector (benefiting from its
involvement and expertise);
• quality of implemented projects is better because they select those that
have a high capacity for repayment of investments.
23
Coordination mechanism of EU financial engineering instruments and national
The principle of complementarity:
Because resources are used in order to serve in the best way national
interests, the principle of complementarity requires the European Structural Funds
and Investment FESI not be used in isolation, but taking into account other national
or European instruments. This means that consecutive actions correlate related or
funds from several sources, so as to avoid double funding and investment schemes
adopt counter to the FESI.
FESI investments and other national or European tools can directly support
achieving the targets in areas such as environment, climate action, education and
employment.
The Multiannual Financial Framework 2014 - 2020 will ensure
complementarity between FESI and programs managed directly or indirectly by the
European Commission, such as Horizon 2020 - the Framework Programme for
European Research and Innovation. The line separating how and tools are designed
mainly consists of the following:
• non-territorial and transnational approach of Horizon 2020 to intervene in
local ESI Funds;
• focus on individual research and development projects to focus on
capabilities and systems research and development funds ESI;
• groups to the international call for tenders for Horizon 2020 and the
political prioritization of individual companies, consortia.
It will create complementarities possible to unlock the potential of
excellence nationwide, including ERA cooperation initiatives, to support
participation in Horizon 2020, access to international networks to support centers
of excellence to connect with similar centers in other Member States to support
cross-border networks, institutional development to coordinate nationwide.
FESI funded interventions targeting SMEs have great potential to create
synergies and complementarities with cosmic Competitiveness Programme for
Small and Medium Enterprises. It provides funds to improve access to finance,
improve market access, improve the framework conditions for the competitiveness
and sustainability of enterprises and promote entrepreneurship and entrepreneurial
culture.
Particular attention will be paid consistent with the ERASMUS program
which has a number of areas of intervention and duplication with them. There are a
number of additional areas to be pursued: employment, research and innovation,
industry and entrepreneurship2.
2
Anica-Popa Adrian, Manole Alexandru, „Senzitivitatea indicatorilor de performanţă a
investiţiilor de mediu la nivelul Rezervaţiei Biosferei Deltei Dunării”, Seminarul Ştiinţific
Naţional „Octav Onicescu” şi Simpozionul Ştiinţific Internaţional organizat de Societatea
Română de Statistică la 5 mai 2008 cu privire la dezvoltarea economico-socială a României
24
LIFE program covers three priority areas by component "Environment"
Environmental and resource efficiency; nature and biodiversity; environmental
governance and information. Component "Climate Action" covers climate change,
adaptation to climate change and environmental governance and information.
Regarding coordination between EAFRD and Guarantee Fund for
Agriculture, Romanian authorities will not transfer between the two pillars of the
CAP. Synergies between Pillar I and Pillar II are provided by separate national
viticulture program and the national program for beekeeping.
A significant source of financing in Romania in 2009-2014 are EEA and
Norway grants schemes. Grants are available in four main areas of intervention: (i)
research and innovation in green industry, (ii) gender equality, (iii) biodiversity and
ecosystems, pollution reduction, energy efficiency, renewable energy, adaptation to
climate change (iv) strengthening civil society development, increasing its
contribution to social justice, the fight against transnational organized crime, etc.
The program is being implemented, with management authority within the MFE,
which will facilitate cooperation with AM relevant actors involved in policy
making to ensure policy coherence.
Similar to the previous period, the period 2014-2020 will be needed EIB
funding instruments. "During the implementation of the 2007-2013 programs have
been situations where the parallel EU-funded schemes, the Romanian Government
has provided grants like simplified procedures that competed European funding
counterproductive manner, eg the Environment Fund Administration managed
funds water infrastructure, investments in renewable energy sources, or the Agency
for SMEs (now a division within the Ministry of Economy) managed grants for
SMEs and entrepreneurship. "
Romania will ensure better coordination between funding from national
and European level following the following: avoid duplication, establish clear lines
of demarcation between EU and national schemes, harmonization of procedures,
ensure the same degree of difficulty in understanding and developing their
potential complementary aspects. This will be developed through institutional
coordination mechanism proposed for the next programming period.
The main financial instruments established in the Union, directly or indirectly
managed by the European Commission:
Inside the Multiannual Financial Framework 2014 - 2020, the European
Commission will provide, directly or indirectly through entities entrusted
management of European programs containing the following financial instruments:
• COSME Programme for Competitiveness of Enterprises and SMEs
• Horizon 2020 Programme - Programme - European Framework for Research
and Innovation
în structurile europene, Revista Română de Statistică, Bucureşti, 2008, cod ISSN 1018046X Revista Română de Statistică - Supliment nr. 10/2014
25
Joint Initiative for SMEs.
COSME Programme for the Competitiveness of Enterprises and SMEs: General
Objectives:
Improving access to finance for SMEs in the form of credit facilities and
participation capital facilities:
Facility Guarantee of Loans - Loan Guarantee Facility (LGF) counter-guarantees,
co-guarantees and other risk sharing Guarantee Scheme;
Direct guarantees and other risk sharing instruments for other financial
intermediaries.
Facility Participation Capital - Equity Facility:
Venture Capital Investment in the growth phase SMEs.
Program Horizon 2020 - the Framework Programme for European Research and
Innovation - Goal:
Access to risk finance through financial instruments:
Credit Facility for Research and Development;
Sub - Facility: Facility Credit for industrial demonstration projects in low-carbon
energy;
Credit Guarantee Facility for Research and Development for SMEs and small and
medium enterprises with capitalization (small midcaps);
Sub - feature: Climate Change
Additional mechanism of participation:
Tools for Research and Development Joint guarantee to SMEs and midcaps small
Three. Participation Capital Facility - Equity Research and Development Facility;
Sub - pilot facility: Co-investment by Business Angels in innovative ICT
companies;
Pilot Facility Financing Technology Transfer;
External expertise:
Evaluation of investment potential of SMEs emerging Phase I instrument for
SMEs;
Technical advisory service and financial risk finance Research and Development;
Evaluation of proposals
Current MFF 2014 - 2020 offers three different options for implementing
financial engineering instruments available to the Member States (MS):
1. financial instruments established in the EU and managed by the European
Commission, directly or indirectly, such as for example: Cosmic Horizon 2020
program;
2. financial instruments set up at national or regional level, managed in accordance
with common rules, which can be existing financial instruments or financial
instruments standard;
26
3. financial instruments for loans or guarantees directly implemented by the
Managing Authority.
EU Regulation. 1303/2013, Title IV, Financial Instruments, art. 38, Financial
Instruments:
"(1) when applied to art. 37, the MA can provide a financial contribution for the
following financial instruments:
(a) financial instruments established in the Union, managed directly or indirectly
by the Commission;
(b) financial instruments set up at national, transnational, regional or cross-border
managed by the managing authority or under its responsibility. (...)
(4) If the supports financial instruments mentioned in paragraph (1) (b), the
managing authority may:
(...)
(b) was given the task of implementation:
(i) the EIB;
(ii) international financial institutions in a Member State is a shareholder or
financial institution established in a Member State aimed at achieving public
interest under the control of a public authority;
(iii) a body governed by public or private;
(c) to perform implementation tasks directly in financial instruments consisting
only loans or guarantees. If that authority is considered beneficial management as
defined in Art. 2, Section 10 (...)
(5) When implementing funds of funds, the bodies referred to in paragraph (4)
points (a) and (b) in turn can assign some of the tasks of implementation of
financial intermediaries, provided that these entities to ensure, under its own
responsibility that financial intermediaries meet the criteria stipulated in art. 140
(1), (2) and (4) of the Financial Regulation. Financial intermediaries are selected
on the basis of open, transparent, proportionate and non-discriminatory, avoiding
conflict of interest. "
27
Involvment of state owned Romanian Banks in the efficient management of
European finance instruents for programs related to multiannual budget 2014
– 2020:
•
•
•
•
Government Programme 2013 provides:
Increasing the absorption of structural funds by simpler and more transparent
procedures for accessing and by credit solutions in co SMEs;
Enhance CEC and Eximbank, along with a major objective activity: Eximbank
- for exports and industry; CEC - SMEs, small businesses, agriculture and selfemployment;
Improving SMEs' access to finance through the establishment of hedge funds
with the Romanian economy's concentration on creating access to finance of
SMEs to maximize the opportunities for local and international investments by
creating a financial instrument specialist, flexible, reusable and durable;
Capitalization National Credit Guarantee Fund SMEs. Supporting SMEs in
difficulty due to the economic crisis by establishing a state aid scheme to
include the use of funds.
There is a tendency in Europe to involve financial institutions - banks in the
efficient management of financial engineering instruments related to the
Multiannual Financial Framework 2014 - 2020:
Crystallized as a current of thought that supports the use of more active financing
instruments / guarantee innovative. Funding instruments / guarantee innovative
could generate a new wave of co-financing of European projects. Thus, if the
European budget should be able to attract investment / financing / guarantees and
other public or private sources, the same European fund will achieve growth targets
of the national policy much easier.
Financial institutions can play an important role in the absorption of EU
funds through the establishment of management authority (eg Venture Finance
Hungary established by The Group of Hungarian Development Bank is supervised
by the Hungarian Financial Supervisory Authority) and Banque publique
d'Investissement France (Bpifrance ). This demonstrates that we EU development
banks is a significant possibility, even successful and developed Member States.
Especially BPIFfrance example is an example worthy of consideration, is a
new development bank established in 2013 and owned jointly by France and Caisse
des Depots et Consignations. It was established to provide efficient funding for
technological innovation, developing businesses by combining the services
previously provided by OSEO (bank loans for SMEs and Research - Development)
loan guarantees and Strategic Investment Fund (FSI ). The purpose of this merger
was to create a more efficient and centralized channel all development finance so
that long-term development goals can be coordinated on a wider range of projects
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and stakeholders in accessing funds (including European) to have a more efficient
and simplified application through a one-stop shop, but by several institutions
overlap.
Pros:
Financial Institutions
expertise in the evaluation and selection of projects
financed from structural funds can be used successfully, especially in SMEs and
public beneficiaries;
• Financial Institutions / Guarantee can accelerate European projects by
providing pre-financing until the European grant reimbursements;
• Given that not all European project expenses are eligible, these new types of
management authorities can provide co-financing loans and guarantees.
Advantages of this approach to that used in the European Multiannual Budget
2007 - 2013:
• For the future, may be more effective management of a managing authority of
institutions with experience in analysis, financing, ensuring entrepreneurial
businesses that have in their composition qualified personnel with experience
in evaluating business profitability;
• A Management Authority that would provide besides structural funds and their
sources of financing / guarantee would increase the accountability and
professionalism of the officer who signed the financing contracts with
European funds;
• They must be developed innovative financial products that integrate
components of financing, guarantee and other national subsidies so that
projects receiving structural funds to benefit specific multiplier effect of these
financial instruments;
• It should be borne in mind that the MFF 2014-2020, the share of innovative
financial instruments will be much higher. Therefore, at the national level
should be achieved mechanisms to support companies and products that
complement these European measures;
• We can take the example of other European Union member states where there
are already successful models of management authority type (One Stop Shop)
who reported a high degree of absorption efficiency (almost 100%) of the
Structural Funds and works as a integrator of products and services covering
all aspects of the management of a European project (information, education,
consulting, valuation, financing, bonding, monitoring);
• Following European model, there are suggestions that these new types of
management authority to be supervised by the FSA (see in this Ordinance
93/2012 regarding the establishment, organization and functioning FSA).
Proven ability of financial institutions - Romanian bank, to effectively manage EU
programs:
29
One solution may be outsourcing operations evaluation and granting
European funds by participating in quality management authority financial
institutions (owned / majority state Eximbank, CEC BANK, FNGCIMM) in the
management of European Structural Funds 2014 annual budget related - 2020.
This approach will help to multiply European money because funding
institutions / guarantee professional (Banking / Venture Capital Funds in
partnership with Guarantee Funds) are paid not by how much money attract
Europeans but on profitability / return on net business they lend / invest the money
and their own money, so we could see a shift in thinking and the allocation of the
EU budget 2014 - 2020 This is the main reason why the new financial year
European financing institutions / Guarantee (Guarantee Funds, Banking, Venture
Capital funds) will play an increasingly important role in the management of
structural funds by acquiring quality management Authority.
Also, especially in this time of crisis, it was observed that even if the bank
or venture capital funds large amounts of money available, they avoid to grant cofinancing of European projects. The reasons are lack of collateral eligible
reimbursement uncertainty debt / capital invested.
It is proposed to establish a management authority to engage these
financial institutions - banks:
Eximbank in:
- Projects large enterprises;
- Infrastructure Projects and priority projects;
CEC BANK in:
- Projects SMEs;
- Regional projects and in agriculture;
VENTURE CAPITAL FUND (type CATALYST funded JEREMIE
program) in:
- innovative micro projects;
- ICT projects;
FNGCIMM can occur along all three above mentioned institutions to
purchase guarantees.
Cost - Benefit Analysis vs. Banking Financial Analysis:
At the top of the EU bureaucracy, there is currently heated discussion
about efficient use of funds. The problem was identified as coming from a lack of
understanding of economic phenomena by bureaucrats who allocate and approve
these funds: no official signing these funds is not in any way responsible for how
these funds generate positive social and economic effects. There is no real
measurement of success of projects based on European funds.
To access and successfully implement a project financed by EU funds, an
applicant must submit at the moment each one (Applications / business plan /
feasibility study / application level) in the following entities:
- Management Authorities (to access grants);
30
-
Bank (ineligible to obtain co-financing part of the project);
Guarantee Fund (to obtain credit guarantee).
Currently, each institution mentioned above, there is a chronic mismatch
between:
- applicant eligibility assessment criteria on the one hand;
- and project profitability assessment criteria on the other.
Lack of a transparent set of common financial indicators to be met by
applicants for European funds to be agreed by banks and guarantee institutions
intermediary bodies, while proved to be an effective factor in the failure of
accessing money Europeans.
This is due primarily to differences in the goals pursued by these
institutions. The IBs are interested in social results of the allocation of public
money: creating jobs, sustainable development, etc..; and banks are interested in
the profitability of the project and the applicant's ability to pay back the loan plus
the interest.
Due to the lack of harmonization between the evaluation criteria of the two
main categories of institutions involved (intermediate bodies and banks), at present
(2014) observe the following paradox: Although there are many projects that have
signed contracts with funding bodies intermediate restrains only one percent of
them have managed to get credit for their implementation. This has led to the
freezing of funds reserved for the winner but bankable projects, which ultimately
led to poor absorption of European funds.
It substantiates the need and urgency to create an IT platform of European
co-financing that would be used by all institutions involved in the analysis of
projects financed by European funds and to facilitate and standardize the process of
evaluating, analyzing, approving grants, co credit, letters of guarantee required to
implement a successful European projects. The platform will use a public set of
indicators and common financial parameters to be accepted by the Intermediate
Bodies, Banks and Guarantee Fund to be known Applicant since the time of
writing (Applications / business plan / feasibility study).
Thus, an educated and well informed company can achieve a single
business plan to be approved by all iinstitutiile involved in the approval, financing
and guarantee European projects, which will automatically lead to streamlining the
process of absorption of structural funds.
COST BENEFIT ANALYSIS VERSUS BANK (General aspects):
In most cases, projects get EU funding locks because mismanagement of
cash flow. This was found both to companies and to local authorities. Most times,
though the European project was approved co missed completely, which led to
bottlenecks in European projects.
Often when companies at the start of a project does not consider the need
to ensure a co-most entrepreneurs say they will handle the loan co. Primary step
31
should be to achieve a realistic projection of cash flow for the entire period of the
European project, in order to be able to quantify the impact on the current activity
of the company.
Not a problem if during the development of cash-flow projection, you
expand a little interval for the settlement costs by managing authority. Often
unforeseen problems that delay expenditures, or settlements made by the managing
authority. The party, these delays may consist unable to contract a financial banking support necessary for the implementation and management of the
authority, legislative issues, or control actions massive anti - fraud projects.
Some questions (related to finance) who must answer before starting a
project:
- What is its contribution?
- Have it or not own contribution?
- You can contract a financial product - Bank covering its contribution?
Often, financial analysis methodology - banking differs from the
management authorities, which lead to completely different results between the
two types of ratings. The result of this differentiated approach is that most times, a
project that received a high score on the authority of management, will not be
eligible in terms of financial institution - bank. From here appear jams European
projects that have signed financing contracts with management authorities, but are
not eligible for co-financing from the point of view of financial institutions - banks.
(!) As anomaly was observed that some applicants submit documentation to match
different criteria for evaluating the financial institutions - banks, on the one hand
and management authorities on the other side!
(!) Also often uses financial indicators that have the same name, but are calculated
by different methods!
(!) From the point of view of collateral that can be taken by the bank mortgage, an
important step consists in the GD no. 606/2010 which enabled the beneficiaries of
European funds to mortgage bank assets components of European projects!
Conclusion: Asymmetry financial indicators - banking on the one hand and
those required by the management, on the other hand, can be mitigated by
identifying a set of financial indicators to be jointly accepted by both sides, so that
not need to be done, different documentation aceelasi investment project,
depending on the entity that performs evaluations. (For this reason it is important to
analyze both sides of a European project analysis).
Cost - Benefit Analysis of European Projects:
CBA (Cost Benefit Analysis) is a method of socio - economic challenges in
1844, which argument feasibility of investment in public works, in terms of a cost
analysis model - benefit. In the second half of the twentieth century, government
bodies, international financial institutions gave (WB, IBRD, EBRD) have begun to
use this method of analysis. In 1997, the European Commission produced the first
guide cost - benefit analysis, updated in version 2008 which states that the Cost Benefit Analysis help public decision maker to sort out projects to maximize net
32
social benefits and thus determine the order in which they will be made
infrastructure works and how public policy decision-making.
Cost - Benefit Analysis is an important utility in drafting feasibility studies
to identify the best option, depending on the criteria of economic, technological,
social and ecological investment projects, especially those offered by the public
sector, in constii, industry, transport, environmental infrastructure, tourism,
agriculture, etc...
Commission documents state that Cost - Benefit Analysis is a conceptual
framework applied quantitative assessments, systematic, a public or private project
to determine if or how much the project is worthwhile from a public or social
perspective. Cost - Benefit Analysis Net financial estimates differ in that they take
into account all the benefits and costs, regardless of who it belongs to.
In Romania, is carried Cost - Benefit Analysis of investment projects
carried out by the EAFRD and ERDF.
Cost - Benefit Analysis contains basically the following steps:
1. Presentation and discussion of the socio-economic context and project
objectives - in this phase is to analyze and consider the relationship between the
objectives and priorities established by the operational program, the national
strategic reference mentioned above and consistent with the objectives of EU
programs.
2. Identification project - is important for managing authorities to clearly
identify a project. This can be achieved when: a. Covered project can be framed in
a stand-alone unit (ie. Factory half is not a project); b. direct and indirect effects are
taken into account; c. were considered positive social issues affecting groups - the
project target.
3. project feasibility analysis and other options - considering the extent to
which an applicant pote demonstrate that choice on the project is the best option of
all feasible alternatives. For any project can be considered at least three
alternatives: a. Alternative of doing nothing; b. alternative forms of a minimum; c.
alternative of doing something.
4. Financial analysis - provides decision makers information on inputs and
outputs, their prices and the structure of revenues and expenses during the entire
period. The purpose of financial analysis is to use the project's cash flow
projections to calculate the appropriate return rates, especially financial rate of
return (FRR) investment (FRR / C) or capital (FRR / K) and the net current
financial appropriate (FNPV / C, FNPV / K).
5. Economic analysis - is made from the point of view of society. Cash
flows from financial analysis are taken as a starting point to perform an economic
analysis. Determination of economic indicators is by following adjustments: a.
Fiscal adjustments; b. corrections for externalities; c. market prices to book values.
33
6. Sensitivity analysis and risk - consists of studying the probability that a
project will achieve a satisfactory performance (as IRR or NPV) result variability
compared to the best estimate made.
ANALYSIS OF THE EUROPEAN PROJECT MANAGEMENT AUTHORITY:
Financial analysis criteria:
Key indicators to assess:
1 Financial Internal Rate of Return on Investment;
2 Internal Rate of Return on Investment International;;
3 net financial worth the investment;
4 Economic net present value;
5 Benefit / Cost;
6 positive cash flow;
7! The residual value of investment! (treated differently in the analysis and the
analysis of bank management authorities)
Criteria regarding the socio-economic impact of the project (not of interest
to financial analysis - banking)
1 number of jobs created;
2 equal opportunities;
3 Sustainable Development;
4 use local resources that are conceptually relevant donors.
Existing implementation capacity at beneficiary level (many are found in
the financial analysis - banking)
1. organizational structure;
2 experience;
3 the existence of a reasonable number of employees;
4 the existence of relevant certifications - quality management, environmental
management project.
Quality and consistency of the project: (many are found in the financial
analysis - banking)
1 the existence of proper feasibility studies;
2 the existence of a budget well founded;
3 existing technical projects;
4 market research;
5 marketing studies;
6 degree of maturity of the business idea.
Sustainability of the project in terms of technical, financial, organizational:
Managing Authority: follow the beneficiary's capacity to sustain
investment in sustainability;
34
Financial Institution - Banking: follow the company's ability to sustain the
project, while the repayment, and the company's ability to provide strong
guarantees for loans.
Evaluation of the proposed business idea:
Management Authority treats these issues only briefly through the innovations
brought, etc;
Financial Institution - Banking deemed important this analysis to assess future
business success
(!) Contradiction! Often, management authorities require values of financial
indicators in contradiction with the bank, as follows:
- for RIRF, accept values below 13%, 9%, and just under 5% in some
programs (see SOP IEC);
- for VANF, often require negative! (see POR)
Financial Analysis - European Banking Project:
Analysis steps :
1 Information and Documentation on bank credit applicant (beneficiary of EU
funds);
2 Information and documentation necessary credit analysis;
3 analyze trustworthiness of loan applicants;
4. applicant's ability to return the bank loan.
Economic analysis - financial statement granting / rejecting a loan, usually
contain the following elements:
1 analysis of accounts in evolution;
2 considering cost, profit, revenue;
3 analysis of indicators;
4 Breakeven analysis;
5 analyze projections in terms of funds and cash flows.
Key Indicators:
1. liquidity ratios;
2 indicators management: rotation of current assets, inventories, receivables,
rotation suppliers, etc;
3 indicators of profitability: gross profit margin, net profit margin;
4 indicators of solvency: leverage, debt coverage (operating income / interest paid);
5 indicators treasury: cash flow = total revenues of the period / total payments
made.
The following indicators are important in the assessment of bank:
1. overall solvency ratio: reflects the company's ability to cover total debt from
total assets in the patrimony, namely, the ability of an enterprise to cope with all
his maturity, both short and long term. It is recommended that the overall solvency
ratio to be less than 1.5. RSG = Total assets / total liabilities.
35
2. financial autonomy rate: expresses how the firm's assets is funded at the expense
of own resources. It is recommended that the minimum amount allowed to be 30%.
RAFG = Equity / Total Assets x 100.
3. rate financial debt repayment capacity of self: in number of years, the unit's
capacity to repay debts incurred in the long term, based on the enterprise's ability to
repay debts incurred in the long term, based on the cash flow. Banking rules
require a maximum of three years to repay debts on account of the cash flow.
RCAF = medium and long term liabilities / CAF.
4. speed rotation of assets: reflects the efficient use of assets. Being a synthetic
indicator and quality, Vratsa reflect changes in operating activities, but also in the
financial enterprise. Vratsa characterize both the supply and production and cost
reduction policy, shortening the cycle of production and sales and collection period
production. Vratsa = Turnover / Total assets.
5. Return on equity: measures the company's ability to make a profit from the use
of equity. Return on equity shareholders of the company remunerates or through
the payment of dividends or by increasing reserves, which actually represents an
increase in the intrinsic value of the company's shares. This rate must register
above average bank interest. Rf = Net Profit / Equity x 100.
Another method consists in evaluating the bancability of projects cash flow in
future periods. The main indicators used in this case are: a. Financial Internal Rate
of Return on Investment (RIRF). Banking system accepts a level of between 9%
and 15%; b. amount of net financial investment (VANF). Banking system and
eliminatory criterion recommends that it be positive.
Financial Instruments FINANCING / GUARANTEE / INSURANCE used in
lifecycle projects financed from European funds:
Stage 1 - Submission of Application Form:
- Credit to pre expenditures necessary for the elaboration of a project;
- letter of comfort (issued by a bank / lender);
- Letter of Guarantee Letter of Comfort employer (government guarantee
funds);
Step 2 - Signing of the contract:
- Letter of Bank Guarantee;
- letter of comfort (issued by a bank / lender);
- Letter of Guarantee Letter of Comfort employees (issued by the Guarantee
Fund);
- Other documents proving financial capacity of project implementation
include:
• Statement of Account;
• Credit Agreement;
• Line of Credit;
• Bank deposit.
Step 3 - Application of pre-financing:
- Letter of guarantee of pre (issued by a credit institution);
36
- Letter of Guarantee of pre (issued by the Guarantee Fund);
- pre-financing insurance policy (issued by an insurance company).
Step 4 - Request for Reimbursement:
- Revolving Credit Agreement;
- VAT Credit Facility;
- Letter of Guarantee Advance;
- Insurance Policy of real estate and / or mortgaged securities in European
funded projects;
- Letter of Credit Guarantee co-financing;
- Letter of Guarantee Facility VAT;
- Counter Letters of Credit Guarantee co-financing;
- Performance Insurance Policy.
Step 5 - Closing the works (process - Verbal completion of works) (start of
sustainability):
- Working Capital Loan;
Step 6 - Payment of the last request for reimbursement:
- Investment Loan (Loan Refinancing Revolving loan balance);
- Working Capital Loan;
- Letter of Credit Guarantee Investment;
FINANCIAL PRODUCTS - BANK USE IN EUROPEAN PROJECT CYCLE
MANAGEMENT:
CONCLUSIONS:
37
-
-
-
-
-
-
Currently identifies a mismatch between the legal, financial and economic
characteristics of European funding on the one hand and product support
provided by (banks / funds guarantee / insurance companies) on the other.
So often occurs when beneficiaries of European funds fail to carry out the
project implementation because unable to access financial products to
ensure their co-financing or cash flows necessary.
Management Authorities and financial institutions need to correlate their
own procedures to develop collaborative relationships that lead to the
implementation of European projects in seamlessly and without financial
type jams.
In this respect it is necessary to know the current situation of financial
products / guarantee / insurance that can be offered by financial institutions
in order to support current and future absorption of European funds.
seen fit to include financial institutions - banks, directly or indirectly, in the
creation of innovative financing products / guarantee / insurance to
facilitate the absorption of European funds related to the Multiannual
Financial Framework 2014-2020.
Because financial institutions - Romanian banks have a better
understanding of the domestic market, Romania's future ability to
effectively manage EU programs involving financial institutions - state
owned Bank (Eximbank, CEC Bank Funds Venture capital, FNGCIMM,
FRC).
Romania can create their own development bank by creating a new entity
to be part of CEC Bank and Exim Bank, FNGCIMM, and to strengthen the
management of financial instruments funded by FESI. The result would be
an entity that can specialize and focus on developing optimal financing to
meet both short-term and national development objectives in the long term.
However, this process can take over the financial institutions - EU
(European Investment Bank and European Investment Fund) may propose
their own solutions used in other EU countries, solutions designed to use
standardized instruments "of the self ".
References
World Bank. 2013. "Rethinking the Role of the State in Finance '. Global Financial
Development Report 10.1596 / 978-0-8213-9503-5. Washington DC: The
World Bank.
EU Regulation. 1092/2010 the European Parliament and of the Council of 24
November 2010 on European Union macro-prudential oversight of the financial
system and establishing a European Systemic Risk;
Commission Communication on the application of Articles 87 and 88 of the EC
Treaty to State aid in the form of guarantees 92008 / c 155/02)
38
"Report on Effectiveness of EU Structural Funds in the Use of Romania and
Bulgaria." 2013 German Marshall Fund of the United States. Accessed
December 9.
European Fund Investments: Financial Instruments - past, present, future Bucharest, 10 April 2014
Financial Stability Report - NBR 2014;
Last Steps-AbsorbtiaFondurilorEuropene - Victor Bostinaru MEP;
Guidelines for SME Access to Finance Market Assessments (GAFMA) - Helmut
Kraemer-Eis Frank Lang, Working Paper 2014/22 European Investments Fund Research & Market Analysis
Monitoring Committee meeting minutes Sectoral Operational Programme Increase
of Economic Competitiveness << >> November 24, 2011 "
"Report on the implementation of the National Reform Programme 2011-2013" of
the Ministry of European Affairs of Romania March 15, 2012
"Monitoring Committee meeting minutes Sectoral Operational Programme
Increase of Economic Competitiveness << >> Bucharest 06.06.2012" no.
229818 / 09.07.2012
EU Regulation. 1303/2013.
39
40
The Risk of the Firm's Marketing
Assoc. Prof. Dan NASTASE PhD
Master Ana Maria Melania PAUN
Master Adrian RADU
Abstract
The complexity of economic and social relations, plus the development of
science and technology have created significant changes in the approach of the
theoretical and practical concepts of risk and uncertainty at the firm level. First,
issues were imposed on the content and meaning of concepts of risk and
uncertainty in general, the views of various experts in this area is extremely
diverse.
Risk can be viewed as representing the inability of firms to adapt to time and
at the lowest cost to environmental changes. Viewed from this perspective, the risk
of which affect a company's primary source of business climate instability (item
exogenous firm) and inability to counter the economic timely and inexpensively
effects of the evolving environment in which it operates. In this sense, a profitable
activity today may become uneconomic in the future due to changes in unfavorable
environmental conditions. It follows that risk is a permanent feature of the activity
of a firm, it must implement appropriate risk management mechanisms,
highlighting the changes faster and intervention measures.
Key words: economics, risk, company, market, marketing, management,
bankruptcy, relationship.
In the economic sphere, to materialize the idea that gain and risk in a
business are directly proportional sizes. Any human activity (and therefore
economic activity) is subject to disruptive action of risk factors. Permanence risk is
not negligible in the decision-making process within the company and beyond. It is
a certainty as there is, and the uncertainty is given by the impossibility of
accurately predicting its occurrence; In other words, even if there is a specific risk
probability to occur or occurs.
Risk is a characteristic of those actions you can complete the more results,
knowing the probability of each outcome. Uncertainty expresses insecurity about
the future. Economic uncertainty is a source or character of a process unpredictable
economic or incompleteness of information available at a time.
Involves risk-taking more or less conscious choice made results. He refers
to the probability of success-failure action taken based on a certain decision. Risk
41
can come either from an ontological indeterminacy of the result of the action or the
fragility of knowledge we have at any given time.
