Works Councils and Personnel Turnover Alexander Dilger

DISCUSSION
PAPER SERIES
IN ECONOMICS
AND MANAGEMENT
Works Councils and Personnel Turnover
Alexander Dilger
Discussion Paper No. 03-04
GERMAN ECONOMIC ASSOCIATION OF BUSINESS
ADMINISTRATION - GEABA
Works Councils and Personnel Turnover
Alexander Dilger*
Note: This paper is based upon one chapter of my habilitation thesis (Dilger 2002) in German.
Abstract
According to theoretical arguments and previous empirical studies, works councils reduce
personnel turnover. This result is confirmed by an empirical examination of the NIFA-Panel
containing information on the production area of German mechanical engineering plants.
Furthermore the effects of the introduction or closure of a works council are considered for
the first time. The same is true for different types of works councils. In particular, cooperative relations between management and works council foster a lower personnel turnover.
Thus, this lowered turnover has to be in the common interest of employees and employers.
JEL-Codes: J53, J63, M51, M54, L64, C20
Keywords: Co-determination, Labour-Management Relations, Labour Turnover, Works
Councils
*
Visiting Prof. Dr. Alexander Dilger, University of Vienna, Institute of Business Administration, Bruenner
Strasse 72, A-1210 Vienna, Austria, Phone: +43-1-4277-38127, Fax: +43-1-4277-38034, e-Mail:
[email protected]
Works Councils and Personnel Turnover
1. Introduction
German works councils participate actively in social, personnel and economic affairs and
have been given a wide scope of action by law. Even rights to veto are granted them to block
an initiative in cases of hiring and dismissals (cf. Niedenhoff 2000, see Federal Minister of
Labour and Social Affairs 1990 for an official translation into English of the decisive
"Betriebsverfassungsgesetz"). These facts lead then to question what is the impact of works
councils on labour turnover.
Following the assumption that works councils aim to protect the interests of the employees,
who voted them, it could be expected that they use their co-determination rights to ensure job
security for its electors. Consequently it can be deduce that works councils attempt in general
to reduce the dismissal rate. Their position concerning the recruitment of new employees is
not as clear. On the one hand, a works council could be interested to enlarge the number of its
followers, especially to get further rights by law if the number of employees exceeds certain
threshold values. On the other hand, the danger is latent that young newcomers oust old
employees. To prevent this, works councils should be in general interested in maintaining a
low personnel turnover. Moreover, a lower dismissal rate implies by itself a reduced rate of
new employees ceteris paribus. Finally, works councils may vote against the recruitment of
new employees to keep a labour force’s scarcity within the firm. Although works councils are
not eligible for wage bargaining, they might try to influence indirectly the pay conditions, e.g.
by reducing the labour supply to get overtime pay.
Labour turnover is not only a consequence of a firm’s decisions but also influenced by
decisions of its employees. An employee might leave the firm voluntary without being
dismissed. The works council has no original interest in preventing workers from leaving
voluntarily the organization. Even if a works council would like to keep the leaving
employees as followers, it has no legal rights to stop them in contrast to its rights of veto
concerning dismissals. Nevertheless, there are methods a work council can make use of to
reduce indirectly this factor of labour turnover. According to the exit-voice-theory of
Hirschman (1970), a works council has the needed influence to improve bad working
conditions which would have induced employees to leave the firm. Employees working for
1
firms without a work council would just give notice as they have a weak power to influence
their working conditions.
All in all, there are quite a few theoretical reasons why works councils should try to reduce
labour turnover in the firm. How successful their attempts are can only be empirically cleared.
Additionally, owners’ and managers’ own interests should be also considered. Delayed or
prevented human resource’s measures, as well as a raise in related costs are not in the owners’
interest. An artificially created scarcity of the firm’s labour force to raise wages would also be
against their interests. But employees and employers can both win if the reduction of labour
turnover contributes to retain existing firm-specific human capital, to foster investments in
this kind of capital or to save recruiting costs. Such a reduction is in the interest of both sides,
too, as long as it increases productivity by raising the workers’ motivation. Moreover, works
council might contribute to improve the credibility of the company’s dismissal what makes in
consequence seniority wages acceptable to the employees (cf. Lazear 1979, 1981).
