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Insider power, market power, firm size and wages: Evidence from Dutch manufacturing industries
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LABOUR ECONOMICS ELSEVIER
Labour Economics 3 (1996) 93-107
Insider power, market power, firm size and wages: Evidence from Dutch manufacturing industries Marcel H.C. Lever *, Jolanda M. van Werkhooven ElM, P.O. Box 7001, 2701 AA Zoetermeer, The Netherlands
Received 15 May 1995; accepted 19 July 1995
Abstract The objective of this study is to assess the impact of internal (sector-specific) and external (labour-market-related) factors, the number of insiders, product market power and finn size on wages in Dutch manufacturing industries. The weight of the internal factors approximates that found in earlier research for the UK, it is higher than that found for Scandinavian countries, yet lower than that found for the US. A high weight of the internal factors is generally deemed favourable as it stabilizes employment. Evidence for the emergence of insider effects, which may cause unemployment persistence, cannot be established. It is however observed that product market power increases the weight of internal factors. Finally, the weight of internal factors appears to be substantially higher for large finns than for small ones. JEL classification: J31 Keywords: Wage formation; Insider power; Product market power; Firm size; Dutch manufacturing
industry
* Corresponding author. Tel.: 31-79-3448450; fax: 31-79-3415024; e-mail: [email protected]. 0927-5371/96/$15.00 Copyright © 1996 Published by Elsevier Science B.V. All rights reserved PII S0927-5 37 1(96)00004-8
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1. Introduction The neoclassical model of perfect competition cannot explain the persistence of unemployment and the existence of inter-sectoral wage differentials of employees with comparable qualifications performing similar tasks. So as to be able to explain this unemployment and the wage differentials, three alternative theories were developed in the eighties, i.e. the union bargaining theory, the efficiency wage theory and the insider-outsider theory. In view of the influential role of trade unions in the Netherlands where wage formation is concerned, we have adopted a model which is based on the union bargaining theory and the insideroutsider theory. The insider-outsider theory emphasizes that workers (insiders) have more bargaining power in wage bargaining than the unemployed (outsiders). This difference in bargaining power is due to different levels of know-how and skills. Given their bargaining power, insiders are able to obtain a share of the revenue of a finn in addition to the reservation wage of outsiders. The single-period models of Lindbeck and Snower (1988) imply that in addition to the reservation wage of an outsider, an insider can at the most acquire the amount of the cost of replacing one insider by one outsider. In their multi-period model, Vetter and Andersen (1994) illustrate that in addition to the reservation wage of an outsider, an insider cannot acquire more than the amount of the cost of replacing one insider by one outsider, divided by the number of periods (years) of active service in the finn. The insider effect may generate a state of equilibrium where unemployment exists. After this sketch of the theoretical background, four issues deserve further discussion. Firstly, if this bargaining approach is correct, the wage rate at firm- or sectoral level depends on both the performance of the firm or sector and the situation in the labour market. A high weight of internal factors implies that the wage rate adapts to the performance of the firm or sector. This produces not only stable employment but also changes in relative wage rates. A high weight of external factors implies that the wage rate primarily adapts to overall performance of the economy. This produces less stable employment and fewer changes in relative wages. A high weight of internal factors is generally deemed favourable. Secondly, the bargaining approach suggests an increasing level of wage rate with decreasing numbers of insiders. For, given a low number of insiders, related to the production technology of that firm and market demand for its products, even in the event of a high wage rate their employment is not at immediate risk if the firm is affected by a temporary adverse shock; see Gottfries and Horn (1987). The existence of this insider effect may be tested by examining whether employment from the previous period, as an approximation for the number of insiders, exerts negative impact on the wage rate. However, as noted in Lever (1995), the negative correlation between the wage rate and the previous employment level depends crucially on the assumptions with respect to both the persistence of the exogenous shock and the sluggishness in labour demand. Blanchard and Summers (1986), for
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example, argue that if labour demand is sluggish and the exogenous shocks are correlated over time, a positive correlation results between the wage change and the employment change. Insider effects are deemed unfavourable, as they delay the post-recession recovery of employment. Thirdly, if wages are determined by bargaining, it is probable that workers share in the rents which are due to the firm's power in the product market. So, product market power may have a positive impact on the wage rate. Fourthly, the weight of internal factors is likely to be lower for small firms than for large ones, one reason being that large firms have an internal labour market at their disposal. This internal labour market is created to ensure remunerative investment in employees. Through their know-how and experience employees in the internal labour market command a comparatively strong position in wage negotiations and may demand larger parts of revenue effected. Another reason entails that large firms enter their own collective labour agreements more often than small firms do. Previous studies confirm the relevance of internal and external factors in wage formation. The evidence with respect to the impact of the number of insiders on wages is mixed. Nickell and Wadhwani (1990), using data for 219 manufacturing firms in the UK covering the 1975 through 1982 span, estimate the weight of internal factors at 0.11 and that of external factors at 0.89. The impact of the number of insiders on the wage rate does not appear to be robust. In a comparable analysis, Holmlund and Zetterberg (1991) find similar or lower weights for internal factors for Finland (0.00-0.01), Norway (0.03-0.04), Sweden (0.03-0.12) and West Germany (0.04-0.12), and higher weights for the US (0.30-0.48). In Nickell et al. (1994), the sample is extended to 814 manufacturing firms. As regards the weight of internal factors (0.11-0.16) and the impact of the number of insiders, the results are comparable to the findings of the former study. New findings comprise that the market share of a firm in the product market appears to exert positive impact on the wage rate, and that the weight of internal factors is virtually identical for large and small firms. Brunello and Wadhwani (1989), however, find that in Japan and the UK internal factors in large firms exert a significantly positive impact, and that internal factors are insignificant for small firms. Conceivably, the discrepancy between the findings of Brnnello and Wadhwani and those of Nickell et al. (1994) is attributable to different definitions of the boundary between small and large firms. Nickell et al. probably define the boundary between large and small above 1,000 employees, 1 whereas Brnnello and Wadhwani draw the boundary at 300 (Japan) or 500 (UK) employees. The objective of this study comprises the following four aspects. Firstly, a determination of the relative weight of internal (sector-specific) and external
I Nickell et al. draw the boundary between 'large' and 'small' at median employmentlevel. While not reporting the size of the median, they indicate that the sample comprises large firms with 4,332 employeeson averagein 1982.
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(labour-market-related) factors as regards wage formation in Dutch manufacturing industries. Secondly, an examination as to whether the number of insiders, based on employment in the previous period, exerts negative impact on the wage rate. Thirdly, an investigation as to whether market strength of firms in the product market affects the level of wages or the weight of the internal factors. Finally, an analysis as to whether there are differences in weight of internal factors between large and small firms. The composition of this paper includes the derivation of a wage equation in Section 2. The data and the estimation method are presented in Section 3, while the empirical findings are recapitulated in Section 4. Section 5 comprises the conclusions.