Risk is the uncertainty of the occurrence of a phenomenon which, if
happens, could influence (most often negative) the objectives of the project. Risks
relate mainly to uncertainty hanging over future events. He expressed the impact
that has an event (or factor) of future economic activities today. In other words,
risk is the uncertainty associated with a hit. Risk can occur in the following
situations:
- When a certain event occurs, but its outcome is uncertain;
- When the result of a phenomenon or event is known in detail, but there is
uncertainty about the occurrence of that phenomenon or event;
- When both the event and its impact on company goals are uncertain.
Size uncertainty is measured by probability, which in turn can be
determined by mathematical calculations or statistical observations of similar
phenomena in the past. Assess the effects of the emergence of risk is vital to know
whether or not it is necessary to assume that risk.
The economic activity is a constant risk that influence good way to develop
it. He can have a huge impact on any project; therefore, success can only be
guaranteed when the knowledge of all risks that can affect simultaneously with the
adoption of necessary measures to prevent or mitigate them.
Analyzing these considerations, we can draw some basic features of the
concept of economic risk:
• risk is permanent facing any participant in economic life, regardless of
the scale of its business;
• risk is an element that harm both financial as well as moral;
• the risk is non reversible in the sense that its effects once produced, can
not be removed only with some additional expenses expensive.
The classical theory believes that the risk is the loss that occurs after the
adoption of certain decisions and the implementation of certain courses of action.
Decision risks (risks related to the adoption of a particular management
style, on a certain way of decision-making, etc.) are frequently encountered in
marketing, with information risks (are the risks of a business information system
and deficiencies its specific: information overload channels, redundancy etc...) and
methodological risks (take into account risks arising from the use of certain
instruments of management methods and techniques).
We are dealing, however, with the company's external risks (risks are those
that occur outside the company, have a direct influence on them, and managers
need to make decisions to minimize their effects). Within this category we
distinguish:
• legal risks (eg. Adoption of legislation that does not encourage free
enterprise and the spirit of competition between operators can seriously affect the
companies' activity);
42
• contractual risks (those risks are related to the fulfillment or nonfulfillment of obligations under the contract by a partner entity).
Attitude operators can be classified into two main types, depending on the
reaction I have to this phenomenon:
- Proactive - is based on the allocation of significant resources (financial, material
and human) to predict future events undesirable.
- Reactive - is considering addressing and solving various problems as they occur.
Obviously proactive approach generates long term returns much higher
than the reactive trader. We must not forget that this kind of attitude should be
supported by a strong financial and human support that businesses and not many
can afford.
Risk can be any element that has a measurable probability to deviate from
the plan originally set. Strategies and projects of companies are elements that allow
foreshadowing actual reality and then dealing with the expected outputs. To
achieve these objectives it is necessary to conduct business activities sets. Thus, an
event denoted by X, can be regarded as risk event if the following conditions
simultaneously:
1 0 <P (X) <1
2 L (X)> 0
in which:
P (X) is the probability that an event X to occur;
L (X) - monetary valuation of the event X.
In terms of probability, risk is the variability of profit to the average
profitability in recent years. This understanding is very important in achieving
predicted that "the risk is estimated as the variability of profits in relation to the
expectation of return." In this case, the criterion for determination were chosen
oscillations profit compared to an average, considering that the development of
future profits lower than the average, considered as the reference level may lead to
the emergence of crisis situations and adversely affect economic activity.
The OECD definition, it is estimated that "risk consists of the possibility
that an unwanted consequences actually occur." This definition is based on an
event event (expected or unexpected with a certain probability the decision maker)
to materialize and adversely affect certain aspects of economic activity.
Besides these, there are other definitions of risk, which seeks to find new
meanings thereof:
- A wide range of uncertainty about the economic future work;
- The probability of occurrence of an undesirable event;
- Variability likely future profitability of the asset;
- Variability of earnings under pressure environment;
- Possibility of future revenues to be different from those expected to be obtained.
In other words, the risk is influenced by environmental variability in income,
implying the event of an adverse event;
43
- Risk translates into earnings variability affecting the return on assets and,
consequently, the capital invested;
- An element of uncertainty that may affect the activity of an economic agent or a
transaction;
- Uncertainty of a leak from accidental causes, accidental or unexpected
circumstances;
- The probability of an adverse event to occur, the probability of success or failure,
where success means making a profit and failure involves sustaining a loss of
money from an investment.
International Accounting Standards believes that the risk is the variety of
results. Adjusting for risk may involve increasing the value of which is estimated
debt. The evaluation and expenditure affected by conditions of uncertainty, the
precautionary principle should be applied, not to overstate assets and understate
debt. However, elements of uncertainty does not justify the creation of excessive
provisions or obligations understatement.
Looking at these definitions, we can draw the main features of risk:
a) the risk arising from uncertainty; decision takes place today, and the
implementation and outcomes will occur in the future. The uncertainty stems from
ignorance about which of the identified event will occur and at what time be real
effects and the magnitude of their occurrence;
b) implies the risk of potential loss of whatever nature, caused by the
evolution of a factor to the contrary expectations maker;
c) the effects of risk, once produced, can not be removed;
d) the risk appears both in the business, social, and beyond, as a result of
the relationship between man and nature;
e) involves risk taking proper remuneration of invested capital;
f) the risk is an inability to adapt to the environment of the company;
g) risk is a measure of the vulnerability of the firm, the probability of
success or failure.
Knowing these specific features of the concept of risk can act on the
development of modern political risk prevention, protection against risk and to
remove its effects.
Analyzing scientific papers written in recent decades on the issue of risk,
highlighted in assessing evolving notions of risk and uncertainty, and the
manifestation of three main trends in this field:
- Increasing at an unprecedented rate risk situations and uncertainty caused
by the expansion of internationalization of activities to outsource a part of their
diversification of financial instruments, economic crises takes on a growing scale,
increased competition etc..;
- Extending the economists to develop scientific knowledge in this area by
calling a number of branches of science (management, marketing, finance,
statistics, etc.) and identifying, testing and implementation of new assessment
tools, prevention and protection against risk;
44
- Amplification and diversification consequences that the implementation
of tools and techniques to prevent and protect against the risk generated on the
economic, social, natural.
The three mentioned are interrelated trends and issues of risk and
uncertainty in the economic agent becomes more complex, enriching with new
meanings. At times, managers need to know the level of risk for each business
project, and if it is greater than the potential gain. At the same time, economic and
social conditions of transition to market economy, the economic stability and
security are dictated not only by their actions but by all participants in economic
life. In this complex system of interdependencies fall:
- Undertaking acting to obtain results allowing expenses incurred and
record profits;
- The financial system, which, in case of risk and instability, assigns, in
certain circumstances, cash funds for the ongoing production process;
- State through subsidies, and taxes and fees;
- Consumers, which is the firm's clients.
Conscious and unconscious actions performed by all of the contributors to
the company's activity can cause direct effects expected appropriate targets set, and
the manifestation of random effects, unwanted, which defines literature as risks.
References
Bârsanu Puiu, Popescu Ion: „Managementul riscului. Concepte, metode, aplicaţii.”,
Editura Universităţii Transilvania, Braşov, 2003.
Cătălin Zamfir: „Incertitudinea – o perspectivă psiho-socială”, Editura Ştiinţifică,
Bucureşti, 1998.
Cişmaşu Irina: „Riscul, element în fundamentarea deciziei. Concepte, metode,
aplicaţii.”, Editura Economică, Bucureşti, 2009.
Cornel Târhoacă: „Economia riscului şi incertitudinii”, Editura A.S.E., Bucureşti,
2008.
Coşea Mircea, Nastovici Luminiţa: „Evaluarea riscurilor – metode şi tehnici de
analiză la nivel micro şi macro economic”, Editura Lux Libris, Braşov, 1999.
Dudian Monica: „Evaluarea riscului de ţară”, Editura All Beck, Bucureşti, 2010.
George Pleşoianu: „Diagnosticul şi strategia firmei”, Editura Universităţii din
Piteşti, 2010.
Dan Nastase, Evaluarea riscului in activitatea de marketing, Ed. Axioma Print,
Bucuresti, 2013
Wen-fei, L. Uva, Senior Extension Associate: ”Mnaging marketing risks”, Dept.
Of Applied Economics and Management, Cornell University, 2004.
45
Macro-economic Analysis based on Econometric
Models
Prof. Gabriela Victoria ANGHELACHE PhD
Professor Ioan PARTACHI PhD
Academy of Economic Studies of Moldova
Emilia STANCIU PhD Student
Bogdan DRAGOMIR PhD Student
Abstract
The authors propose the identification and measurement of the existing
correlation between the evolution of the country's final consumption (total of sum
of private and public consumption), net investment and GDP variation. The
analysis methodology is based on linear multiple regression, defining the GDP as
outcome variables and the variable factor the final consumption value and net
investments in Romania.
Key words: GDP, correlation, investments, regression, quality
The economic situation in which correlations involves only two variables
are very rare. Rather we have a situation where a dependent variable, Y, can depend
on a whole series of variables factorial or regressor. In practice, there are
correlations of the form:
Y = β1 + β2 X2 + β3X3 + β4X4 +...+ βkXk + ε
where values Xj (j = 2, 3, ..., n) represents the variable factor or regressors, the
values βj (j = 1, 2, 3, ...,k) are the regression parameters, and ε is the residual factor.
Residual factor reflects the random nature of human response and any other
factors, others than Xj, which might influence the variable Y.
We adopted the usual notation, respectively assigned to the first factor
notation X2, the second notation X3 and so on. Sometimes it is convenient that the
parameter β to be considered that coefficient of one variable X1 whose value is
always equal to unity. Then the relationship is rewritten as:
Y = β1X1+β2X2 + β3X3 +...+ βkXk + ε
In the case of regression with two variables (E(ε) = 0), then, substituting,
for given values of the variables X, we get:
E(Y)=β1 + β2 X2 + β3X3 + β4X4 +...+ βkXk
46
The relationship is multiple regression equation. For now, conventional, we
consider that it is the linear form. Unlike the case of two-variable regression, we
cannot represent this equation in a two-dimensional diagram. βJ are regression
parameters. Sometimes, they are also called regression coefficients. β1 is a constant
(intercept) and β2 , β3 and so on, are the regression slope parameters.
β4, measuring the effects of E(Y) produced by changing one unit of X4,considering
that all other factor variables remain constant. β2 measures the effects on E(Y)
produced by changing one unit of X2, considering that all other variables remain
constant factor. As the population regression equation is unknown, it has to be
estimated based on data sample. Suppose that we have available a sample of n
observations, each observation containing the dependent variable values for both Y
and for each factorial variables X. We write the values for observation i as:
Yi , X2i , X3i , X4i ,..., Xki
For example, X37 is the value of X3 in the 7th observation and X24 is the
value X2 taken in the 4th observation. For a similar manner, Y6 is the variable Y in
the observation of 6 and so on.
Given that it is assumed that the sample data were generated by the
correlation of the population, each observation have to involve a set of values
satisfy the multiple equation regression.
We can write the equation:
Yi = β1 + β2X2i + β3X3i + ...+ βkXki + εi for all the values,
where εi represents the residual value for the observation of the i.
We can rewrite the relationship in a simple matrix form, as follows:
Y = Xβ + ε , where
X is a matrix the form of n x k with k column of values and then all sample
values of the k – 1, X variables.
Thus, the fourth column of X, for example, contains the values of X4 of the
sample n, the seventh column contains the values of X7 and so on. β is a vector of k
x 1 column containing the parameters βj and ε is an vector of n x 1 column
containing the residual values.
The effective values of Y will not coincide with the expected values of Y
and, in the case of two-variable regression, the differences between them are
known as residual values.
^
Y =Y +e
i
i
Like i
for all values of i
where ei is the residual corresponding to the observations of i.
The relationship can be written as:
^
^
^
^
β + β 2 X 2 i + β 3 X 3i + ... + β ki X ki + ei , for all values of i or on matrix
Yi = 1
form:
^
Y = X β + e , where X and Y are already defined
47
There are two issues to be retained on the residual values.
First, regardless of the method used to estimate the regression equation, we
get such residual values - one for each of the sample observations. Second, as
^
expected
βj
when it becomes known and can be used to calculate them. Now, we
^
need to calculate the differential with the vector β and equalizer to zero the result.
Such of this matrix lead to the following relation:
∂S
^
∂β
^
= −2 X ' Y + 2 X ' X β = 0
The above equation is a set of k equations that can be written as:
^
X ' X β = X 'Y
Example:
In the analysis of the factors that determine the variation of GDP, we
started from specific component elements of using the final production method
(expenditure method), considering that this is a significant source of information on
the main correlations that influence the evolution of the main macroeconomic
aggregate.
Thus, according to the calculation method above, GDP involves
adding components that express using of goods and services for final production,
as follows:
PIB = CF + FBC + EXN
Based on the elements mentioned above we want to identify the existing
relationship between the evolution of the country's final consumption (regarded as
a sum of private and public consumption), net investment and GDP variation. In
this regard, we used linear multiple regression analysis as a method in which we
consider GDP as outcome variables and the variable factor the final consumption
value and net investments in our country during 1998-2013.
The three indicators can be presented in summary form as follows:
Evolution of GDP, final consumption and net investment
in Romania during 1998-2011
FINAL
NET
GDP
Year
CONSUMPTION
INVESTMENT
(mil. lei) Y
(mil. lei) X1
(mil. lei) X2
2006
247,368.0
211,054.6
44,869.9
2007
288,954.6
251,038.1
54,566.0
2008
344,650.6
294,867.6
72,891.0
2009
416,006.8
344,937.0
98,417.7
2010
514,700.0
420,917.5
99,525.6
48
FINAL
CONSUMPTION
(mil. lei) X1
404,275.5
419,801.2
436,485.0
NET
INVESTMENT
(mil. lei) X2
2011
501,139.4
74,939.3
2012
523,693.3
72,294.7
2013
556,708.4
87,815.8
TOTAL 3,393,221.1 Source: Statistical Yearbook of Romania, Gross Domestic Product,
categories of uses, NIS, Bucharest, 2008, 2009, 2010, 2011, 2012, 2013
For an pertinent analyze of the correlation between the three macroeconomic
indicators presented in the table above, it is necessary in a first step of this research
to identify a number of features aiming the evolution of each indicator considered
in the period under review. To prove this, using the software Eviews 7.2, we
studied in the first stage, the evolution of the three indicators. As can be seen from
analyzing the data series under investigation, especially as in the figure shown
above, in the period considered, the three of our country's macroeconomic
indicators have registered a steady growth from year to year.
The purpose of multiple regression (term used by Pearson, 1908) is to
highlight the relationship between a dependent variable (explained endogenous
effect) and a lot of independent variables (explanatory factors, exogenous
predictors).
Multiple linear regression model equation will look like this:
Y=b0+b1X1+b2X2+ ε
Year
GDP
(mil. lei) Y
in which:
Y - Gross Domestic Product- GDP;
X1 - Final Consumption- CF;
X2 -Net investments- INV;
b0,b1,b2 - parameters of the regression model;
ε is a variable, interpreted as error (disturbance, measurement error).
The regression model may be rewrite under the following mathematical equation:
PIB= b0+b1CF+b2INV+ ε
To estimate the regression model parameters we used the software Eiews
7.2 in which we defined an equation that has as outcome variables GDP, and factor
variables the final consumption and net investments. We also thought that this
regression model will also include free term c, which is expected to influence
dimming terms that were not taken into account when we building this model.
Estimation method defined in the program is the method of least square.
Based on the above, using Eiews 7.2 we obtained the following results:
49
Characteristics of the regression model
From the above, multiple regression model describing the relationship
between the three macroeconomic indicators that are are the subject of previously
determined may be given in the form of equation as follows:
PIB = -8.927,569 + 1,165488 CF + 0,284958 INV
Thus, we can say that an increasing with a monetary unit of final
consumption (with its two component - private consumption and public
consumption) will lead to an increase of 1.165488 units monetary of gross
domestic product value. In case of the net investment, the difference is more
significant, we can see that every leu invested brings an increase of only 0.284958
lei of the level of gross domestic product. This situation corresponds with the
reality economics of Romania because in the last twenty years the Romanian
economy was based almost exclusively on stimulating consumption and less on
promotion of an investment policy correctly.
The influence of the free term as a picture of the factors that were not
included in the analysis model is one significant. In fact, it can be said, that the
factors that were not included in the econometric model of analysis, they have an
significant decrease in the value of gross domestic product.
The probability for this model to be correct is very high - about 98.89%,
this conclusion can be formulated on the basis of statistical tests R-squared
(0.988909) and Adjusted R-squared (0.986892).
Also the validity of the regression model is confirmed by the F test value statistically superior value table level that is considered to be the benchmark in the
analysis of the validity of econometric models and by the value of the test Prob (F statistic) that it is zero.
Based on observations made on the analysis of Romania's GDP, using
50
multiple regression model, we conclude that the value of this indicator is
significantly influenced by the variation of final consumption and net investment
less variation.
Using a multifactorial regression model allows to obtain more
edifying results in macroeconomic analysis and conducting relevant research on the
evolution of the national economy.
The Linear and Non-displaced Estimator
A general matrix demonstration on the features BLUE in case of multiple
regression is outside the goal.
We will limit ourselves only to find expressions for the variations and
covariance of OLS estimators.
As we shall see, these expressions are important if we want to develop
inferences about the parameters of the multiple regression.
The matrix is known as the matrix variation – covariation of the vector β̂,
which generally is written in the form of Var ( β̂). Note that in the bottom of its
main diagonal, it contains variations vector β̂j. Outside the diagonal elements
represents the covariance between different β̂j values that would result in case of
more samples extraction. It is clear that if we need to develop inferences about the
true value of βj , it is necessary to find an expression for this matrix.
The equation is just the expression for the matrix variation – co-variation
of vector OLS β̂.
We write the element of row i and column j of the (X’X)-1 inverse matrix
ij
as X . Since (X’X)-1 is symmetric, we have Xji = Xij. The comparison indicates that
the variation of β̂j ,which is written in the form σ β2ˆj is given by: σ β2ˆj = Var ( β̂j ) =
σ2Xjj , j = 1, 2, ..., k.
Thus, to find the variation of β̂j , we have to take the j element of the
diagonal matrix (X’X)-1 and to multiply it by the change in average residual values,
σ2. Square root of Var ( β̂j ) is known as the standard error of β̂j and it is noted by
σ βˆj .
Comparing the two equations further, resulting that:
Cov ( βˆi , βˆ j ) = σ2 Xij for all values i ≠ j
The expressions obtained are of considerable importance for inference in
multiple regression.
It is possible to obtain equivalent expressions if we work in terms of
deviations of variables from their average. It is merely necessary to work in terms
of the inverted matrix (x’x)-1 instead of the matrix (X’X)-1. A complete derivation
would prove repetitive but it is not difficult to prove that:
51
2 jj
σ β2ˆj = Var ( β̂j ) = σ x , j = 1, 2, ..., k
and
Cov ( βˆi , βˆ j ) = σ2xij
for all values i ≠ j
where xij is the element from row (i – 1) and column (j – 1) of matrix (x’x)-1.
It should be noted that the relationship does not lead to an expression for
Var ( β̂j ).
In the particular case of two-variable regression, (x’x)-1 is only the scalar
22
∑ x so that x = 1/ ∑ x22 , which leads to the relationship:
2
2
Var ( β̂2) = σ2/ ∑ x 22
This is identical to the corresponding expression for the variance estimator
OLS for the slope regression parameter with two variables.
• Additional properties of the model
As in the case of two-variable regression, where the OLS estimators have
to to be mainly but not only stationary and asymptotically efficient and effective, it
is necessary that the IID assumption of classic model to self-sustain – that means
the residual values have to be normally distributed. Therefore, if OLS estimators
must have these properties, it is necessary that all classical assumptions are valid.
A proof of ownership efficiency is outside the goal we have set. Remember only
that efficiency implies that OLS estimators have the minimum variance of
stationary estimators of all - not only of linear stationary estimators.
Normality residual values have other two important consequences for OLS
regression. First, it means that the distributions of OLS estimators will be the
selection of normal distributions. A demonstration of this statement is analogous to
the case of two-variable regression. However, that, whereas under all classical
assumptions, each β̂j is stationary with set variation:
2 jj
β̂j is N(βj, σ X ), j = 1, 2, 3, ..., k
A precise knowledge of the distributions of selection of OLS estimators,
respectively β̂j , is of vital importance for inference.
It is often helpful for the relationship to be expressed in an alternative form,
working in terms of deviations from their average variables X, in which case we
get:
2 jj
β̂j is N(βj, σ x ), j = 1, 2, 3, ..., k
The second consequence of the assumption of normality of the distribution
of residual factors is, as in the case of two-variable regression, that OLS estimators
52
are maximum probability estimator. As in the two-variable regression, MLE for σ2
's proves:
σ~ 2 =
∑e
where
∑e
2
i
n
2
i
is the sum of squared residual factors. However,
σ~ 2
proves to be an
2
moved estimator of σ real. In fact, it can be shown that if multiple regression:
E( σ~ 2 ) = n − k σ 2 ≠ σ 2
n
and is a generalization of the two-variable regression results.
Since, under classical assumptions, OLS and ML estimators of the
βj
parameters are identical at this point it may seem that ML estimation contribute
little to our analysis of regression equations.
Maximum probability estimation becomes most relevant when classical hypotheses
are refused.
For example, this method is often used in cases where the regression
equation is nonlinear.
There is also of great importance when classical assumptions on the
variable factor and/or to the residuals are invalidated. As we have seen, if the
classical assumptions are not valid, then the OLS estimators lose some, or all, of
the desired properties. It proves that, in such circumstances, OLS estimators and
ML estimators are not identical. In such a situation, ML estimators have the
advantage that they still maintain their properties, namely compatibility and
asymptotic efficiency.
• Inference in multiple regression
By condition that all classical assumptions are valid, inferences on the
slope parameters in multiple regression can be based on the outcome β̂j = N(βj,
σ2xjj) which implies that, for j = 1, 2, 3, ..., k, have:
βˆ j − β j
has a distribution N(0, 1)
σ βˆj
We will focus on the slope parameters that are of interest. The inference on
the parameter β1, it should be based on the set equation, with j = 1.
The problem that arises it is that the standard errors, σ βˆj , are unknown
because the residuals variations, σ2 is unknown.
When we substituting σ βˆj on stationary estimators, sβ̂j , as in the twovariable regression, we have to change the distribution of t. It can be shown that:
53
βˆ −β
sβˆj
has a distribution t, cu n – k g.l.
For example, at a 95% confidence interval for any value βj (j = 2, 3, ...,k) is:
βˆ j + t 0 , 025 s βˆj
the value of t0,025 depending on n – k and on the number of degrees of freedom. In
order to obtain a 99% interval are replaced t0,025 with t 0,005 .
Trustworthiness check can continue over the similar lines of the twovariable regression determined.
To test the null hypothesis like H0 : βj = 0 (j = 2, 3, ...,k), we have to say
that under the null hypothesis, which implies: βˆ j / s βˆj have a t distribution with n k degrees of freedom.
Therefore, we use βˆ j / s βˆj like test statistic and reject the null hypothesis
that variable Xj does not influence the variable Y whether the absolute value of the
test statistic is sufficiently large.
As in the case of two-variable regression, the statistical test is often called
the coefficient t.
References
Anghelache, C., Mitruţ, C. (coordonatori), Bugudui, E., Deatcu, C. (2009) –
„Econometrie: studii teoretice şi practice”, Editura Artifex, Bucureşti
Anghelache, C.,Voineagu, V., Manole, A., Soare D.V., Prodan, L. (2013) - „The
Linear and Non-displaced Estimator in Multiple Regression”, Revista Română
de Statistică, suplimentul trim. II/2013, ISSN 1018-046x.
Bardsen, G., Nymagen, R., Jansen, E. (2005) – „The Econometrics of
Macroeconomic Modelling”, Oxford University Press
Dougherty, C. (2008) – “Introduction to econometrics. Fourth edition”, Oxford
University Press
Gourieroux, C., Jasiak, J. (2001) – „Financial econometrics: problems, models and
methods”, Princeton University Press, Princeton
Mario G.R. Pagliacci, Gabriela Victoria Anghelache,Ioana Mihaela Pocan, Radu
Titus Marinescu, Alexandru Manole “Multiple Regression – Method of
Financial Performance Evaluation”, ART ECO – Review of Economic Studies
and Research, Editura Artifex, Vol. 2/No.4/2011, pp. 3-9.
Mitruţ, C. (2008) – „Basic econometrics for business administration”, Editura ASE,
Bucureşti
Voineagu, V., Ţiţan, E. şi colectiv (2007) – “Teorie şi practică econometrică”,
Editura Meteor Press
54
The Direct Foreign Investments in Romania by the
End of 2013
Adina Mihaela DINU PhD Student
Abstract
Nowadays, the economic reform is directed mainly towards finalyzing the
restructuring and privatization of the large state-owned companies as well as
towards securing the coherence between the different components of the reform.
This is why, the foreign investments policy is aiming a continuous increase of the
production and, on this ground, of the exports, the development of the small and
medium companies as well as a balanced regional development, these targets
being considered as major instruments allowing the premises of the European
integration of Romania.
The foreign investments are holding a special place within the volume of
the investments achieved in the Romanian economy. The foreign investments policy
has to be considered as a first step for supplementing the domestic requirements of
capital as well as a source for bringing in new technologies, know-how and
performant management.
Key words: economic reform, foreign investments, development, regional
development, policy
The foreign investments are holding a special place within the volume of
the investments achieved in the Romanian economy. The foreign investments
policy has to be considered as a first step for supplementing the domestic
requirements of capital as well as a source for bringing in new technologies, knowhow and performant management.
Nowadays, the economic reform is directed mainly towards finalyzing the
restructuring and privatization of the large state-owned companies as well as
towards securing the coherence between the different components of the reform.
This is why, the foreign investments policy is aiming a continuous increase of the
production and, on this ground, of the exports, the development of the small and
medium companies as well as a balanced regional development, these targets being
considered as major instruments allowing the premises of the European integration
of Romania1.
1
Anghelache Constantin, Marinescu Radu Titus, Manole Alexandru, „Utilizarea modelelor
dihotomice în analizele economico-financiare”, Revista Română de Statistică, Bucureşti,
decembrie 2009, cod ISSN 1018-046X. Revista Română de Statistică - Supliment nr. 10/2014
55
The ISD net flow for the year 2012 recorded the level of 2,138 million euro
• Net participations of the direct foreign investors to the capital of direct
foreign investment from Romania, amounting 795 million euro (37.2% out
of the IDS net flow). The net participations to capital are resulting from the
diminishing of the capital participations, amounting 2,676 million euro, by
the net loss, amounting 1, 881 million euro. The net loss resulted by
deducting, out of the ISD companies profit recorded in 2012, amounting 4,
691 million euro, the dividends distributed for the year 2012, counting for
2,212 million euro, followed by diminishing this value with the losses
recorded by the ISD companies in 2012, amounting 4,360 million euro.
The calculation procedure is complying with the international methodology
for setting up the re-invested profit by the ISD companies, respectively the
net loss recorded by these ones.
• The net credit received by the companies with direct foreign investment
directly from the direct foreign investors, including within the group,
amounted 1,343 million euro, counting for 62.8% from the ISD net flow.
Out of the data concerning the ISD net flow and its components (there are
relevant conclusions to underline.
• For the majority of the economic activity domains, where the ISD hold a
significant weight, there are increases of the participation to capital as to
the ISD companies, which means a continuation of the investment process
during the year 2012. The domains recording the most significant increases
of capital have been the industry (1, 072 million euro), in which frame, the
manufacturing industry (529 million euro) and the energy (497 million
euro) are leaders; other domains recording significant capital investment
have been financial intermediations and insurances (646 million euro), as
well as constructions and real estate transactions (295 million euro);
• The main economic domains where the losses exceeded the profits have
been financial intermediations and insurances (376 million euro profit, 1,
015 million euro loss) and constructions and real estate transactions (255
million euro profit, 747 million euro loss).
• Through the distribution for the year 2012 of significant amounts as
dividends within the above mentioned domains, the net loss gets deeper
(profit minus distributed dividends, minus losses). Thus, dividends
amounting 134 million euro have been distributed in the domain of
financial intermediations and insurances and 158 million euro in
constructions and real estate transactions.
• A number of domains have taken the advantage of important financings,
through net credits mother-daughter, respectively: the manufacturing (606
million euro), energy (173 million euro), trade (423 million euro),
constructions and real estate transactions (213 million euro).
56
•
As far as the industry is concerned, although significant losses have been
recorded (1,491 million euro) and dividends amounting 960 million euro
have been distributed, by the recorded capital participations level (1,072
million euro), the net credits (862 million euro) received and the achieved
profit (2,345 million euro), it benefited of a net flow if ISD amounting
1,828 million euro, representing 85.5 % from the ISD net flow for the year
2012.
The ISD net flow for the year 2011 recorded the level of 1815 million euro.
The net participations of the direct foreign investors to the capital of direct foreign
investment from Romania, amounted 1512 million euro (83.3% out of the IDS net
flow).
The net participations to capital are resulting from the diminishing of the
capital participations, amounting 4009 million euro, by the net loss, amounting
2497 million euro. The net loss resulted by deducting, out of the ISD companies
profit recorded in 2011, amounting 4710 million euro, the dividends distributed for
the year 2011, counting for 2075 million euro, followed by diminishing this value
with the losses recorded by the ISD companies in 2011, amounting 5132 million
euro.
The net credit received2 by the companies with direct foreign investment,
directly from the direct foreign investors, including within the group, amounted
303 million euro, counting for 16.7% from the ISD net flow.
The ISD net flow for the year 2010 recorded the level of 2220 million euro
• The net participations of the direct foreign investors to the capital of direct
foreign investment from Romania, amounted 1824 million euro (82.2%
out of the IDS net flow).
• The net participations to capital are resulting from the diminishing of the
capital participations, amounting 4067 million euro, by the net loss,
amounting 2243 million euro. The net loss resulted by deducting, out of the
ISD companies profit recorded in 2010, amounting 4222 million euro, the
dividends distributed for the year 2010, counting for 4495. The calculation
procedure is complying with the international methodology for setting up
the re-invested profit by the ISD companies, respectively the net loss
recorded by these ones.
• The net credit received by the companies with direct foreign investment,
directly from the direct foreign investors, including within the group,
amounted 396 million euro, counting for 17.8.7% from the ISD net flow.
2
Mădălina Gabriela ANGHEL – Actual Romanian Capital Market Characteristics, ART
ECO - Review of Economic Studies and Research, Vol. 3/No. 3, Editura Artifex, 2012, pg.
10 – 13, ISSN 2069 - 4024 Revista Română de Statistică - Supliment nr. 10/2014
57
The final sold of the ISD by December 31st, 2012 recorded the level of 59,
126 million euro, 7.2% higher as against the final ISD sold relating to th eyear
2011. This outcome resulted out of adding to the sold of the initial net flow of the
ISD the positive/negative value differences originating both in the re-evaluations
due to the alterations of the exchange rate of leu and certain assets prices and to
accounting reconsideration of the initial sold of certain reporting companies.