2. Previous Findings
There are only a few empirical studies concerning the influence of works councils on labour
turnover. Frick (1996, 1997) uses data from 2392 German firms of the private sector with at
least five employees for the period between 1985 to 1987. He finds a significant influence of
a works council’s existence on the density of dismissals as well as on the density of
employees leaving voluntary the firm. Drawing from the same data, Frick (1997) and Frick &
Sadowski (1995) find an insignificantly negative influence of works councils on the
recruitment rate of all firms, but a significantly positive one for the sub-sample of growing
firms. Addison et al. (1998, 2001) use the first wave (1994) of the Hanover Panel (cf. Brand
et al. 1996) to show significantly negative effects of a works council’s existence on entry, exit
and total fluctuation of employers. Schnabel & Wagner (1999) replicate this result for the exit
rate and present evidence for a significantly higher proportion of long-term employment in
firms with works councils. Addison et al. (2000) use the same panel and find an
insignificantly negative influence of works councils on the change of employment between
1991 and 1994. Gold (1999) confirms this significantly by using the first three waves of the
Hanover Panel.
Only Kraft (1986) finds surprisingly an insignificant, but positive effect of works councils on
the rate of quits by employees. However, Cable (1987) and Frick (1996, 1997) point out
considerable deficits of Kraft’s study: He took only 62 firms of the metal industry into
consideration for his survey which furthermore were not representative for this industry; the
2
dependent variable is a dummy variable of the subjective estimate by the management
whether the quite rate is “high” or “low”; participation is measured by an arbitrary additive
index; the influence of the firm’s size on the quit rate is positive, contrary to all other studies
and theoretical arguments.
Concluding it may be said that the previous studies besides Kraft (1986) have the expected
result namely that works councils reduce labour turnover. However, this evidence is based on
only two data sets so long. Hence, it is desirable to check it over by applying a third
independent data set.
3. The Data
In this paper the NIFA-Panel is analysed. The NIFA-Panel is a survey of all firms in the
German sector of mechanical engineering which have been queried each year from 1991 to
1998 (cf. Schmidt & Widmaier 1992 and Widmaier 1996, 2001). There are two advantages in
comparison to the previous studies which are only using a dummy variable for the existence
of a works council. First, the NIFA-Panel allows for discrimination between different types of
works councils (cf. Kotthoff 1981, 1994) according to their relationship with the
management. Second, changes of the works council’s existence between 1994 and 1996 can
be observed.
The average firm in the NIFA-Panel has 140 employees at the beginning of the year 1996. 64
of them (46 %) work in the firm’s manufacturing area. In the following, only this area will be
analysed because the questions in the panel about labour turnover focus on just this sector.
The average firm hires five employees for the manufacturing sector in the year 1995 and has a
slightly higher number of leavings including dismissals, quits and retirements (5.57 leavings
versus 5.09 hires). Relative to the number of employees at the beginning of 1996 this is a
hiring rate of eight per cent and a leaving rate of nine per cent.
63 % of the firms have a works council at the beginning of 1996. They have on average quite
more employees than firms without works council (188 versus 44). The reason is that a works
council is more likely in large than in small firms. The average firm with a works council has
87.61 employees in the manufacturing sector at the beginning of 1996, hires 6.40 (7 %) and is
left by 7.68 (9 %) in the year 1995. The average firm without a works council has only 25.98
workers in the manufacturing sector, hires 2.95 new (11 %) and loses 2.13 (8 %). These
results remain to be checked and other influences have to be considered, for instance the size
effect. This will be done in the next section of this article.
3
There is one question in the NIFA-Panel that allows for differentiation of five types of works
councils. The management is questioned about how it describes the attitude of the works
council in its firm regarding important technical and organisational switches during the last
years. The question is not about the relationship between management and works council in
general, but it will be used here as pars pro toto. The management can choose between five
answers that describe the works council’s attitude as (1) antagonistic in most cases, (2)
sometimes difficult, (3) unrestrictedly co-operative, (4) indifferent, (what means that the
works council does not take part,) or (5) excluded by the management. 4 % of the works
councils are described as antagonistic by the management, 47 % as difficult, 36 % as cooperative, 4 % as indifferent and 9 % as excluded. A one-to-one mapping of these five
categories to the six works council’s types from Kotthoff (1994) is not possible. Regardless of
the concrete typology used, however, it is plausible that different works councils behave
differently and that their relationship to the management plays an important role. The effects
of works council’s type on the firm’s returns are shown in Dilger (1999, 2002). This paper
investigates these effects on the labour turnover.