2. Theoretical framework
The wage equation which is used is derived from a bargaining model. This model is proposed by Nickell and Wadhwani (1990), Layard et al. (1991) and Nickell et al. (1994). An important reason to base wage equations on a bargaining model is that negotiations between trade unions and firms play an important part as regards the determination of wages in the Netherlands. Figures of the Ministry of Social Affairs and Employment reveal that during the seventies and eighties around 75 percent of all employees in the market sector are covered by collective labour agreements. The model presumes that wages are determined through negotiations between firm and trade union and that the employment level is set by the firm. Further, there is imperfect competition in the product market. Output demand is subject to exogenous shocks, which are unknown at the stage of bargaining. The output price and the employment level are set by the firm after the wage negotiations and after the size of the shock is identified. The output price and the employment level are set such that profits are maximized. Finally, it is presumed that the trade union maximizes the expected income for their members, who are the existing employees. The bargaining model results in the following wage equation (cf. Nickell et al., 1994): Wi = ~/Oi + A[ pi + 4'i -}- (1 -- ol ) ( ki -- nli) ]
+ ( 1 -- ~)[W "[- ~/3 b + ~4 u + ff/5Auk] + ~t6K i "[- ~913i, 0<,h.< 1,0
1,~3>0,~4
<0,~/5 < 0 , ~ 6 < 0 ( ? ) , ] / 9 > 0
(1) ,
where: wi is the sectoral wage rate (in logs); p/ is the sectoral output price (value added, in logs); 4'/ is the sectoral productivity index (in logs); k/ is the sectoral capital stock (in logs); nt/ is the sectoral number of insiders (in logs); w is the wage rate outside industry i (in logs); b is the ratio of unemployment benefits to
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the average wage rate; u is the aggregate unemployment rate; u k is the aggregate rate of short-term unemployment (less than one year); Ki is the sectoral index of competition in the product market; /3i is the sectoral index of union bargaining power. Eq. (1) shows that sectoral wages are a log-linear combination of internal and external factors, product market power and union bargaining power. The equation also shows that the weight of the internal factors (A) and that of the external factors (1 - A) add up to unity. Unemployment u and the change in short-term unemployment A u k exert negative impact on the wage rate. Unemployment benefits b and the bargaining power 13 exert positive impact on the wage rate. The impact of the degree of competition in the product market on wages cannot be signed a priori. There is a negative effect from K (so a positive effect from market power) on wages which arises because the union can expropriate part of the rents of monopoly power in the form of higher wages. However, there is also a positive effect from K on wages which results from the reduced probability of insiders' employment, as monopoly power in the product market reduces output and employment. It is reasonable to assume that these effects on the probability of employment are small, so the total effect from K on wages is negative. The weight of the internal factors (A) depends positively on union power (/3) and negatively on product-market competition (K); see Layard et al. (1991, p. 186). Several adjustments are required so as to estimate the industry-specific wage equation. An important assumption in this respect is that the number of insiders on whose behalf trade unions negotiate is equivalent to the number of employees employed in the previous period ( n t i = n i _ l ) . Based on the Cobb-Douglas production function Yi = (/)i K/~N~1-~ which is used to derive (1), it thus holds that tbi + (1 - t ~ ) ( k i - n t i ) = ( Yi - n i ) - (1 - a ) ( n l i - ni). Using these two equivalences, it thus holds that ~bi + (1 - a ) ( k i - n l i ) = ( Y i - n i ) + (1 - c e ) A n i , with Yi is sectoral value added (in logs). The second adjustment entails the exact definition of the industry wage rate and the wage rate outside industry i. With respect to w, the wage rate outside industry i, either the manufacturing wage rate or the macro wage rate can be adopted. With respect to w i it is not evident whether bargaining entails negotiations in respect of labour costs or gross wages. Therefore, the difference between the sectoral and the aggregate rate of employers' contributions is included in the regression equation. Employers' contributions at macro or manufacturing level are expressed by TX, those at industry level by TXi. Both rates are expressed in terms of perunages. The logarithmic tax terms which can be used to obtain gross wages from labour costs may be defined as tx = - In(1 - TX) and tx i = - ln(1 - TXi). If the coefficient of the difference between the tax rates T8 equals zero, bargaining implicitly entails labour-costs negotiations, and if T8 equals one, bargaining entails gross-wage negotiations. Probably, "Y7 ranges between these extremes. The third adjustment entails the inclusion of the yearly number of hours worked, which (in logs) is denoted by h i . In the present study the industry-specific
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employment is measured in persons and the industry-specific wage rates are measured per person per year. The manufacturing wage rate and the macro wage rate are measured per labour year. Differences between these units of measurement arise if the actual average number of hours worked differs from the number of hours in a labour year. This may be due to overtime, reduction of working time, part-time work, etc.. In order to correct for these differences the actual number of hours worked is included as explanatory variable. The fourth adjustment entails the bargaining power of trade unions. So as to identify the bargaining power of trade unions the extent of coverage of collective labour agreements can be used. Figures in respect of the coverage of collective labour agreements are published at high aggregation level only. A publication by the Department of Collective Labour Agreements (Dienst Collectieve Arbeidsvoorwaarden, 1987) illustrates that the percentage of employees which is covered by collective labour agreements is practically constant over time at aggregate level. This variable becomes void when first-differences are used for an estimation by GMM. The variable fli has therefore been omitted in the empirical study. The fifth adjustment entails that the degree of competition in the product market Ki is deemed a declining function of the degree of market concentration in an industry and an increasing function of foreign competition; see Cowling and Waterson (1976). The four-firm concentration ratio C 4 i and the export share x i are used as indicators here. C 4 i is defined as employment in the four largest firms in an industry, divided by total employment in firms with ten or more employees at 30 September; x i is defined as the share of exports in industrial sales. In line with the earlier discussion we expect that the coefficient of C 4 i in the wage equation is positive and that of x i is negative. The sixth adjustment entails rearranging of the equation so as to ensure that the weights of internal and external factors add up to unity. The equation is rearranged by subtracting the aggregate wage rate from both the sectoral wage rate and sectoral value added per employee. Finally, the degree of concentration C4ia and the unemployment rate u t are lagged by one year, as the lagged variables comprise the most recent data available during wage negotiations. Besides, the adoption of lags prevents the emergence of endogeneity-related problems. Following these adjustments, the wage equation may be written as Wi,t -- Wt = ~/Oi 3¢- A ( Pi,t q- Yi,t -- Fli,t -- Wt) "~- ~/I Al2i,t 3¢. ,.)/2hi, t ~_ ,Y3b t
+ Y4ut
j + ysAukt+
+ 0 < A < 1, TI > 0 , 0 ~ ' f 2
"YrC4i,t_ I + "Y7Xi,t
tx,] + ,i,,, ~ 1, T3 > 0 , ")/4<0, T5 < 0 , "~6~>0(.9),
')/7 < 0 ( ? ) , 0,~ "Y8 <" 1. This equation is the basis for the empirical work.
(2)
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3. Data and estimation method
The data for the empirical study comprise a panel of annual observations for 68 industries (at 3-digit level) in Dutch manufacturing and cover the period from 1974 through 1986. In their majority, the data stem from the DUMA database, which is based on the CBS's 'Produktiestatistieken Industrie'. For the composition of the 'Produktiestatistieken Industrie', all firms with 10 or more employees are approached; data of firms with less than 10 employees are thus omitted. Separate data for small (10 to 50 employees) and large firms (50 or more employees) are available for 36 industries. A more detailed description of the DUMA database is provided by Bakker and Prince (1992). This database is supplemented by industry-level data in respect of hours worked and employers' contributions. The number of hours worked, which is available for 11 2-digit industries, is computed by correcting the contractual number of hours worked for vacation, holidays, overtime, sick leave, idle days, reduction of working hours, strikes, etc. The construction of the actual number of hours worked is described in Bol et al. (1982). As data in respect of employers' contributions at 3-digit level are not available, the corresponding 2-digit figures are adopted. The database is further supplemented by the average manufacturing wage rate and by macro-level data in respect of unemployment rate, short-term unemployment rate and unemployment-benefit ratio. The computation of industry-specific value-added prices from output prices and prices of material inputs is carried out along the suggestions rendered by Nickell and Kong (1992, p. 1584). The ordinary least-squares method (OLS) and the fixed effects method do not provide consistent estimates of the wage equation as some of the explanatory variables are endogenous. The industry-specific price, output and employment are factually determined after wage negotiations only. The endogenous variables generate correlation between the explanatory variables and the disturbances. One method for a consistent estimation of the wage equation is the generalized method of moments (GMM); see Arellano and Bond (1991). This method produces consistent estimates by using instrumental variables. So as to eliminate the industry-specific constant, first differences over time are used. Instruments must be selected in such a way that they are correlated with the explanatory variables yet not correlated with the disturbances in the model in first differences, while the number of instruments must be higher than the number of regressors. For endogenous variables (eventually including a lagged dependent variable) only those dating back from two previous or earlier periods may be used as instruments, while all variables may be used as instruments for strictly exogenous variables. This matrix of instruments is nonetheless only suitable in the event of compliance with the hypothesis that no serial correlation exists. In the event of e.g. first-order serial correlation (i.e. correlation between Ei. t and Ei.t_ j), the use of endogenous variables is restricted to variables dating back from three previous or earlier periods. Otherwise, correlation will emerge between instru-
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m e n t s a n d d i s t u r b a n c e s in first differences. T h e s e l e c t i o n o f i n s t r u m e n t s thus d e p e n d s o n h y p o t h e s e s w i t h r e s p e c t to the d i s t u r b a n c e s . In v i e w o f the a b o v e , the h y p o t h e s i s that n o serial c o r r e l a t i o n exists will b e tested.