The final sold of the ISD by December 31st, 2011 recorded the level of
55,139 million euro, 4.9% higher as against the final ISD sold of the year 2010.
This outcome resulted out of adding to the sold of the initial net flow of the ISD the
positive/negative value differences originating both in the re-evaluations due to the
alterations of the exchange rate of leu and certain assets prices and to accounting
reconsideration of the initial sold of certain reporting companies.
The participations to the social capital (including the re-invested profit as
well) of the companies with direct foreign investment recorded, by the end of the
year 2012, a value 39,266 million euro (66.4% of the ISD final sold), while the
total net credit which they have received from the direct foreign investors,
including within the group, recorded the level of 19,860 million euro, reprezenting
33.6% of the ISD final sold.
The final sold of the ISD by December 31st, 2010, resulting out of adding
to the sold of the initial net flow of the ISD the positive/negative value differences
originating both in the re-evaluations due to the alterations of the exchange rate of
leu and certain assets prices and to accounting reconsideration of the initial sold,
recorded the level of 52,585 million euro, 5.2% higher as against the final ISD
sold of the year 2009.
The final sold of the ISD for the year 2009, resulting out of adding to the
sold of the initial net flow of the ISD the positive/negative value differences
originating both in the re-evaluations due to the alterations of the exchange rate of
leu and certain assets prices and to accounting reconsideration of the initial sold,
recorded the level of 49,984 million euro, 2.4% higher as against the final ISD
sold of the year 2008.
The evolution of the net flow and sold of the direct foreign investments is
submitted in the following table :
Table 1. Indicators of the foreigninvestment in Romania 2008-2012
Indicators
2008
2009
2010
2011
2012
ISD net flow (mil.euro)
9496
3488
2220
1815
2138
ISD sold (mil.euro)
48798 49984 52585 55139 59126
From the point of view of the distribution of the ISD in 2012, by economic
branches (according to CAEN Rev. 2), they have been concentrated mainly in the
58
ceramics (2.8 %).
Besides industry, the other activities which have drawn significant ISD are
the financial intermediations and insurance (representing 18.5 % of the total ISD),
the trade (11.4%), constructions and real estate transactions (9.2%), information
To note that the corporal and non-corporal immobilizations, recording a
sold of 27,412 million euro by the end of the year 2012, are representing 46.4 % of
the total sold od ISD which leads to a significant degree of stability of the foreign
investment. The economic activities where the ISD are found as corporal and noncorporal immobilizations at a significant level are: the industry (27.7% of the total
ISD, while in this frame the manufacturing industry counts for 17.9 % of the total
ISD); trade (5.9%) as well as constructions and real estate transactions (4.8%).
Table 2. ISD by economic activities, 2008-2012
Activities
Total, off which
Industry, off which
Extractive industry
Manufacturing industry
Electric energy, gas and
water
Vocational,
scientific,
technical and administrative
activities and supporting
services
Agriculture, forestry and
fishing
Commerce
Constructions and real estate
transactions
Information technology and
communications
Financial
intermediations
and insurances
Transports
Other activities
Million euro
2012
59126
27455
3225
18509
5721
2008
48798
20138
2158
15236
2744
2009
49984
20680
2221
15555
2904
2010
52585
23093
2388
16840
3865
2011
55139
24487
2753
17372
4362
1617
2299
2560
2679
2843
707
552
1068
1316
1402
6060
6155
6164
6453
6519
4746
6282
5897
6714
5466
181
3283
213
3235
417
10055
431
10026
348
2854
10026
9510
3081
2967
10914
500
131
684
194
788
258
787
267
876
254
59
From the point of view of the distribution of the ISD in 2011, by economic
branches (according to CAEN Rev. 2), they have been concentrated mainly in the
ceramics (3.2 %). Other activities which have drawn significant ISD are the
financial intermediations and insurance (representing 18.2% of the total ISD), the
trade (11.4%), constructions and real estate transactions (10.7%), information
From the territorial point of view it is obvious that the ISD have been
directed mainly towards the development region BUCUREŞTI-ILFOV (60.6%),
the next to count as beneficiaries of ISD being the following development regions:
CENTER (7.8%), WEST (7.6%), SOUTH-MUNTENIA (7.2%) and SOUTHEAST (5.5%). To note the fact that the ISD have been located from the territorial
point of view according to the social headquarter of the companies with direct
foreign investments, which does not always correspond to the actual place the
activity is carried on.
Table 3. Number of companies with foreign participation to capital
Value of the subscribed social capital
Sold by the
end of the
period
Number of Total expressed Total expressed Total expressed
companies
in national
in foreign
in foreign
currency
currency
currency
equivalent
equivalent
Nr.
0
December 31st,
2013, off which
%
1
mii Lei
2
%
mii USD
3
%
mii EURO %
4
192.416 103,6 129.484.939, 108,8
1
50.548.651,9 106,6
37.692.344,7 106,7
December 31st t, 185.792 103,6 119.055.965, 111,9
2012
0
December 31st,
179.407 103,7 106.351.276,3 110,6
2011
December 31st
173.030 103,8 96.160.790,2 122,1
2010
December 31st
166.728 104,3 78730295,5 124,1
2009
December 31st
159927 108,3 63426984,9 131,1
2008
December 31st
147663 100,0 48392059,2 100,0
2007
47.398.370,7 108,4
35.336.541,0 108,8
43.719.608,5 111,9
32.480.124,4 111,9
39.059.823,5 115,2
29.150.692,0 115,5
33915262,8 116,6
25236251,3 116,2
63426984,9 125,6
63426984,9 122,5
23173116,8 100,0
17739208,0 100,0
60
Depending on the origin, in the year 2013 the number of entries of
commercial companies with foreign participation to the subscriebed social capita is
reflecting a close connection of the Romanian economy with the European
economy. Thus, 85.83% of the investments are coming from Europe and i 6.57%
only from countries located in Asia, North Americac or other regions of the world.
In December 2013, the top ten of the values of the total suscriebed social
capital, expressed in euro, by residence countries of the investors, included: France,
Germany, Cyprus, Italy, Holland, China, Luxembourg, Poland, USA and Russia.
Although the factor foreign investments is considered as fundamental for
the positive development of any national economy3, there have been not enough
steps taken in order to increase the atractiveness of Romania for the perception of
the foreign capital. A series of major difficulties in this respect are given by certain
provisions of the economic legislation and fiscal policies, so that the impact of
certain fiscal steps on the vision of the existing and potential foreign investors was
not always a priori evaluated.
It is necessary to have convincing and energic steps adopted in order to
draw additional funds of capital from abroad, steps meant to improve the reticence
among the foreign investors.
Presently, it is stated out that investors from certain countries4 are showing
an increased reticence as regards the potential opportunities offered by our country.
Thus, out of the analysis of the data for the year 2013, the Czech Republic, Spain,
Switzerland, Belgium, the United Kingdom and Turkey hold a low weight in the
invested foreign capital. Among the neighboring counties, Russia is the only
partner country in this field holding a more significant weight.
As far as the Arabic countries are concerned, the only notable presence is
Lebanon.
The territorial profile of the foreign investments for the year 2013 is
reflecting significant disparities between districts. If in Bucureşti, Timiş, Ilfov,
Constanţa or Cluj, we can note a high participation of the foreign capital to the
economic activity, in Alba, Bistriţa-Năsăud, Buzău or Călăraşi, this aspect is not
reflecting the actual potential of the respective districts.
Meantime, to note that part of the foreign investors belong to the diaspore,
being of Romanian nationality.
3
Păunică Mihai, Ţurlea Carmen, Matac Liviu Marian, Manole Alexandru, „Proiectarea
depozitelor de date prin prisma instrumentelor analizei economico-financiare”, Revista
Română de Statistică, Bucureşti, iunie 2009, cod ISSN 1018-046X. 4
Anghelache, Gabriela Victoria, Mădălina Gabriela ANGHEL – Efectele crizei
economico-financiare asupra pieţei de capital din ţara noastră, Simpozionul Ştiinţific
Internaţional „Efecte şi soluţii prentru criza economico-financiară”, Editura Artifex,
Bucureşti, 2009, pg. 174 – 177, ISBN 978-973-7631-63-3 Revista Română de Statistică - Supliment nr. 10/2014
61
Acknowledgement
This work was cofinanced from the European Social Fund through
Sectoral Operational Programme Human Resources Development 2007-2013,
project number POSDRU/159/1.5/S/142115 „Performance and excellence in
doctoral and postdoctoral research in Romanian economics science domain”
References
Anghelache C. şi alţii (2014) – „Budgetary Execution, Monetary Market –
Resources and Placements”,Romanian Statistical Review, Supplement no.
4/2014, pp. 115-128
Anghelache C. şi alţii (2013) –„Investiţiile străine directe în România în perioada
2003 - 2012”, Romanian Statistical Review, Supplement no. 1/2013, pp. 266284
Anghelache C. şi alţii (2013) – „The Decline of Capital Investments in Romania”,
Anghelache C.; Manole A. (2012) – „Analysis Models of Romania's Foreign Trade
”, Economic Computation and Economic Cybernetics Studies And Research, nr.
2/2012, pp. 23-36, ISSN 0424 – 267 X
62
Using the Value at Risk Model in the Portfolio
Management
“Artifex” University of Bucharest
Abstract
In the frame of this article I have submitted the main elements describing
the way to set up the VAR indicator – by means of various methods of calculation
as well as a series of practical aspects concerning the estimation of the volatility
for a financial asset through this type of econometric model, with direct
applications on the capital market from our country. Using the Value at Risk model
allows a more efficient allocation of the available financial resources, eliminating
thus an over-exposure in connection with a single source of risk and allowing the
investors of capital to adequately evaluate their activity and position on the capital
market, depending on the risk level which they are willing to undertake. In the
frame of this study, I have applied this method directly on a portfolio formed by ten
equities in order to estimate the VaR level through stimulating various variants of
portfolios, taking into account the various weights of the financial assets
participation.
Key words: Value at Risk, the variance – covariance, volatility, confidence
level, simulation.
Introduction
The Value at Risk model is representing a maximum statistical estimation,
with a certain probability and under the normal conditions of the market, of the
level of the loss for a portfolio over a certain determined period of time. In other
words, the VaR is representing the amount which a portfolio or an entity may lose
during a certain time interval as a result of the fluctuations of the market prices for
the financial instruments being held. The possible time horizon can be a day for
most of the transacted positions or a month or more for the portfolio investments.
The Value-at-Risk model shows the following specific features:
• the capacity to express numerically the level of risk for a portfolio at a
given moment;
• it is a flexible instrument for measuring the market risk which can work
with different probabilities of confidence – mostly comprised between 90% and
99% – and time horizons;
• capacity to quantify the degree of risk for an open position at a given
moment in assets on the capital market, goods, currencies or granted credits;
63
• the model does not submit an estimate of the actual loss but expresses a
potential loss which, in fact, is not up-limited.
Methods used in calculating the Value at Risk indicator
In practice there are several methods being used for the calculation of the
VaR, among the most known and applied being the analytical method; the
historical method; the Monte Carlo simulation. The selection of the method of
calculation depends on a series of specific factors, such as: the type of the financial
instruments being held; the statistical hypotheses on which the risk is based; the
methods for the risk evaluation; the risk decomposition; the easiness to
communicate the resulting outcomes to the users.
The Monte Carlo simulation
The Monte Carlo method is indicated whenever instruments of non-linear
evolution are used and requires a relatively long time of calculation. The
application of this method consists of running through several stages:
• specifying the alleatory processes for the portfolio factors of risk;
• indicating the modality in which the factors of risk are influencing the
portfolio;
• simulating a large number of evolution for the said factors;
• simulating the final values of the portfolio on the basis of these
hypotheses. Each simulation leads to a possible profit or loss.
The density of probability for the possible profit or loss is set up in the
situation when a large enough number of possible values of profit or loss is
simulated. In this context, the VaR can be generated on the basis of the smallest
percentiles of the distribution.
Farther on, we are submitting the Monte Carlo analysis for the price of a
share (S). If S follows a geometrical Brownian movement, then:
μ = the expected yield per time unit;
σ = the volatility of the spot rate of the share;
dW = a Wiener process.
The Wiener process can be written as:
Φ = an alleatory variable which has a normal standard distribution.
The dW is replaced within the main relation and we get:
μdt = trend
64
The instantaneous yield of the share price is evaluating depending on the
trend and on the alleatory term ϕ. In the most of the cases in the practical activity,
the model in discreet time is used.
Δt = the time frequency at which the yield of the share price is measured
ΔS = the modification of the share price during the time interval Δt
It is considered that the share yield has a normal distribution with the mean
μΔt and the standard deviation
.
It is assumed that the simulation for the evolution of the share price takes
place for a time interval of length T. In this situation, the period of length T is
divided into a large number N of sub-periods Δt, where:
The simulation process is carried on as follows:
• the initial value of S is set up, respectively S(0);
• during the next stage, an alleatory value for ϕ is extracted and the share
value is calculated for the first sub-period, this process keeping to be repeated for
all the sub-periods Δt;
• an enough large number of trajectories for the share rate is forecasted to
be generated;
• it is necessary that the number of simulations for the share price
trajectory is as large as possible in order to have the simulated distribution of the
share rate at the moment T as close as possible to the real distribution of the price
by the end of the considered horizon;
• the estimated VaR-ul for the share rate is set up on the basis of the share
price distribution at the moment T,, S(T).
Advantages and disadvantages of the historical simulation
Advantage
Disadvantage
Capturing a large diversity of market High calculating power required
behaviors
Supplying information about the
impact of extreme scenarios
Detecting the risk included into the
scenarios which do not imply
extreme alterations of the market
65
Analytical VaR
The analytical method implies estimates of parameters based on the
historical data – average yields of the assets, volatility, correlation coefficients –
and is grounded on the hypothesis according to which the yields of the portfolio
assets (R) on the holding horizon (h) are normally distributed, having the mean μ
and the standard deviation σ:
R ~ N(μ,σ )
The VaR for the horizon of h days, with the relevance level 100(1−α )% is
:
where: S = the to-date value of the portfolio
xα = the smallest percentile α of the distribution N(μ,σ )
The normal transformation is applied, which has the following form:
where Zα = the smallest percentile α of the normal standard distribution
Although relatively easy to implement, the analytical method used for
estimating the value-at-risk is bearing certain disadvantages too:
• in practice, the statistical hypothesis on which the method is based –
namely, the evolution of the financial assets price has a normal distribution - is
hardly accomplished;
• most of the sensitivities (volatilities, correlation coefficients) are time
variables and the variability has an important significance on the risk steps –
mainly in the situation of the portfolios including options.
The historical VaR method
The principle at the basis of the historical VaR method is stating that in
order to measure the risk from the near future the information included in the prices
of the near past are enough. The model implies the setting up, for a well-defined
interval of time, of a hypothetical series of profit and loss (P/L) or yields for the
current portfolio. Similar to the precedent method, the historical method implies as
well the examination of the yields over a standard period of time (one day, one
week etc.) on a large enough set of historical observations.
For a portfolio” composed of „n” financial instruments, the yield is
calculated for every financial instrument „i” for each interval of time „T”.
The simulated P/L (profit or loss) for the considered portfolio during the
sub-period „t” is:
66
Ai = the amount invested in the financial instrument „i”
ri,t = the yield of the asset i for the sub-period t
The hypothetical P/L for the considered portfolio is established by
calculating the P/L for all the sub-periods „t”, the VaR being estimated on the basis
of the distribution of the P/L series.
For calculating the historical VaR there are also other methodologies, some
of them weighing the values P/L used for building up the distribution of the series
of P/L. Thus, in the year 1998, J. Boudoukh considered as justified the weighing of
the values P/L depending on their occurrence so that the newer information hold a
higher weight as comparatively the older ones since the first ones mentioned bear a
bigger content of information as regards the future risks.
In 1998 as well, Hull and White are showing that the data can be weighted
depending on the estimated contemporary volatility in the situation that the assets
volatility is variable. In order to estimate the VaR for the day „T”, the actual yields
are replaced by the yields adjusted depending on the volatility:
r*i,t = the historical yield of the asset i for the day t
σi,t = the forecasted volatility for the day t - 1 of the yield of the asset i for
the day t
σi,T = the most recent prognosis for the volatility of the asset i
Advantages and disadvantages of the historical simulation
Advantage
Disadvantage
The results obtained are completely
Easy to communicate to the
dependent on the set of utilised data (it
management (conceptual the
forecasts the future evolution on the
methodology is intuitive and simple)
basis of the past).
It can be adapted to the leptokurtosis The VaR values being obtained through
distributions, to those with asymmetry historical simulation cannot capture the
and to other non-normal distributions as risk associated to the occurrence of
the simulations are not dependent on the plausible evens in the future which did
hypotheses referring to the parameters not happen in the past.
of the markets evolution.
It admits modifications meant to It shows difficulties as to take into
allocate higher influences to certain consideration the modifications in the
observations (depending on the season, markets evolution which intervene
during the considered period.
oldness, volatility).
It allows the simulation of extreme
historical events.
67
The required data are easily available.
Easy to implement for any kind of
positions, including the derivatives.
In the situation that time series of the yields of the financial instruments1
portfolio are available, it is possible to apply a series of statistical techniques and
methods in order to set up the probability of losing the portfolio. Thus, if the
portfolio yields are following a normal distribution in time, VaR is easily
established for any level of confidence, by multiplying the confidence factor with
the standard deviation of the distribution of the portfolio yields.
The utilization of the variance-covariance method in order to set up the
VaR for a portfolio composed of ten equities
This study consists of the application of the model of setting up the Value at
Risk in order to estimate the level of the indicator under various scenarios for a
portfolio composed of ten equities with different proportions of participation
(fifteen simulations). The VaR estimation through the application of the variancecovariance method is requiring to establish the confidence level depending on
which the estimation of the variance of the portfolio which calculation is achieved
is taking place.
By applying this method, the value at risk is established taking into account
the market value of the portfolio, the confidence coefficient relating to the
considered probability distribution which is to be found out in the form of tableted
values and the portfolio volatility:
The participation weights of the ten equities to the portfolio construction
(%) and its volatility
P
P1
P2
P3
P4
P5
P6
P7
P8
P9
P10
P11
P12
X1
10
0
5
5
0
10
0
5
0
5
5
20
X2
10
15
20
5
5
10
5
5
15
0
5
15
X3
10
20
25
30
20
10
35
25
15
45
5
10
X4
10
5
5
5
5
10
10
10
20
5
10
5
X5
10
5
5
5
15
10
10
10
15
5
10
10
X6
10
20
5
5
20
10
10
5
5
5
15
20
X7
10
20
5
5
10
10
5
10
5
5
20
5
X8
10
10
5
5
0
5
0
5
5
5
20
5
X9
10
5
10
5
20
15
10
15
15
5
5
5
X10
10
10
15
30
5
10
15
10
5
10
5
5
σP
0.041569
0.072217
0.041131
0.043906
0.021466
0.039913
0.024880
0.038702
0.040228
0.041738
0.183658
0.538211
1
Păunică Mihai, Ţurlea Carmen, Matac Liviu Marian, Manole Alexandru, „Proiectarea
depozitelor de date prin prisma instrumentelor analizei economico-financiare”, Revista
Română de Statistică, Bucureşti, iunie 2009, cod ISSN 1018-046X 68
P13
P14
P15
15
0
5
15
20
5
15
15
5
15
15
5
15
10
5
5
10
15
5
15
15
5
0
15
5
10
15
5
5
15
0.184535
0.029862
0.135509
Further on we are submitting the results of the estimation for several
scenarios of the VaR by utilizing the variance-covariance method under the
conditions of an investment value 250,000 lei.
For the beginning, let’s consider the case of a equi-weighted portfolio
containing the ten equities P1 (σP1 for this equi-weighted portfolio is 4,1569%), the
portfolio of minimum risk P5 (σP5 = 2,1466%) and the portfolio of maximum risk
P12 (σP5 = 53,8211%).
Daily VaR (historic)
Confidence
*
Portfolio of
Portfolio of
Equic
level
minimum risk maximum risk
weighted
portfolio
90%
1,28
13302.080
6869.120
172227.520
95%
1,65
17147.213
8854.725
222012.038
97,5%
1,96
20368.810
10518.340
263723.390
99%
2,33
24213.943
12503.945
313507.908
*
The values for the parameter „c” corresponding to the probabilities are to
be found out in the tables concerning the repartition function of the standard
normal distribution
Applying the same methodology, the VaR for the other 12 analysed
portfolios are also calculated.
Confidence level
90%
95%
97,5%
99%
Confidence level
90%
95%
97,5%
99%
Confidence level
90%
95%
97,5%
99%
P2
23109.440
29789.513
35386.330
42066.403
P7
7961.600
10263.000
12191.200
14492.600
P11
58770.560
75758.925
89992.420
106980.785
P3
13161.920
16966.538
20154.190
23958.808
P8
12384.640
15964.575
18963.980
22543.915
P13
59051.200
76120.688
90422.150
107491.638
P4
14049.920
18111.225
21513.940
25575.245
P9
12872.960
16594.050
19711.720
23432.810
P14
9555.840
12318.075
14632.380
17394.615
P6
0.039913
0.039913
0.039913
0.039913
P10
13356.160
17216.925
20451.620
24312.385
P15
43362.880
55897.463
66399.410
78933.993
69
Source: own calculations
Conclusions
Out of the above submitted analysis, it is resulting that the role of the VaR
model consists of a more efficient allocation of the capitals by the capital investors,
as well as of the delimitation of the minimum undertaken risk by these ones,
aiming to estimate the potential gains and losses not to describe the most
unfavourable possible situations. The models of the Value at Risk type can be
successfully utilized for evaluating the volatility of the financial assets quoted on
the stock exchange market from our country, in the frame of the research
proceeding to the VaR calculation through the parametric method which we
applied on several portfolios formed by the ten analysed equities (various variants
of weights of the assets participation). Meantime, we have to underline the fact that
the portfolios have the VaR indicator directly proportional with the variance risk
indicator.
References
Anghel, M.G. et. al. (2013). Using Patterns of Volatility in Calculating VaR,
Revista Română de Statistică – Supliment/Trim III
Anghel, M.G. (2010). Aspecte generale privind utilizarea modelului Value at Risk
în analiza performanţelor portofoliilor de intrumente financiare, Simpozionul
Ştiinţific Internaţional „România între reglementări şi eşecul pieţelor”, Editura
Artifex, Bucureşti
Anchelache, C.; Anghel, M.G. (2014). Modelare economică. Concepte, teorie şi
studii ce caz, Editura Economică, Bucureşti
Codirlaşu, A. (2009). Utilizarea modelelor VAR pentru managementul
portofoliului, FIAR - The International Insurance-Reinsurance
Codirlaşu, A. (2008). Modele Value at Risk, www.dofin.ase.ro
Munteanu, G.I. (2008). Instrumente de identificare a riscurilor. Metodologia Value
at Risk, Simpozionul Internaţional de Statistică
70
71
The Investments Evolution in Romania
Prof. Dan CRUCERU PhD
Abstract
After 1990s period, the evolution of the economy during the has been
influenced by the structural changes arising as regards the resources forming and
utilization, on one side, and by the economic agents behaviour in connection with
the capital investments, on the other side. The investments achieved, mainly by the
beginning of this period, have been accomplished in the frame of a less favourable
business environment marked, during certain periods of time, by the production
decline, by the budgetary and payments balance deficit, by the high rates of the
inflation, by high interests for credits, by an exchange rate depreciating
continuously, by the lack of managerial exigency of the economic operators as well
as by the imperfections of the legislative and institutional framework.
Key words: evolution, investments, economic agents, balance deficit,
exchange rate.
The evolution of the economy during the after 1990n period has been
influenced by the structural changes arising as regards the resources forming and
utilization, on one side, and by the economic agents behaviour in connection with
the capital investments, on the other side. The investments achieved, mainly by the
beginning of this period, have been accomplished in the frame of a less favourable
business environment marked, during certain periods of time, by the production
decline, by the budgetary and payments balance deficit, by the high rates of the
inflation, by high interests for credits, by an exchange rate depreciating
continuously, by the lack of managerial exigency of the economic operators as well
as by the imperfections of the legislative and institutional framework.
On this ground, the investments volume recorded fluctuations from one
year to another; during the first years of transition, in the context of the
strengthening of the structural unbalances, both macroeconomic and sectorial, of
the decline of the production of goods and labour productivity, a strong decrease of
the investments has been recorded which, generally speaking, have been directed
towards modernizations of production and distribution capacities, mainly in the
frame of the private sector of the economy.
To the extent of developing the private sector, the private investors have
enlarge their sphere of activity, based on the setting up of the legislative and
institutional framework as well as on the strengthening of the investment effort.
72
The general juridical framework concerning the supporting steps from the
side of the Romanian State, meant to stimulate the investments, have been
regulated by the Emergency Ordinance of the Government no. 85/2008 concerning
the investments stimulation, along with the subsequent modifications and
completions.
„The investments stimulation in accordance with the provisions of the
present emergency ordinance is grounded on the following principles:
a) equal treatment - the non-discriminatory application of the criteria and
means for the granted facilities ;
b) transparency – bringing to the attention of all interested parties the
information referring to the procedure to follow for getting facilities for
investments;
c) efficiency in utilising the facilities – the application of criteria for
granting facilities for investments and for following up their accomplishment,
meant to reflect the advantages of economic nature of the investment projects,
taking into consideration, if the case is, the effects to the social domain, the
environment protection and the promotion of a durable economic development;
d) confidentiality – guaranteeing the protection of the information
concerning the intellectual property rights belonging to the investors as well as of
other data which might prejudice their legitimate interests;
e) eligibility depending on the source of the financing funds. “
The economic growth, started as from the year 2000, is due also to the relaunching of the investment process which contributed to the diminishing of the
unfavourable tendencies of the previous period as well as to the drawing into the
economic circuit of part of the available labour force, generating thus positive
macroeconomic effects1.
Comparatively with the year 2006, the year 2007 showed that the
investments achieved in the national economy amounted 68391.4 million lei,
increasing by 29.0 %. The investments materialized in new construction works
counted in 2007 for 31041.6 million lei (45.4 % of total, as against 44.5 % in the
year 2006), increasing by 31.3 % as against the year 2006.
The investments in equipment and conveyance means amounted 31488.4
million lei (representing 46.0 % of total, again against 47.6 % in the year 2006)
with an increase of 26.8% as against the previous year.
The year 2007 is recording 45867 finalized new dwellings, with 7689
dwellings more than in 2006. Most of the finalized dwellings have been achieved
out of private funds. These have represented 92.3% of the total finalized dwellings,
heir number being with 8905 bigger as against the year 2006.
1
Mădălina Gabriela ANGHEL – Bursa de valori Bucureşti – componentă fundamentală
a pieţei de capital, Simpozionul ştiinţific internaţional „Economia României şi perspectiva
globalizării”, Editura Artifex, Bucureşti, 2007, pg. 185 – 196, ISBN 978-973-7631-36-7 Revista Română de Statistică - Supliment nr. 10/2014
73
If to consider the spread over development regions, most of the dwellings
have been put into use in the regions: North-East (17.8% as against the total
country), Bucureşti-Ilfov (14.7%), South-East (14.6%), South-Muntenia (13.5%)
and North-West (13.1%).
By December 31st 2007, a number of 120570 dwellings were in various
stages of the execution of the construction works, out of which those achieved with
budgetary subsidies counted for 9.7%. Out of the total number of dwellings under
different stages of construction, 1.2% were finalized but not checked and signed
for, 37.7% were in the finishing stage, 31.1% in the stage of the structure execution
while for 30.0 % of the total the foundation works were started.
In the year 2008 the investments materialized in new construction works
counted for 43877.6 million lei (48.7 % of total, as against 45.4 % in the year
2007), showing an increase of 22.0 % comparatively with the year 2007.
The investment in equipment and conveyance means amounted 39209.5
million lei, increasing by 14.1% as comparatively with the year 2007.
The branches recording bigger volumes of investments are the following:
trade/services (transport, storage and communications); the wholesale and retail
commerce, repair of auto vehicles, motor cycles and personal belongings; real
estate transactions, renting and services activities carried out mainly to the
companies), industry and constructions.
In the year 2008 a number of 64414 dwellings have been finalized, with
17115 dwellings more as comparatively with the year 2007.
The majority of the finalized dwellings have been achieved out of private
funds. They have represented 93.1% of the total finalized dwellings, their number
being with 16955 bigger as comparatively with the year 2007.
have been put into use in the regions: North-West (20.9% as against the total
country), North-West (17.3%). Bucureşti-Ilfov (12.9%) and South-East (12.2%).
By December 31st 2008, a number of 143139 dwellings were in various
stages of the execution of the construction works, out of which those achieved with
budgetary subsidies counted for 7.4%. Out of the total number of dwellings under
different stages of construction, 1.2% were finalized but not checked and signed
for, 38.4% were in the finishing stage, 34.1% in the stage of the structure execution
while for 26.3 % of the total the foundation works were started.
counted for 33371, 3 million lei representing 53.4 % of total, as against 44.9 % in
the year 2008). The investment in equipment and conveyance means amounted
23352,4 million lei, decreasing from 46.8% to 37.4% as comparatively with the
year 2008.
6154 dwellings less as comparatively with the year 2008.
74
being with 5761 lower as comparatively with the year 2008. If to consider the
spread over development regions, most of the dwellings have been put into use in
the regions: North-West (19.8% as against the total country), North-East (18.7%),
South-East (13.4%), Bucureşti-Ilfov (11.3%) and Centre (10.6%).
trade/services (wholesale and retail commerce, repair of auto vehicles) and
industry. In the year 2010 the investments materialized in new construction works
counted for 28486,3 million lei representing 51.2% of total, as against 53,4% in the
year 2009. The investment in equipment and conveyance means amounted 21411,9
million lei, representing 38.4% of total, as against 37.4% in the year 2009.
industry and trade/services (wholesale and retail commerce, repair of auto
vehicles). In the year 2010 a number of 48812 dwellings have been finalized, with
13708 dwellings less as comparatively with the year 2009. The majority of the
finalized dwellings have been achieved out of private funds. They have represented
94.4% of the total finalized dwellings, their number being with 10678 lower as
comparatively with the year 2009. If to consider the spread over development
regions, most of the dwellings have been put into use in the regions: North-East
(19.1% as against the total country), North-West (15.8%), Sout5h-Muntenia
(14.8%), South-East (13.5%) and Bucureşti-Ilfov (13.2%).
counted for 31913,7 million lei representing 49,5% of total, as against 51,2% in the
year 2010. The investment in equipment and conveyance means amounted 26305,0
million lei, representing 40.8% of total, as against 38.4% in the year 2010.
industry and trade/services (wholesale and retail commerce, repair of auto
vehicles). In the year 2011 a number of 44456 dwellings have been finalized, with
4356 dwellings less as comparatively with the year 2010. The majority of the
finalized dwellings have been achieved out of private funds. They have represented
94.9% of the total finalized dwellings, their number being with 3896 lower as
comparatively with the year 2010.
have been put into use in the regions: North-East (20.5% as against the total
country), North-West (16.1%), South-Muntenia (14.9%), South-East (13.6%) and
Bucureşti-Ilfov (11.1%).