Unfortunately, the question concerning the attitude of the works council is asked in the NIFAPanel only once, namely in the year 1996. Thus, the panel-character of the NIFA-Panel
cannot be used. The question if a works council does exist in the firm is asked twice, besides
1996 also in the year 1994. By linking the two waves of the NIFA-Panel, a fourfold
differentiation is possible: firms without a works council in both years, firms with a works
council only in 1994, firms with a works council only in 1996 and finally firms with a works
council in both years. There are only a few firms with a change in the works council’s
existence: 14 firms (1 %) lose and 68 (7 %) gain a works council compared to 354 firms
(35 %) constantly without and 584 (57 %) in both years with a works council. Nevertheless,
predictions can be hypothesized and empirically tested.
4. Empirical Results
Labour turnover is not only affected by the works council, but by many different factors. It is
useful to estimate OLS models to figure out the effects of works councils while controlling
for other variables. The following procedure is similar to that of Addison et al. (1998, 2001).
Here as well, certain measures in log-odds form for the rate of the leaving employees, the
new-hired ones and the sum of both as the total labour turnover are used as the dependent
variables in different estimates. More precisely, the dependent variable is defined as
ln[Rate/(1-Rate)], where Rate denotes the number of the hires, departures or their sum in the
4
manufacturing sector of the firm divided by the total number of employees in this sector.
Moreover, the value of one is added to the number of hires, departures and their sum, because
many firms do not have any turnover in the year 1995. According to Addison et al. (1998,
p. 69), Frick (1996, 1997) exerts the same method, but without pointing to this addition of
one. However, the formula can produce missing values even with this kind of addition,
namely in the case of a labour turnover that is higher than the personnel stock. Indeed, this
happens in some cases of the NIFA-Panel, but these cases may be dismissed as outlying.
Another problem with the formula is that the OLS results are sensitive to the chosen
construction of the dependent variable. A changed formula to calculate the dependent variable
can bring about very different results. The rather complex logarithmic construction, which is
possibly ascribable to Berry (1994), is selected here to make the results comparable with
those of Addison et al. (1998, 2001) and Frick (1996, 1997). Alternative models, especially
Tobit ones, remain to be tested.
There are two differences between the rates as they are used here and those used by Addision
et al. (1998, 2001) and Frick (1996, 1997). First, they do calculate the rates of hires,
departures and total labour turnover or dismissals and quits respectively for the whole firm,
whereas here, only the manufacturing sector of the firm can be analysed. This is because of
the fact that the decisive questions in the NIFA-Panel are only for this sector. Second, in these
other studies the number of employees from the previous year is applied in the denominator.
Here, the current number of employees in the manufacturing sector is chosen. Otherwise the
inclusion of the 5th wave would have been necessary. Doing this, however, diminishes the
amount of valid cases substantially. In addition, there are some inconsistencies in the answers
between the different waves.
The important differences of this study compared to the previous ones are not those in the
computation of the dependent variable but the following ones with consideration to the works
councils. All prior studies can only use a dummy variable for the mere existence of a works
council. In this study two additional measures are used. On the one hand, different types of
works councils are used. This is not only interesting in its own sake because different types of
works councils can be expected to behave and thereby influence the labour turnover in
different ways (cf. Kotthoff 1981, 1994). Different types of works councils are also
interesting to control for size effects because the type of a works council is much less affected
by the firm’s size than its pure existence. On the other hand, the effects of a change in a works
council’s existence between 1994 and 1996 can be analysed.