4. Empirical findings Firstly, w a g e Eq. (2) is e s t i m a t e d for the entire p a n e l o f 68 industries. S u b s e q u e n t l y , this e q u a t i o n is e s t i m a t e d for the 36 i n d u s t r i e s for w h i c h s e p a r a t e data a b o u t large a n d s m a l l f i r m s are available. Finally, the e q u a t i o n is s e p a r a t e l y e s t i m a t e d for the large a n d the s m a l l firms in t h e s e industries. T h e e s t i m a t i o n results are s u m m a r i z e d in T a b l e 1. In the r e p o r t e d r e g r e s s i o n s the m a n u f a c t u r i n g w a g e rate is a d o p t e d for the w a g e rate outside i n d u s t r y i. C o l u m n 1 s h o w s that for the 68 i n d u s t r i e s the w e i g h t o f the i n t e r n a l factors e q u a l s 0.12. T h i s w e i g h t is m o r e or less in a c c o r d a n c e to that f o u n d b y Nickell a n d
Table l Wage rate in manufacturing industries in the Netherlands (1974-1986); dependent variable: wi, t - w,. a Variables
68 industries
36 industries
Large firms
Small finns
Pi.t+Yi.t--ni.t--wt
0.118 (0.009) -- 0.095 (0.007) 0.149 (0.012) -0.169 (0.036) -0.151 (0.026) - 0.123 (0.058) 0.140 (0.014) - 0.048 (0.006) 0.489 (0.05 r)
0.151 (0.0 ! 6) - 0.055 (0.009) 0.171 (0.035) -0.219 (0.124) -0.347 (0.041) - 0.541 (0.062) 0.135 (0.039) - 0.002 (0.016) 0.799 (0.114)
0.197 (0.023) - 0.053 (0.007) 0.244 (0.043) -0.376 (0.117) -0.344 (0.047) - 0.707 (0.069) 0.096 (0.042) 0.022 (0.021 ) 1.015 (0.113)
0.007 (0.004) -- 0.012 (0.004) -0.308 (0.058) 0.472 (0.141) -0.110 (0.069) 0.459 (0.097) 0.230 (0.042) - 0.080 (0.015 ) -0.112 (0.181)
- 1.373 33.57 (df = 25)
1.063 29.85 (df = 25)
Ani., hi, t bt
ut- l Auk t
C4i.tl xi. t
lxi. t -- tx t
m ~ N(0, 1) s ~ X2
-0.904 58.16 (df = 55)
0.994 30.87 (df = 25)
a Standard errors are denoted in parentheses. The wage equation is estimated in first differences by DPD, a computer program written by Arellano and Bond, Institute of Economics and Statistics, University of Oxford. The variables Api.t, Ayi. t and Ani. t are treated as endogenous. They are instrumented by a constant term, A w i . , _ 2 , A w i , t _ 3 , Awl, ~ 4 up to Awi,t_ 7 (only for 68 industries), Api,t-2' Ayi,t 2 and Ani, t 2.
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Wadhwani (1990) and Nickell et al. (1994) for the UK. It is higher than that found by Holmlund and Zetterberg (1991) for Finland, Norway, Sweden and West Germany. It is lower than the weight found by Holmlund and Zetterberg for the US. The change in employment appears to have a negative impact on wages. So, we find no evidence in favour of insider or hysteresis effects. The impact of the change in employment on wages appeared to be non-robust in previous studies as well; see Nickell and Wadhwani (1990). The negative sign can be explained by assuming that employment adjustment is sluggish and that there is persistence in the exogenous shocks. The estimates of the four-firm concentration ratio and the export share imply that product market power has a positive impact on the wage rate. The coefficient of C 4 i . t 1 implies that an increase in the share of employment of the four largest firms in an industry by one percentage point generates an increase in wage rate by 0.14 percent. The coefficient of x i . t implies that an increase in the export share by one percentage point reduces the wage rate by 0.05 percent. The coefficient of the difference between sectoral and aggregate employers' contributions txi, t - t x t factually has a value ranging from zero to one, viz. 0.49. This suggests that bargaining between employers and trade unions implicitly entails negotiations in respect of gross wages and, approximately, 51 percent of employers' contributions. The negative sign of the unemployment-benefit ratio b is against the assumptions of the theoretical model. 2 The inclusion of a lagged dependent variable to capture adjustment lags appeared unnecessary. The table recapitulates the test statistics m and s. The statistic m tests for second-order serial correlation of residuals; the absence of second-order serial correlation of the residuals in first differences is a prerequisite for the absence of first-order serial correlation of the residuals in levels. The distribution of the test statistic is standard normal N(0, 1). The test statistic m denotes the Sargan test on the validity of instruments (see Sargan, 1958), which is distributed chi-square. The null hypotheses, i.e. that no serial correlation exists and that suitable instruments are selected, are not rejected at the 5 percent significance level. To investigate whether firm size affects the weight of the internal factors, wage Eq. (2) is estimated separately for large and small firms. The estimation results for the industries for which separate observations are available are summarized in column 2. For these industries, the weight of internal factors is equivalent to 0.15. The impact of unemployment, change of short-term unemployment and taxes is stronger in these 36 industries than in all 68 industries. The results for large and
2 If the wage rate in the market sector is adopted for wt, the impact of the unemployment-benefit rate becomes positive; however, the impact of unemployment and the change in short-term unemployment become positive as well. This corresponds to a finding by Graafland and Lever (1996), that unemployment has a strong negative impact on wages in the service sector and is insignificant in the industrial sector. The choice of the wage rate outside industry i (from the manufacturing sector or the market sector) does not seriously affect the relative weight of internal and external factors.
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small firms are denoted in columns 3 and 4. As anticipated, the weight of internal factors in small firms is substantially lower than that in large finns. For large finns, the weight of internal factors is equivalent to 0.20. For small finns, the weight of internal factors amounts to 0.01. Similar results were previously established by Brunello and Wadhwani (1989) for Japan and the UK. Besides the difference in weights of internal and external factors, there are other differences between the results for large and small finns. The unemployment-benefit ratio has a positive impact on wages in small finns and a negative impact on wages in large firms. A high concentration in the output market has a positive impact on wages in small firms; lbr large firms the impact of market concentration on wages is much smaller. The coefficients of the tax rates suggest that bargaining in large firms entails negotiations in respect of gross wages, and in small firms negotiations in respect of labour costs. The signs of the number of hours worked and of the change in short-term unemployment in the wage equation for small firms are against the assumptions of the theoretical model. To investigate whether product market power increases the impact of internal factors on wages interaction terms of market power and internal factors can be included. In order to secure that the weight of the internal and external factors add up to unity, the aggregate wage rate is subtracted from the internal factors. The interaction term of the export share with the internal variables appeared to be highly correlated with the export share itself, leading to quite imprecise estimates. Therefore, only an interaction term of the four-firm concentration ratio with the internal variables is included. This results in the following wage equation: wi, ,
- w, = To, + A0( Pi.t + Yi., - ni., - w , ) + y l C 4 i , t ( Pi,, + Yi,, - ni,, - w t ) + y l A n i , , q'- Y2hi,, + Y3bt + ~/4/~/t- 1 + ysAukt + T6C4i,t
+
+
00, > o(?),
< o ( ? ) , o _<
I
+
T~>0,00,
(3)
T4<0, Ts<0,
_< 1.
The elasticities of the sectoral wage with respect to the internal factors and the concentration ratio are determined by A0 + C 4 i A j and Y6 + ( P i + Yi - ni - w)Al, respectively. The corresponding standard errors can be computed using Var(A o + C 4 i A I) = Var(A 0) + ( C 4 i ) 2 V a r ( A l ) + 2 C 4 i C o v ( A o, AI) and Var(y 6 + (Pi + Yi n i - w)AI) = V a r ( y 6) + ( P i + Yi - n i - w)2Var(Al ) + 2 ( P i + Yi - n i w)Cov(y 6, At), respectively. The estimation results are denoted in Table 2; the corresponding elasticities evaluated at the sample mean are denoted in Table 3. From Table 2 it is clear that for the 68, the 36 and the large firms in 36 industries market concentration increases the impact of the internal factors. Table 3 shows that the direct impact of market concentration on wages becomes insignificant.
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Table 2 Wage rate in manufacturing industries in the Netherlands (1974-1986); dependent variable: wi, t - w r a.b Variables Pi,t + Yi,l - ni,t - wt C 4 i , ( Pi,t + Y i , t - n i , t - w t
~ni, t hi, t
b~ ut_ I Auk t C4i.t-1
xi, z txi, t - t x t
m~N(0,1) s ~ X2
68 industries
36 industries
Large firms
Small firms
(0.015) -0.045 (0.007) 0.476 (0.041)
0.121 (0.019) 0.014 (0.005) -0.063 (0.011) 0.174 (0.038) -0.200 (0.132) - 0.292 (0.052) -0.529 (0.067) 0.184 (0.039) 0.003 (0.014) 0.934 (0.138)
0.162 (0.028) 0.011 (0.006) -0.046 (0.007) 0.215 (0.044) -0.238 (0.129) -0.237 (0.074) -0.599 (0.085) 0.131 (0.042) -0.017 (0.021) 1.152 (0.133)
0.013 (0.004) -0.087 (0.016) -0.001 (0.008) -0.350 (0.052) 0.041 (0.137) -0.365 (0.070) 0.231 (0.158) -0.032 (0.113) -0.022 (0.015) 0.035 (0.271)
-0.976 55.96 ( d f = 5 5 )
-0.799 - 1.310 27.93 (df= 25) 30.56 ( d f = 2 5 )
0.112 (0.010) ) 0.012 (0.002) -0.094 (0.008) 0.135 (0.013) -0.054 (0.046) - 0.104 (0.029) - 0.051 (0.055) 0.185
a See notes of Table 1. b Besides A p i , t , Ayi, t and Ani,t, A C 4 i , t ( P i , t + last variable is instrumented by A C 4 i , t 2(Pi,t_2
1.144 31.26(df= 25)
Yi,t - - ni,t - - w t ) has been treated as + Yi,t
2 - - ni,t
endogenous. The
2 -- Wt-2)"
T h e e s t i m a t e s for the s m a l l f i r m s are s o m e w h a t e x c e p t i o n a l . T h e i m p a c t o f m a r k e t c o n c e n t r a t i o n o n the w e i g h t o f the i n t e r n a l factors (see T a b l e 2) a n d the elasticity o f the i n t e r n a l factors (see T a b l e 3) are f o u n d to b e n e g a t i v e , c o n t r a r y to t h e theoretical model. The direct impact of market concentration on small firms'
Table 3 Elasticities of wage rate in manufacturing industries in the Netherlands (1974-1986). " Elasticities
68 industries
36 industries
Large firms
Small firms
Internal factors
0.117 (0.009) 0.022 (0.031)
0.126 (0.019) 0.003 (0.070)
0.166 (0.027) - 0.020 (0.078)
-0.017 (0.007) 1.130 (0.104)
Concentration ratio
a Standard errors are denoted in parentheses.