Table 1
The evolution of investments over the 2009-2012
2009
2010
2011
2012
The investments indices as against the
70,7
93 114,6
97,1
previous period
Source: www.insse.ro, data base TEMPO and press releases
75
In the year 2012, the total volume of the achieved net investments counted
for 89092.3 million lei, increasing by 1.45% as against the previous year. The most
significant evolution has been recorded in industry, where the increase recorde as
against the year 2011 counted for 7%. In 2012 the investments achieved in
industry have been by 1..10 higher as comparatively with the year 2009 and have
been directed with priority towards the branches of the manufacturing industry
(48.9% of the industry total), a sector which recorded a diminishing of almost 18%
as against the year 2009. As far as the extractive industry is concerned, the
investments in 2012 increased by 6% as against the year 2009. Although it is
obvious that the bigger weight is held by the services (41.7% in 2012), it is
significant to point out the fact that the investments structure in industry kept on
ameliorating during the analysed period. In the frame of the services sector,
significant investments have been achieved in activities concerning the wholesale
and retail commerce and repair of auto vehicles and motor cycles, transport and
storage services and real estate transactions.
The investments achieved in 2013 at the national economy level recorded
a decrease by 9.3% as against the year 2012. The investments in new construction
works diminished by 9.4% while the investments in equipment, including the
conveyance means as well, recorded a decrease of 13.1% as comparatively the year
2012.
The branches recording a higher volume of investments are: the industry,
the commerce and the services.
Figure 1. Structure of the investments at the level of the national economy
3945 dwellings less as comparatively with the year 2012.
being with 1563 lower as comparatively with the year 2012. If to consider the
spread over development regions2, most of the dwellings have been put into use in
2
Mădălina Gabriela ANGHEL – Utilizarea modelelor econometrice în analizele
economice, Simpozionul ştiinţific internaţional „Necesitatea reformei economico – sociale
76
the regions: North-East (19.1% as against the total country), South-East (15.4%),
South-Muntenia (14.0%), Bucureşti-Ilfov (13,2%), North-West (12.9%). The
steady diminishing of the budgetary sector investment capability, reaching a weight
of 8% only in 2012, keeps on being noticed. The credits weight is not of the kind to
generate concern (about 7%).
Fig. 2. The weight of the investments financing sources
Starting with the year 2010, after the decrease recorded during the period
2007-2009, the own-sources contribution to the quantum of the invested amounts
shows a continuous increase.
Fig. 3. The weight of own-sources for investments financing
However, the weight of the own-sources did not recovered the level
recorded in 2007.
a României în contextul crizei globale”, Editura Artifex, Bucureşti, 2010, pg. 145-151,
ISBN 978-973-7631-71-8 Revista Română de Statistică - Supliment nr. 10/2014
77
References
4/2014, pp. 115-128
2/2012, pp. 23-36, ISSN 0424 – 267 X
www.insse.ro, Tempo Database and press releases
78
Does Corporate Governance Affect Firm Liquidity?
Empirical Evidence from Romania
Floriniţa DUCA PhD Student
The Bucharest University of Economic Studies
[email protected]
Abstract
This paper examines the relation between corporate governance and
liquidity from roumanian firms. We construct a measure of corporate governance
based on publicly available information for each firm listed on the Bucharest Stock
Exchange over the 2006-2013 interval. Results of the study suggest a positive
relationship between the liquidity and the corporate governance.
Key words: Corporate governance; Firm liquidity; Firm size
J.E.L. Classification: C10; G10; G30
Introduction
Corporate governace is a the framework of rules and practices by which a
board of directors ensures accountability, fairness, and transparency in a company's
relationship with its all stakeholders (financiers, customers, management,
employees,
government,
and
the
community)
(http://www.businessdictionary.com/).
According to Andrei Shleifer from Harvard Business School and Robert
Vishny from the University of Chicago, “corporate governance deals with the ways
in which suppliers of finance to corporations assure themselves of getting a return
on their investment”( Shleifer and Vishny, 1997). Liquidity is the measure of the
extent to which a person or organization has cash to meet immediate and shortterm obligations, or assets that can be quickly converted to do this(
www.businessdictionary.com). In other words, liquidity is the relationship between
the cash which will be given to the company in a short time period and the cash
which the company needs (Talebi, 1997).
The solvency ratio measures the size of a company's after-tax income,
excluding noncash depreciation expenses, compared with the firm's total debt
obligations. It provides a measurement of how likely it is a company can continue
to meet its debt obligations(financial-dictionary.thefreedictionary.com).
Li et al. (2012) studied their paper examines the channel relationship of
liquidity, corporate governance, and firm valuation for Russian firms over the
period of 2005 to 2007. They tested the hypotheses that liquidity improves
corporate governance, and better corporate governance enhances firm value. They
formed the system of equations of liquidity measures (share turnover, market value
79
turnover and the Amihud liquidity ratio), the transparency and disclosure (T&D)
scores, and firm valuation (market value equity). Their results showed that liquidity
has a significant positive effect on corporate governance for Russian firms, which
consequently increases firm valuation. According to Gillan (2006) provides a
broad overview of these issues and recent work in the area. The authors review the
main prior research on the impact of corporate governance on liquidity and
examine how the investor protection affect stock returns and firm value.
Chung et al. (2010) investigate the empirical relation between corporate
governance and stock market liquidity. They find that firms with better corporate
governance have narrower spreads, higher market quality index, smaller price
impact of trades, and lower probability of information-based trading. They showed
that changes in our liquidity measures are significantly related to changes in the
governance index over time. These results suggest that firms may alleviate
information-based trading and improve stock market liquidity by adopting
corporate governance standards that mitigate informational asymmetries.
Data and Methodology
The aim of this study is to investigate the effect of corporate governance on
liquidity. The data were sourced from the Annual Reports and Accounts of the
random sample of 10 firms listed on the Bucharest Stock Exchange over the 20062013 interval. Analysis does not include the companies operating in financial
sector due to their different financial structures.
Measuring corporate governance
We construct an overall governance index for each romanian listed firm to
measure the quality of corporate governance based on disclosed governance-related
information in their annual financial reports.
We classify the governance related information into 4 groups: Access and
Content of the Information, board of directors, ownership structure, shareholders'
rights and committees. These 4 groups consist of 24 variables in total. The
construction of the index is straightforward, I first code the 24 questions as 1 or 0
depending on whether the firm has satisfactory corporate governance standards or
not. Each positive answer adds one point to the index, and the companies present a
quality of governance level that ranges, in theory, from 0 to 24.
Size
Size is considered a key factor that can influence the financial structure of
the firm. Firm size has been suggested to be an important variable related to the
leverage ratios of the firm. The variable Size of Firm is measured as logarithm of
total assets.
Leverage
As it can be seen in the literature, various definitions of leverage exist. All
these characterizations of leverage revolve around some form of debt ratio. The
definitions depend on whether market value or book values are used. In addition,
definitions also depend on whether short term debt, long-term debt or total debt is
used. Firms have several types of assets and liabilities and there can be further
80
adjustments made to the definition. Leverage: Represents the value of debt divided
by book value of total asset.
Liquidity
Firms prefer internal financing to external financing. Therefore, firms are
likely to create liquid reserves from retained earnings. If the liquid assets are
sufficient to finance the investments, firms will have no need to raise external
funds. Hence, liquidity is expected to be negatively related to leverage. Here we
use the current ratio (calculated as current assets over current liabilities) as a proxy
of liquidity. The relation between corporate governance and firm liquidity is
estimated using the fixed effect panel regression.
Our empirical model is specified as:
Liquidity = β0 + β1*CGI + β2*Size + β3*Leverage
Results and discussion
Descriptive analysis are presented in Table 1.
Table 1- Descriptive statistics of the variables in the study
Mean
Median
Maximum
Minimum
Std. Dev.
Lichiditate
4.800268
1.945631
29.17241
0.918033
5.803753
IGC
16.36667
17.00000
21.00000
9.000000
3.324112
Leverage
0.248003
0.163962
0.773369
0.013836
0.208896
Size
20.81282
20.15067
24.38117
17.49698
1.869654
Table 1 provides a summary of the descriptive statistics of the dependent
and explanatory variables. As shown in Table 1, average liquidity of the firms
listed in Bucharest Stock Exchange and reviewed in scope of the analysis is 4.80.
The mean leverage of the firms is 0.24 with a maximum of 0.77. The average
corporate governance index (CGI) is 16.36, with a standard deviation of 3.32.
Results of regression analysis
Table 2: Results of Regression Analysis
Dependent Variable: Lichiditate
Method: Panel Least Squares
Variable
IGC
Leverage
Size
C
R-squared
Adjusted R-squared
F-statistic
Coefficient
Std. Error
t-Statistic
0.4901
0.2275
2.1535
-17.1654
3.1586
-5.4344
-0.6360
0.3897
-1.6317
14.2730
7.0772
2.0167
0.3490
Mean dependent var
0.3141
S.D. dependent var
10.0099
Durbin-Watson stat
Prob.
0.0356
0.0000
0.1000
0.0485
4.8002
5.8037
0.7682
81
Prob(F-statistic)
0.00002
The results of estimating equation are reported in Table 2.The model
explains almost 34% of variation in liquidity, with significant F-statistic. Thus, we
can say that based on p-values, in our model for listed companies, corporate
governance and leverage is statistically significant, is 0.0356 and 0.000(sig. < 5%).
The index of corporate governance is positiv correlated with liquidity (0.49; Table
2) but it is statistically significant.
To test whether there is influence toward firm size to liquidity, t test is
used. Through the result from data processing, the value of t statistic obtained is
equal to -1.63, and the level of significance is 0.10 (sig.<10%). This shows that
there is significant effect between firm size and liquidity. Thus, is significantly and
negative at the 0.10 level. The results accepted any significant relationship between
leverage and liquidity. This suggests that leverage of all companies significantly
affects liquidity of firm. This indicates a high negative influence on liquidity.
Conclusion
Aim of this research was to explore the impact of corporate governance on
its liquidity. This research observed a 10 firms listed over the 2006-2013 interval at
the Bucharest Stock Exchange. Beside corporate governance variable the analysis
included some other variables such as leverage and size. This paper studies the
relation between corporate governance and firm liquidity. The positive relation
between corporate governance and liquidity relieves the concern that enhancing
corporate governance dampens liquidity(Bolton and Thadden, 1998).
References
Chung, K. H., Elder, J. & Kim, J.-C, 2010, „Corporate Governance and Liquidity”,
Journal of Financial & Quantitative Analysis, 45.
Bolton, P. and E. Thadden,1998, “Blocks, liquidity, and corporate control.” Journal
of Finance, 53.
Gillan, S. L., 2006, „Recent developments in corporate governance: an overview”,
Journal of Corporate Finance, 12.
Talebi M.,1997, „Recognizing the company’s liquidity management”, Financial
Reserch,Vol 11.
Wei-Xuan L, Chia-Sheng Chen C, Joseph J. French, 2012, „The relationship
between Liquidity,corporate governance,and firm valuation:Evidence from
Russia”, Emerging Markets Review, Vol 13.
Tang K., Wang C., 2011, „Corporate Governance and Firm Liquidity: Evidence
from the Chinese Stock Market”, Emerging Markets Finance and Trade,
Volume 47, Supplement 1.
82
The Autochtonous Investments and the Business
Environment
Abstract
The importance of the national, autochtonous capital, cannot be
underestimated, as maintaining over a long period a mixed structure of the
economy, by the coexistence of the private sector in the process of getting
established, exclusively represented by small and medium companies, with a state
or mixed sector at the level of the large economic units subject, at this turn, of
successive and difficult formulas of privatization, was not of the kind to concede, at
the overall national economy, that positive trend presumed by the reforme process.
Key words: capital, investment, production, population, trend
1. Autochthonous investments
So far, extended discussions were made about the mode in which the
foreign capital investments have been made in our country. Further on, we shall
approach some aspects concerning the drawing of the autochthonous investments.
At the beginning, the Romanian capital, the autochthonous one, was
insignificant because of lack of financial means and of the impossibility for certain
individuals or juridical persons to participate to projects, either independently or in
collaboration with outside commercial companies.
The former „social parts” (about 38 milliard lei at the level of the 1990,
namely about five milliard US dollars) passed automatically from the production
sphere (as financing source), to the cunsumption sphere.
This transfer has been achieved on the ground of lack of productive
activity and of stocks of products needed by the population, which had a double
negative effect: first of all, the funds meant to development diminished and,
secondly, a surplus of monetary mass has been generated, without cover in goods
and services at the level of prices of the year 1990.
The social parts existing in 1990 could have been transformed in shares,
making thus the embryo of the privatization in Romania1. Simultaneously, in this
1
Mădălina Gabriela ANGHEL – Aspecte generale privind produsele structurate în
România, International Symposium “Romania – Measures to Avoid the Failure of the
Markets”, Editura Artifex, 2011, pg. 73-79 Revista Română de Statistică - Supliment nr. 10/2014
83
way, the inflation in our country would have not been stimulated by the
unbalancing of the ratio between the reduced volume of goods and services, on one
side, and the excessively high monetary mass available with the population on
short term, at the respective moment, on the other side.
In this context, the legislation referring to the commercial companies,
although positive in its essence, couldn’t do but generate the framework for making
conspicuous the free initiative and the mechanisms of the market economy which,
however, in the absence of a real and substantial autochthonous capital, could not
generate far-reaching developments.
As the time elapsed and under the impact of certain steps of economic and
fiscal policy, the large economic units have been de-capitalized and depreciated so
that their privatization became, irrespectively the forecasted method, hard to
achieve or, at the best, achievable under non-efficient terms2.
In the privatization process, the issue to apply massively to credits cannot
be considered as the national currency is expensive; the real positive interests run
by the commercial banks are high while the investments are not in the position to
bring in incomes (profits) but within a future period.
It is important that the privatization proces to be finalized starts from the
real situation existing on the capital market of Romania now, after being accepted
into the European Union.
2. The business environment
Over the transition years, the business environment, although facing a lot
of difficulties (among which, the lack of a specific legislation in the field, which
characterized the first years, the various practices of state intervention in the
economy, the involvement of certain officials in the companies activity, outside
their current atributions), the business environment recorded a steady improvement
of the economic functioning and access to the market mechanisms. The last years
have been marked by some progresses among which to note: the setting up of the
unique office in the frame of the chambers of commerce and industry through
which, at the territorial level, not only that the duration of setting up and
authorizing of the new commercial companies has been shortened (from 90 days
to about 20 days) but also the decrease of the setting up taxes (by 40%) has been
achieved; the improvement of the legal and institutional framework concerning
the investors, which has been completed with the establishment of the Romanian
Agency for Foreign Investments; the initiation and implementation of a number of
legislative steps meant to support the small and medium companies, out of which
2
Anghelache, Gabriela Victoria, Mădălina Gabriela ANGHEL – Efectele crizei
economico-financiare asupra pieţei de capital din ţara noastră, Simpozionul Ştiinţific
Internaţional „Efecte şi soluţii prentru criza economico-financiară”, Editura Artifex,
Bucureşti, 2009, pg. 174 – 177, ISBN 978-973-7631-63-3 84
the most significant consists of the decrease to zero of the tax on profit in case this
is re-invested.
For the foreign investors coming to Romania, a series of incentives have
been secured, meant to contribute to the improvement of the economic
development of the country, mainly to the speeding up of the industrialization of
the un-favoured regions and to the development of the small and medium
companies3.
At the end of the year 2013, over 124 thousand companies were enlisted
with the National Office of the Commerce Register, as entries during the year.
Most of the recorded companies had as main object of activity the
commerce – wholesale or retail – among the total number of active companies.
The commercial companies running productive activities, of industrial kind, are to
be found within the following domains: foodstuff and beverage industry, light
industry, wood processing, metallic constructions and metal products, furniture
production, printing houses, polygraph and reproduction of the recordings on
supports.
From the point of view of the size of the commercial companies, the
biggest weight has been held by the small and medium companies, with up to 249
employees.
Acknowledgement
This work was cofinanced from the European Social Fund through Sectoral
Operational Programme Human Resources Development 2007- 2013, project
number POSDRU/159/1.5/S/134197 „Performance and excellence in doctoral and
postdoctoral research in Romanian economics science domain”
References
4/2014, pp. 115-128
3
Mihai Bădulescu, Manole Alexandru, „Analiza datelor multidimensionale pe baza SSRS”,
Revista Română de Statistică, Bucureşti, martie 2008, cod ISSN 1018-046X Revista Română de Statistică - Supliment nr. 10/2014
85
2/2012, pp. 23-36, ISSN 0424 – 267 X
86
On Motivation and Motivation
Prof. Mircea UDRESCU PhD
Abstract
Economic motivations were a big influence on consumer behavior
motivation. In this context, it is considered that the general motives which give
motivation to purchase content can be structured into rational and emotional
motives, the motives innate and acquired motives, all gaining an individual or
group event. The study of consumer behavior, with general motivations, attention
increasingly larger granted special incentives, consisting of assertiveness feeling
(emerging desire for a product); feeling of self-gratification (to achieve and
maintain a certain standard); sense of appreciation and affection (to impress,
correlation own impressions suggested aspects of product); creative spirit (in
children, the passion, the choice of objects that can be converted); feeling of origin
(for consumer products originated remember that arouse curiosity or nostalgia)
etc. Motivation to purchase thus becomes motivation of consumer behavior and
motivation of the design and the production.
Key words: motivation, motivation, customer, management, commerce,
marketing, interest, satisfaction
The two words - motivation and motivation - were formed by derivation
from the word reason, which has the meaning of cause, reason, cause of action, an
action that pushes stimulus or action causes a mobile. Noun reason is closely
correlated with the verb to motivate, that show why an action of a fact, to bring
explanations, arguments in favor of action, from which nouns formed motivation,
motivate action and outcome and noun motivation, reasons or motives fully
conscious or not, that causes someone to perform a particular action or to work
towards certain goals1.
The psychological motivation as a state that characterizes human behavior
is an intellectual and moral significance approach through which the person relates
to his or any other reasons. It is considered that there is a motivation project that
involves anticipating probable grounds to base their own behavior and
interpersonal relationships in this way preparing expanding conscious control of
the present situation in the future, and retrospective reasoning that requires
1
DEX Explanatory Dictionary of the Romanian Language, Publishing House, Bucharest,
1975, p . 571
87
explanation and the justification for acts already committed, for the reasons which
have led, thus aiming revaluation previous behavior 2.
Those who have dealt with the speculative thought they saw all the
motivation factors it determines the individual to perform certain acts or to work
towards certain goals., A correlation of these factors in terms of internal
psychological dynamics. It causes a certain tension that persists to achieve the goal
or until a other motives much stronger. Motivation is conditional necessities.
Therefore, the people, the motivations are very different from those of animals,
reflecting the material and spiritual necessities realized in the well-regulated social
relations. Motivation factors can be both conscious and unconscious, but man is
aware of specific reasons which I orient behavior towards certain actions related to
the convictions of the person stable3.
As such, the motivation appears as a process by which an action is
prepared, it is declared, is triggered and sustained energy, a way to justify the
action, a systematization of the reasons that led to a claim for a particular purpose.
Motivation is conscious action to justify a certain motivation or make someone
accept or embrace a certain motivation. Active necessities, requirements or inner
urges, impulses, etc. are reasons the trigger individual actions ; they are reasons
that justify or argue subjects and own attitudes or actions of others. Within their
emotional reasons expressed by tensions, tendencies and desires that maintain the
energy and directs the actions of individuals. In general, we can say that every
human action is based on a reason that is justified by a need of. Fulfill the role of
human instincts biological reasons, but with these, man made and accepted for
reasons of social, moral, cultural, etc. Thus, learning the rules of social life
becomes grounds of social action aimed at schools, training, aesthetic band, career
path, attitude towards consumption etc. Therefore, in various situations, man is
assaulted by a lot of needs, for reasons, which means prioritizing actions and
enhance the grounds. To act knowingly and fully in line with the moral values of
society.
Motivation, in its widest sense, is considered an inner state that mobilizes
the body for a specific purpose that customizes a general context rather complex.
Any body has the basic law of existence and development of biological
conservation and restoration and ongoing maintenance of a fair balance in
continuous exchange with the environment. Therefore, as soon as it triggers a
shortage of food, air, moisture, heat, etc., that endanger the well being and integrity
of the body, fires warning signals designed to return to normal acceptable
condition. In humans, alarm mechanisms are fixed phylogenetic nervous system,
2
Paul Smith Neveanu, Dictionary of Psychology, Albatros Publishing House, Bucharest,
1978, p . 468
3
Collectively Glossary philosophical Political Publishing House, Bucharest, 1973, p.385386
88
the instincts, the most common being : self-preservation instinct of defense, sex
drive, etc. Every instinct manifests itself in two major components, one energy, and
other enforceable by execution.
From a psychological perspective, the energy component, tensional side of
instinct, it appears necessary, the needful. Along with necessities instinctive
develops a lot of other needs, called necessities acquired as a result of long social
life. As an expression of needs, necessities creates anxiety, restlessness, tension,
tension etc. Under and by virtue of necessity, as internal impulse is conducted all
human actions, only necessity satisfaction leading to organic rebalance. When
necessity is perceived as such, restlessness and tension is acknowledged and
developed so that triggers action, justified by reasons.
The reason is awareness necessity puts man in motion. It is an internal
issue that answers the question : Why ? Reasons explain psychologically
necessities and human actions, but not always confused with the protesters. The
goal is achieved by actions, but actions have their own motivations. For example, a
consumer can determine the purpose to buy a watch, the motivations of its being
different from case to case : the desire to make a gift, need to know what time it is,
the need to take medication at precise hours, need to be recognized as such by a
particular reference group etc.
Whenever reasons correlates to the purposes, subject unveils an interest, a
concern directed to obtain that which is necessary, helpful, pleasant, helpful, gives
satisfaction, he cultivates pride ensures victory makes gain etc. Therefore, people
act daily mobilized a lot of interest.
Among them, special attention is given to economic interests, understood "
as manifestations of human needs become conscious motives, which determine
individual behaviors to achieve economic performance for acquiring goods needful
to meet the needs. They are an element of the composition of the economic
mechanism, the cause of immediate and vigorous stimulation of human actions
directed towards achieving goals. Viewed as a whole and in their interdependence,
economic interests form a complex system that includes personal interests (
manifested in each individual and in relation to a particular need of his), group (
manifested in the form of an ad hoc social group or institutionalized and necessities
linked to the level specified ) or general (ie residents of an area, country or the
planet ) ; Private and public interests ; current interests, prospective permanent
periodic accidental passive, active, etc. An individual or that occurs in a way or
another, the various types of vehicle of interest. Their harmonization within social
groups, regions or countries can be provided through a democratic framework of
achievement. Meeting the economic interests can accomplish both by considering
and meeting all types of interests, and by providing personal interests priority over
the group or general "4
4
Nita Dobrotă, Dictionary of Economics, Economic Publishing House, Bucharest, 1999, p .
251-252
89
From the above it follows that each individual has mastered the basic
necessities, biogenetic, and the secondary necessities, acquired, which is expressed
by the interests, beliefs and attitudes, all revolving around social trinom reason motivation - motivation. As such, we support the views they consider that the
reasons " have a strong multifunctional, being built between biological and social,
between internal impulses and knowledge between subjective necessity and value
as a reference system between the relationship of objects and links to people etc.
and therefore can not be reduced to any one of the factors that determine and
influence.. "5
In general, the attitude is reporting how a certain aspect of reality, a
reaction, a gesture, a certain position on something. It occurs both as inner speech,
mental, and the outer expression as behavioral form. Of behavior based on a need
of a reason etc. Comprise an interest or belief 6.
Seeing the motivation an expression of reasons, the overall level of
savings, and motivation shape capture behavior of firms and individuals daily
economic actors, JM Keynes explained the occurrence of a crisis in the way it
translates into reality precautionary motivation, motivation and motivation came
speculation. The precautionary reasons, gave explanations about economic actors
tend to keep the money bigger or smaller to meet random phenomena arising from
changes in prices, changes in tastes, changes in periods of production and transport
etc. Motivation explains the preference for liquidity speculation because based on
the idea that everyone has a different opinion to the dominant view of the interest
rate change. Anyone looking to have money to be able to use to get an advantage,
gain from the change which he anticipates interest developments. Motivation
income is justified by the gap of time between charging or collection of income and
spending its time for specific purposes by their owners. The greater the gap, the
greater must be the money available, and vice versa. The conclusion was that the
great economist, so long as those savings are generated by real economic
incentives are not possible major crisis, but in situations where economies are
moving toward speculative risk of major economic crisis greatly increase 7.7
In conclusion, economic motivations were a big influence on consumer
behavior motivation. In this context, it is considered that the general motives which
give motivation to purchase content can be structured into rational and emotional
5
Cătoiu, I., Teodorescu, N., Comportamentul consumatorului, Uranus Publishing House,
Bucharest, 2004, p . 19
6
Neveanu, P.P., Introducere în psihologia militară, Military Publishing House, Bucharest,
1970, p . 253-255
7
John Maynard Keynes, The General Theory of Employment, Interest and Money, Public
Publishing, Bucharest, 2009, p.197-311
90
motives, the motives innate and acquired motives, all gaining an individual or
group event. The study of consumer behavior, with general motivations, attention
increasingly larger granted special incentives, consisting of assertiveness feeling (
emerging desire for a product ) ; feeling of self-gratification ( to achieve and
maintain a certain standard ) ; sense of appreciation and affection ( to impress,
correlation own impressions suggested aspects of product) ; creative spirit (in
children, the passion, the choice of objects that can be converted ) ; feeling of
origin ( for consumer products originated remember that arouse curiosity or
nostalgia that ) etc. Motivation purchase thus becomes motivation of consumer
behavior and motivation of the design and the production.
References
Cătoiu, I., Teodorescu, N., Comportamentul consumatorului, Uranus Publishing
House, Bucharest, 2004
Dobrotă, N., Dictionary of Economics, Economic Publishing House, Bucharest,
1999
Keynes, J.M., The General Theory of Employment, Interest and Money, Publishing
Public Bucharest, 2009
Neveanu, P.P., Dictionary of Psychology, Albatross Publishing House, Bucharest,
1978
Udrescu, M., Nastase, D., Study on Consumer’s Behavior, Artifex Publishing,
Bucharest, 2009
91
General Aspects Concerning the Development of the
North-West Region of Romania
Assoc. prof. Alexandru MANOLE, PhD.
Assoc. prof. Aurelian DIACONU, PhD.
Abstract
By this study we aimed to emphasize the main specific elements of the
North-West Region, known also as North Transylvania, as well as to accomplish a
study concerning the evolution of the main indicators characterizing the activity of
this zone of the country over the period 2007-2013. In this respect, we have
submitted and analysed the region from the point of view of the geographic
position, the available resources, administrative organization, demographic
structure, the structure of the economic agents depending on the field in which they
are running their activity, the touristic potential as well as the importance of
drawing non-reimbursable European funds for the economic activity of the region.
Key words: regional development, forms of relief, resources, demographic
structure, landed fund, touristic units.
Introduction
The North-West Region area is representing 14.3% of the entire national
territory. The region includes the districts Bihor, Bistriţa-Năsăud, Cluj, Maramureş,
Satu-Mare and Sălaj.
From the geographic point of view, the region is located in the north-west
part of Romania. The neighborhood of the region are the following: Ukraine at
north; the North-East Region at eastl; the Centre Region at south and Hungary at
west.
By December 31st, 2013, the six districts which are forming the region
included 15 municipalities, 28 towns, 403 communes and 1800 villages. The
significant municipalities for the region are Cluj-Napoca, Oradea, Bistriţa, BaiaMare, Satu-Mare and Zalău, as district residences. As important towns on the
administrative territory of the region, we refer Turda, Dej, Câmpia Turzii and
Gherla (from Cluj), Sighetu Marmaţiei from Maramureş, Carei (District Satu-
92
Mare), Marghita, Beiuş and Salonta from Bihor, Năsăud, Beclean and Sângeorz –
Băi (district Bistriţa-Năsăud).
Specific features of the North-West Region
The region relief and its geographic position is generating a natural frame
in form of an amphitheatre which limits are marked by the Oriental Carpathians (at
north-east), the Apuseni Mountains (at south-west), the Someşan Plateau, the
Western Hills and the Western Plain.
Thus, in the Bihor District, the main forms of relief are the Western Plain,
the Westerns Hills, the Plopișului Mountains, the Pădurea Craiului Mountains, the
Bihor Mountains and, partially, Vlădeasa Mountains.
The alpine zone of the District Bistriţa Năsăud is including a part of the
Oriental Carpathians arch. Two thirds of the district surface are occupied by hills,
located in the centre and west part of the administrative territory. The
hydrographical network is basically represented by the river Someşul Mare, its
affluent rivers as well as the glacier lakes located in the Rodnei and Călimani
Mountains.
In the district Cluj, the hilly area is covering approximately two thirds of
the surface, being constituted by Someşan Plateau, part of the Transylvanian Plain
and the Feleacului Massif, while a third of the territory belongs to the alpine relief.
In the alpine zone, structures belonging the Mountains Apuseni, Gilăului and
Trascăului are to be met.
The predominant form of relief in the district Maramureş is the mountain
which counts for 43% of the territory, being represented by the Mountains Rodnei,
Gutâiului and Maramureşului. The hilly zone represents 30% of the district surface
the remaining part going to the depressions.
The relief of the district Satu-Mare is diversified, the main form of relief
from the surface point of view being the plain which makes part of the Panonică
Depression (63% of the territory) and is located in the west and south-east of the
district. The alpine zone, including Oaşului Mountains and part of the Gutâiului
Mountains, is located in the north –east part of the district.
In the district, the hilly and alpine forms of relief are holding the bigger
weight as occupied. The hilly zone is part of the Someşan Plateau and as main
reference points of the alpine zone, we can consider the peaks Meseşului and
Plopişului.
The hydrographical network of the North-West Region includes several
important rivers (Crişul, Someşul, Crasna, Iza etc.), as well as a series of lakes,
both natural and artificial, glacial as well, which contributes to the touristic
attractiveness of the adjacent zones.