5
Besides a dummy variable for the existence of a works council or dummies for the types or
changes in time, the following independent variables are included in the models with the
mentioned expectations. The number of Manufacturing Workers is expected to have a
negative influence on the different kinds of labour turnover, if only for “mechanical” reasons
because this number is in the denominator of the dependent variables (cf. Addison et al. 1998,
2001). The square of this number, Manufacturing Workers (sq.), is included to cover nonlinear size effects. Positive effects are anticipated for this squared variable because the
relationship between firm size and labour turnover is probably a convex one. The number of
all workers in the firm without trainees, the Total of Workers, allows for answering the
question, whether larger firms have a higher or lower labour turnover than smaller firms. The
square of this number, Total of Workers (sq.), is for considering non-linear effects again. The
Manufacturing Worker Rate, the ratio of workers in the manufacturing sector to all workers of
the firm, shows the relative size and relevance of this sector. Therefore, a negative influence
on the labour turnover is predicted. The Skilled Worker Rate (the rate of “Facharbeiter” in the
manufacturing sector of the firm) is expected to have a negative influence on all three kinds
of turnover for two different reasons: Firstly, skilled workers have a high level of firmspecific human capital such that their turnover is especially costly. Secondly, skilled workers
are well represented in works councils and are quite effective in pushing their interests
through. The Sales per Capita (lg.), the logarithmic quotient of the entire firm’s turnover and
employees, can be seen as a signal for the capital stock. A smaller staff compared to the
capital stock can be assumed to fluctuate more than a larger one, such that a positive influence
on leavings, hires and the total personal turnover has be to expected. A Branch Plant,
measured by a dummy variable with the value of one if the establishment is part of a multiplant firm, should have less dismissals for reputational reasons because dismissals might also
lead to a moral decline of the workers in all other branches of the same enterprise. However,
transfers of employees between the plants can raise the labour turnover as it is measured here.
Therefore, the total effect can not be predicted. The dummy variable for the existence of
Organisational Change in the firm should be accompanied by changes in the staff. Working
Groups, recorded by another dummy variable, are a kind of firm-specific organisational
capital embedded in the incumbent workforce that should be stabilised accordingly. Models
of Flexible Working Time, also a dummy variable, indicate firm-specific organisational
capital as well, but are simultaneously sign of higher flexibility in personnel matters, such that
the total effect of using these models is not clear. Further Training, represented by another
dummy variable with the value of one if it exists for any employees in the manufacturing
6
sector of the firm, increases the human capital of the employees. Nevertheless, only firmspecific human capital lowers the labour turnover, whereas general human capital which
might be taught in formal further training has no such effect. Moreover, the use of further
training can indicate an actual lack of qualified employees. Then it is cheaper to dismiss some
of the workers and perhaps necessary to hire new, more qualified ones. The dummy variable
Product Innovation is a sign for already qualified employees. Thus, a lower leaving rate and
possibly more hires can be expected. The same holds for the predominantly or solely use of
Computerised Machines, portrayed by a further dummy variable. A high Capacity Utilisation
of Machines (in per cent) makes the leaving of qualified employees more costly, without
forcing to more hires by itself. That is the case if the Capacity Utilisation of Staff (in per cent)
is high. Then, more hires and fewer leavings can be expected. The same is true for At least
Satisfactory Returns, a dummy variable. Table 1 shows the means and standard deviations for
all variables used.
What is about the dummy variables for the existence of a works council, the works council’s
types and change in time which are at the focus of this article? The following expectations
can be formulated: According to all the theoretical arguments mentioned in the introduction,
the mere existence of a works council has a negative influence on all three kinds of labour
turnover, that is the hiring rate, the leaving rate and the total labour turnover as the sum of
hires and departures divided by the number of all employees. Differentiating between
different types of works councils in new OLS estimates, the same should hold for all of them
but with different degrees. A Co-operative Works Council with good a relationship to the
management is predicted to have the strongest effect in stabilising the staff and therefore in
reducing all three rates of labour turnover. The second strongest effect can be expected from a
Difficult Works Council. It follows the Antagonistic Works Council. Only a small effect if any
can be caused by an Indifferent Works Council or an Excluded Works Council because these
two types are quite similar to the non-existence of any works council. Regarding the change
of works councils, OLS estimates are expected to show a clear reduction of hires and leavings
and therefore the total labour turnover only for a Works Council 94 and 96 existing. A Works
Council only 96 is correlated with a rising number of employees (cf. Dilger 1999, p. 66), such
that more hires and less departures are predicted. A Works Council only 94 is in firms where
the average number of employees is falling (cf. Dilger 1999, p. 66), so a lower hiring and a
higher leaving rate are expected. Certainly, the reference firms to compare with are always
those without any works council.