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wages is positive and quite large. Including the interaction effect does not seriously affect the other estimates.
5. Conclusions The wage rate in Dutch manufacturing industries is determined by both internal (sector-specific) and external (labour-market-related) factors. In comparative terms, the weight of external factors is by far the highest, given that for 68 industries, the weight of internal factors is estimated at 0.12, while that of external factors is estimated at 0.88. The weight of internal factors fairly approximates that established in previous findings for the UK; it is higher than that established for Finland, Norway, Sweden and West Germany, yet lower than that established for the US. The hypothesis of increasing wage rates with decreasing numbers of insiders is not substantiated by the empirical results. Market concentration, used as an indicator of product market power, appears to exert a significantly positive impact on the wage rate. The export share, used as an approximation for foreign competition, appears to exert a significantly negative impact. After including interaction effects the weight of the internal factors appears to be higher in more concentrated industries, whereas the direct impact of market concentration on wages disappears. In large firms, internal factors play a substantially higher role as regards wage formation than in small firms; conceivably, because large firms have a superior internal labour market at their disposal, and because they are more often covered by their own collective labour agreements. For large firms, the weight of internal factors is estimated at 0.17-0.20; for small finns at 0-0.01. For the entirety of the 36 industries incorporated in these estimations, a total weight of 0.13-0.15 is found. One suggestion for further research is to estimate the influence of the bargaining power of trade unions on wages. This estimate has been omitted in this study, given the non-existence of a publication of detailed data in respect of the numbers of employees covered by collective labour agreements. As for the future, we hope to be able to obtain relevant data through the Ministry of Social Affairs and Employment. Another suggestion for further research is to improve the estimation of the impact of market power on wages by using data of individual firms.
Acknowledgements The authors acknowledge the suggestions rendered by A. Kleijweg, A. van Soest, M. Verbeek and an anonymous referee in respect of a previous version of this paper.
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Appendix A. Data appendix
The empirical study is based on data for 68 3-digit industries (or combinations thereof) in Dutch manufacturing. The SBI codes and the description of these industries are narrated hereinafter. For 36 of these industries, separate data are available for large (50 or more employees as per 30 September) and small firms (10 to 50 employees). These 36 industries are indicated by an asterisk (*). No
SBI
1
20.1 *
2 3
20.4 20.6 *
4 5 6 7 8 9 10 11 12
20.7 20.8 * 20.9 * 21.2 * 21.3 * 21.4 21.5 21.6 22.1 + 22.2 22.3 22.5 23.1 + 23.2 24.1 24.2 24.3 25.3 25.4 25.5 25.7 26.1 26.2 * 26.3 * 27.1" 27.2 * 27.3 * 29.1 29.2
13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30
Description slaughtering and meat processing industry flour mills, groats and rice husking mills, etc. manufacture of margarine and other vegetable and animal oils and fats canning, preserving and processing of fruits and vegetables manufacture of bread, rusks, pastries, cakes and biscuits manufacture of cocoa, chocolate and confectionery manufacture of compounded animal stock feeds manufacture of other food products alcohol manufacturing and distilleries breweries and malt houses non-alcoholic beverages wool industry cotton industry knitting and hosiery industry manufacture of carpets and rugs manufacture of ready-made clothing contract manufacture of ready-made clothing leather industry leatherware industry (excl. clothing) footwear industry carpeting, parqueting industry manufacture of wooden containers manufacture of other wooden articles furniture industry (excl. metal furniture) paper and cardboard industry paperware industry corrugated cardboard and cardboard industry printing industry publishing industry book binding industry manufacture of fertilizers manufacture of plastics
lO6 31 32 33 34 35 36 37 38 39 40
M.H. C. Lever, J.M. van Werkhooven / Labour Economics 3 (1996) 93-107
29.3 29.4 + 30.0 29.5 * 29.6 * 29.7 *
52 53 54 55 56
29.8 29.9 * 31.1 31.3 32.1 +32.2 32.3 32.5 * 33.1 +33.2 +33.4 33.3 * 34.0 * 34.1 * 34.2 * 34.3 * 34.4 * 34.5 * 34.6 * + 34.8 * 34.7 * 34.9 35.1 * 35.2 * 35.3 *
57
35.4 *
58 59
35.5 35.6 *
60 61 62 63 64
35.7 * 35.8 35.9 * 36 37.1 *
41 42 43
44 45 46 47 48 49 50 51
manufacture of dye-stuffs and pigments other chemical basic industry manufacture of artificial and synthetic yams and fibres manufacture of paint, lacquer, varnish and printing ink manufacture of pharmaceutical and antiseptic dressings manufacture of soap; other washing and cleaning materials, perfumes and cosmetics manufacture of chemical detergents etc. manufacture of other chemical products rubber-processing industry plastic-processing industry manufacture of brick and tiles manufacture of earthenware manufacture of sand-lime bricks manufacture of concrete and cement products iron and steel industry manufacture of steel tubes non-ferrous metal industry wire-drawing and cold-rolling industry foundries iron works, crushing and pressing industry manufacture of screws, mass products from lathes and springs construction of tanks, reservoirs and pipelines other metal construction manufacture of metal furniture metal-packing industry manufacture of other metal products manufacture of heating and cooking apparatus (excl. electric) forges, surface treatment manufacture of agricultural machinery manufacture of metal-working machinery manufacture of machinery for food-processing, chemical and related industries lifting and other transport equipment for mining, construction, building-materials and metallurgic industries manufacture of cog-wheels, bearings and other driving gear manufacture of machinery and other equipment for industries n.e.s. manufacture of steamboilers, engines and turbines manufacture of office machinery manufacture of other machinery and apparatus electrotechnical industry manufacture and assembly of automobiles
M.H.C. Lever, J.M. van Werkhooven / Labour Economics 3 (1996) 93-107
65 66 67 68
+ 37.3 * + 37.7 * 37.2 * 37.4 37.6 * 37.9 *
107
manufacture of car parts aircraft-construction and repair industry manufacture of coach work and trailers shipbuilding and ship repair industries manufacture of bicycles and motorcycles manufacture of other transport equipment
References Arellano, M. and S. Bond, 1991, Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations, Review of Economic Studies 58, 277-297. Bakker, K. and Y.M. Prince, 1992, DUMA: Industriebestand 1974-1986, drie-digit bedrijfsgroepen, Data research 2 (ELM, Zoetermeer). Blanchard, O.J. and L.H. Summers, 1986, Hysteresis and the European unemployment problem, in: S. Fisher, ed., NBER macroeconomics annual 1 (NBER, Cambridge, MA) 15-87. Bol, A., A. Nijsen, G. Regter and F. van Rossum, 1982, Werkgelegenheid en arbeidsvolume in het midden- en kleinbedrijf, 1960-1980: Een analyse over de bijdrage van het MKB in de totale werkgelegenheid (ELM, Zoetermeer). Brunello, G. and S. Wadhwani, 1989, The determinants of wage flexibility in Japan: Some lessons from comparison with the UK using micro-data, Discussion paper 362 (Centre for Labour Economics, London School of Economics, London). Cowling, K. and M. Waterson, 1976, Price-cost margins and market structure, Economica 43, 267-274. Dienst Collectieve Arbeidsvoorwaarden, 1987, De betekenis van cao's in kwantitatieve zin, Sociaal Maandblad Arbeid 42, 707-713. Gottfries, N. and H. Horn, 1987, Wage formation and the persistence of unemployment, Economic Journal 97, 877-884. Graafland, J.J. and M.H.C. Lever, 1996, Internal and external forces in sectoral wage formation: Evidence from the Netherlands, Oxford Bulletin of Economics and Statistics 58, 241-252. Holmlund, B. and J. Zetterberg, 1991, Insider effects in wage determination: Evidence from five countries, European Economic Review 35, 1009-1034. Layard, P.R.G., S.J. Nickell and R. Jackman, 1991, Unemployment: Macroeconomic performance and the labour market (Oxford University Press, Oxford). Lever, M.H.C., 1995, Insider-outsider effects in wage formation: An empirical survey, Bulletin of Economic Research 47, 257-274. Lindbeck, A.J. and D.J. Snower, 1988, The insider-outsider theory of employment and unemployment (MIT Press, Cambridge, MA). Nickell, S.J. and P. Kong, 1992, An investigation into the power of insiders in wage determination, European Economic Review 36, 1573-1599. Nickell, S.J. and S. Wadhwani, 1990, Insider forces and wage determination, Economic Journal 100, 496-509. Nickell, S.J., J. Vainiomaki and S. Wadhwani, 1994, Wages and product market power, Economica 61, 457-473. Sargan, J.D., 1958, The estimation of economic relationships using instrumental variables, Econometrica 26, 393-415. Vetter, H. and T.M. Andersen, 1994, Do turnover costs protect insiders?, Economic Journal 104, 124-130.