The North-West Region is rich in natural resources. In this respect, to note
in this respect the carboniferous resources (lignite), bauxite, salt, gold and silver
bearing ores, raw and building materials. We cannot neglect the forestry resources,
particularly rich in the area (forests and forestry vegetation terrains), characterized
93
by a surface of the forestry fund counting for 990.6 thousand hectares by
31.12.2013. The structure by districts of the forestry funds underlines the fact that
the district Maramureş holds the biggest weight (259.1 thousand ha., respectively
26.16%),followed by Bihor (209,2 thousand ha., meaning a weight of 21.12%),
Bistriţa-Năsăud (192.5 thousand ha., respectively 19.43%), Cluj (161.3 thousand
ha., namely 16.,28%), Sălaj (9.68% for a surface of 95.9 thousand ha.) and SatuMare (72.6 thousand ha., respectively 7.33%).
The archeological discoveries achieved on the region territory revealed
remains of very ancient human establishments, the most far away back in time
being dated as belonging to the Paleolithic period, this early human civilization
taking the advantage of a favourable environment for development offered by the
relief and clime of the respective period.
The Someş and Transylvania Plains is representing the richest source of
archeological resources attesting the human presence on these parts, since the very
ancient times. In this respect, we have to note the discoveries from the Satu Mare
(human establishments from the period of the years 6000 a.Ch.), vestiges
associated to the polished stone epoch from Oradea, Secuieni, Sândreni.
The outcomes of the archeological diggings on the territory of the district
Cluj (locality Gura Baciului) are proving the man’s existence during the period of
the years 5000 a.Ch.
During the antiquity period, the daces have mastered these areas until the
Roman conquest. The present territory of the district Maramureş was not occupied
by the Romans but remained as a part of the free Daces state.
The Roman civilization put its imprint on the places, through developing
certain economic activities and setting up new establishments, among the most
significant being Potaissa (the present Turda), Porolissum and Napoca (presently,
Cluj-Napoca). The Roman Empire incorporated the territories of the region for a
period of over two centuries, up to the Aurelian retreat. Subsequently, the
geographic space of the region remained on the way of the big migrations.
By 31.12.2013, the permanent population of the region counted for
2,704,348 inhabitants, which represents 12.72% of the stable population of
Romania. The demographic structure emphasizes the fact that 1,433,408 persons
(53.01%) had an urban domicile, while 1,270,940 persons lived in the rural
environment (a weight of 46.99%).
Analysing the distribution by districts, it results that the bigger number of
inhabitants are located in the district Cluj (25.67%, respectively 694,088 persons),
followed by Bihor (590,068 inhabitants, namely 21.82%), Maramureş (a weight of
18.70% and 505,788 inhabitants), Satu-Mare (360,969 inhabitants, respectively
13.35%), Bistriţa – Năsăud and Sălaj (315,608, respectively 237,797 inhabitants).
The population evolution during the period 2007-2013 is submitted by the table
below:
94
Table no. 1. The stable population at January 1st, over the period 2008-2014
District
Bihor
BistriţaNăsăud
Cluj
2008
2,724,176
2009
2,721,468
2010
2,719,719
2011
2,717,532
2012
2,712,188
2013
2,707,926
2014
2,704,348
593,897
593,606
592,957
593,041
592,046
591,283
590,068
316,869
317,346
317,316
316,947
316,480
315,734
315,638
Maramureş
692,021
690,590
692,339
694,136
692,819
693,419
694,088
Satu Mare
512,560
511,946
511,093
509,660
508,773
507,139
505,788
Sălaj
365,975
365,508
364,597
363,488
362,536
361,758
360,969
Bihor
242,854
242,472
241,417
240,260
239,534
238,593
237,797
The population density records the highest value in district Cluj (104
inh./km2), the lowest value of this indicators being associated to the district
Bistriţa-Năsăud (58.94 inh./km2), which is indicating a significant disparity
between the component districts of the region.
The economic activities of the North-West Region describe the region as
holding a high potential of development and is based on the natural resources as
well as on the resources drawn from other geographic regions.
In 2012, there have been 225 companies acting in the extractive industry,
7,585 companies in the manufacturing industry, respectively 143 companies
running activities of production and distribution of electric and thermic energy,
gas, hot water and conditioned air functioning on the region territory.
The evolution of the number of companies during the period 2007-2012 is
submitted in the following table:
Table no. 2. Number of companies by activities in industry,
during the period 2008-2012
Industrial branch
2008
2009
2010
2011
Extractive industry
221
281
244
231
225
9,316
8,697
7,806
7,340
7,585
65
83
147
122
143
235
268
286
295
331
Manufacturing industry
Production and supply of electric and
thermic energy, gas, hor water and
conditioned air.
Water distribution, sanitation, residues
management, decontamination activities
2012
The contribution of the non-reimbursable European funds to the economic
activity of the region is definitely not to be under-estimated, the situation of the
95
projects contracted under the POSDRU programme during the period 2007-2013
being submitted by the table below:
Table no. 3. Contracted projects during the period 2007-2013
Major domains of
intervention
AP 3 Increasing the
adaptability of the
workers and
companies
AP 5 Promoting
active occupying
steps
AP 6 Promoting
social inclusion
TOTAL
Total
Reimbursements paid
during 20072013
Payments (total
payments during
2007-2013)
Total prefinancing paid
during 20072013
175,127,064.29
128,453,648.97
37,130,845.29
91,322,803.68
224,230,830.23
224,230,830.23
224,230,830.23
224,230,830.23
204,100,119.50
142,037,202.04
21,686,473.61
55,492,875.49
454,950,238.77
3,328,935.93
Contracted
value up to
31.12.2013
603,458,014.02
454,950,238.77
Source: The Activity Report for the year 2013, OIPOSDRU the North-West
Region
http://www.runv.ro/doc/Raport_activitate_2013.pdf
By December 31st, 2013, a number of 96,767 juridical persons were in
function, most of them on the territory of the Cluj (37.53%), followed by Bihor
(slightly over a quarter), Maramureș (13.96%), the fewest one being recorded in
the district Sălaj (5.81%).
By the end of the year 2013, the landed fund of the North-West Region
counted for a surface of 3,416,406 ha, off which 78.02% were private property.
The biggest weight is held by the district Bihor, while the smallest surface of the
landed fund is associated with the district i Sălaj. Out of the total landed fund, the
agricultural surface holds 2,067,045 ha, respectively 60.51%, the arable surface
counts for 1,022,379 ha, while 1,032,339 ha were forests and other forestry
vegetation. The communication ways and railways occupied 1.68%, respectively
57,454 ha.
In the structure of the arable terrains by districts, the largest surface is
located on the territory of the district (30.21%). The district Cluj holds the largest
surface of pastures, slightly over a quarter of the region total, as well as the second
one, as size, surface of the terrains of hayfields type. The districts Bistrița Năsăud
and Satu-Mare are the most important from the point of view of the orchards and
fruit-growing nurseries.
In the agricultural year 2013, the cereals production of the region counted
for 1,779,269 tons, representing 8.51% of the national production. The production
of wheat and rye reached the level of 458,231 tons, 112,.949 tons barley and tworow barley have been recorded, 71,534 tons oat, 1,094,982 tons grain corn. As far
96
as the vegetable culture is concerned, a production of 352,539 tons has been
recorded, respectively 8.9% of the crop recorded at the level of the entire country.
The districts Cluj and Satu-Mare contributed significantly to the vegetable
production of the region, with 25.87%, respectively 25.14%, in fact over half of the
crop has been achieved on the territory of the two districts. The fruit cultures of the
North-West Region led to the achievement of a total crop of 272,248 tons,
respectively 20.94% of the national production. The best results for this sector of
the agriculture have been recorded by the districts Bistriţa-Năsăud and Maramureş.
The production of fruit by districts has been balanced, except the district Cluj with
a contribution of 7.25% to the region outcomes.
The evolution of the main indicators of the agricultural production during
the period 2007-2013 is described in the table below:
Table no. 4. The evolution of the agricultural production in the North-West
Region during the period 2007-2013
District
Bihor
BistriţaNăsăud
Cluj
Year
2007
Year
2008
Year
2009
Year
2010
Year
2011
Year
2012
Year
2013
557,861
750,974
386,350
701,869
717,510
449,927
700,492
86,754
102,156
98,431
94,118
117,792
71,184
84,630
161,811
181,080
170,664
196,537
238,858
156,457
209,667
Maramureş
74,996
89,480
81,844
77,710
89,423
65,242
88,716
Satu Mare
347,864
359,074
339,280
448,630
418,350
339,317
570,603
Sălaj
111,683
148,038
87,916
87,205
110,535
79,736
125,161
Among the activities employing a large part of the population of this region
we have to point out those referring to the wood, wool and clay processing, which
products are well known not only in the country but abroad as well. The wooden
churches, the Maramureș sculptured wooden gates, the woollen blankets, ceramics
from the commune Vama etc., are famous.
In 2013, in the frame of the region there were over 1,000 educational units
at all the education levels. Out of these units, 187 are meant to the pre-school
education, 542 units are offering primary and gymnasia education, 262 secondary
education cycle 2; the classes of these units have been attended by a number of
344,433 pupils. The national system of high education is represented by prestigious
universities such as Babeş-Bolyai University and the Technical University from
Cluj- Napoca, the Agricultural Sciences and Veterinary Medicine University from
Cluj-Napoca, the Visual Arts Academy, the Music Academy and „Bogdan Vodă”
University from Cluj – Napoca, the University from Oradea, as well as a
significant number of sections and faculties of these universities or other
97
universities located in other regions. The number of students recorded in 2013
counted for 70436 persons.
In 2013, the didactic personnel from the pre-school education counted a
number of 5,746 persons. 25.708 didactic staff were employed by the preuniversity education system while the didactic university body included a number
of 5,328 persons. The cultural units network comprises theaters and other types of
units carrying out cultural activities, among which: the National Theatre, the
Romanian State Opera House, the State Philharmonic, all of them from ClujNapoca, the Dramatic Theatre form the municipality Turda, the North Theatre and
the Philharmonic „Dinu Lipatti" from Satu Mare, the Theatre and the Philharmonic
from Oradea and a significant number of professional and amateurish assemblies,
territorial studios of radio and television etc.
In 2013, within the districts of this macro-region, there were 1,611 libraries
out of them a number of 343 being public libraries, 86 museums and public
collections. The sanitary system included in 2013 a number of 74 sanitary units,
from which 24 were private property. The medical personnel counted 7,728
doctors, 2,005 running their activity in the private system. Meantime, all over the
region there were 1,570 family physicians registered.
The tourism of the region is developed mainly in the districts Bihor (the
resorts Felix, 1 Mai, Stâna de Vale and Tinca), Ocna Şugatag from the district
Maramureş and Bizuşa from the din district Sălaj, the resort Sângiorz-Băi from the
district Bistriţa-Năsăud, which provide balneary treatments as well, along with the
resorts such as Borşa and Izvoarele from the din district Maramureş and a number
of others.
The touristic accommodation capacity recorded for the year 2013
amounted a number of 30,029 places. The evolution of the accommodation
capacity by districts is submitted in the following table:
Table no. 5. The accommodation capacity in the districts of the North-West
Region, for the period 2007-2013
District
2007
2008
2009
2010
2011
2012
2013
Bihor
10,126
9,984 9,746
9,152
9,718 10,284 10,071
BistriţaNăsăud
2,730
2,728 2,689
2,626
2,752
3,101
3,105
Cluj
7,070
6,598 7,352
6,960
7,760
8,925
8,215
Maramureş
3,635
3,995 4,207
4,368
4,629
4,730
4,805
Satu Mare
2,415
2,425 2,629
1,616
2,091
1,961
2,110
Sălaj
829
754 1,263
1,381
1,509
1,686
1,723
98
To the region beauties a significant number of wooden churches and other
wooden constructions – gates, house – have to be added as they are typical for
Maramureşului and other alpine zones and attract tourists from the country and
from abroad.
The touristic activities are carried on also within other zones attractive
from the point of view of the existing objectives, such as the caves „Urşilor”,
„Meziad” and „Vântului” from the district Bihor, the Happy Cemetery from the
commune Săpânţa and the “Sorrow Memorial” Museum from Sighetu Marmaţiei,
the Mineralogy Museum from the district Maramureş, the „Sâmbra Oilor” chalet,
the Călineşti-Oaş lake, the Daces Reservation from the commune Medieşul Aurit
from the district Satu Mare and many other zones of the Apuseni Mountains, the
Maramureşului Mountains and Gutâi Mountains, with valleys and narrow straits
offering natural landscapes of a particular beauty.
Conclusions
The North-West Region is one of the eight regions of development of the
country, representing 14.32% of the country surface, being created by the voluntary
association of the local public administrations. It must be pointed out that it is not
an administrative-territorial unit and has not juridical personality. Out of the
development regions of Romania, this one is the most attractive from economic
point of view, after Bucureşti-Ilfov Region, in its frame being included cities which
represent real poles of economic development as well a particular historic and
cultural patrimony (Cluj-Napoca, Oradea, Baia Mare, Bistriţa etc). The North-West
Region benefits of the fame of being one of the most picturesque zones in
Romania, starting from the particular charm of Apuseni Mountains, up to the
unique ethnographic zones from this part of Europe.
References
crizei” , Editura Economică, Bucureşti
www.apmmm.anpm.ro
www.prefecturabn.ro
www.runv.ro
www.insse.ro, TEMPO database, press releases
99
100
New Concepts and Successful Entrepreneurial
Models
Associate Professor Sorin Gabriel GRESOI PhD
Abstract
To increase the chances of success for a business, the entrepreneur must
carefully plan the activity. The most used tool for business planning is the business
plan. Because a business plan is a comprehensive document, which requires much
time for writing it and for that the sheer volume of information and details can
destroy the entrepreneur's attention on the truly important things. Alexander
Osterwalder and Yves Pigneur designed a simpler. more concise planning tool
namely business model Canvas.
Key words: business planning, business plan, business model Canvas.
1. The importance of business planning
In order for a business to make ends meet on the market it is important that
every employee in the company to know exactly what to do, what are the
objectives that need to be performed. This may be done by means planning.1
Planning is the process of identifying, fixing, blending and logical ordering
of objectives, tasks required, and of the means available for achieving the intended
purpose.2 This is considered as the basic function of management of any activity.
The importance of business planning has been debated over time of the
academic community, the latter being divided into two sides. A part of the business
planning argue that researchers may hamper the company's expansion because it
will only develop as planned. At the same time they claim that planning introduces
a rigidity in the management, thus influencing the ability of adaptation to market
conditions.3
1
http://ebooks.unibuc.ro/StiinteADM/manageinent/3.htm 2
http://www.mpt.upt.ro/doc/curs/gp/Bazele Managementului/Functia de planificare
cap2.pdf 3
Garonne. C., Business planning, idea change, flexibility and performance: the best o f
both worlds?,Frontiers of Entrepreneurship Research, Vol. 31, nr. 12, 2011,
http://digitalknowledge.babson.edu/fer/vol31/iss 12/18/, accesat pe data de 17.04.2014 Revista Română de Statistică - Supliment nr. 10/2014
101
Although some consider that when you start a business it is not necessary4
that it is fruitless to even make a schedule5, most are of the opinion that when you
plan your business chances of success are higher as resources are used more
efficiently, the decisions are taken more quickly.6
Planning is used by organizations for7:
● setting objectives;
● efficiency of the activity;
● reducerea costurilor;
● reduce risks;
● decisions;
● promoting innovative ideas;
● promote teamwork;
● establish control measures.
The main role of planning is to help the company to establish objectives
and the steps you must follow to achieve them.
All small and large organizations have limited resources. With the help of
planning these limited resources are allocated in an effective way by helping to
achieve the objectives proposed. Organizations that do not plan activities are not
effective, since chances of success much lower.8
The planning is done for the future and the future is always uncertain. For
this reason when it planned activity must be taken into account and the risks to
which the company is vulnerable. The planning encourages the use of scenarios
„what – if”.9
By planning to obtain the necessary information to top management. This
information is used in making effective decisions regarding the allocation of
resources that will enable the achievement of their objectives proposed.
It goes without saying that the planning are selected through the best
choice of action. It goes without saying that the planning are selected through the
best choice of action. The process of uncovering the best variations lead to the birth
of innovative ideas and creative.
4
http://www.quiicksprout.com/2009/12/15/whv-vou-shouldnt-write-a-business-plan/ http://www.forbes.com/sites/actiontrumpsevervthing/2013/08/14/why-business-plans-area-waste-of-time/ 6
Ciumara, T., Importance o f business planning in an environment lacking economic
predictability, http://www.ipe.ro/RePEc/vls/vls pdf/voll 4i3p147-151.pdf., accesat pe data
de 17.04.2014 7
http://www.vourarticlelibrarv.com/planning/what-is-the-importance-of-planning-inmanagement/903/ 8
http://smallbusiness.chron.com/importance-planning-organization-l 137.html
9
http://smallbusiness.chron.com/importance-planning-organization-l 137.html 5
102
Activity planning must not only be done by the manager but must involve
as many employees. Once objectives have been established it can perform and
control over their fulfilment.
2. Business Plan
The most used tool for business planning is the business plan. It is intended
to demonstrate that the business is viable, that is funded and designed to guide the
contractor operating the business.10
The business plan is a written document in which the entrepreneur has
crystallized the idea of describing your product/service offer, market, customers,
suppliers as they will attract customers, competitive advantages, resources and
business application skills, as well as the feasibility study of the business.
This tool provides an overview of the company and the external
environment in which it operates. It is a tool both for internal and external use. The
usefulness of the organization relates to its use for business planning, while,
externally, the business plan is used for communication with the external
environment and potential investors or specifically with suppliers.
In order for a business plan to be useful for entrepreneurs, it must be
simple, clear, realistic, easy to follow, SMART objectives contain and allow
periodic review.11
The business plan has 4 functions namely::
● development of crystallization and il business an idea;
● evaluation of a new business ideas;
● to obtain financing;
● control.
2.1 Advantages of a business plan
Like any business plan tool has both advantages and disadvantages.The
main advantages of the business plan are:
● help entrepreneurs clarify their idea and to determine whether or not to invest;
● helps to avoid errors caused by lack of information about the market,
competitors or clients;
● assists in obtaining external funding;
● helps establish as accurately as possible the investment necessary for the
implementation of the idea;
● helps develop planning skills of the entrepreneur;
● "forcing" the entrepreneur to be as realistic, objective with regard to the idea
of business;
● facilitates communication with the external environment.
10
11
http://tribunaeconomica.ro/blog/?p=1420 http://socioumane.ctasachi.ro/el07_files/downloads/Economie%20aplicata702.3%20Elaborarea%20pla
nului%20de%20afaceri%20%20cf.pdf
103
2.2. The disadvantages of business plan
The desire to achieve a business plan as good and realistic, the
entrepreneur is mainly dedicated its attention to getting as much information as
required by the business plan but not all of them are equally relevant to the
business, thus wasting time and energy entrepreneur with less elements essential
for business. This is one of the biggest disadvantages of business plan.
Another downside of the business plan is that it requires a lot of time to
achieve and in business time is money and lost opportunities.
For writing a business plan, the entrepreneur should possess certain skills
or if it's less prepared for this purpose, he will have to turn to financial advisors
which implies additional costs, at the same time a business plan is a comprehensive
document containing a lot of information that can distract the entrepreneur on the
truly important things.
For these reasons, Alexander Osterwalder and Yves Pigneur have designed
a tool planning simpler, more concise and specific business model Canvas.
3. Business Model Canvas
Alexander Osterwalder and Yves Pigneur, together with published in the
book "Business Model Genereation", a business planning tool called business
model Canvas.12
They believe that any business to stand on the market it needs to have a
business model. A business model describes the process by which a rational
organization creates and delivers value to the target consumers.
Figure nr. 1 Business Model Canvas13
The business model Canvas is made up of 9 „blocks”: target customers,
relations with clients, the value of the product/service, channels of transmission of
the value of the product/service, key partners, key activities, key resources,
12
Osterwalder, A. et all, Business Model Generation, John Wiley & Sons, Inc., Hoboken,
2010 13
http://ctrl-d.ro/wp-content/Liploads/2014/03/bmc.jpeg
104
revenues and costs of the business. The blocks are arranged from right to left, being
interconnected between them, one cannot exist without the other.14
These blocks are also the human brain and the left side are the building
blocks of efficiency (logic) and on the right side of the emotional value of business
(creativity). (figure nr. 3).
To complete the business model Canvas contractor must answer the following
questions:
1. To whom is addressed the business?
2. What value offers business to costumers?
3. How is the value offered to customers?
4. What are the costs and revenues?
To identify the most suitable business model Canvas for his idea, the
entrepreneur should follow four steps that succeed in cyclic mode:15
1. Establishment of the model assumption based on initial research findings
made by the entrepreneur;
2. Model testing-at this stage the entrepreneur meets with prospective
clients to validate the model estimate;
3. Hypothetical model analysis-analyse what works and what doesn't in the
presumed model;
4. According to the results of the analysis model is validated, adjusted or
changed radically.
Hypothesis model Adjustment or radical modification of the model Model testing Model analysis
Figure nr. 2 Stages of development of the model Canvas16
14
http://ctrl-d.ro/development/un-model-de-business-pentru-startup-uri-business-modelcanvas/ 15
http://www.tmp.ucsb.edu/outreach/nve_files/pdf/BusinessModels-20130116.pdf 16
Drawn by the authors Revista Română de Statistică - Supliment nr. 10/2014
105
3.1 Construction of business model Canvas
As stated previously, the business model Canvas is a logical structure of
nine blocks arranged in logical order and interconnected.
The first block to be completed is the segment of customers, because
customers are the heart of any business, without whom any deal is doomed to
disappearance.
The entrepreneur shall identify the category of clients that his business will
serve with two questions: "who create value?" and "what are the most important
customers?".
The entrepreneur can choose to apply:
● mass consumers;
● a niche of consumers;
● a consumer segment, the company applies an additional segmentation
segments of consumers already identified, on the basis of sex, age, and/or income
etc.;
● multiple consumer segments.
The second block to be filled is that of the proposed value. The proposed
model can have quantitative aspect (price \ speed serving) or qualitative aspect
(product design, usefulness). As examples of proposed new business value we can
mention: the novelty of product or service, the design, the lower selling price,
increasing the usefulness, reliability increased, standardization of the
product/service, etc.. The amount proposed constitutes the main reason why
customers are choosing a company at the expense of another.
In the third block, at the distribution, noted how the value to our customers.
Depending on the type of customer and product/service offered, the entrepreneur
can choose to convey the value of own channels (stores, sales agents, online store).
through the channels partners {pertners, online stores of partners), or a combination
of these.
The entrepreneur should establish at the outset what relationship it wants to
slabilească with our customers: personal or impersonal relationship. This will be
mentioned in the section "relationships with our clients"
If customers are the heart of any business, business revenue represents
blood without which it cannot survive.17 In the "revenue" is mentioned as the
proposed business will generate revenue namely: sale/lease assets, services,
abonarnente, advertising contracts, etc.. It will include how to determine the price
(if it is fixed, variable, if there is a special price for certain customers).
Under the "key resources" mentioned that are material resources, human,
financial and information needed to create the proposed value.
17
Alex, Ostervvalder et all. Business Model Generation, .lohn Wiley & Sons, Inc.,
Hoboken, 2010
106
How to use key resources for the production and distribution of the
proposed company will be noted in the block "key activity".
Under the "key partners" will be referred to the leading suppliers, business
partners that help to meet business objectives.
Business costs will be passed on the block called "costs". Will mention that
there are fixed costs, which are the variables which activities and resources are
most expensive. Tot în această zonă se menţionează dacă modelul de afaceri este
bazat pe costuri (minimalizarea costurilor) sau pe valoare (se axează în special doar
pe crearea de valoare).
3.2 Advantages and disadvantages of business model Canvas
The business model Canvas fits into the Group new managerial tools
available to entrepreneurs: anal but is a simple but very effective tool, you are
"required" to be entrepreneur's concise and it helps to define your business.
It is a visual, intuitive tool that helps to communicate the idea of business
much easier compared to the business plan. The business model created using this
tool can be easily adapted to market changes.
Unlike the business plan, it shall be completed very quickly, can easily
create many variations. In terms of the volume of information contained, the
Canvas contains fundamental aspects. of the business, without having to tie with
minor details.
The main drawback of this tool we can identify that it is known and used in
large scale of potential investors. Another disadvantage is linked to detailed
revenue and expenditure. In the corresponding blocks are just the final but for a
thorough understanding of the model should be accompanied by a budget of
revenue and expenditure completely.
As a new tool for business planning, the Canvas has real prospects to be
known and used successfully in the future at a scale of increasingly extended.
References
Alex, Ostervvalder et all. Business Model Generation, .lohn Wiley & Sons, Inc.,
Hoboken, 2010
Ciumara, T., Importance o f business planning in an environment lacking economic
predictability, http://www.ipe.ro/RePEc/vls/vls pdf/voll 4i3p147-151.pdf.,
accesat pe data de 17.04.2014
Garonne. C., Business planning, idea change, flexibility and performance: the best
o f both worlds?,Frontiers of Entrepreneurship Research, Vol. 31, nr. 12, 2011,
http://digitalknowledge.babson.edu/fer/vol31/iss 12/18/, accesat pe data de
17.04.2014
http://ctrl-d.ro/development/un-model-de-business-pentru-startup-uri-businessmodel-canvas/
http://ctrl-d.ro/wp-content/Liploads/2014/03/bmc.jpeg
107
http://ebooks.unibuc.ro/StiinteADM/manageinent/3.htm
http://smallbusiness.chron.com/importance-planning-organization-l 137.html
http://socioumane.ctasachi.ro/el07_files/downloads/Economie%20aplicata702.3%20Elabor
area%20planului%20de%20afaceri%20%20cf.pdf
http://tribunaeconomica.ro/blog/?p=1420
http://www.forbes.com/sites/actiontrumpsevervthing/2013/08/14/why-businessplans-are-a-waste-of-time/
http://www.mpt.upt.ro/doc/curs/gp/Bazele Managementului/Functia de planificare
cap2.pdf
http://www.quiicksprout.com/2009/12/15/whv-vou-shouldnt-write-a-business-plan/
http://www.tmp.ucsb.edu/outreach/nve_files/pdf/BusinessModels-20130116.pdf
http://www.vourarticlelibrarv.com/planning/what-is-the-importance-of-planningin-management/903/
Osterwalder, A. et all, Business Model Generation, John Wiley & Sons, Inc.,
Hoboken, 2010
108
109
Population Incomes
Andreea Gabriela BALTAC, PhD Student
Georgeta LIXANDRU BARDAŞU, PhD Student
Abstract
In Romania 56.8 percent of households are to be found in cities and
municipalities and 43.2 percent for the rural areas. Occupational status of
household head has a particularly importance and a strong impact over the size
and structure of revenue, expenditure and household consumption, as well as on
the behavior of household as regards saving and investments. In the current model
of the household from Romania, the consumption of food products from own
production and those received from the wider family (parents, brothers, children)
constitutes one of the ways of covering the needs of households who are
experiencing financial difficulties-induced loss of monetary or any reduction in
their purchasing power, and fulfil their own needs of food consumption and
support of other family members is the main focus of agricultural production made
by households.
Key words: population, households, population incomes, balance, level.
1. General aspects of the population
In Romania 56.8 percent of households are to be found in cities and
municipalities and 43.2 percent for the rural areas. The size of the average a
household being, in 2013, of 2.857 persons, higher in rural areas than in the urban
areas (2.996 to 2.751 people).
Households consisting of 1-4 people have been more numerous in urban
areas than in rural areas, while households made up of 5-6 persons and more have
been more numerous in rural areas, the latter (6 and more than one person) while
sitting in a proportion of 68.3 percent in rural areas.
Distribution households according to the number of children1 the age of 18
years household dependent is characterised by large share of households without
children which represent 72.3 percent of the total number of companies, high share
both in urban areas, as well as in rural areas (71.9 percent in urban areas and sale
agreement for 72.9 percent in rural areas).
Of households with children, the most common are those with a child (54.5
percent ). Households with a child have a weight greater than in urban areas, and,
in the case of those with two, three and four and more children in greater
proportion in rural areas.
110
Distribution according to sex household head is very uneven: 73.0 percent
of households are driven by a man (72.4 percent in urban areas and 73.7 percent in
rural areas) and 27.0 percent of a woman (27.6 percent in urban areas and 26.3
percent in rural areas).
• Occupational status of household head has a particularly importance and a
strong impact over the size and structure of revenue, expenditure and household
consumption, as well as on the behavior of household as regards saving and
investments.
Most households are households of employees and retirees: 80.0 percent,
of which 37.4 percent households of employees and 42.6 percent of retirees.
Households of employees, the unemployed and retirees are more numerous in
urban households, and own-account workers and farmers in rural areas.
Of all households in urban areas, the employees accounted for 49.8
percent, and 38.4 percent of the retired. Almost half of rural households (48.1
percent) were in households of retired, those farmers representing only 19.9
percent.
Distribution of households by category, after
status of the household head, occupational in 2013
By region, the structure of the occupational status of the household head is
characterized by the large proportion of households of retired in most households.
Only in the western regions of the Bucharest-Ilfov and most of the households are
headed by people employed. The share of households of employees ranging from
30.3 percent in the Northeast and 52.0 percent in Bucharest-Ilfov region.
The average size of households of employees was, in 2013, of 3.065
persons per household. Most of the households of wage earners, own-account
workers, farmers and unemployed people are made up of three to four people, and
the majority of households of retired from one and two people.
More than half the households of workers on their own (57.6 percent) and
almost half the households of employees (46.4 percent), agriculture (44.9 percent)
and the unemployed (48.7 percent) were in households that were dependent
children under the age of 18 years.
Among households with children, most categories of households are
characterized by high frequency of households with one child. Those with three or
111
with four and more children have a higher frequency of households to own-account
workers, farmers and unemployed people.
In terms of household head age, most of the households of employees,
own-account workers, farmers and the unemployed are run by people under the age
of 50 years, the largest being the frequency specifies the age group 35-49 years. Of
the total households of retired, 31.9% are head of household, a person in the age
group of 50-64 years and 66,7% of the group 65 years and over.
• Education level of the head of household is a feature that differentiates
sensitive indicators of level and structure of household income and consumption.
On the whole, the number of those households that are headed by a person
who has completed primary education (school or not accompanied), secondary and
higher education is 12.7 percent, 75.1 percent and 12.2 percent. This structure of
households shows the differences between the two environments sensitive to
residence. Thus, the share of households whose head of household has a degree of
instruction at primary education level (including those without school programme)
is over four times higher in rural than in urban (22.8 percent of all households in
rural areas, compared to 5.0 percent in urban area). Significant discrepancies are
recorded on media and in terms of the share of households headed by people with
higher education: 19.8 percent of all households in urban areas and only 2.1
percent in the countryside.
• In 2013 the households were concentrated in the two major age groups:
38.8 percent in the 25-49 age group and 34.2 percent in the group of 50 years and
over 15,1 percent, of which the group 65 years and over. The difference (27.0
percent) were a people aged less than 25 years. Noting that, at the lower age
categories (less than 15 years, 15-24 year olds and 25-49 years), the share of men
was superior to that of women, while the last two (50-64 years and 65 years and
over) was lower.