7
Table 1: Descriptive Statistic
Variables
Standard
Deviation
Mean
Measure of Leaving#
Valid Cases
-2.243
1.067
1483
-2.261
1.165
1482
-1.586
1.082
1444
Works Council*
0.626
0.484
1716
Antagonistic Works Council*
0.023
0.149
1575
Difficult Works Council*
0.279
0.449
1575
Co-operative Works Council*
0.212
0.409
1575
Indifferent Works Council*
0.026
0.159
1575
Excluded Works Council*
0.053
0.225
1575
Works Council only 94*
0.014
0.116
1020
Works Council only 96*
0.067
0.250
1020
Works Council 94 and 96*
0.573
0.495
1020
63.899
142.335
1580
24329.566
250210.435
1580
140.260
321.136
1700
122740.564
1081430.739
1700
Manufacturing Worker Rate
58.520
60.327
1574
Skilled Worker Rate+
67.363
25.242
1556
Sales per Capita (lg.)°
0.188
0.100
1635
Branch Plant*
0.318
0.466
1714
Organisational Change*
0.683
0.465
1688
Working Groups*
0.443
0.497
1678
Flexible Working Time*
0.537
0.499
1680
Further Training*
0.566
0.496
1683
Product Innovation*
0.680
0.467
1700
Computerised Machines*
0.496
0.500
1627
78.286
20.550
1638
Capacity Utilisation of Staff+
91.963
12.855
1636
At least Satisfactory Returns*
0.454
0.498
1708
#
Measure of Hiring
#
Measure of Total Turnover
Manufacturing Workers
Manufacturing Workers (sq.)
Total of Workers
Total of Workers (sq.)
+
Capacity Utilisation of
+
Machines
#
See above in the text; * Dummy variable (0 = no, 1 = yes); + in per cent; ° ln(sales in million DM/total of workers
+ 1); data source is the 6th wave of the NIFA-Panel (1996), for a change in the works councils existence also the
4th wave (1994).
8
Table 2 presents the OLS results with respect to the leaving rate. The theoretical justified
predictions about the influence of the works councils are perfectly confirmed in all three
models. The dummy variable for a works council’s existence has, corresponding to the
previous empirical studies (excepting Kraft 1986), a significantly negative sign at the one per
cent level. It can be calculated that the existence of a works council reduces the leaving rate in
the average firm by 16.8 % or 1.8 per cent points (from 10.7 % to 8.9 %). The dummy
variables for the different types of works councils are also negative. The statistical
significance for a co-operative works council is at the one per mil level the highest as
predicted. Such a type of works council lowers the leaving rate from 10.4 % for an average
firm without a works council to 7.6 %. As expected, it follows the type of difficult works
councils, where the leaving rate falls to 8.6 %. This is statistically significant at the one per
cent level. The other three dummy variables are statistically insignificant (the leaving rate is
9.0 % for antagonistic works councils, 9.3 % for indifferent and 10.3 % for excluded ones).
This verifies that the type of the works council is important. A good relationship between the
works council and firm’s management is in the common interest of employees and employers
and allows an amicable reduction of labour turnover. A difficult but still constructive
relationship is better than pure antagonism or the absence of any relationship between works
council and management. The results of the third model show that a permanent works council
reduces the leaving rate significantly at the five per cent level (the leaving rate falls from
10.3 % without works council at any time to 8.8 %). A new-founded works council brings
about an insignificant reduction (to 9.2 %), a closed works council an insignificant increase of
the leaving rate (to quite high 13.1 %). All the other independent variables have essentially
the expected signs in each of the three models. The effect of the firm’s size is positive. This
result is not doubtful as the seemingly same result of Kraft (1986) because the size of the
manufacturing sector is included here and has the expected negative sign.
Table 3 shows the corresponding results for the hiring rate in the manufacturing sector. As
before, the existence of a works council has the expected negative sign which corresponds to
the previous studies and is statistically significant at the one per mil level. The hiring rate falls
from 11.9 % without works council to 8.6 % for an otherwise representative firm.