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LABOUR ECONOMICS ELSEVIER
Labour Economics 3 (1996) 93-107
Insider power, market power, firm size and wages: Evidence from Dutch manufacturing industries Marcel H.C. Lever *, Jolanda M. van Werkhooven ElM, P.O. Box 7001, 2701 AA Zoetermeer, The Netherlands
Received 15 May 1995; accepted 19 July 1995
Abstract The objective of this study is to assess the impact of internal (sector-specific) and external (labour-market-related) factors, the number of insiders, product market power and finn size on wages in Dutch manufacturing industries. The weight of the internal factors approximates that found in earlier research for the UK, it is higher than that found for Scandinavian countries, yet lower than that found for the US. A high weight of the internal factors is generally deemed favourable as it stabilizes employment. Evidence for the emergence of insider effects, which may cause unemployment persistence, cannot be established. It is however observed that product market power increases the weight of internal factors. Finally, the weight of internal factors appears to be substantially higher for large finns than for small ones. JEL classification: J31 Keywords: Wage formation; Insider power; Product market power; Firm size; Dutch manufacturing
industry
* Corresponding author. Tel.: 31-79-3448450; fax: 31-79-3415024; e-mail: [email protected]. 0927-5371/96/$15.00 Copyright © 1996 Published by Elsevier Science B.V. All rights reserved PII S0927-5 37 1(96)00004-8
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1. Introduction The neoclassical model of perfect competition cannot explain the persistence of unemployment and the existence of inter-sectoral wage differentials of employees with comparable qualifications performing similar tasks. So as to be able to explain this unemployment and the wage differentials, three alternative theories were developed in the eighties, i.e. the union bargaining theory, the efficiency wage theory and the insider-outsider theory. In view of the influential role of trade unions in the Netherlands where wage formation is concerned, we have adopted a model which is based on the union bargaining theory and the insideroutsider theory. The insider-outsider theory emphasizes that workers (insiders) have more bargaining power in wage bargaining than the unemployed (outsiders). This difference in bargaining power is due to different levels of know-how and skills. Given their bargaining power, insiders are able to obtain a share of the revenue of a finn in addition to the reservation wage of outsiders. The single-period models of Lindbeck and Snower (1988) imply that in addition to the reservation wage of an outsider, an insider can at the most acquire the amount of the cost of replacing one insider by one outsider. In their multi-period model, Vetter and Andersen (1994) illustrate that in addition to the reservation wage of an outsider, an insider cannot acquire more than the amount of the cost of replacing one insider by one outsider, divided by the number of periods (years) of active service in the finn. The insider effect may generate a state of equilibrium where unemployment exists. After this sketch of the theoretical background, four issues deserve further discussion. Firstly, if this bargaining approach is correct, the wage rate at firm- or sectoral level depends on both the performance of the firm or sector and the situation in the labour market. A high weight of internal factors implies that the wage rate adapts to the performance of the firm or sector. This produces not only stable employment but also changes in relative wage rates. A high weight of external factors implies that the wage rate primarily adapts to overall performance of the economy. This produces less stable employment and fewer changes in relative wages. A high weight of internal factors is generally deemed favourable. Secondly, the bargaining approach suggests an increasing level of wage rate with decreasing numbers of insiders. For, given a low number of insiders, related to the production technology of that firm and market demand for its products, even in the event of a high wage rate their employment is not at immediate risk if the firm is affected by a temporary adverse shock; see Gottfries and Horn (1987). The existence of this insider effect may be tested by examining whether employment from the previous period, as an approximation for the number of insiders, exerts negative impact on the wage rate. However, as noted in Lever (1995), the negative correlation between the wage rate and the previous employment level depends crucially on the assumptions with respect to both the persistence of the exogenous shock and the sluggishness in labour demand. Blanchard and Summers (1986), for
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example, argue that if labour demand is sluggish and the exogenous shocks are correlated over time, a positive correlation results between the wage change and the employment change. Insider effects are deemed unfavourable, as they delay the post-recession recovery of employment. Thirdly, if wages are determined by bargaining, it is probable that workers share in the rents which are due to the firm's power in the product market. So, product market power may have a positive impact on the wage rate. Fourthly, the weight of internal factors is likely to be lower for small firms than for large ones, one reason being that large firms have an internal labour market at their disposal. This internal labour market is created to ensure remunerative investment in employees. Through their know-how and experience employees in the internal labour market command a comparatively strong position in wage negotiations and may demand larger parts of revenue effected. Another reason entails that large firms enter their own collective labour agreements more often than small firms do. Previous studies confirm the relevance of internal and external factors in wage formation. The evidence with respect to the impact of the number of insiders on wages is mixed. Nickell and Wadhwani (1990), using data for 219 manufacturing firms in the UK covering the 1975 through 1982 span, estimate the weight of internal factors at 0.11 and that of external factors at 0.89. The impact of the number of insiders on the wage rate does not appear to be robust. In a comparable analysis, Holmlund and Zetterberg (1991) find similar or lower weights for internal factors for Finland (0.00-0.01), Norway (0.03-0.04), Sweden (0.03-0.12) and West Germany (0.04-0.12), and higher weights for the US (0.30-0.48). In Nickell et al. (1994), the sample is extended to 814 manufacturing firms. As regards the weight of internal factors (0.11-0.16) and the impact of the number of insiders, the results are comparable to the findings of the former study. New findings comprise that the market share of a firm in the product market appears to exert positive impact on the wage rate, and that the weight of internal factors is virtually identical for large and small firms. Brunello and Wadhwani (1989), however, find that in Japan and the UK internal factors in large firms exert a significantly positive impact, and that internal factors are insignificant for small firms. Conceivably, the discrepancy between the findings of Brnnello and Wadhwani and those of Nickell et al. (1994) is attributable to different definitions of the boundary between small and large firms. Nickell et al. probably define the boundary between large and small above 1,000 employees, 1 whereas Brnnello and Wadhwani draw the boundary at 300 (Japan) or 500 (UK) employees. The objective of this study comprises the following four aspects. Firstly, a determination of the relative weight of internal (sector-specific) and external
I Nickell et al. draw the boundary between 'large' and 'small' at median employmentlevel. While not reporting the size of the median, they indicate that the sample comprises large firms with 4,332 employeeson averagein 1982.
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(labour-market-related) factors as regards wage formation in Dutch manufacturing industries. Secondly, an examination as to whether the number of insiders, based on employment in the previous period, exerts negative impact on the wage rate. Thirdly, an investigation as to whether market strength of firms in the product market affects the level of wages or the weight of the internal factors. Finally, an analysis as to whether there are differences in weight of internal factors between large and small firms. The composition of this paper includes the derivation of a wage equation in Section 2. The data and the estimation method are presented in Section 3, while the empirical findings are recapitulated in Section 4. Section 5 comprises the conclusions.