Of 78.6 percent total single persons are aged 50 years and older, of which
54.7 percent are 65 years and older. The share of persons aged 50 years and over is
high and two-person households (66.7 percent) In households consisting of three to
four people predominate in the age group of 25-49 years of age (47.6 percent and
45.0 percent), while in many households, persons up to 25 years: 40.0 percent in
households of five people and with 49.2 percent in those six and more people.
Analysis on category of households, their structure after the occupational
status of household members, highlights the significant presence of employees not
only in salaried households, which represent on average more than half the number
of members (54.6 percent) but also in other categories of households. In the
households of the unemployed and the retired employee rate exceeded 10 percent
(16.3 percent and 13. 3 percent).
The share of pupils, students and other categories of persons was 47.4
percent in households of workers on their own, 34.7 percent in households of
employees, 37.1 percent in the 38.4 percent of farmers and unemployed
households.
112
In 2013, the total revenue in nominal terms, were of 2559,1 lei per month
per household and 895,9 lei per person, with 3.4 percent, 4.0 percent respectively,
higher than in the year 2012.
The main source of income was a total, both in 2013, as well as in the
previous year, cash income (83.5 percent, up 1.1 percentage points from the year
2012).
Total household income structure was noted and in 2013 by the share of
income in kind (16.5 percen, down 1.1 percentage points compared to the previous
year), mainly on account of the value of agri-food products from own resources
(14.7 percent, down one percentage point). These are food products and
manufactured goods of agricultural origin falling within its own production of
household consumption, out of stock, and those received for work performed in
other households or received as a gift from relatives, friends or other people.
In the current model of the household from Romania, the consumption of
food products from own production and those received from the wider family
(parents, brothers, children) constitutes one of the ways of covering the needs of
households who are experiencing financial difficulties-induced loss of monetary or
any reduction in their purchasing power, and fulfil their own needs of food
consumption and support of other family members is the main focus of agricultural
production made by households. The subsistence economy, characteristic of the
agricultural society, is highlighted and the relatively low share of money incomes
from agriculture, which accounted for, entire households, only 3.3 percent of total
revenues, in slight decline, however, compared with the previous year (-0.1
percentage points).
Salaries and other income associated with their friends have made up the
largest category of revenues, with the largest share in the total incomes of
households (51.2 percent) rising, however, compared to the year 2012, 1.1
percentage points. However, their contribution to the formation of income is low
compared with that which characterizes the developed market economies. This
situation is related to the relatively small number of employees in the composition
of households (0.8 employees/household).
Another category of income who owned a major share in the total income
of the household structure, both in the year 2013, as well as in the previous year, it
represents income from social benefits (22.8 percent, declining towards 2012, 0.3
percentage points). Note that income from agriculture (sales of agri-food products,
animals and birds, provision of farm work and revenues from agricultural societies
and associations), income from independent activities (commerce, services, the
practice of trades and liberal professions), and those of ownership (interest,
dividends, rents, lease) still have a low share in the total income of households (6.2
percent in 2013 and 2012).
• The level and structure of a household's income is determined by the
number of people came, bringing especially for the number of employees and the
type of work which they carried. And, obviously, the household income level
113
depends on the position that its members hold in active income hierarchy
appropriate to the type of activity carried out, meaning the level of wages and
salaries, income from agriculture or those made from non-agricultural selfemployed activities.
The comparative evaluation of the situation of categories of the population
studied, on the basis of the average income level of these categories of producers, it
must be borne in mind, however, that a large proportion of households are actually
mixed households, comprising persons who benefit from different types of income.
Therefore, the average income in a household or a person of the categories
analysed show their economic situation more or less different from the “pure”
households, meaning households who live only from salary or pension only. For
example, in households of retired live and bring revenue to a large number of
employees (in 2013, the total number of persons in households of pensioners 13.3
percent were wage earners, however, rising 0.7 percentage points compared to the
year 2012) and, whereas wages are generally higher than pensions, income of
households that comprise the media raises the incomes of salaried households of
retired.
The formation of income of unemployed households, the income of the
household head status-specific income from social benefits-not the main ranks:
household income of unemployed from social payments at the rate of 19.4 percent
from wages and salaries in proportion of 42.8 percent, and from its own resources
at the rate of 15.0 percent.
Analysis of revenue by category of households grouped by level of
education of the household head reveals the existence of a direct relationship
between the level of preparedness of persons who bring revenue and income level.
One can notice the big difference between the level of wages made by the
three categories of producers, as well as the difference between the level of income
from property (rent, rents, dividends, interest) made by households falling in the
category of those with higher levels of education, compared with households in the
other two categories.
Income households made up of two personae amounted, in 2013, the 100.2
percent in income levels of households made up of single people, those in
households consisting of three persons-at 88.5%, those in households made up of
four people – 69.3 percent, those from households that comprise five people-to
56.0 percent, and those in households with six or more members-to 44.3 percent.
In 2013, the average income per person in households with children under
18 years of age dependant were 22.2 percent lower than those registered in
households without children (21.9 percent in 2012).
The low income households falling in the category of those headed by
people aged 65 years and above is linked to a large extent with age, households in
this category are 96.8 percent in the proportion of households of pensioners. Of the
revenues of those households headed by people aged 65 years and over 21.5
percent are income in kind and 53.5 percent income from pensions.
114
From the analysis of the average household income is grouped by sex of
household head, the highest level of total income is found in households headed by
persons of male (2711.1 lei per month in 2012 and 2800.9 lei per month in 2013),
1.1 times higher than the average for all households and 1.5 times higher than that
of households headed by persons of the female sex.
Household income driven by female people lies to 68.1 percent (66.8
percent in 2012) of the income levels of households headed by persons of male sex
and below the average calculated on all households with 25.5 percent (by 26.8
percent in 2012).
The total income of households, sources of training,
after which a household head, sex in the year 2013
Differences in level and, especially, the structure between household
income were registered and depending on the country of residence. In the year
2013, average incomes on a household in urban areas have been with 32.1 percent
higher than rural households.
An important contribution to the formation of income of rural households
had returned and salaries (23.0 percent) and those in social benefits (24.1 percent).
In terms of income differentiation by region, it can be noticed that the
highest average monthly income was registered in Bucharest-Ilfov region (3327.5
lei per household), and the lowest in the Southeast (2206.9 lei per household).
Another category of revenue with a quite important in the structure of total
revenue is the income from social benefits, which exceeds 20 percent in all regions.
ncome in kind is also a source of great weight in the total revenue in all
regions (between 15.0 percent in the Centre, 20.8% and in the North-East), with the
exception of Bucureşti-Ilfov (4,5%).
115
The total income of households, sources of
training in territorial aspect, in 2013
• Money income of surveyed households, which expresses the capability,
strength and their ability to engage in market relations, is characterized by relative
low general level, even very low in the case of certain categories of households,
with implications for the level and structure of consumption, saving and capacity
development of the national economy.
In 2013, the average level of cash income was 2137.5 lei per household
(748.3 lei per person) and accounted for 83.5 percent of the total income of
households, up 0.7 percentage points from the previous year.
The biggest money, monthly average income per a household, they have
achieved the households of employees (3100.0 lei), and the smallest households of
farmers (1114.4 lei), the report of which was 2.8: 1.
The money the average household incomes in urban areas were 1.8 times
higher than that of households in rural areas and have represented 92.2 percent of
total income of urban households and 68.4 percent of the rural households.
The report of financial revenue in the average household in the first and
last decile was 1: 7.3 and 1: 13.8 in case of monetary payable in average per
person. Their share in total revenues was 52.6 percent in the lower decile and 94.2
percent in the upper part.
Money income of households in monthly average decile D1 accounted for
31.4 percent of the monetary income of all households, while those of decile D10
were 2.3 times higher.
The much lower level of wages earned on average for other categories of
households surveyed, is explained mainly by the lower rate of employees in these
households (724.0 lei per month-unemployed; 449.5 lei per month-retired; 305.3
lei per month-freelance workers in non-agricultural activities and 175.8 lei per
month-farmers).
• The subsistence economy, characteristic of the agricultural society, is
evidenced by the low share of monetary from agriculture, which represented, in
2013, only 3.9 percent of the population, from which proceeds the proceeds from
116
sales of agri-food products, animals and birds accounted for 2.8 percent, and
revenue from the provision of employment in agriculture by 1.1 percent.
• The average income of a household's from non-agricultural self-employed
activities was, in 2013, 72.5 lei monthly, providing cash income of 3.4 percent. The
aggregate revenue 14.0 percent from 28.8 percent in commerce, services, 43.6
percent of trades and 13.6 percent in the liberal professions and intellectual
property rights.
This category of income average monthly level recorded the largest farms
on their own workers in non-agricultural activities, and the youngest retirees.
The largest part of these revenues are the pensions (86.9 percent, rising by
0.5 percentage points from the year 2012).
Benefits from the unemployment fund accounted for 1.6 percent of the
total social benefits, both in the year 2013, as well as in the previous year.
Family benefits, which include children's allowances, allowances for
family support, as well as scholarships for pupils and students, formed the 5.5
percent of the volume of social benefits, decrease by 0.2 percentage points
compared to 2012. Social assistance benefits, held a 3.1 percent share of total
income from social benefits, both in 2013 as well as in the previous year.
Social benefits have made up 53.3 percent and 41.0 percent of the
monetary income of households consisting of one or two people, most of them
pensions.
Share of social benefits (including pensions) is much greater in monetary
income of households without children (35.6 percent) compared with that of the
households have children under 18 years of age dependent (9.8 percent).
Their ability to contribute to the reduction of income inequality, however,
is limited by the low level of benefits.
Determined by subtracting from the household income taxes on income
and social insurance contributions in their task, and expenditure on household
production (cash and in-kind), net revenues means that part of the income that
remains available to households for consumer spending and saving.
The relatively high level of taxes and contributions paid by households, in
particular those which carry out wage income as well as expenses incurred by
households for their own household production, causing large differences between
total and available income (net).
All households, in 2013, the average net income a household were 1943.9
lei per month, the average person 680.5 lei, while their share in total revenues from
76.0 percent.
• In general, for most households, income levels they achieved and in
particular of those who remain at their disposal after the household expenses for
production and for the payment of taxes, fees, contributions, etc. is very low in
relation to the expenses that need to be made to meet the needs of the consumer.
The share of households that have turned to savings to meet current
expenditure was 6.3 percent, of those who have made loans from relatives, friends
117
or other guests 8.6 percent (15.4 percent in households of the unemployed), and
those who needed financial assistance, without obligation to refund, from relatives,
friends or other people was 12.6 percent (29.0 percent in households of the
unemployed). Extra work in order to obtain the necessary resources to deal with
current expenditure was performed by 9.7 percent, the proportion is higher in
households of farmers (29.8 percent) and own-account workers (15.6 percent).
• Households as a whole, actual total revenue, on a monthly average
household, have seen a relative dynamic negative (-0.6 percent). Total actual
income analysis highlights, a slight increase from the households of employees and
own-account workers (1.5 percent or 0.2 percent), while other categories of
households surveyed, the dynamics is negative.
Of the total revenues, money incomes have actually increased slightly (0.7
percent), while income in kind have been reduced by 6.7 percent. Categories of
producers, with the exception of households of pensioners (-0.3 percent), real
money incomes was positive.
References
Anghelache C. şi alţii (2014) – „Analysis on the Gross Domestic Product
Evolution”,Romanian Statistical Review, Supplement no. 4/2014, pp. 7-15
Anghelache C. şi alţii (2014) – „Analysis of the Evolution of the Agricultural
Production in Romania”,Romanian Statistical Review, Supplement no. 4/2014,
pp. 78-86
Anghelache C. şi alţii (2014) – „The Evolution of the Services to the
Population”,Romanian Statistical Review, Supplement no. 4/2014, pp. 183-189
Anghelache C. şi alţii (2014) – „The Population and the Labor Force
Market”,Romanian Statistical Review, Supplement no. 1/2014, pp. 7-17
Anghelache C. şi alţii (2013) - „Model of analysis of the correlation between the
population and the labor force market”, Theoretical and Applied Economics,
No. 12/2013
Anghelache C. şi alţii (2013) - „General aspects regarding the evolution of GDP in
Romania”, Theoretical and Applied Economics, No. 12/2013
Anghelache C. şi alţii (2012) – „Model for the Analysis of GDP”, Metalurgia
International, nr. 5/2012, pp. 182-185, ISSN 1582-2214, Editura ştiinţifică
F.M.R., revistă citată în bazele de date internaţionale SCOPUS, EBSCO,
THOMSON SCIENTIFIC MASTER JOURNAL LIST, Sci Search
118
119
Multiple Linear Regression Model Used in
Economic Analyses
Lecturer Mădălina Gabriela ANGHEL PhD
Ligia PRODAN PhD Student
Marius POPOVICI PhD Student
Abstract
The multiple regression is a tool that offers the possibility to analyze the
correlations between more than two variables, situation which account for most
cases in macro-economic studies. The best known method of estimation for multiple
regression is the method of least squares. As in the two-variable regression, we
choose the regression function of sample and minimize the sum of squared residual
values. Another method that allows us to take into account the number of variables
factor when determining the validity of harmonization is given by the Akaike
information criterion.
Key words: regression, parameter, residual factor, consumer prices
• Theoretical aspects regarding multiple regression
The situation in which economic correlations involve only two variables
are very rare. Rather we have a situation where a dependent variable, Y, can
depend on a whole series of factorial variables or regressions. For example, the
demand for a commodity depends not only on price but also on the prices of
substitutes or complementary goods, the general level of consumer prices and
resources. Thus, in practice, there are normally correlations as:
Y = β1 + β2 X2 + β3X3 + β4X4 +...+ βkXk + ε
where values Xj (j = 2, 3, ..., n) represents the variable factor or regressors, the
values βj (j = 1, 2, 3, ...,k) represents the parameters of the regression and ε is the
residual factor factor . Residual factor reflects the random nature of human
response and any other factors other than Xj, which might influence the variable Y.
Note that we have adopted the usual notation, we assigned to the first factor,
120
notation X2,, the second, notation X3 etc. In fact, as we shall see, it is sometimes
convenient that a parameter β to be considered a coefficient to a variable X1 whose
value is always equal to unity. Then it becomes possible to rewrite the equation in
the form:
Y = β1X1+β2X2 + β3X3 +...+ βkXk + ε
If we assume, as in the case of two-variable regression that E(ε) = 0, then,
by substitution results:
E(Y)=β1+β2X2+β3X3+β4X4+...+βkXk
The equation is known as the multiple regression equation. For moment,
conventionally, we consider that it is of linear form. Unlike the case of twovariable regression, we cannot represent the equation by means of a twodimensional diagram.
βJ are the regression parameters. Sometimes they are also called regression
coefficients. β1 is a constant (intercept) and β2 , β3 and so on, are the parameters of
the regression slope.
Note that β4, for example, measure the effect of E(Y) produced by a unit
change of X4, provided all other factorial variables remain constant. Similarly, β2
measures the effects on E(Y) produced by changing one unit of X2, given that all
other factorial variables remain constant.
As the population regression equation is unknown, it will be estimated
based on a sample. Suppose that we have available a sample of n observations,
each observation containing values for dependent variable Y and for each factorial
variables X. We write the values for observation i as:
Yi , X2i , X3i , X4i ,..., Xki
Thus, for example, X37 is the value of X3 in the 7th observation and X24 is
the value X2 taken in the 4th observation. For a similar manner, Y6 is the variable Y
in the observation of 6 and so on.
Given that it is assumed that the sample data were generated by the
correlation of the population, each observation has to involve a set of values as the
initial model.
Therefore, we can write Yi = β1 + β2X2i + β3X3i + ...+ βkXki + εi for all
values, where εi represents the residual value for the i observation.
It is convenient to rewrite the above equation in a simple matrix form,
namely:
Y = Xβ + ε
where we use the vector form (matrix) for Y, X, β and ε.
We assume that the sample data were used to estimate the regression
equation.
Estimation method remains unspecified and we assume that it was
estimated by the sample regression equation, which we write in the form:
^
^
^
^
^
Y = β 1 + β 2 X 2 + β 3 X 3 + ... + β k X k ,
121
^
where β
^
j
is estimators for βj and Y is known as the expected value of Y.
If we take the i observation of the sample and enter its X values into the
^
equation, as it β
j
is known estimates, we obtain the expected value of Y
^
corresponding to the i observations, Y i namely the value. As in the two-variable
regression, we obtain the expected value of Y for each observation in the sample.
These values can be written as:
^
^
^
^
^
Y = β 1 + β 2 X 2 i + β 3 X 3i + ... + β ki X ki for all values of i
The effective values of Y do not coincide with the expected values of Y
and, in the case of two-variable regression, the differences between them are
known as residual values. The relationship becomes:
^
Yi = Yi + ei
for all values of i, where ei represent the residual corresponding to the
observations of i.
The above equation is in fact identical to that of the two-variable
regression but in general we were not able to illustrate the graphic of ei. From the
last two equations we get the form:
^
^
^
^
Yi = β 1 + β 2 X 2 i + β 3 X 3i + ... + β ki X ki + ei
for all values of i
The equation can be written in matrix form, namely:
^
Y = X β+ e
where X and Y are as already defined.
There are two issues to be retained regarding the residual values. First,
regardless of the method we used to estimate the regression equation, we get such
residual values - one for each of the sample observations. Second, by estimation,
^
β
j
becomes known and the equation can be used for their determination. As in
the case of two-variable regression, residual values are known.
^
^
^
^
We select those values for β 1 , β 2 , β 3 ... β k
following relation:
^
⎛
⎞
S = ∑ e = ∑ ⎜ Yi − Yi ⎟
⎝
⎠
which minimizes the
2
2
i
Minimizing the above equation implies the calculation of the differential of
^
S in relation to each β j . This is complicated in terms of ordinary algebra so it is
122
better at this stage to work in terms of matrices. Remember that
∑e
2
i
= e' e . It
results the following relationship:
^
^
^
^
⎛
⎞⎛
⎞ ⎛
⎞⎛
⎞
S = e' e = ⎜ Y − X β ⎟' ⎜ Y − X β ⎟ = ⎜ Y '− β ' X ' ⎟⎜ Y − X β ⎟
⎝
⎠⎝
⎠ ⎝
⎠⎝
⎠
^
^
^
^
= Y 'Y − β ' X 'Y − Y ' X β + β ' X ' X β
^
^
^
= Y 'Y − 2 β ' X 'Y + β ' X ' X β
^
^
where the last step is possible because β ' X ' Y = Y ' X β are scaled.
^
Now we need to calculate the differential with the vector β and we equal
to zero the result. Such matrix leads to the following relation:
^
∂S
=
−
2
X
'
Y
+
2
X
'
X
β
=0
^
∂β
This is a set of k equations which can be written in the form:
^
X ' X β = X 'Y
^
The equations X ' X β = X ' Y are normal in the case of multiple
regression equations and are analogous to regression equations for two variables.
Note that if we substitute Y we obtain:
^
^
⎛ ^
⎞
X ' X β = X '⎜ X β + e⎟ = X ' X β + X 'e
⎝
⎠
Therefore:
X’e = 0
From the definitions of X and e it is apparent that the relationship X’e = 0
implies: ∑ ei = 0 , ∑ ei X 2i = 0 , ∑ ei X 3i = 0, ∑ ei X 4i = 0 and so on.
Thus, a property estimators OLS method is that the residual values results
satisfy the above correlation. Remember that there is a similar correlation in the
case of two-variable regression.
Imposing the condition that the matrix X'X is non-singular, the normal
^
equations can be solved to obtain β , or the vector for usual estimators of least
squares (OLS). Multiplying by (X’X)-1 we get:
^
( X ' X )−1 X ' X β )( X ' X )−1 X 'Y
Therefore:
^
β = ( X ' X )−1 X ' Y
123
Equation, which is the expression of OLS estimators for multiple
regression is the most famous formula in econometrics.
^
In order to calculate the vector β we have to follow the following steps:
(i)
we make the k x k matrix for X’X and k x 1 for one for X’Y;
(ii) we make the k x k inverse matrix for (X’X)-1;
(iii) we multiply the k x k matrix for (X’X)-1 in k x 1 matrix for X’Y.
Step (iii) above, leads to the vector k x 1 of OLS estimates.
Step (ii) involves the best effort calculation. Even with only two variables
X factor, k = 3, we face the reversal of a number of 3 x 3 matrices. As the number
of factorial variables increases, the difficulty of calculation increases exponentially.
Typically, there are packages available of OLS estimators ready compiled in
computer.
Computational effort involved in obtaining OLS estimators can be reduced
if we work in terms of deviation variables of their average. As we shall see, it is
clear that instead of overturned k x k matrix, as shown in step (ii) above, we needs
to reverse a matrix only of the order of (k - 1) x (k – 1).
If we sum this equation for all values of i and divide the result by n, we
get:
^
^
^
^
Y = β 1 + β 2 X 2 + β 3 X 3 + ... + β k X k + e
You have to remember that one of the properties OLS estimation method is
that
∑e
i
and therefore,
^
e is equal to zero.
^
^
y i = β 2 x 2 i + β 3 x 3i + ... + β k x ki + ei for all values of i
We deduce that y i = Yi − Y and x 2 i = X 2 i − X 2 so on.
We can write
Yi
^
^
^
^
= β 1 + β 2 X 2 i + β 3 X 3i + ... + β ki X ki + ei in a similar way with
^
Y = X β + e , that:
^
y = xβ + e
^
In this form we define matrices for y , x and β .
^
^
The equation y = x β + e is different than Y = X β + e by the fact that the
values of the variables are now diverted, the columns of some of them does not
^
appear in the matrix of x, which is of the order n x (k – 1) and β 1 does not appear
124
^
in the β vector, that, now, it is of the order of (k – 1) x 1. The e vector is left as the
previous definition.
The problem is that, because the definition of e remains unchanged, the
sum of the squares of the residuals is still e’e and thus can be expressed in a true
form, except for the fact that the matrices x and y replace the X and Y matrices.
^
Doing the differential with redefined the β vector leads to an similar
expression, except that the values of the variables are presented in a modified form.
^
This means that: β = (x’x)-1x’y
^
^
The advantage presented by β = (x’x)-1x’y to β = ( X ' X ) X 'Y is that
the matrix (x'x) is of the order of (k – 1) x (k – 1) to the k x k. The only problem
−1
^
^
^
that arises is that the new vector β does not contain a value for β 1 . Since β it is
^
known, it can be obtained a value for β 1 by re-arranging the equation because
e =0:
^
^
^
^
β 1 = Y − β 2 X 2 − β 3 X 3 − ... − β k X k
Summarizing, we can calculate the OLS estimators in two ways. The first
^
is to use the β = (x’x)-1x’y function but involves working with a matrix of order k
x k. Alternatively, we can work in terms of deviations from the average of the
variables, which only requires inverse of the matrix of order (k – 1) x (k – 1).
• Aspects regarding determination in multiple regression
In approach of the two variables of regression we defined the coefficient of
determination, which measures the proportion of variation due to the X explanatory
variable in total variation of the variable Y.
A similar measurement of harmonization accuracy can be defined also for
the multiple regression.
^
We consider the equation Yi = Yi + ei . By removing Y from each side of
the equation we get:
^
Yi − Y = Y i − Y + ei for each value i
Thus, if we measure the deviations of Y around its average, Y , we can say
that for each observation, the total deviation of Y can be divided into an explained
^
deviation, Y i − Y , and residual deviation, ei . The above equation is identical to
that of the two-variable regression.
125
As in the case of two-variable regression, first we square and then proceed
to the adding of all observations.
The last equation is identical to that of the two-variable regression. It
means that, during the entire measurement, the measurement result of the total
variance of Y, SST, can again be divived into a measure of the variation factor of Y,
SSE, and a residual variation, SSR. We have to emphasize that the relationship is
available, as in the two-variable regression, only if the estimation method is OLS,
because the correlation is only support for this form of estimation.
We can define the coefficient of multiple determination, R2, as the
proportion of total variation of Y that can be attributed to variations in all variables
factor acting focused.
Given the equation SST = SSE + SSR, it means that:
R2 =
explicit sum of squares SSE
=
total sum of squares
SST
We can consider the principle like in two-variable regression and so
results:
R2 = 1−
∑e
∑y
2
i
2
i
Sum of squares of residues from above relation can then be calculated by
expansion, which demonstrably is supported for multiple regression, like:
∑e
2
i
=
∑y
2
i
^
−β
2
∑x
^
2i
yi − β
3
∑x
^
3i
y i − ... − β
k
∑x
ki
yi
• Akaike criterion as base in econometric models
The Akaike information criterion (AIC) is defined as:
⎛ ∑ ei2
AIC = ln⎜
⎜ n
⎝
⎞ 2k
⎟+
⎟ n
⎠
In this case we are not concerned with the theoretical basis of AIC, we will
only mention that in this case the criterion is to include an additional variable only
2
if it leads to lower AIC. Like, R , AIC depends on the residual sum of squares,
∑ ei2 and the number of parameters to be estimated, k. However, in the case of a
decrease in the level ∑ ei2 , which occurs when it includes an additional
explanatory variable, it is possible that this does not necessarily lead to a decrease
and AIC. Additional variable represents an increase of k, respectively the number
of parameters to be estimated, and this leads to increased AIC. Therefore, AIC is
reduced only if the decrease recorded of ∑ ei2 is large enough to counteract the
increase of k.
126
Among the measurements of accuracy of harmonization in relation to the
inclusion of additional factors variables, the Schwartz criterion and the Amemiya
criterion are included.
Acknowledgement
Operational Programme Human Resources Development 2007- 2013, project
number POSDRU/159/1.5/S/134197 „Performance and excellence in doctoral and
References
Anghelache, C. şi alţii (2012) – „Elemente de econometrie teoretică şi aplicată”,
Editura Artifex, Bucureşti
Bardsen, G., Nymagen, R., Jansen, E. (2005) – „The Econometrics of
Macroeconomic Modelling”, Oxford University Press
Benjamin, C., Herrard, N., Houée-Bigot, M., Tavéra, C. (2010) – „Forecasting
with an Econometric Model”, Springer
Dougherty, C. (2008) – “Introduction to econometrics. Fourth edition”, Oxford
University Press
Jesus Fernandez-Villaverde & Juan Rubio-Ramirez (2009) – “Two Books on the
New Macroeconometrics”, Taylor and Francis Journals, Econometric Reviews
Mitruţ, C. (2008) – „Basic econometrics for business administration”, Editura
ASE, Bucureşti
Voineagu, V., Ţiţan, E. şi colectiv (2007) – “Teorie şi practică econometrică”,
Editura Meteor Press
127
128
Routes and Trends
of Romanian Core Economic Variables
Lecturer Oana Simona HUDEA (CARAMAN) PhD a,b
a
Post PhD Researcher
b
Bucharest University
Abstract
The present paper is centred on the analysis of a basic, classical, closed
economy dynamic stochastic general equilibrium model, revealing some core
economic variables, captured at the level of our country, both from the perspective
of their reaction to the shock on technology and from the one relating to their
evolution on medium to long term. After a brief rendering of the problems
maximised and solved, given the constraints, by the two economic agents
considered, households and firms, as well as subsequent to the presentation of the
equilibrium established on the market of goods and services, the final equations
are selected and implemented in Dynare, a specific tool of Matlab. The numeric
results obtained and the related graphical representations are thereafter
construed, the end purpose being the formulation of several suggestions regarding
the appropriate economic decisions to be made in the future, by the entitled
entities, in order to lay the grounds of a desirable economic growth.
Keywords: dynamic stochastic general equilibrium model, real business
cycle, closed economy, impulse-response function, forecasting patterns
JEL codes: C53, C68, E20, E27
1. Introduction
Used for pure estimation only, for impulse-response function analysis or
even for forecasting purposes, the dynamic stochastic general equilibrium models
acquired more and more adepts in the entire world.
The studies of Kydland & Prescott (1982), pioneers of the classical side of
such models, subsequently improved by Rotemberg & Woodford (1997), as well as
those of Smets & Wouters (2003), Christiano et al. (2005) or Adolfson et al. (2005)
are just some examples of works dedicated to this last generation modelling
approach.
Their echo reverberated also at the level of central banks, Harrison et al.
(2005), Erceg et al. (2006) or Christoffel et al. (2007), among many others,
129
developing models enabling the authorities representing the Bank of United
Kingdom, the Federal Reserve Bank or the Central European Bank to take
appropriate measures so as to adequately sustain the real economy.
Using microeconomic fundamentals to reach, by aggregation, the
macroeconomic space, considering the rationality of economic agents and the wellgrounded expectations of the same, capturing the impact of structural shocks at the
level of economic variables and accepting the flexibility of prices, wages and
interest rate and the rather perfect competition specific to a classical approach or
their rigidity in the context of an imperfect market according to the Keynesian
thinking, the dynamic stochastic general equilibrium models turned, step by step,
into a veritable cornerstone in the matter.
This paper continues a previous study of a classical model, then dedicated
to the Bayesian estimation of parameters, with the analysis of the reaction of core
variables on the occurrence of the technology shock and with the forecasting of
such variables in the medium to long run. If section 2 resumes the model, section 3
gathers information on the data and the methodology used, as well as on the results
obtained, and section 4 comes with the work overall conclusions.
2. Model
The model used herein for the analysis of the impulse-response function
and for the forecasting of the Romanian economic variables is a simple, classical,
real business cycle model designed for a closed economy. This model, previously
approached by the undersigned for estimation purposes, is rendered below in brief,
so as to capture the preferences of households, maximised under the budget
constraint, the benefits pursued by intermediary and final firms, aiming at
minimising their production-related costs, and the aggregated equilibrium of the
same.