Differentiating for the five types of works councils, all of them have negative signs, the
difficult and the co-operative works council statistically significant at the one per mil level
(the hiring rate is 7.5 % and 7.6 % instead of 11.5 % without works council), the antagonistic
one at the one per cent level (the hiring rate is only 6.8 %) and the excluded works council at
the ten per cent level (with an hiring rate of 9.2 %, whereas the insignificantly changed hiring
9
Table 2: Determinants of Leaving
Independent Variables
Works Council
Works Council’s
Existence
-0.198**
Works Council’s
Type
Works Council’s
Change
(0.062)
Antagonistic Works Council
-0.163
(0.198)
Difficult Works Council
-0.206**
(0.079)
Co-operative Works Council
-0.346***
(0.079)
Indifferent Works Council
-0.129
(0.171)
Excluded Works Council
-0.010
(0.125)
Works Council only 94
0.281
(0.291)
Works Council only 96
-0.120
(0.152)
Works Council 94 and 96
-0.165*
(0.080)
Manufacturing Workers
-0.005*** (0.001) -0.005***
(0.001) -0.005*** (0.001)
Manufacturing Workers (sq.)
0.000*** (0.000) 0.000***
(0.000) 0.000*** (0.000)
Total of Workers
0.001+
(0.000) 0.001**
(0.000) 0.000
(0.000)
Total of Workers (sq.)
-0.000
(0.000) -0.000
(0.000) 0.000
(0.000)
Manufacturing Worker Rate
-0.002*** (0.000) -0.002**
(0.000) -0.001**
(0.001)
Skilled Worker Rate
-0.007*** (0.001) -0.007***
(0.001) -0.006*** (0.001)
Sales per Capita (lg.)
1.265*** (0.329) 1.270***
(0.340) 1.732*** (0.453)
Branch Plant
0.031
Organisational Change
(0.065) -0.002
+
0.103
(0.061) 0.121
+
(0.067) 0.007
(0.083)
+
(0.064) 0.017
(0.076)
+
(0.060) -0.063
(0.073)
Working Groups
-0.106
(0.059) -0.117
Flexible Working Time
0.039
(0.058) 0.048
(0.060) 0.080
(0.073)
Further Training
0.034
(0.059) 0.049
(0.061) 0.037
(0.075)
Product Innovation
-0.028
(0.060) -0.037
(0.063) -0.064
(0.074)
Computerised Machines
-0.170**
(0.058) -0.171**
(0.060) -0.159*
(0.073)
Capacity Utilisation of
-0.004**
(0.002) -0.004*
(0.002) -0.002
(0.002)
Machines
Capacity Utilisation of Staff
-0.010*** (0.003) -0.010***
(0.003) -0.009**
(0.003)
At least Satisfactory Returns
-0.121*
(0.057) -0.127*
(0.059) -0.153*
(0.071)
Constant
-0.278
(0.249) -0.307
(0.254) -0.586+
(0.316)
Number of Valid Cases
2
Adj. R
1274
1183
779
0.161
0.169
0.167
OLS estimates; dependent variable is in each case the logarithmic transformed ratio of leaving employees in the
manufacturing part of the firm; data source is the 6th wave of the NIFA-Panel (1996), last column also 4th wave
(1994); standard deviations in parentheses; +/*/**/*** denote statistical significance at 0.10/0.05/0.01/0.001
levels.
10
Table 3: Determinants of Hires
Independent Variables
Works Council
Works Council’s
Existence
Works Council’s
Type
Works Council’s
Change
-0.358*** (0.066)
-0.584**
-0.479***
-0.464***
-0.266
-0.252+
Antagonistic Works Council
Difficult Works Council
Co-operative Works Council
Indifferent Works Council
Excluded Works Council
(0.211)
(0.085)
(0.084)
(0.181)
(0.135)
-0.234
(0.302)
0.101
(0.158)
-0.439*** (0.083)
Works Council only 94
Works Council only 96
Works Council 94 and 96
Manufacturing Workers
-0.005*** (0.001) -0.004***
(0.001) -0.005*** (0.001)
Manufacturing Workers (sq.)
0.000*** (0.000) 0.000***
(0.000) 0.000***
(0.000)
Total of Workers
0.000
(0.000) 0.000
(0.000) 0.001
(0.000)
Total of Workers (sq.)