2. Theoretical framework
The wage equation which is used is derived from a bargaining model. This model is proposed by Nickell and Wadhwani (1990), Layard et al. (1991) and Nickell et al. (1994). An important reason to base wage equations on a bargaining model is that negotiations between trade unions and firms play an important part as regards the determination of wages in the Netherlands. Figures of the Ministry of Social Affairs and Employment reveal that during the seventies and eighties around 75 percent of all employees in the market sector are covered by collective labour agreements. The model presumes that wages are determined through negotiations between firm and trade union and that the employment level is set by the firm. Further, there is imperfect competition in the product market. Output demand is subject to exogenous shocks, which are unknown at the stage of bargaining. The output price and the employment level are set by the firm after the wage negotiations and after the size of the shock is identified. The output price and the employment level are set such that profits are maximized. Finally, it is presumed that the trade union maximizes the expected income for their members, who are the existing employees. The bargaining model results in the following wage equation (cf. Nickell et al., 1994): Wi = ~/Oi + A[ pi + 4'i -}- (1 -- ol ) ( ki -- nli) ]
+ ( 1 -- ~)[W "[- ~/3 b + ~4 u + ff/5Auk] + ~t6K i "[- ~913i, 0<,h.< 1,0
1,~3>0,~4
<0,~/5 < 0 , ~ 6 < 0 ( ? ) , ] / 9 > 0
(1) ,
where: wi is the sectoral wage rate (in logs); p/ is the sectoral output price (value added, in logs); 4'/ is the sectoral productivity index (in logs); k/ is the sectoral capital stock (in logs); nt/ is the sectoral number of insiders (in logs); w is the wage rate outside industry i (in logs); b is the ratio of unemployment benefits to
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97
the average wage rate; u is the aggregate unemployment rate; u k is the aggregate rate of short-term unemployment (less than one year); Ki is the sectoral index of competition in the product market; /3i is the sectoral index of union bargaining power. Eq. (1) shows that sectoral wages are a log-linear combination of internal and external factors, product market power and union bargaining power. The equation also shows that the weight of the internal factors (A) and that of the external factors (1 - A) add up to unity. Unemployment u and the change in short-term unemployment A u k exert negative impact on the wage rate. Unemployment benefits b and the bargaining power 13 exert positive impact on the wage rate. The impact of the degree of competition in the product market on wages cannot be signed a priori. There is a negative effect from K (so a positive effect from market power) on wages which arises because the union can expropriate part of the rents of monopoly power in the form of higher wages. However, there is also a positive effect from K on wages which results from the reduced probability of insiders' employment, as monopoly power in the product market reduces output and employment. It is reasonable to assume that these effects on the probability of employment are small, so the total effect from K on wages is negative. The weight of the internal factors (A) depends positively on union power (/3) and negatively on product-market competition (K); see Layard et al. (1991, p. 186). Several adjustments are required so as to estimate the industry-specific wage equation. An important assumption in this respect is that the number of insiders on whose behalf trade unions negotiate is equivalent to the number of employees employed in the previous period ( n t i = n i _ l ) . Based on the Cobb-Douglas production function Yi = (/)i K/~N~1-~ which is used to derive (1), it thus holds that tbi + (1 - t ~ ) ( k i - n t i ) = ( Yi - n i ) - (1 - a ) ( n l i - ni). Using these two equivalences, it thus holds that ~bi + (1 - a ) ( k i - n l i ) = ( Y i - n i ) + (1 - c e ) A n i , with Yi is sectoral value added (in logs). The second adjustment entails the exact definition of the industry wage rate and the wage rate outside industry i. With respect to w, the wage rate outside industry i, either the manufacturing wage rate or the macro wage rate can be adopted. With respect to w i it is not evident whether bargaining entails negotiations in respect of labour costs or gross wages. Therefore, the difference between the sectoral and the aggregate rate of employers' contributions is included in the regression equation. Employers' contributions at macro or manufacturing level are expressed by TX, those at industry level by TXi. Both rates are expressed in terms of perunages. The logarithmic tax terms which can be used to obtain gross wages from labour costs may be defined as tx = - In(1 - TX) and tx i = - ln(1 - TXi). If the coefficient of the difference between the tax rates T8 equals zero, bargaining implicitly entails labour-costs negotiations, and if T8 equals one, bargaining entails gross-wage negotiations. Probably, "Y7 ranges between these extremes. The third adjustment entails the inclusion of the yearly number of hours worked, which (in logs) is denoted by h i . In the present study the industry-specific
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employment is measured in persons and the industry-specific wage rates are measured per person per year. The manufacturing wage rate and the macro wage rate are measured per labour year. Differences between these units of measurement arise if the actual average number of hours worked differs from the number of hours in a labour year. This may be due to overtime, reduction of working time, part-time work, etc.. In order to correct for these differences the actual number of hours worked is included as explanatory variable. The fourth adjustment entails the bargaining power of trade unions. So as to identify the bargaining power of trade unions the extent of coverage of collective labour agreements can be used. Figures in respect of the coverage of collective labour agreements are published at high aggregation level only. A publication by the Department of Collective Labour Agreements (Dienst Collectieve Arbeidsvoorwaarden, 1987) illustrates that the percentage of employees which is covered by collective labour agreements is practically constant over time at aggregate level. This variable becomes void when first-differences are used for an estimation by GMM. The variable fli has therefore been omitted in the empirical study. The fifth adjustment entails that the degree of competition in the product market Ki is deemed a declining function of the degree of market concentration in an industry and an increasing function of foreign competition; see Cowling and Waterson (1976). The four-firm concentration ratio C 4 i and the export share x i are used as indicators here. C 4 i is defined as employment in the four largest firms in an industry, divided by total employment in firms with ten or more employees at 30 September; x i is defined as the share of exports in industrial sales. In line with the earlier discussion we expect that the coefficient of C 4 i in the wage equation is positive and that of x i is negative. The sixth adjustment entails rearranging of the equation so as to ensure that the weights of internal and external factors add up to unity. The equation is rearranged by subtracting the aggregate wage rate from both the sectoral wage rate and sectoral value added per employee. Finally, the degree of concentration C4ia and the unemployment rate u t are lagged by one year, as the lagged variables comprise the most recent data available during wage negotiations. Besides, the adoption of lags prevents the emergence of endogeneity-related problems. Following these adjustments, the wage equation may be written as Wi,t -- Wt = ~/Oi 3¢- A ( Pi,t q- Yi,t -- Fli,t -- Wt) "~- ~/I Al2i,t 3¢. ,.)/2hi, t ~_ ,Y3b t
+ Y4ut
j + ysAukt+
+ 0 < A < 1, TI > 0 , 0 ~ ' f 2
"YrC4i,t_ I + "Y7Xi,t
tx,] + ,i,,, ~ 1, T3 > 0 , ")/4<0, T5 < 0 , "~6~>0(.9),
')/7 < 0 ( ? ) , 0,~ "Y8 <" 1. This equation is the basis for the empirical work.
(2)
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3. Data and estimation method
The data for the empirical study comprise a panel of annual observations for 68 industries (at 3-digit level) in Dutch manufacturing and cover the period from 1974 through 1986. In their majority, the data stem from the DUMA database, which is based on the CBS's 'Produktiestatistieken Industrie'. For the composition of the 'Produktiestatistieken Industrie', all firms with 10 or more employees are approached; data of firms with less than 10 employees are thus omitted. Separate data for small (10 to 50 employees) and large firms (50 or more employees) are available for 36 industries. A more detailed description of the DUMA database is provided by Bakker and Prince (1992). This database is supplemented by industry-level data in respect of hours worked and employers' contributions. The number of hours worked, which is available for 11 2-digit industries, is computed by correcting the contractual number of hours worked for vacation, holidays, overtime, sick leave, idle days, reduction of working hours, strikes, etc. The construction of the actual number of hours worked is described in Bol et al. (1982). As data in respect of employers' contributions at 3-digit level are not available, the corresponding 2-digit figures are adopted. The database is further supplemented by the average manufacturing wage rate and by macro-level data in respect of unemployment rate, short-term unemployment rate and unemployment-benefit ratio. The computation of industry-specific value-added prices from output prices and prices of material inputs is carried out along the suggestions rendered by Nickell and Kong (1992, p. 1584). The ordinary least-squares method (OLS) and the fixed effects method do not provide consistent estimates of the wage equation as some of the explanatory variables are endogenous. The industry-specific price, output and employment are factually determined after wage negotiations only. The endogenous variables generate correlation between the explanatory variables and the disturbances. One method for a consistent estimation of the wage equation is the generalized method of moments (GMM); see Arellano and Bond (1991). This method produces consistent estimates by using instrumental variables. So as to eliminate the industry-specific constant, first differences over time are used. Instruments must be selected in such a way that they are correlated with the explanatory variables yet not correlated with the disturbances in the model in first differences, while the number of instruments must be higher than the number of regressors. For endogenous variables (eventually including a lagged dependent variable) only those dating back from two previous or earlier periods may be used as instruments, while all variables may be used as instruments for strictly exogenous variables. This matrix of instruments is nonetheless only suitable in the event of compliance with the hypothesis that no serial correlation exists. In the event of e.g. first-order serial correlation (i.e. correlation between Ei. t and Ei.t_ j), the use of endogenous variables is restricted to variables dating back from three previous or earlier periods. Otherwise, correlation will emerge between instru-
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m e n t s a n d d i s t u r b a n c e s in first differences. T h e s e l e c t i o n o f i n s t r u m e n t s thus d e p e n d s o n h y p o t h e s e s w i t h r e s p e c t to the d i s t u r b a n c e s . In v i e w o f the a b o v e , the h y p o t h e s i s that n o serial c o r r e l a t i o n exists will b e tested.