The utility function of households depends positively on consumption and,
negatively on the labour time, as in equation [1]:
∞
Εt
∑β
t
× [log c t + ζ × log(1 − l t )]
[1]
t =0
where Et denotes expected value, βt, subjective discount factor, ct, consumption, lt,
labour time, and ζ, spare time utility parameter
The budget restriction considers the financial resources, on one hand, and
the utilisation of the same by households, taking the following form:
ct + k t +1 = wt × lt + rt × k t + (1 − δ ) × k t
[2]
where kt denotes capital stock, wt, real wage, rt, real interest rate and δ, depreciation
rate
with
130
it = k t − (1 − δ ) × k t −1
[3]
where it denotes investments
The solution to the maximisation problem provides us we two equations,
namely the Euler consumption and the labour supply equations:
⎡ 1
⎤
1
(1 + rt +1 − δ )⎥
= β × Εt ⎢
ct
⎣ ct +1
⎦
[4]
c
ζ × t = wt
1 − lt
[5]
The intermediary firm i uses capital and labour, as inputs, in order to
produce differentiated products, according to a Cobb-Douglas function:
(
y i ,t = k iα,t + e zt × li ,t
)
1−α
[6]
where yi.t denotes production of firm i, α, capital share in total production and zt,
technology level
with z t following a first order autoregressive process:
z t = ρ × z t −1 + et
[7]
The resulting capital-labour ratio is as follows:
k i ,t
li ,t
=
α
× wt
1− α
[8]
The level of prices established by the above mentioned firms is related to
the condition of general mark-up prices, given the monopolistic competition
premises:
pi ,t =
ε
× mct × pt
ε −1
[9]
where pi,t denotes price set by firm i, pt, average price and mct, real marginal cost
By assuming the adoption, by all intermediate producers, of the average
level of prices for their related products, we get:
mct =
ε −1
ε
[10]
Going forward, considering the real marginal cost of firms, arising from
their expenses with the input factors:
⎛ 1 ⎞
mct = ⎜
⎟
⎝1− α ⎠
1−α
α
⎛1⎞ 1
×⎜ ⎟
× w1t −α × rtα
⎝ α ⎠ At
[11]
where At denotes total productivity of factors
131
and the previously referred condition of general mark-up prices, we obtain the real
wage and real interest rate equations:
wt = (1 − α ) ×
rt = α ×
yi ,t
k i ,t
y i ,t
l i ,t
×
×
ε −1
ε
ε −1
ε
[12]
[13]
The production function of the final firms, taking also a Cobb-Douglas
type form, is determined by the aggregation of the output of all intermediate firms:
yt = At × k tα × lt1−α
[14]
At equilibrium, on the market of goods and services, we have:
y t = c t + it
[15]
3. Data, Methodology and Results
The variables used in the analysed model are explicitly divided, within the
Dynare code implemented in Matlab, into nine endogenous variables: production
(y), labour time (l), production-labour time ratio, consumption (c), capital (k),
investments (i), real wage (w), real interest rate (r) and technology level (z) and one
exogenous variable: the shock on technology (ε). Among such variables, only one
is observable, namely the gross domestic product, analysed quarterly, for a 15-year
period, from 2000Q1 to 2014Q2, giving 58 entries, reduced to 57 after the first
order differentiation of the said variable in logarithm. The above variable-related
data are taken over from the Romanian National Institute of Statistics, being
expressed as Million RON average prices of year 2000.
The prior distribution of the model parameters: capital share in production
(α), subjective discount factor (β), capital depreciation (δ), technology level
autoregressive parameter (ρ) and spare time utility parameter (ζ), as well as the
standard deviation of the technology shock (σε) was set previously to the model
transposing into Dynare.
Only 8 such equations are finally selected, more precisely the investment
equation [3], the consumption Euler equation [4], the labour supply equation [5],
the intermediary firm production function [6], the AR(1) process of the technology
level [7], the real wage equation [12], the real interest rate equation [13] and the
market equilibrium condition [15].
Below are rendered the results arising from the implementation of these
equations.
We start by presenting two figures standing for the validity of our model
and the significance of its related output. The structural shock on technology is
centred on the zero value, having a relatively constant variance (Figure 2), while
the Monte Carlo Markov Chains multivariate diagnostics, measuring the parameter
132
vectors within chains and between chains (Figure 2), reveals that both lines are
rather constant and convergent to each other for the mean confidence interval,
variance and skewness.
Figure 1. Smoothed technology shock
e
0.06
0.04
0.02
0
-0.02
-0.04
-0.06
5
10
15
20
25
30
35
40
45
50
55
Figure 2. MCMC multivariate diagnostics
Interval
5
4
3
1000
1500
2000
2500
3000
3500
4000
3000
3500
4000
3000
3500
4000
m2
4
3
2
1000
1500
2000
2500
m3
20
10
0
1000
1500
2000
2500
Figure 3 shows the reaction of the model variables under the impact of a
technology shock. If consumption, capital and real wage register a constantly
increasing trend, reaching the peak value after about 40 to 55 periods, followed by
133
a smoothed return towards the steady state level, being however far from reaching
it for the remaining period subject to analysis, investments, labour time and real
interest rate react suddenly and strongly when hit by the same shock, thereafter
continuously decreasing for the entire 80-period interval and meeting, by the end of
the same, their initial equilibrium. Getting into more detail, we could state that a
positive technology shock determines immediate and significant investments in the
related new technology, which, once acquired, leads to the flattening of interest for
it. This pattern is also followed by the labour time. Assimilating the know-how
necessary to benefit from such technology involves additional working hours, these
one diminishing step by step when the related knowledge is obtained.
On the other side, the level of capital held by firms slowly augments, an
obvious tendency given the above-mentioned investments. Increasing capital and
decreasing labour force, denoted by labour time, allow the movement of real wags
upward, as firms have to pay fewer but more qualified people, in other words more
efficient employees. Higher wages generate higher consumption which, as
component of gross domestic product, determines the overall increase of the latter.
A superior aggregate demand leads to upper prices, therefore an ascendant
inflation rate and, as a consequence, an augmented nominal interest rate. Yet, not
only the nominal value of interest rate increases, as, under the impact of suddenly
increased investments, its real value quickly goes upward too, relaxing thereafter in
line with the same.
As for the technology level, an obvious ascendance is initially remarked, it
flattening in time when new technology is expected to replace the old one.
Figure 3. Impulse-response function to technology shock
-3
y
x 10
0.014
c
k
0.12
0.1
0.08
0.06
0.04
0.02
10
0.012
0.01
8
5
20
40
-3
i
x 10
60
80
40
-4
l
60
80
10
4
5
20
40
60
80
60
80
60
80
y_l
15
6
2
0.045
0.04
0.035
0.03
0
20
40
60
80
w
20
40
-4
r
x 10
60
80
20
40
z
6
0.026
0.024
0.022
0.02
0.018
0.016
4
0.015
2
0
20
134
20
x 10
40
60
80
0.01
20
40
60
80
20
40
The forecasted trend of model variables (Figure 4) is encouraging,
revealing a significant increase of consumption, doubled by a less intense, still
obvious ascendance of investments, which, altogether, contribute to a sustainable
growth of gross domestic product. The overall capital increases too, in compliance
with the related investments, while the labour time remains practically unchanged,
somewhere above the steady state level. The higher demand for products forces the
existing firms to produce more. Given the previously mentioned unchanged
working time, we assume a superior efficiency of workers, therefore justifying the
upward level of wages.
Wages reach a sufficient level for covering the consumption and
investments related needs of households and firms, the crediting not being an
option. On the other side, such orientation of financial resources leads to a
limitation of the volumes of deposits. Given the above mentioned, the real interest
rate gently goes down. As we have both an increase of wages and of the aggregated
demand for products, the inflation rate augments. Considering this, the overall
tendency of the nominal interest rate does not significantly change for the
forecasted period, being almost flattened.
As for the technology level, this is the only variable clearly starting from a
point lower that its steady state. Even if the route of such variable is ascendant, the
related increase is irrelevant, the economy not being able at least to recover its
technological equilibrium within the forecasted period.
Figure 4. Forecasted trend of model variables
y
c
k
0.5
0.4
5
0
0.2
0
-0.5
20 40 60 80 100
0
i
20 40 60 80 100
-5
l
y_l
0.2
0.4
2
0
0.2
0
-0.2
20 40 60 80 100
0
w
1
20 40 60 80 100
-2
r
20 40 60 80 100
z
0.05
0
0
-1
20 40 60 80 100
-1
20 40 60 80 100
0
20 40 60 80 100
-2
20 40 60 80 100
If we take a look at the graphical representation above, as a whole, we
remark the areas where the entitled authorities should intervene in order to
strengthen the economic development, namely the encouragement of sustainable
135
investments, the increase of labour hours, transposed into a reduction of
unemployment rate, and a sharp support of new technology acquisition. The
policies to be adopted in this regard should be mainly oriented towards the
injection of money in the real economy, therefore inducing a lowering of the
interest rate and a stimulation of investments on medium to long term, this
including the appropriation of new technology, with all its subsequent, extended
benefits. As for the unemployment rate, adequate measures, such as tax exemption
for firms, under certain circumstances, should be taken so as to determine the same
to employ new personnel, therefore lowering the average level of ineffective
households.
4. Conclusions
This study is focussed on the analysis of the impulse-response function and
on the forecasting of the economic evolution of our country, perceived from the
perspective of a basic dynamic stochastic general equilibrium model. The main
purpose of the paper is related to the identification of the route and trends of the
economic core variables, considering the exogenous forces affecting the same.
For the 80 periods of analysis, subsequent to the occurrence of a
technology shock, only two variables, namely labour time and real interest rate,
regain their steady state position, the level of investments gets close to it, while the
rest of them remains more or less away from equilibrium. On the other hand, all
model analysed variables are positively affected by a favourable influence on the
technology level, however, some of them, like consumption, capital and real wage,
having a soft, constantly increasing evolution immediately after such impact, as
opposed to investments, labour hours, gross domestic product and real interest rate
which are suddenly affected by the shock.
Concerning the forecasted pattern of the model variables, our predictions
reveal a desirable perspective, the Romanian economy going, to a large extend,
into the right direction, as, mainly consumption, but also investments and,
implicitly, gross domestic product increase progressively for the 100 periods of
study. Also, an increase is captured as regards the capital and the technology level,
still the latter being far from what we wish to target in the matter. The increase of
wages is not at all a sombrous perspective, as it creates the grounds for sustainable
consumption and investments, but it should be adequately correlated with a
reasonable overall number of employees, therefore avoiding high rates on
unemployment.
Given the results obtained, several measures could be forwarded to the
entitled authorities, these being specifically related to the decrease of interest rate,
by more money supply, this leading to a superior degree of consumption and
investments or, in other words, to an increased gross domestic product. Such step,
doubled by firms-oriented stimulating decisions, like tax exemption for the same,
could greatly solve unemployment-related problems. And, above all, technology
quick and significant evolution should be supported by all means, as this is the core
136
mechanism generating, as arising from the impulse-response function analysis,
synergic economic growth.
Acknowledgments
Operational Programme Human Resources Development 2007-2013, project
number POSDRU/159/1.5/S/ 134197 „Performance and excellence in doctoral and
References
Adolfson, M.; Laseen, S.; Linde, J.; Villani, M. (2005). “Bayesian estimation of an
open economy DSGE model with incomplete pass-through”, WPS no.179,
Sveriges Riksbank
Christiano, L.; Eichenbaum, M.; Evans, C. (2005). “Nominal Rigidities and the
Dynamic Effects of a Shock to Monetary Policy”, Journal of Political Economy,
113 (1): 1-45
Christoffel, K.; Coenen, G.; Warne, A. (2007). “Conditional versus Unconditional
Forecasting with the New Area-Wide Model of the Euro Area”, Central Bank
Workshop on Macroeconomic Modelling 2007, Norges Bank
Erceg, C. J.; Henderson, D. W.; Levin, A. T. (2000). “Optimal monetary policy
with staggered wage and price contracts”, Journal of Monetary Economics, 46
(2): 281–313
Griffoli, T.M. (2010). “An introduction to the solution & estimation of DSGE
models”, Dynare v4 - User Guide, Public beta version
Harrison, R.; Nikolov, K.; Quinn, M.; Ramsay, G.; Scott, A.; Thomas, R. (2005). “Bank
of England Quarterly Model”, Bank of England
Hudea (Caraman), O.S. (2013). “DSGE Modelling Architecture. Exemplification of the
Romania Case”, IECS
Hudea (Caraman), O.S. (2014). “Impulse-Response Function Analysis and Forecasts
with a Dynamic Stochastic General Equilibrium Model”, ECECSR Journal, 48(3):
99-121
Kydland, F. E.; Prescott, E. C. (1982). “Time to Build and Aggregate
Fluctuations”, Econometrica, 50 (6): 1345–1370
Rotemberg J.; Woodford, M. (1997). “An Optimization-Based Econometric
Framework for the Evaluation of Monetary Policy”, NBER Chapters, in: NBER
Macroeconomics Annual 1997, 12: 297-361, National Bureau of Economic
Research, Inc
Smets, F.; Wouters, R. (2003). “An Estimated Dynamic Stochastic General
Equilibrium Model of the Euro Area”, Journal of the European Economics
Association, 1(5): 1123-1175
137
Evolution of the Population Expenditure in 2013
Zoica NICOLA, PhD Student
Alexandru URSACHE, PhD Student
Abstract
The main destinations of the expenditure incurred by households are
consumption of food, manufactured goods, services and transfers to private and
public administration and the social security budgets, in the form of taxes,
contributions and contributions, as well as covering needs related to household
production (poultry, animal feed and labor payment for household production,
product deterioration, veterinary services, etc). The structure of the destination
charges included and investment expenditure, consisting in the purchase or
construction of housing, purchase of land and household equipment production,
purchase of shares, etc.
Key words: consumption, services, population expenditure, investment,
evolution.
The total expenditure of households were in 2013, on average, from 2317.4
lei per month per household and 811.3 lei per person, and accounted for 90.6
percent of the total revenues (down 0.1 percentage points from the year 2012). Of
the categories of households considered the highest level of total expenditure, the
average per person (991.8 lei per month), was carried out by salaried households,
and highest income and lowest jobless households (506.0 lei). Low levels and
below average on all households were registered and in the households of workers
on their own in non-agricultural activities, farmers and retires.
The main destinations of the expenditure incurred by households are
consumption of food, manufactured goods, services and transfers to private and
public administration and the social security budgets, in the form of taxes,
contributions and contributions, as well as covering needs related to household
production (poultry, animal feed and labor payment for household production,
product deterioration, veterinary services, etc). The structure of the destination
charges included and investment expenditure, consisting in the purchase or
construction of housing, purchase of land and household equipment production,
purchase of shares, etc.
Spending on household production in 2013, representing 7.5 percent of
total expenditure, of which 0.1 percent had returned money spending, and 6.4
percent value of productive consumption from own resources (feed, seed, etc.) used
for household production. The latter amounted, on average, 148.4 lei a month per
138
household. Taxes, dues, fees, contributions have a large share in the total
expenditure of households whose incomes prevailing wage income. Thus, in 2013,
their share in total expenditure was 26.0 percent for the salaried households,
compared to 11.6 percent for the unemployed, 8.6 percent for households of
retired, 4.8 percent for the workers on their own in non-agricultural activities and
only 2.6 percent in households of farmers. Incidentally, in 2013, the average
amount of transfers under the burden of households of employees was 15.1 times
higher than those paid by farmers, producers of 8.4 times higher than transfers paid
by households for own-account workers in non-agricultural activities, 4.0 times
higher than that of those unemployed and 4.9 times greater than households of
retired. The regional profile, the location of the two regions on the two extremes
(lower and upper): North-East, with the minimum level of this type of expenditure
287.9 lei per month in average per household (13.2 percent of the total
expenditure) and Bucharest-Ilfov, with the maximum level of 666.5 lei (23.7
percent), the rest of the recording levels between 313-429 lei and the total
expenditure weights between 14.8 percent -17.1 percent.
The differences between the level of transfers paid by households in the
different deciles, and share in total expenditures are much higher: the decile
households paid on average a D10 amount of 56 times higher than that paid by
households in the decile D1, the share in the total expenditure of the amount paid
was 28.1 percent D10, and the D1 paid of 1.5 percent.
Expenditure for household production are higher in the case households
which carry on its own resources a significant part of of the consumption needs. In
2013, the most important were those carried out by households of farmers: 611.7
lei per month on average household (30.0 percent of the total expenditure of these
households, on the rise by 0.3 percentage points compared with the previous year).
A relatively high level is recorded and in the case of households pensioners 1781.1
lei (9.6 percent, declining by 1.3 percentage points). Households of employees
spent money for household production on average 2.4 percent of the total
expenditure, and, in the case of those of self-employed persons and unemployed
persons 7.1 percent, question 3.7 percent.
Investment spending grew, on average, across all categories of households
surveyed, almost negligible levels. In the year 2013, their share in total expenditure
was only 0.6 percent, and the region has varied between 0.1 percent and 1.3 percent
of the total expenditure.
• The total expenditure of households include two components of a different
nature: money and spending the equivalent of consumption from its own resources.
Financial expenses include expenses for the purchase of goods and services
for consumption and those used for household production, for investment, for the
payment of taxes, contributions, membership fees, and other expenses. The average
level of money spending in 2013, was of 1940.3 lei per a household and 679.3 lei
per person, and their share in total expenditure represented, on average, 83.7
139
percent households as a whole, increasing by 1.0 percentage points compared to the
year 2012.
Cash expenditures of rural households of 461.4 lei per month per person
amounted to 53.7 percent of the level in urban areas. Their share in total
expenditure of urban households was 93.4 percent, and in rural households of
expenditure 67.9 percent. The regional profile, highest level of money spending,
average per person, was recorded in Bucharest-Ilfov (1020.6 lei, with a share of
96.3 percent of total expenditures), and the lowest in South-West Oltenia (584.3 lei
and 79.0 percent of total expenditures).
For the most part of household expenditure is allocated to the consumer.
The size and structure of household consumption expenditures are direct function
of income levels. But there are other factors that differentiate the level and
structure of consumer expenditures, factors whose effects are aggregated at the
level of households depending on the different features. Total expenditure includes
consumption, in different proportions, two components: purchases on the market,
which means the amount of money and consumption costs from its own resources.
In the year 2013, expenditure on food consumption have held, on all
households, the share of 44.9 percent of total consumer spending, down by 0.2
percentage points compared to the year 2012. Analysis of the dynamics of the
overall expenditure of the actual average monthly consumption per household,
highlights a downward trend (-0.5 percent of households as a whole compared with
the previous year). Of the three categories analysed only those households of wage
earners and own-account workers had a descent (+ 0.8 percent, concerned + 2.5
percent). Dynamics analysis on main elements of real consumer spending shows a
negative trend for the food and non-food products only for dynamic services is in
slight increase (+0.9 percent). Thus, the expenses for food goods had the largest
decline (-1.1 percent), followed by expenditure on foodstuffs (-0.9 percent).
An important factor that distinguishes consumer spending per person in the
household is the household size, concerned the number of persons making up the
household.
Total cost structure of consumption, household size, in 2013
140
Thus, both in 2013, as well as in the previous year, the total expenditure of
the average consumption per person in the household will decrease with the
increase in the number of persons making up the household, that this indicator
calculated for households consisting of 6 and more persons represent 39.0 percent
(39.3 percent in 2012) of those determined for households consisting of one person
and 58.8 percent (60.2 percent in 2012) of the average for all households.
Analysis of the consumption expenditure of households grouped by level
of education of the household head show relatively large differences in level and
structure of expenditure among households where schooling is a primary level and
higher.
Households headed by people with a primary level schooling have a level
of total consumption expenditure less than those with higher education with 1437.8
lei per month. Households headed by persons with secondary education have level
with 527.4 lei more than those driven by people with a primary level of education,
and for households headed by people with higher level have less with 910,4 lei.
This reveals the limited access to resources, especially financial ones, causing a
different structure of consumer expenditures in households led by people with
primary education, compared to those with higher education. In 2013, the first
category of households 55.0 percent of consumption expenditures is allocated for
food consumption and only 16.9 percent for services. Households whose head has a
higher level of schooling has a structure with obvious tendencies of modernization,
with an allocation of 35.7 percent for food consumption and 31.5 percent for
services.
By region, total expenditure of households are close in size average per
household. Exception is Bucharest-Ilfov region, both in the year 2013, as well as in
the previous year, where these are higher with 406.2 lei (372.1 lei in 2012), 24.3
percent respectively (with 23.1 percent in 2012) than the country average. And in
terms of spending on food consumption and those for non-food commodities is a
close relative. Some differentiate are consumer spending for services, the highest
level being reached in Bucharest-Ilfov region, where there are 1.6 times higher than
the country average and 1.9 times higher than those in South-West Oltenia, the
region with the lowest level of expenditure for household services. The structure of
expenditure on the three groups-food, non-food consumer goods and services - is
relative homogenous.
• According to the standard classification by destination of consumer
expenditures (COICOP), food and non-alcoholic drinks have on average 41.4
percent of households in consumption growth by 0.5 percentage points compared
with the previous year.
Another component of consumption, with relatively large share in
expenses, is related to housing. It was assigned to 20.6 percent in consumer
spending, the biggest part of them being absorbed by consumption of utilities
necessary for operation and home heating (water, heat and electricity, natural gas
and other fuels), which largely involve expenditure required for households (16.7
141
percent). Instead, the relevant expenditure of equipping and maintenance of
housing have a much lower (3.9 percent).
There are significant differences between the level of expenditure incurred
for the different component of consumption by households in urban areas and those
in rural areas, caused in part by differences in the pattern of consumption, and the
level and structure of revenues. Thus, if the consumer spending for agri-food
products, alcoholic beverages and tobacco consumption in rural households was
8.3 percentage points higher than that allocated for the same purpose of households
in urban areas, they have spent more than the first from almost all the other
components of consumption.
• The market generally has an especially important role in satisfying all
needs of consumption. She attended almost entirely to the supply of manufactured
goods and services for consumption of the population. In the case of food products,
with purchases from the market, an important contribution to the coverage of the
consumption needs of the agri-food products from its own resources.
• Average monthly expenditure for the purchase of food (including in
catering) were, in 2013, from 522.1 lei per household and 182.8 lei per person.
Expenditures for the purchase of food (including in catering) in the total
expenditure for food consumption-average per household has increased from the
previous year (from 69.0 percent in 2012 from 69.5 percent in 2013), differentiated
by weight categories of households, average residence and regions. Thus, the total
expenditure for food consumption, purchases accounted for more than 75 percent
in households of wage earners (77.2 percent) of urban areas (80.4 percent) and
Bucharest-Ilfov region (being 87.1 percent).
Households as a whole, compared with the previous year, the quantities
purchased were presented to most of the group's main growth products.
• The average monthly level of expenditure for the purchase of manufactured
goods was in 2013, from 495.6 lei per household and 173.5 lei per person. Their
share in overall consumer spending has dropped from the previous year (from 29.9
percent in 2012 from 29.7 percent in 2013).
Categories of producers surveyed the size of spending on non-food goods,
on a monthly average household ranged between 639.1 lei at salaried households
and households of 325.0 lei unemployed, the ratio between those two extremes
being 2.0: 1.
In 2013, with the exception of households of pensioners, all other
categories of households surveyed were allocated for purchase of items of clothes
and shoes over 15 percent of the total amount of expenditure for the purchase of
non-food goods.
The following priorities for the majority of households were linked to the
purchase of cigarettes, tobacco and smoking products, as well as the procurement
and use of means of transport. On the whole, these groups of households
expenditure, together with the clothes and shoes, absorb 49.7 percent of
142
expenditure for the purchase of non-food goods, down by 0.3 percentage points
compared with the previous year.
In the year 2013, in households with 4 and more children were spent for
purchase of non-food goods, per capita, of 3.7 times less than in households
without children. The main destination of them all remains a group of garments
and footwear which absorbs 15.5 percent of the total, the childless households, up
0.5 percentage points compared to the year 2012, tending to 27.4 percent in
households with 4 and more children.
A feature to be highlighted concerns the relatively small discrepancies in
relation to the size of the expenditure for the purchase of non-food products,
between households grouped by area of residence or in a regional profile. Thus, the
ratio between the average spending on a rural farmstead (421.9 lei per month) and
urban (551.6 lei per month) was 1: 1.3. In urban areas, which absorb most of the
costs for the purchase of non-food goods are those items of clothing and shoes and
those for cigarettes, tobacco, and smoking accessories items. Together, they hold a
share of 37.9 percent in total. In rural areas, more than 50 percent of the total
expenditure for the purchase of non-food goods were carried out, both in the year
2013, as well as in the previous year, for the procurement of three groups of goods:
clothing and footwear, fuels (solid and liquid) and cigarettes, tobacco, smoking
articles and accessories (55.3 percent).
By region, the average expenditure for the purchase of non-food goods
presents the highest level in Bucharest-Ilfov region (605.5 lei per month per
household) and lowest in the North-East region (435.1 lei per month per
household).
• In the configuration of the population consumption represents an important
milestone for the assessment of living conditions. Recourse to the use of services to
meet the needs of consumption is closely tied to many factors, among which the
most important are: the purchasing power of money incomes, respectively; the
residence and living conditions; consumer behaviour.
In the year 2013, the entire households, expenditure on various services
have a relatively low weight: 25.4 percent in the total consumer expenditures and
29.4 percent in the total money expenditures consumption.
Health services and education have a relatively low proportion in the total
paid services: health services 4.1 percent, and educations services by 1.6 percent.
Expenses for telephone has the second place as volume and expenditure for
payment of services for households of employes and households of their own
workers, unemployed, farmers and retired, those for electricity.
Territorial plan, region, level and structure of expenditure for services are
less differentiated. In all regions, expenditure on housing-related services have the
highest share, 45.8 percent range in the Northeast and 58.0 percent in BucharestIlfov region.
Two of the services relating to the dwelling, concerned those of electricity
and natural gas, absorbing more than 20 percent of the total expenditure for
143
payment of services in all regions. Services related to housing, along with those of
transport and Telecom, accounts for more than 70 percent of the expenditure for
payment of services in all regions, in the South-East and West of them surpassing
even 80 percent. This means that households in all the regions primary service
charged with the binding, and the financial resources for which they have no
access, except in a very small degree, to a broader range of services.
Households as a whole, in 2013, the economies represented in average per
household 241.7 lei per month, which meant 9.4 percent of total revenues, in the
fall, compared with the previous year with 0.1 percentage points. Situation on the
categories of households analysed shall be submitted as follows: salaried
households have saved on average 11.1 percent of the income of retirees 10.4
percent, the farmers, the 2.9 percent of own-account workers in non-agricultural
activities by 1.6 percent, while the jobless households have made expenses higher
than income registering a deficit of -1.4 percent.
With the exception of households in the first decile, the analysis of the
relationship between income and total expenditure of households broken down by
various features highlights the existence of savings to all types of households,
regardless of distribution. The smallest savings (up to 10 4 percent of total
revenues) have been found in households with 1, 2, 3, 4 and more children (+9.4
percent, +7.5 percent, +2.4 percent, +1.4 percent) in households made up of single
people, four, five, six and more people (+4,9 percent, +8.9 percent, +7.6 percent,
+5.5 percent) in the age groups 15-24 years 25-34 years 35-49 years, 50-64 years
of age (+6.2 percent, +8.8 percent, +9.1 percent, +9,0 percent), those driven by
people with a level of primary and secondary education (+6,3 percent, +8.3
percent), as well as the household head sex distributed (+9.6 percent from those
driven by male persons and +8.7 percent from those run by a woman).
Revenues exceeded expenses by nearly 15 percent only to households
falling in the category of those with higher education level (+14.8 percent).
The difference between income and expenditure of rural households was in
the year 2013, from 5.9 percent, while in urban areas have registered average
savings that accounted for 11.5 percent of total revenues, compared with the
previous year, down 0.5 percentage points in rural areas, meaning 0.4 percentage
points in urban areas. In territorial expenditures have exceeded revenue in all
regions. The savings were recorded between 5-6 percent of total revenues in the
region of the Northeast and 15.3 percent in Bucharest-Ilfov region.
The total number of households, reported amounts for some of the
households they have saved by using them for repayment of credits and loans in
order to lend other households or that they have deposited in banks, are larger with
about 81.6 lei a month on a farm than those who entered the household budgets in
the form of loans, savings withdrawals, etc. In average per household, the latter
accounted for represented 106.6 lei monthly, meaning 4.2% of total revenue.
To all categories of households analyzed, the amount inputs resulting from
credit operations to participating households is less than the amount of withdrawals
144
incurred as a result of these operations. With all that, on average on all households,
The balance these flows is negative (-81.64 lei monthly income per household),
which together with the balance balance revenue and expenditure ( 160.01 lei)
consists of increasing with 78.37 lei, on average per household, the balance in cash
in households.
References
Anghelache C. şi alţii (2014) – „Evolution of the Inflation and Price
Index”,Romanian Statistical Review, Supplement no. 7/2014, pp. 48-52
Anghelache C. şi alţii (2014) – „International Exchange of Goods and
Services”,Romanian Statistical Review, Supplement no. 7/2014, pp. 90-97
Anghelache C. şi alţii (2014) – „The Evolution of the Index of Population
Consumption Prices”,Romanian Statistical Review, Supplement no. 4/2014, pp.
98-107
Anghelache C. şi alţii (2014) – „The Analysis of the Production of Goods for the
Population”,Romanian Statistical Review, Supplement no. 4/2014, pp. 151-155
Anghelache C., şi alţii (2012) – „Metode de măsurare şi analiză a inflaţiei”,
Editura Economică, Bucureşti
Anghelache C.; şi alţii (2012) – „GDP and the Final Consumption of Romania.
Evolution and Correlation in the Last Decades”, Metalurgia International nr.8,
p.158 ISSN 1582-2214, Editura ştiinţifică F.M.R., revistă citată în bazele de
date internaţionale SCOPUS, EBSCO, THOMSON SCIENTIFIC MASTER
JOURNAL LIST, Sci Search
Anghelache C şi alţii (2012) – „The Inflation and Industrial Production Costs”,
Metalurgia International, nr. 5/2012, pp. 175-178, ISSN 1582-2214 , Editura
ştiinţifică F.M.R., revistă citată în bazele de date internaţionale SCOPUS,
EBSCO, THOMSON SCIENTIFIC MASTER JOURNAL LIST, Sci Search
145
An Overview of the Construction Materials
Manufacture Sector at Six Years after the start of
Economic Crisis in Romania
Lecturer Adrian ANICA-POPA PhD
Abstract
The objective of the research is the analysis of the actual status of the
manufacture of construction materials. In the last six years, real estate developers,
companies that offer construction materials and construction companies
experienced a regress, following the start of the economic crisis at the end of 2008.
The study has as purpose the identification of correlation between the economic
conjecture identified at national level and the evolution of the sector of
construction materials manufacture. There have been emphasized the unfavorable
effects of economic crisis on the field of construction materials production.
Key words: economic crisis, construction materials production industry,
performance
Introduction At the level of the real estate market, the construction field and
construction materials industry, these effects were deeply felt since the fourth
trimester of 2008, when, on the background of international financial crisis, the real
estate market recorded a block and even a decrease, with repercussions for real
estate agencies and developers. The immediate effects were felt also in the
construction companies and producers of construction materials, by reduction of
activities and implicitly by decrease of performances at the level of the firm.
Of the studies made and results recordered at the level of activity fields, it
has been observed that the main channels of expansion of the crisis are represented
by the financial one – with restraint of access to credit by limiting external
financing, by the commercial one: the slower increase or even reduction of exports
and the exchange ratio one – depreciation of the national currency
Romania’s construction materials manufacturing sector
Before 2008, we were used to characterize constructions as the most
dynamic sector of the economy, a normal conclusion following a really fulminant
evolution, but followed by a decrease that started in January 2009 and then
continued during the subsequent period.
146
Currently, the greatest part of construction materials, some 60% - 70%, are
manufactured in Romania. This is the reason for which we wish to do now an
analysis of the construction materials manufacturing sector.