-0.000
(0.000) -0.000
(0.000) -0.000
(0.000)
Manufacturing Worker Rate
-0.001*
(0.000) -0.001*
(0.000) -0.001*
(0.001)
Skilled Worker Rate
-0.005*** (0.001) -0.005***
+
(0.001) -0.005*** (0.002)
Sales per Capita (lg.)
0.629
(0.350) 0.519
(0.364) 1.053*
(0.471)
Branch Plant
-0.107
(0.069) -0.085
(0.072) -0.075
(0.085)
Organisational Change
-0.010
(0.065) 0.011
(0.068) -0.010
(0.079)
+
Working Groups
-0.167**
(0.062) -0.161*
(0.065) -0.148
(0.076)
Flexible Working Time
-0.017
(0.062) 0.003
(0.064) -0.009
(0.076)
Further Training
0.051
(0.062) 0.055
(0.065) 0.121
(0.077)
Product Innovation
0.072*
(0.064) 0.129+
(0.067) 0.118
(0.077)
Computerised Machines
0.002
(0.062) -0.002
(0.064) -0.092
(0.075)
Capacity Utilisation of
-0.004*
(0.002) -0.004*
(0.002) -0.003
(0.002)
Machines
Capacity Utilisation of Staff
0.014*** (0.003) 0.013***
(0.003) 0.015***
(0.003)
At least Satisfactory Returns
0.281*** (0.061) 0.261***
(0.063) 0.224**
(0.074)
Constant
-2.461*** (0.262) -2.514***
(0.269) -2.825*** (0.324)
Number of Valid Cases
2
Adj. R
1273
1184
782
0.192
0.199
0.195
OLS estimates; dependent variable is in each case the logarithmic transformed ratio of hired employees in the
manufacturing part of the firm; data source is the 6th wave of the NIFA-Panel (1996), last column also 4th wave
(1994); standard deviations in parentheses; +/*/**/*** denote statistical significance at 0.10/0.05/0.01/0.001
levels.
11
rate for an indifferent works council is 9.1 %). A works council that exists 1994 and 1996
lowers the hiring rate significantly at the one per mil level (from 12.4 % to 8.4 %). The sign
for a works council only existing 1994 is insignificantly negative (hiring rate of 10.1 %), for
the works council that exists only 1996 it is insignificantly positive (hiring rate of 13.6 %).
There is nothing unusual about the other independent variables.
Table 4 includes the results for the total labour fluctuation in the manufacturing sector. The
existence of a works council without further differentiation has the expected and in previous
studies found negative sign. This, the labour turnover lowering influence, is statistically
significant at the one per mil level (the turnover rate falls from 19.7 % without works council
in the average firm to 16.3 %). All different types of works council have a negative sign. For
a co-operative works council it is statistically significant at the one per mil level (total
turnover falls from 20.0 % to 15.0 %), for a difficult works council it is significant at the one
per cent level (15.9 %) and for the three other types it is insignificant (antagonistic works
council 17.4 %, indifferent one 17.9 % and excluded one 19.8 %). A works council 1994 and
1996 has a negative sign that is statistically significant at the five per cent level (total turnover
falls from 17.3 % to 14.9 %). If there is a change in the works council’s existence between
1994 and 1996, the sign is insignificantly positive (20.9 % when the works council is not
longer existent, 17.5 % in case of a new works council). The signs of the other variables are in
association with the expectations. Because for some of them the effects on hires and
departures countervail each other, less variables are significant than before and the explained
variance of the models is lower.