4. Empirical findings Firstly, w a g e Eq. (2) is e s t i m a t e d for the entire p a n e l o f 68 industries. S u b s e q u e n t l y , this e q u a t i o n is e s t i m a t e d for the 36 i n d u s t r i e s for w h i c h s e p a r a t e data a b o u t large a n d s m a l l f i r m s are available. Finally, the e q u a t i o n is s e p a r a t e l y e s t i m a t e d for the large a n d the s m a l l firms in t h e s e industries. T h e e s t i m a t i o n results are s u m m a r i z e d in T a b l e 1. In the r e p o r t e d r e g r e s s i o n s the m a n u f a c t u r i n g w a g e rate is a d o p t e d for the w a g e rate outside i n d u s t r y i. C o l u m n 1 s h o w s that for the 68 i n d u s t r i e s the w e i g h t o f the i n t e r n a l factors e q u a l s 0.12. T h i s w e i g h t is m o r e or less in a c c o r d a n c e to that f o u n d b y Nickell a n d
Table l Wage rate in manufacturing industries in the Netherlands (1974-1986); dependent variable: wi, t - w,. a Variables
68 industries
36 industries
Large firms
Small finns
Pi.t+Yi.t--ni.t--wt
0.118 (0.009) -- 0.095 (0.007) 0.149 (0.012) -0.169 (0.036) -0.151 (0.026) - 0.123 (0.058) 0.140 (0.014) - 0.048 (0.006) 0.489 (0.05 r)
0.151 (0.0 ! 6) - 0.055 (0.009) 0.171 (0.035) -0.219 (0.124) -0.347 (0.041) - 0.541 (0.062) 0.135 (0.039) - 0.002 (0.016) 0.799 (0.114)
0.197 (0.023) - 0.053 (0.007) 0.244 (0.043) -0.376 (0.117) -0.344 (0.047) - 0.707 (0.069) 0.096 (0.042) 0.022 (0.021 ) 1.015 (0.113)
0.007 (0.004) -- 0.012 (0.004) -0.308 (0.058) 0.472 (0.141) -0.110 (0.069) 0.459 (0.097) 0.230 (0.042) - 0.080 (0.015 ) -0.112 (0.181)
- 1.373 33.57 (df = 25)
1.063 29.85 (df = 25)
Ani., hi, t bt
ut- l Auk t
C4i.tl xi. t
lxi. t -- tx t
m ~ N(0, 1) s ~ X2
-0.904 58.16 (df = 55)
0.994 30.87 (df = 25)
a Standard errors are denoted in parentheses. The wage equation is estimated in first differences by DPD, a computer program written by Arellano and Bond, Institute of Economics and Statistics, University of Oxford. The variables Api.t, Ayi. t and Ani. t are treated as endogenous. They are instrumented by a constant term, A w i . , _ 2 , A w i , t _ 3 , Awl, ~ 4 up to Awi,t_ 7 (only for 68 industries), Api,t-2' Ayi,t 2 and Ani, t 2.
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101
Wadhwani (1990) and Nickell et al. (1994) for the UK. It is higher than that found by Holmlund and Zetterberg (1991) for Finland, Norway, Sweden and West Germany. It is lower than the weight found by Holmlund and Zetterberg for the US. The change in employment appears to have a negative impact on wages. So, we find no evidence in favour of insider or hysteresis effects. The impact of the change in employment on wages appeared to be non-robust in previous studies as well; see Nickell and Wadhwani (1990). The negative sign can be explained by assuming that employment adjustment is sluggish and that there is persistence in the exogenous shocks. The estimates of the four-firm concentration ratio and the export share imply that product market power has a positive impact on the wage rate. The coefficient of C 4 i . t 1 implies that an increase in the share of employment of the four largest firms in an industry by one percentage point generates an increase in wage rate by 0.14 percent. The coefficient of x i . t implies that an increase in the export share by one percentage point reduces the wage rate by 0.05 percent. The coefficient of the difference between sectoral and aggregate employers' contributions txi, t - t x t factually has a value ranging from zero to one, viz. 0.49. This suggests that bargaining between employers and trade unions implicitly entails negotiations in respect of gross wages and, approximately, 51 percent of employers' contributions. The negative sign of the unemployment-benefit ratio b is against the assumptions of the theoretical model. 2 The inclusion of a lagged dependent variable to capture adjustment lags appeared unnecessary. The table recapitulates the test statistics m and s. The statistic m tests for second-order serial correlation of residuals; the absence of second-order serial correlation of the residuals in first differences is a prerequisite for the absence of first-order serial correlation of the residuals in levels. The distribution of the test statistic is standard normal N(0, 1). The test statistic m denotes the Sargan test on the validity of instruments (see Sargan, 1958), which is distributed chi-square. The null hypotheses, i.e. that no serial correlation exists and that suitable instruments are selected, are not rejected at the 5 percent significance level. To investigate whether firm size affects the weight of the internal factors, wage Eq. (2) is estimated separately for large and small firms. The estimation results for the industries for which separate observations are available are summarized in column 2. For these industries, the weight of internal factors is equivalent to 0.15. The impact of unemployment, change of short-term unemployment and taxes is stronger in these 36 industries than in all 68 industries. The results for large and
2 If the wage rate in the market sector is adopted for wt, the impact of the unemployment-benefit rate becomes positive; however, the impact of unemployment and the change in short-term unemployment become positive as well. This corresponds to a finding by Graafland and Lever (1996), that unemployment has a strong negative impact on wages in the service sector and is insignificant in the industrial sector. The choice of the wage rate outside industry i (from the manufacturing sector or the market sector) does not seriously affect the relative weight of internal and external factors.
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small firms are denoted in columns 3 and 4. As anticipated, the weight of internal factors in small firms is substantially lower than that in large finns. For large finns, the weight of internal factors is equivalent to 0.20. For small finns, the weight of internal factors amounts to 0.01. Similar results were previously established by Brunello and Wadhwani (1989) for Japan and the UK. Besides the difference in weights of internal and external factors, there are other differences between the results for large and small finns. The unemployment-benefit ratio has a positive impact on wages in small finns and a negative impact on wages in large firms. A high concentration in the output market has a positive impact on wages in small firms; lbr large firms the impact of market concentration on wages is much smaller. The coefficients of the tax rates suggest that bargaining in large firms entails negotiations in respect of gross wages, and in small firms negotiations in respect of labour costs. The signs of the number of hours worked and of the change in short-term unemployment in the wage equation for small firms are against the assumptions of the theoretical model. To investigate whether product market power increases the impact of internal factors on wages interaction terms of market power and internal factors can be included. In order to secure that the weight of the internal and external factors add up to unity, the aggregate wage rate is subtracted from the internal factors. The interaction term of the export share with the internal variables appeared to be highly correlated with the export share itself, leading to quite imprecise estimates. Therefore, only an interaction term of the four-firm concentration ratio with the internal variables is included. This results in the following wage equation: wi, ,
- w, = To, + A0( Pi.t + Yi., - ni., - w , ) + y l C 4 i , t ( Pi,, + Yi,, - ni,, - w t ) + y l A n i , , q'- Y2hi,, + Y3bt + ~/4/~/t- 1 + ysAukt + T6C4i,t
+
+
0
< o ( ? ) , o _<
I
+
T~>0,0
(3)
T4<0, Ts<0,
_< 1.
The elasticities of the sectoral wage with respect to the internal factors and the concentration ratio are determined by A0 + C 4 i A j and Y6 + ( P i + Yi - ni - w)Al, respectively. The corresponding standard errors can be computed using Var(A o + C 4 i A I) = Var(A 0) + ( C 4 i ) 2 V a r ( A l ) + 2 C 4 i C o v ( A o, AI) and Var(y 6 + (Pi + Yi n i - w)AI) = V a r ( y 6) + ( P i + Yi - n i - w)2Var(Al ) + 2 ( P i + Yi - n i w)Cov(y 6, At), respectively. The estimation results are denoted in Table 2; the corresponding elasticities evaluated at the sample mean are denoted in Table 3. From Table 2 it is clear that for the 68, the 36 and the large firms in 36 industries market concentration increases the impact of the internal factors. Table 3 shows that the direct impact of market concentration on wages becomes insignificant.