The turnover achieved at the level of enterprises in construction materials
industry, in Romania it has recorded a major decrease following the start of the
financial crisis, at the end of 2008. Therefore, in 2010 the turnover was by 10%
lower than the value recorded in 2008 for the subsector Manufacture of other
porcelain and ceramic products, and by some 43% lower for Manufacture of clay
building materials și Manufacture of articles of concrete, cement and plaster.
Table 1. Evolution of Turnover in 2008-2012- mil. eur
Symbol
231
232
233
234
235
236
237
239
23
Name of industry
Manufacture of
glass and glass
products
Manufacture of
refractory products
Manufacture of clay
building materials
Manufacture of
other porcelain and
ceramic products
Manufacture of
cement, lime and
plaster
Manufacture of
articles of concrete,
cement and plaster
Cutting, shaping
and finishing of
stone
Manufacture of
abrasive products
and non-metallic
mineral products
n.e.c.
Manufacture of other
non-metallic mineral
products
2008
2009
2010
2011
2012
356,6
256,4
265,9
276,2
258,2
45,2
22,5
25,4
25,6
28,7
203,3
140,1
149,4
153,5
149,9
150,5
116,8
134,8
143,5
142,1
1.108,7
714,4
629,7
648,5
642,8
1.667,9
1.022,4
990,3
1.041,7
1.047,4
77,9
62,5
52,8
54,0
52,3
290,2
164,2
209,4
236,6
233,5
3.900,3
2.499,3
2.457,7
2.579,6
2.554,9
The comparative analysis of data recorded for Romania during the period
2005-2012, it is observed a major gap until 2010, then a period of relative stability
until 2012. At the end of the analyzed period, a turnover is reached that is similar to
values recorded in 2005-2006 for the sectors Manufacture of glass and glass
products, Manufacture of cement, lime and plaster and Cutting, shaping and
finishing of stone, the only exception being Manufacture of articles of concrete,
147
cement and plaster where the turnover was by 38,36% higher. These differences
were given by the expansion of the real estate sector during the period 2005-2008.
Figure 1. Turnover, by activities in 2005-2012
The prices of construction materials increased very much during the period
that preceded the financial crisis, depending on segments. Thus, the price of
cement grew by some 20% in 2008 as against 2007 and by 45% as against 2006.
The price increase for raw materials, along the doubling of salaries in constructions
across the aforementioned period, were the main factors that have influenced the
final cost of construction materials. In conditions of stagnation of real estate
market, caused by the global financial crisis, companies producing construction
materials have started in 2009 to practice a policy of price reduction.
From the point of view of the industrial production for the sector
Manufacture of other non-metallic mineral products, a significant decrease is
recorded in 2009 (-34,99). The evolution of this indicator is similar to the turnover.
Thus, at the end of the period analyzed, there is a reached level of 66,33% out of
the value for 2008.
Table 2. Evolution of Production value in 2008-2012 – mil. eur
Symbol
231
232
233
234
148
Name of industry
2008
Manufacture of glass and
glass products
Manufacture of refractory
products
Manufacture of clay
building materials
Manufacture of other
porcelain and ceramic
2009
2010
2011
2012
343,5
241,3
245,8
258,8
251,4
37,0
23,5
24,9
25,8
28,8
226,3
126,2
151,3
160,0
142,2
146,3
111,0
123,1
139,7
138,6
Symbol
Name of industry
2008
2009
2010
2011
2012
products
235
236
237
239
23
Manufacture of cement,
lime and plaster
Manufacture of articles of
concrete, cement and
plaster
Cutting, shaping and
finishing of stone
Manufacture of abrasive
products and non-metallic
mineral products n.e.c.
Manufacture of other nonmetallic mineral products
1.131,8
804,9
720,4
769,6
712,8
1.572,3
947,3
862,8
933,9
973,1
72,9
55,6
51,5
54,4
47,7
255,5
151,1
177,3
207,6
216,4
3.785,6
2.460,9
2.357,1
2.549,8
2.511,0
As for the other indicators, previously analyzed, the added value recorded
at the level of companies acting in the sector Manufacture of other non-metallic
mineral products has experienced a significant regress. This decrease was given by
the substantial modification of five sub-sector, with values ranging from „-40%” to
„-55%”, with the exception of only three sub-sectors: Manufacture of refractory
products (-13,64%), Manufacture of other porcelain and ceramic products (7,28%) şi Manufacture of abrasive products and non-metallic mineral products
n.e.c. (-22,39%).
Figure 2. Evolution of value added in 2012 as against 2008 (%)
From the viewpoint of the operational profit, during the period 2008-2009
decreases can be seen for most sectors, exceptions being Manufacture of other
porcelain and ceramic products, where increase is really recorded both in 2009 and
2010. This situation was reached, on one hand, because of the decrease of sales
volume and selling price, and, on the other hand, because there was not possible to
149
reduce the expenses in the same manner, taking into account the existence of fixed
costs.
Table 3. Evolution of the operational profit 2008-2012 – mil. eur
Symbol
Name of industry
2008
2009
2010
2011
2012
231
Manufacture of glass and glass
products
58,5
35,8
39,6
43,7
29,1
232
Manufacture of refractory products
-0,2
0,9
4,0
2,4
1,5
233
Manufacture of clay building materials
Manufacture of other porcelain and
ceramic products
Manufacture of cement, lime and
plaster
Manufacture of articles of concrete,
cement and plaster
61,3
29,6
39,9
34,1
23,2
10,2
13,1
15,0
14,0
12,7
432,4
327,7
299,5
280,8
219,8
301,2
162,0
150,7
119,0
126,9
14,3
8,4
9,6
-3,0
3,6
59,6
45,9
45,8
50,3
44,8
937,3
623,4
604,1
541,3
461,6
234
235
236
237
Cutting, shaping and finishing of stone
Manufacture of abrasive products and
non-metallic mineral products n.e.c.
Manufacture of other non-metallic
mineral products
239
23
By correlating the evolution of the turnover to the operational profit one we
come across other indicator that emphasizes the changes occurred in the sector of
construction materials manufacture, that is the commercial profitability ratio.
Table 4. Evolution of the commercial profitability ratios in 2008-2012
Symbol
231
232
233
234
235
236
237
239
23
150
Name of industry
products
products
Manufacture of clay building
materials
Manufacture of other porcelain
and ceramic products
Manufacture of cement, lime
and plaster
concrete, cement and plaster
Cutting, shaping and finishing
of stone
Manufacture of abrasive
products and non-metallic
mineral products n.e.c.
mineral products
2008
2009
2010
2011
2012
16,40%
13,96%
14,89%
15,82%
11,27%
-
4,00%
15,75%
9,38%
5,23%
30,15%
21,13%
26,71%
22,21%
15,48%
6,78%
11,22%
11,13%
9,76%
8,94%
39,00%
45,87%
47,56%
43,30%
34,19%
18,06%
15,85%
15,22%
11,42%
12,12%
18,36%
13,44%
18,18%
-
6,88%
20,54%
27,95%
21,87%
21,26%
19,19%
24,03%
24,94%
24,58%
20,98%
18,07%
This indicator too suffers a decline at the level of the entire industry, by
some six percentage points. In detail, we observe that for certain sub-sectors, the
years 2009 and 2010 brought forward an increase of the commercial profitability
ratio, with as much as 7,42 percentage points in 2009 for Manufacture of abrasive
products and non-metallic mineral products n.e.c., respectively by 11,75
percentage points in 2010, for Manufacture of refractory products.
At the end of 2008 there were 3.151 companies recorded in this activity
sector. The financial problems, the contraction of the market and the increase of
pressure from competition has determined the closure of many companies,
reaching in 2012 a total of 2.411 firms (decrease by 23,41%).
Table 5. Number of enterprises in 2008-2012
Symbol
231
232
233
234
235
236
237
239
23
Name of industry
products
materials
Manufacture of other porcelain and
ceramic products
plaster
Manufacture of articles of concrete,
cement and plaster
Cutting, shaping and finishing of
stone
Manufacture of abrasive products
and non-metallic mineral products
n.e.c.
mineral products
2008
2009
2010
2011
2012
603
577
479
432
427
38
30
33
28
30
314
250
190
147
171
203
190
162
137
143
67
60
51
48
45
1.333
1.314
1.115
997
1.010
511
543
510
473
489
82
101
99
97
96
3.151
3.065
2.639
2.359
2.411
As it can be observed from the previous table, in 2012, most companies in
the production are to be found in the sub-division Manufacture of articles of
concrete, cement and plaster (41,89%), followed Cutting, shaping and finishing of
stone (20,28%) and Manufacture of glass and glass products (17,71%). In the other
sub-divisions of productive activities, in total, some 20,12% of total companies are
acting.
The evolution of the number of employees is an indicator that follows the
economic evolution of any activity sector, meaning that the contraction of the
activity volume has negative effects on the labor market.
151
Table 6. Number of employees in 2008-2012
Symbol
231
232
233
234
235
236
237
239
23
Name of industry
products
products
materials
Manufacture of other porcelain
and ceramic products
plaster
concrete, cement and plaster
Cutting, shaping and finishing of
stone
Manufacture of abrasive products
and non-metallic mineral products
n.e.c.
mineral products
2008
2009
2010
2011
2012
9.412
7.284
6.676
6.656
6.608
1.333
973
965
967
763
6.758
4.302
3.445
3.316
3.062
7.883
6.226
5.954
6.311
6.256
4.040
3.805
3.524
3.060
2.904
21.721
18.637
15.511
16.469
15.927
3.372
2.986
2.685
2.811
2.679
2.957
2.597
2.381
2.533
2.582
57.476
46.810
41.141
42.123
40.781
The number of employees in construction materials manufacturing has
reached, at the end of 2012, the level of 40.781 thousand persons, after the
companies made over 16.500 firing decisions since 2009. Still, in 2011 982 jobs
were created, but this value is not significant compared to the figures from the
previous years.
Figure 3. Indices of average yearly productivity of labor during the period
2009-2012
152
The analyzed data emphasize the fact that, overall, the productivity of labor
records increases. The values for the indicators of labor productivity, calculated as
against the previous year, are reasonable, if we take into account the fact that
Romanian economy was and is still affected by the economic crisis. By making an
analysis in parallel with the evolution of annual average salary, it can be observed
that the correlation between these two elements was not always respected, as
salaries recorded a more accentuated increase at some moments, compared to the
evolution of labor productivity. By respecting these correlation, there would be
secured permanently the efficiency of salary expenses, and by respecting the
correlation between the growth index of salary expenses and index of employees’
number increase, the growth of average salary will be ensured. Respecting the
correlation between the increase of labor productivity and average salary reflects
itself in the decrease of salary expenses per 1000 lei turnover.
Table 7. Salary expenses per 1000 lei turnover in 2008-2012
Symbol
231
Name of industry
Manufacture of glass and glass products
2008
2009
2010
2011
2012
104,6
106,9
95,9
96,7
102,6
232
119,5
173,3
165,4
152,3
115,0
233
Manufacture of clay building materials
Manufacture of other porcelain and ceramic
products
150,5
141,3
114,5
117,3
116,1
227,9
212,3
201,8
212,5
205,5
43,9
60,6
62,4
58,3
56,5
234
235
236
237
239
23
Manufacture of cement, lime and plaster
Manufacture of articles of concrete, cement
and plaster
Cutting, shaping and finishing of stone
Manufacture of abrasive products and nonmetallic mineral products n.e.c.
Manufacture of other non-metallic mineral
products
70,4
92,0
82,6
82,5
79,8
134,8
132,8
149,6
220,4
145,3
66,2
88,9
67,3
67,6
69,0
77,8
94,5
88,3
89,4
86,1
Based on the data in the previous table, we reach the conclusion that,
generally, in 2009 there was a decrease of salary expenses efficiency (except the
sectors Manufacture of clay building materials, Manufacture of other porcelain
and ceramic products and Cutting, shaping and finishing of stone), after which,
due to the decrease of staff number, there was recorded a successful approach to
the values recorded at the start of the analyzed period.
Conclusions
The analysis of information gathered for the period 2008-2012 emphasizes
a relative stability of the industrial production and a recovery of the potential of the
153
construction materials industry of Romania to produce, at the proper qualitative
level and structure of products necessary in the European economy. There was
recorded a major decline of activity in 2008-2010, followed then by a slight
increase, but without go over the values recorded in 2008. For certain indicators, in
2012, there were recorded values similar to the ones corresponding to the period
before the economic crisis, which is 2005-2006.
The crisis triggered at the end of 2008 led to the decrease of activity
volume, the fall of commercial profitability ratios, the disappearance from the
market of 700 companies and the firing of more than 16.500 employees.
There still are premises regarding the possibility of recovery for industrial
activity, especially in the private sector. The issue is complex and therefore must
be analyzed with maximum urgency in the idea to find solutions regarding the
stabilization of those sub-branches of construction materials industry that are of
national interest and can be taken into account for the European market.
References Anghelache, C. (2013) – „România 2013. Starea economică sub povara efectelor
crizei” , Editura Economică, Bucureşti
Anica-Popa A.; Manole A.; Barbu C., Aprovizionarea internă vs. aprovizionarea
externă în industria fabricării materialelor de construcţii, Revista Română de
Statistică- Supliment, nr. 12, 2009
Anica-Popa A., Oancea-Negescu M. D., Cişmaşu I. D., Industria materialelor de
construcţii între mărire şi decădere, Revista Română de Statistică, Supliment,
Nr. 7, iulie 2009 nr. 12, 2009
Eurostat: http://epp.eurostat.ec.europa.eu
www.insse.ro
154
The Influence of Atmospheric Methane on Human
Health
Assistant Cristina Stirbu PhD Student
Abstract
In this article we try to determine whether there is a relation between the
quantity of athmospheric methane and the number of diseases of circulatory
system, at the level of the whole country.We first analyze the time series of the
quantity of pollutant between 1990 and 2008 and then we predict the values for the
years 2009-2012. In the end we calculate the correlation coefficient between the
polution and the number of circulatory system diseases.
Key words: Time series, trend, seasonal deviation, least square method,
correlation coefficient.
The methane, the main component of natural gas, is used in domestic
economy for cooking and central heating, and in the same time is largely consumed
in industrial processes, thus a large quantity of this compound is released into
atmosphere. Methane is a colourless and odourless gas and also toxic for human
organism. Released into atmosphere, it contributes to global warming, in a higher
proportion than CO2, although the life time of CH4 is shorter than that of carbon
dioxide.
In this article we tried to emphasize the effect that methane has on human
body, respectively on how it influences the circulatory system diseases occurrence.
The values measured in tones for the pollutant quantities, between years
1990 and 2008, are presented in table 1. We collected the data from the National
Statistical Insitution site, and the calculations were made using Excel 2003.
Regarding data analisys, we operate with time series, and we addopt the
following additive model:
y =t+S +r
(1)
where:
y is a known value of the time series ;
t is the trend ;
S is the seasonal component;
r is the residue ;
155
The evaluation and interpretation of the three components is made with
detailed analysis. Each component will be treated separatelly.
Regarding the trend, this will be evaluated by the least square method,
using a linear adjustment.
t = ax + b
(2)
where the coefficients a and b are calculated by the formulas :
a=
nΣxy − ΣxΣy
nΣx 2 − (Σx )
2
(3)
and
b=
Σy
Σx
−b
n
n
( 4)
Using the values from table 1, we get :
a=-27187,9973 and b=1628409,5.
To obtain the trend values, we replace the x values of time instants into
equation (2) .
Table 1
x
(year)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
190
156
y
CH4 (tons)
1931957,22
1695267,42
1532579,05
1448614,96
1400681,89
1460324,24
1487613,12
1312724,74
1200511,99
1168105,07
1196917,6
1189067,15
1227544,31
1277007,78
1249915,59
1260126,89
1275081,88
1235956,5
1224062,87
25774060,27
xy
x2
1931957,22
3390534,84
4597737,15
5794459,84
7003409,45
8761945,44
10413291,84
10501797,92
10804607,91
11681050,7
13166093,6
14268805,8
15958076,03
17878108,92
18748733,85
20162030,24
21676391,96
22247217
23257194,53
242243444,2
1
4
9
16
25
36
49
64
81
100
121
144
169
196
225
256
289
324
361
2470
t
(Trend)
1601221,464
1574033,466
1546845,469
1519657,472
1492469,474
1465281,477
1438093,48
1410905,482
1383717,485
1356529,488
1329341,491
1302153,493
1274965,496
1247777,499
1220589,501
1193401,504
1166213,507
1139025,51
1111837,512
y-t
330735,7564
121233,9537
-14266,41898
-71042,51168
-91787,58439
-4957,237088
49519,64021
-98180,74249
-183205,4952
-188424,4179
-132423,8906
-113086,3433
-47421,186
29230,2813
29326,0886
66725,38589
108868,3732
96930,99049
112225,3578
We further determine the seasonal component. To this end, we first divide
the time interval of 19 years into 5 periods; the first 4 periods of 4 years each, and
the last one of three years. We will follow the steps:
• We calculate the y-t values (we subtract the trend from the known y
values) for each time instance (for each year);
• We determine the arithmetic mean for each of the five periods ;
• If the sum of all arithmetic means is different from zero, we adjust one or
more means for the total to be zero.
As we can see from table 2 in which we made these calculations, the sum
of the arithmetic means of the five periods is very close to zero, so it is
insignifficant and we can take it as zero.
Table 2
Period1
Period2
Period3
Period4
Period5
Total
Arithmetic
means
Sum
year1
330735,7564
-91787,58439
-183205,4952
-47421,186
108868,3732
117189,864
29297,46601
The seasonal deviation S
year2
year3
121233,9537
-14266,41898
-4957,237088
49519,64021
-188424,4179
-132423,8906
29230,2813
29326,0886
96930,99049
112225,3578
54013,57053
44380,77702
13503,39263
11095,19425
year4
-71042,51168
-98180,74249
-113086,3433
66725,38589
0
-215584,2116
-53896,05289
-5,82077E-10
We further filter the time series using the deviations on each period, see
table 3 :
Table 3
period
year
y
S
1
1
2
3
4
1
2
3
4
1
1931957,22
1695267,42
1532579,05
1448614,96
1400681,89
1460324,24
1487613,12
1312724,74
1200511,99
29297,46601
13503,39263
11095,19425
-53896,05289
29297,46601
13503,39263
11095,19425
-53896,05289
29297,46601
2
3
Filtered values on
each season(y-s)
1902659,754
1681764,027
1521483,856
1502511,013
1371384,424
1446820,847
1476517,926
1366620,793
1171214,524
157
period
4
5
year
y
S
2
3
4
1
2
3
4
1
2
3
1168105,07
1196917,6
1189067,15
1227544,31
1277007,78
1249915,59
1260126,89
1275081,88
1235956,5
1224062,87
13503,39263
11095,19425
-53896,05289
29297,46601
13503,39263
11095,19425
-53896,05289
29297,46601
13503,39263
11095,19425
Filtered values on
each season(y-s)
1154601,677
1185822,406
1242963,203
1198246,844
1263504,387
1238820,396
1314022,943
1245784,414
1222453,107
1212967,676
We calculate the rezidual deviation r by the formula r=y-t-S (see table 4).
Table 4
Period
1
2
3
4
5
TOTAL
158
Year
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
y
1931957,22
1695267,42
1532579,05
1448614,96
1400681,89
1460324,24
1487613,12
1312724,74
1200511,99
1168105,07
1196917,6
1189067,15
1227544,31
1277007,78
1249915,59
1260126,89
1275081,88
1235956,5
1224062,87
25774060,27
s
29297,46601
13503,39263
11095,19425
-53896,05289
29297,46601
13503,39263
11095,19425
-53896,05289
29297,46601
13503,39263
11095,19425
-53896,05289
29297,46601
13503,39263
11095,19425
-53896,05289
29297,46601
13503,39263
11095,19425
53896,05289
t
1601221,464
1574033,466
1546845,469
1519657,472
1492469,474
1465281,477
1438093,48
1410905,482
1383717,485
1356529,488
1329341,491
1302153,493
1274965,496
1247777,499
1220589,501
1193401,504
1166213,507
1139025,51
1111837,512
25774060,27
y-t-s
301438,2904
107730,5611
-25361,61323
-17146,45879
-121085,0504
-18460,62972
38424,44596
-44284,6896
-212502,9612
-201927,8105
-143519,0848
-59190,29041
-76718,65201
15726,88867
18230,89435
120621,4388
79570,90718
83427,59786
101130,1635
-53896,05289
The residual deviation is small compared to cumulated values of variable
y, so we can make prognosis based on presented data. (The data prognosis for a
future period can be done only if we have results for at least three past cycles).
The previsioned values for the pollutant in the next 4 years, 2009-2012, are
obtained with the aid of the relation :
y forecast = t forecast + S
(5)
Where :
yforecast are the estimated values
tforecast are the estimated values for the trend
S is the seasonal component
Table 6
trend t
S
Y
1601221,464
29297,46601
1931957,22
1574033,466
13503,39263
1695267,42
1546845,469
11095,19425
1532579,05
1519657,472
-53896,05289
1448614,96
1492469,474
29297,46601
1400681,89
1465281,477
13503,39263
1460324,24
1438093,48
11095,19425
1487613,12
1410905,482
-53896,05289
1312724,74
1383717,485
29297,46601
1200511,99
1356529,488
13503,39263
1168105,07
1329341,491
11095,19425
1196917,6
1302153,493
-53896,05289
1189067,15
1274965,496
29297,46601
1227544,31
1247777,499
13503,39263
1277007,78
1220589,501
11095,19425
1249915,59
1193401,504
-53896,05289
1260126,89
1166213,507
29297,46601
1275081,88
1139025,51
13503,39263
1235956,5
1111837,512
11095,19425
1224062,87
1084649,515
29297,46601
1113946,981
1057461,518
13503,39263
1084468,303
1030273,52
11095,19425
1052463,909
1003085,523
-53896,05289
949189,4701
Ciculatory System
diseases
(thousands cases)
427
445
459
471
486
492
507
543
614
646
608
625
560
682
609
657
682
713
642
607
159
The last 4 values from the trend column were estimated by the “trend”
function from Excel, which calculates the forecast values with the aid of least
squares method. In the column of y, of the pollutant, the values recorded by year
2008 were kept, and from the year 2009 until year 2012 the values were calculated
by formula (5).
The correlation coefficient between the pollutant and the number of
diseases, has the value -0,67380708, and it is calculated by formula (6).
We thus found a strong relation between the polution and the number of
diseases: although the emission of gas has a slow decrease, the number of sick
persons increases. We can visualize that in the graphs below.
ρ=
nΣxy − ΣxΣy
nΣx − (Σx )
2
(6)
nΣy 2 − (Σy )
2
2
CH4
Cantitate (tone)
2500000
2000000
1500000
1000000
500000
0
1
2
3
4
5
6
7
8
9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
Anii
CH4
Numar persoane (mii)
Numar de imbolnaviri
800
600
400
200
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15 16
17
18
19
20
Anii
Numar de imbolnaviri
160
References
Andy Francis “ Business Mathematics and Statistics 4th edition”, Editura Tehnica
2005;
Emilia Titan “Statistica.Teorie. Aplicatii in sectorul tertiar” , Editura Meteor Press;
www.insse.ro.
161
162
Negotiation team – a brief technical overview
Assoc. prof. Dragoş Gabriel MECU PhD
Abstract
Negotiating team is actually part of the preparation of the negotiation and
its role is solving all problems arising, evaluation, argumentation and counterargumentation, explanation etc.
It is almost impossible that one man could fulfill all preparation
requirements of the negotiation, it is recommended to build a team.
The effectiveness of the negotiating team is not given by the number of its
members, but by socio-professional training of each member, the mobility and
flexibility of their thinking, the organization and coordination of activity.
Key words: negotiation, mandate, authority, team, personal skills
All team members must know and involve in solving specific problems
related to the negotiations that will take place. Team members are charted and
distributed according to the qualities of each, to well-defined objectives that are
designed to be performed. Particularly important is the timing of the activities of
each team member and their coordination. It is preferable to provide continuity for
the team members to know eachother over time and ensure a stable working
relationship. It is also necessary a proper elasticity to the team, allowing
modification of the membership, effective leadership and ownership of all
responsibilities. Each team must have a leader, and his choice is to take account of
factors such as:
- Meeting the required quality of all team members;
- Ability to lead and organize;
- His position within the organization;
- The degree of responsibility and decision he can take in conjunction with
the mandate received;
- Psychological relationship with his team members, defining a main active
cooperation.
One such team leader will have some work to do, including:
- To select and prepare team members;
- Carry out the plan and the draft contract negotiation;
- To take care of the reception office;
- To organize and conduct effective negotiations;
- To complete agreement with our partners;
163
- To support the morale of team members;
- Obtain the maximum contribution from each team member.
Once formed, such a negotiating team has to fulfill certain tasks, since its
formation and until the submission of the report for completion of action assigned.
Those tasks are:
- Develop technical and commercial material;
- Securing the communication links;
- Develop negotiated plan;
- Participation in the development of the negotiating mandate;
- Develop draft contract;
- Develop and launch offer, where appropriate;
- Participation in the specific psychological preparation;
- Participation in debate.
After establishing these tasks, the team training is performed according to
the work style of the management team.
We know, in this respect, two types of leaders:
• authoritarian style - type of leader who keeps everything to himself
• communicator style - type of leader very open in terms of delegation of
authority.
Negotiating team behavior is the most important factor to achieve the
desired objective, as it does the preparation of negotiations, which has no effect
when it fails to establish effective communication between partners. Behaviour
refers to each situation and is subject to well-defined principles and rules, which if
followed, greatly increase the chances of success.
Such behavior implies the following rules:
- Careful preparation of the meeting with the partner. Even if in the debate
the team leader plays the main role, ultimately, each member can participate in the
debate, the analysis of issues.
- Knowledge of psychology and personality of the negotiator. It must be
known the fact that every individual with a thorough training with normal moral
conduct can become a good negotiator.
- Cultivate resilience thinking, presence of mind, ability, spirit of
observation and cooperation.
- Education of will and self-control that leads to perseverance, boldness, to
self-control of "delicate" situations.
A good negotiator is not ever allowed to get angry, he must remain calm,
and be patient.
- Abandon preconceptions about the behavior of the partner. Psychological
methods are used for determining the partner's personality (eg, rationalization,
projection, self-image and others).
- Self preservation and respect of partners. It creates a pleasant working
atmosphere, as long as no exaggeration to ridiculous is made.
164
- Combat reproaches. It is said that the lack of response to an accusation in
the form of criticism can be interpreted as an admission of the accusation made.
- Educate willingness to listen - leaving partner to exhaust all arguments
without being interrupted. Interruption of the partner may provoke discontent,
charging the atmosphere, but silence can lead to despair of the partner, so the
middle point must be found between the two attitudes.
- Maintain dignity, not to be confused with arrogant pride of a poorly
educated individual. The distortion of dignity leads to humiliation, to
subordination, loss of mutual benefit and ultimately compromise the negotiation.
- Express joy - is made with restraint to not lead to withdrawal of bids by
partner, with the impression that he was wrong.
- Elasticity of partial decisions, assumptions and variants thereof. Until
final signing of the contract, no agreement is decisive or intangible.
- Coordination of interventions by the team leader. Interventions are done
in an organized manner, to avoid any mistakes.
- Breakdown of negotiations and postpone them is better not to be made
sudden, but in an elegant form.
- Negotiating partner's care. It assumes that the negotiation must be
concluded, leading to its failure is in fact double failure for both partners. But one
should not take advantage of any situation, neither partner should be allowed to
make mistakes due to ignorance, so that that future business may be totally
compromised.
Management principles suggest that a leader operating in dramatic and
changeable conditions - such as those in the negotiations - can effectively control
only 3-4 people. If the team leader should lead the negotiations and at the same
time to lead a team of 6-7 people, then one will not be able to cope with both tasks
properly. The range of expertise required in negotiations lasting many months can
be quite large, in this case the analysis of more than 20 different views for each
team. However, whatever the view, one meeting will not made possible to analyze
more than three to four perspective. Where detailed discussions will be needed,
however, a team should consist of a leader and 3-4 members. For example, one will
handle production issues may not have enough information about the expansion
plans, the supply of materials or technical details, in this case will need real time
support. This could arrange a sub-negotiation: a subgroup consisting of one
member of the negotiating team assisted by 3-4 specialists who can meet and
negotiate separately with a sub-group of the other, independent of the basic
negotiation. Then, these specialists will report the results of basic negotiating team.
How can be described the ideal leader for a team of negotiators?
It is very a important "caliber" team leader. He or she must be the same
caliber team leader than the counterpart. If there is no equal caliber, and therefore
negotiation skills are at the same level, then the team will be dominated, led by a
defensive attitude, aggressive counter, or even risk being overwhelmed
165
Beyond the issue size and style of the leader do matter. In this respect there
is a work style that is preferred. It is important for the team to work together
effectively, and it also depends on the ability of its members to act in the style
proposed. If we are in a business in which all information is held by a single chief,
who assume all managerial decisions, the negotiating team will have the same type
of leader. It shall be responsible for discussion during negotiations, turning to team
members - just asking for advice about how many situations within and solving
them, which then will be negotiated.
On the other hand, if we stand in a company where management is
distributed, then the leader will be one who will control the negotiation process
more freely, encouraging team members to have major contributions in the talks.
Team leader's style should reflect the style of the organization he
represents, and there is no style that can be called "perfect". This role can be played
equally by well-trained people in financial, commercial fields, or coming from the
production. Preferably would be, however, the people with commercial background
to lineup in place of the technical format. The best negotiators often come from
those who have spent their early years of training in the commercial world and not
in the university.
The negotiations involve a number of special powers from the society,
which usually assume the existence of a negotiating mandate. The negotiating
mandate includes limits within which the negotiator can act. These limits are the
maximum and minimum, and the negotiator can decide only within their premises.
Most negotiations do not bear the full participation of those in authority managers of - but through intermediaries empowered with full authority by the
bosses. In most cases, where negotiations are conducted by individuals with full
authority its purpose can not be reached because of overvaluation.
It is therefore recommended that negotiations be conducted by those who
have limited authority. They act on behalf of one over whose decision they can not
pass, which enables them to do pretty much work.
Upward Authority is an escalation of authority actually placing approval at
higher hierarchical levels. This tactic gives results only when it is well prepared
and supported by a strategic negotiator who is professionally prepared, mentally
strong, able to cope.
References
Dupond, C., La negociation. Conduite, theorie, applications, Dallor, Paris, 1990
Montague-Smith, P.,Debrett’s Correct Form, revised edition, London, Headline,
1992
Stubbs, R., Underhill, G., Political Economy and the Changing global Order,
Second Edition, Oxford University Press, Oxford, 2000
Vermette, J., Cloutier, R., La parole en public, Sainte-Foy, Les Presses de
l’Université Laval, 1992
166

revista română de statistică - Romanian Statistical Review

Transcription

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