All estimations have been repeated for the sub-sample of firms with a number of employees
between 21 and 100, as Addison et al. (1998, 2001) do. This sub-sample is especially
interesting because about the half of its firms (in the NIFA-Panel 51,1 %) does have a works
council and the other half does not. Addison et al. (1998, 2001) do not find any significant
results for this sub-sample. This corresponds to the results from the NIFA-Panel, which are
hence not shown in a table here. Only the negative effects on hiring of the mere works
council’s existence, the difficult works council and the continual one 1994 and 1996 are
weakly significant at the ten per cent level. Thus, the effects presented here before must be
interpreted with some caution. It could be the case that the supposed works council’s effects
are in reality effects of the firm’s size. The probability to find a works council in a firm
increases with the number of its employees. However, the use of different types of works
councils here has some extra value because the type is not an indicator for the firm’s size in
contrast to the mere works council’s existence. That is why the following presumption seems
to be the better explanation for the lack of significant results in this important sub-sample: In
12
Table 4: Determinants of Total Labour Turnover
Independent Variables
Works Council
Works Council’s
Existence
Works Council’s
Type
Works Council’s
Change
-0.230*** (0.067)
-0.169
-0.279**
-0.346***
-0.136
-0.011
Antagonistic Works Council
Difficult Works Council
Co-operative Works Council
Indifferent Works Council
Excluded Works Council
(0.217)
(0.086)
(0.086)
(0.188)
(0.137)
0.234
0.019
-0.177*
Works Council only 94
Works Council only 96
Works Council 94 and 96
(0.311)
(0.166)
(0.086)
Manufacturing Workers
-0.004*** (0.001) -0.004***
(0.001) -0.005*** (0.001)
Manufacturing Workers (sq.)
0.000*** (0.000) 0.000***
(0.000) 0.000***
+
+
Total of Workers
0.001
(0.000) 0.001
Total of Workers (sq.)
-0.000
(0.000) -0.000
(0.000) 0.001
+
(0.000)
(0.000) -0.000
(0.001) -0.001
(0.000)
+
Manufacturing Worker Rate
-0.001*
Skilled Worker Rate
-0.006*** (0.001) -0.006***
(0.000) -0.007*** (0.002)
Sales per Capita (lg.)
0.787*
(0.356) 0.766*
(0.372) 1.155*
(0.492)
Branch Plant
-0.050
(0.070) -0.031
(0.073) -0.003
(0.088)
Organisational Change
0.113+
(0.066) 0.122+
(0.070) 0.102
(0.082)
Working Groups
-0.077
(0.063) -0.081
(0.066) -0.048
(0.079)
Flexible Working Time
0.008
(0.063) 0.011
(0.065) 0.033
(0.078)
Further Training
0.090
(0.063) 0.109+
(0.066) 0.142+
(0.080)
Product Innovation
0.041
(0.065) 0.065
(0.068) 0.007
(0.080)
Computerised Machines
-0.061
(0.063) -0.052
(0.065) -0.115
Capacity Utilisation of
(0.001) -0.001*
(0.000)
(0.001)
(0.078)
+
-0.005**
(0.002) -0.005**
(0.002) -0.004
(0.002)
Capacity Utilisation of Staff
0.002
(0.003) 0.003
(0.003) 0.002
(0.004)
At least Satisfactory Returns
0.089
(0.062) 0.065
(0.064) 0.083
(0.076)
Constant
-0.886**
(0.271) -0.991***
(0.279) -1.077**
(0.339)
Machines
Number of Valid Cases
2
Adj. R
1243
1158
767
0.092
0.093
0.103
OLS estimates; dependent variable is in each case the logarithmic transformed ratio of labour turnover in the
manufacturing part of the firm; data source is the 6th wave of the NIFA-Panel (1996), last column also 4th wave
(1994); standard deviations in parentheses; +/*/**/*** denote statistical significance at 0.10/0.05/0.01/0.001
levels.
13
firms with less then one hundred employees the legal rights and practical means are still too
small for works councils to have an important influence on the labour turnover. In larger
firms this influence is then even larger.
5. Conclusion
Theoretical arguments and previous empirical studies using two data sets let deduce that there
is a negative influence of works council’s existence on labour turnover. In this paper, a third
and independent data set, the NIFA-Panel, covering the German industry of mechanical
engineering, is used to test these results. Additionally, the effects of new founded and closed
works councils as well as different types of works councils are considered for the first time in
this paper. Using OLS estimates, the reducing influence of a works council on labour turnover
can be confirmed. The results are statistical significant on the one per cent or even one per mil
level. This holds for the density of leaving employees, the new-coming ones and the total
turnover. Only new founded works councils have an insignificantly positive effect on labour
turnover. Differentiating between types of works councils helps to screen firm’s size effects.
It also shows that in particular co-operative relations between management and works council
lower labour turnover. Therefore, this reduction should be considered as in common interest
of employers and employees and not only in the interest of the employees.
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