M . H . C . Lever, J.M. van W e r k h o o v e n / L a b o u r E c o n o m i c s 3 (1996) 9 3 - 1 0 7
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Table 2 Wage rate in manufacturing industries in the Netherlands (1974-1986); dependent variable: wi, t - w r a.b Variables Pi,t + Yi,l - ni,t - wt C 4 i , ( Pi,t + Y i , t - n i , t - w t
~ni, t hi, t
b~ ut_ I Auk t C4i.t-1
xi, z txi, t - t x t
m~N(0,1) s ~ X2
68 industries
36 industries
Large firms
Small firms
(0.015) -0.045 (0.007) 0.476 (0.041)
0.121 (0.019) 0.014 (0.005) -0.063 (0.011) 0.174 (0.038) -0.200 (0.132) - 0.292 (0.052) -0.529 (0.067) 0.184 (0.039) 0.003 (0.014) 0.934 (0.138)
0.162 (0.028) 0.011 (0.006) -0.046 (0.007) 0.215 (0.044) -0.238 (0.129) -0.237 (0.074) -0.599 (0.085) 0.131 (0.042) -0.017 (0.021) 1.152 (0.133)
0.013 (0.004) -0.087 (0.016) -0.001 (0.008) -0.350 (0.052) 0.041 (0.137) -0.365 (0.070) 0.231 (0.158) -0.032 (0.113) -0.022 (0.015) 0.035 (0.271)
-0.976 55.96 ( d f = 5 5 )
-0.799 - 1.310 27.93 (df= 25) 30.56 ( d f = 2 5 )
0.112 (0.010) ) 0.012 (0.002) -0.094 (0.008) 0.135 (0.013) -0.054 (0.046) - 0.104 (0.029) - 0.051 (0.055) 0.185
a See notes of Table 1. b Besides A p i , t , Ayi, t and Ani,t, A C 4 i , t ( P i , t + last variable is instrumented by A C 4 i , t 2(Pi,t_2
1.144 31.26(df= 25)
Yi,t - - ni,t - - w t ) has been treated as + Yi,t
2 - - ni,t
endogenous. The
2 -- Wt-2)"
T h e e s t i m a t e s for the s m a l l f i r m s are s o m e w h a t e x c e p t i o n a l . T h e i m p a c t o f m a r k e t c o n c e n t r a t i o n o n the w e i g h t o f the i n t e r n a l factors (see T a b l e 2) a n d the elasticity o f the i n t e r n a l factors (see T a b l e 3) are f o u n d to b e n e g a t i v e , c o n t r a r y to t h e theoretical model. The direct impact of market concentration on small firms'
Table 3 Elasticities of wage rate in manufacturing industries in the Netherlands (1974-1986). " Elasticities
68 industries
36 industries
Large firms
Small firms
Internal factors
0.117 (0.009) 0.022 (0.031)
0.126 (0.019) 0.003 (0.070)
0.166 (0.027) - 0.020 (0.078)
-0.017 (0.007) 1.130 (0.104)
Concentration ratio
a Standard errors are denoted in parentheses.
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wages is positive and quite large. Including the interaction effect does not seriously affect the other estimates.
5. Conclusions The wage rate in Dutch manufacturing industries is determined by both internal (sector-specific) and external (labour-market-related) factors. In comparative terms, the weight of external factors is by far the highest, given that for 68 industries, the weight of internal factors is estimated at 0.12, while that of external factors is estimated at 0.88. The weight of internal factors fairly approximates that established in previous findings for the UK; it is higher than that established for Finland, Norway, Sweden and West Germany, yet lower than that established for the US. The hypothesis of increasing wage rates with decreasing numbers of insiders is not substantiated by the empirical results. Market concentration, used as an indicator of product market power, appears to exert a significantly positive impact on the wage rate. The export share, used as an approximation for foreign competition, appears to exert a significantly negative impact. After including interaction effects the weight of the internal factors appears to be higher in more concentrated industries, whereas the direct impact of market concentration on wages disappears. In large firms, internal factors play a substantially higher role as regards wage formation than in small firms; conceivably, because large firms have a superior internal labour market at their disposal, and because they are more often covered by their own collective labour agreements. For large firms, the weight of internal factors is estimated at 0.17-0.20; for small finns at 0-0.01. For the entirety of the 36 industries incorporated in these estimations, a total weight of 0.13-0.15 is found. One suggestion for further research is to estimate the influence of the bargaining power of trade unions on wages. This estimate has been omitted in this study, given the non-existence of a publication of detailed data in respect of the numbers of employees covered by collective labour agreements. As for the future, we hope to be able to obtain relevant data through the Ministry of Social Affairs and Employment. Another suggestion for further research is to improve the estimation of the impact of market power on wages by using data of individual firms.
Acknowledgements The authors acknowledge the suggestions rendered by A. Kleijweg, A. van Soest, M. Verbeek and an anonymous referee in respect of a previous version of this paper.
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Appendix A. Data appendix
The empirical study is based on data for 68 3-digit industries (or combinations thereof) in Dutch manufacturing. The SBI codes and the description of these industries are narrated hereinafter. For 36 of these industries, separate data are available for large (50 or more employees as per 30 September) and small firms (10 to 50 employees). These 36 industries are indicated by an asterisk (*). No
SBI
1
20.1 *
2 3
20.4 20.6 *
4 5 6 7 8 9 10 11 12
20.7 20.8 * 20.9 * 21.2 * 21.3 * 21.4 21.5 21.6 22.1 + 22.2 22.3 22.5 23.1 + 23.2 24.1 24.2 24.3 25.3 25.4 25.5 25.7 26.1 26.2 * 26.3 * 27.1" 27.2 * 27.3 * 29.1 29.2
13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30
Description slaughtering and meat processing industry flour mills, groats and rice husking mills, etc. manufacture of margarine and other vegetable and animal oils and fats canning, preserving and processing of fruits and vegetables manufacture of bread, rusks, pastries, cakes and biscuits manufacture of cocoa, chocolate and confectionery manufacture of compounded animal stock feeds manufacture of other food products alcohol manufacturing and distilleries breweries and malt houses non-alcoholic beverages wool industry cotton industry knitting and hosiery industry manufacture of carpets and rugs manufacture of ready-made clothing contract manufacture of ready-made clothing leather industry leatherware industry (excl. clothing) footwear industry carpeting, parqueting industry manufacture of wooden containers manufacture of other wooden articles furniture industry (excl. metal furniture) paper and cardboard industry paperware industry corrugated cardboard and cardboard industry printing industry publishing industry book binding industry manufacture of fertilizers manufacture of plastics
lO6 31 32 33 34 35 36 37 38 39 40
M.H. C. Lever, J.M. van Werkhooven / Labour Economics 3 (1996) 93-107
29.3 29.4 + 30.0 29.5 * 29.6 * 29.7 *
52 53 54 55 56
29.8 29.9 * 31.1 31.3 32.1 +32.2 32.3 32.5 * 33.1 +33.2 +33.4 33.3 * 34.0 * 34.1 * 34.2 * 34.3 * 34.4 * 34.5 * 34.6 * + 34.8 * 34.7 * 34.9 35.1 * 35.2 * 35.3 *
57
35.4 *
58 59
35.5 35.6 *
60 61 62 63 64
35.7 * 35.8 35.9 * 36 37.1 *
41 42 43
44 45 46 47 48 49 50 51
manufacture of dye-stuffs and pigments other chemical basic industry manufacture of artificial and synthetic yams and fibres manufacture of paint, lacquer, varnish and printing ink manufacture of pharmaceutical and antiseptic dressings manufacture of soap; other washing and cleaning materials, perfumes and cosmetics manufacture of chemical detergents etc. manufacture of other chemical products rubber-processing industry plastic-processing industry manufacture of brick and tiles manufacture of earthenware manufacture of sand-lime bricks manufacture of concrete and cement products iron and steel industry manufacture of steel tubes non-ferrous metal industry wire-drawing and cold-rolling industry foundries iron works, crushing and pressing industry manufacture of screws, mass products from lathes and springs construction of tanks, reservoirs and pipelines other metal construction manufacture of metal furniture metal-packing industry manufacture of other metal products manufacture of heating and cooking apparatus (excl. electric) forges, surface treatment manufacture of agricultural machinery manufacture of metal-working machinery manufacture of machinery for food-processing, chemical and related industries lifting and other transport equipment for mining, construction, building-materials and metallurgic industries manufacture of cog-wheels, bearings and other driving gear manufacture of machinery and other equipment for industries n.e.s. manufacture of steamboilers, engines and turbines manufacture of office machinery manufacture of other machinery and apparatus electrotechnical industry manufacture and assembly of automobiles
M.H.C. Lever, J.M. van Werkhooven / Labour Economics 3 (1996) 93-107
65 66 67 68
+ 37.3 * + 37.7 * 37.2 * 37.4 37.6 * 37.9 *
107
manufacture of car parts aircraft-construction and repair industry manufacture of coach work and trailers shipbuilding and ship repair industries manufacture of bicycles and motorcycles manufacture of other transport equipment
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