preferred the ten men it replaced!”
2. Union Power and Innovation: A Further Exploration
The difficulty of testing the general bargaining model has been emphasised at many points in this chapter especially in the absence of detailed knowledge of the dynamics of union power over different aspects of the employment contract. As an alternative to industry density we have access to a cross sectional measure of union density at the firm level which may provide more information. The problem with this measure is that it is a firm-specific effect which will disappear in a first differenced model. Therefore it is used only as an interaction term with firm innovations in the estimating equations.
The theoretical interest centered around union models has been accompanied in Britain by a vigorous empirical debate over the role of unions in the great employment shakeout of the early 1980s. The 1984 Workplace
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Experiments with other measures of market structure such as concentration and import penetration were also attempted, but no clear pattern emerged.
Industrial Relations Survey shows that employment contracted fastest where unions where strongest (Millward and Stevens, 1986, pp217-218) and this continues to hold good in multivariate regressions. Opinion divides over the reasons for this correlation. Blanchflower et al (1990) appear to claim there is a ’union growth differential’ of about -3% whereas Machin and Wadhwani (1990b) argue that the association is due to management reasserting their control over restrictive practices. The latter authors produce evidence for this claim by looking at the interactions between union and organizational change. Consequently it is of great interest to see if a similar pattern holds good for technological innovations.
Table 5.7 presents the raw data on employment change, innovation and union power. Panel A displays a pattern gratifyingly similar to the establishment data - employment contracted by about 2.5% across the whole of manufacturing (see also Figure 5.2); this fall was greatest where unions were recognised and where firm level density was higher. In the density sample the falls amongst firms who had innovated at any time in our sample were slightly greater than the falls among the non-innovators but the difference is minute (about one fifth of one per cent). Panel B contains some much more surprising information. Job decline was greater amongst innovative firms with weak unions than in innovative firms with strong unions, but this pattern was reversed for non-innovators. In other words, firms who introduced major technological changes bucked the general trend of the negative association between unions and employment.
The regression results in Table 5.8 broadly confirm the raw correlations. Since 20 union firms had no density information the preferred Labour Demand model was run on the new sample in column (1) to make sure the results were robust - they actually appear stronger. The pattern of firm
level density is most striking when the interaction term is introduced for current innovations only in column (2). The linear innovations term is significantly negative and the union interaction larger and significantly positive. On the basis of these results the average effect of an innovation is to reduce employment for firms where union density is below about 60%.
Although firm level density is pretty stable within firms (see Gregg and Yates, 1992 or Andrews and Harrison ,1991, for plants) there may be a misclassification for a minority of firms where density has changed dramatically. To mitigate this we used a dummy variable split at median density (85%) in column (3). Again, only the interaction is significantly positive, although the linear term is no longer negative. The next column adds in the first and second lags of innovation and their interactions with union density. The first lag reinforces the current effect with larger point estimates, but the third lag has the signs of linear and interactive terms reversed. Still, the long-run effects suggest that high density firms have large positive innovative effects on employment and low density ones small negative effects.
How should one interpret Table 5.8? It is of course possible that the density measure is too static, too endogenous and too crude a proxy for union power, so the results are merely a statistical artifact. Yet it is commonly used and seems to have the advantage of being more disaggregated than the industry level measures used earlier and less crude than the binary split of recognition.
One obvious explanation of the results is to resuscitate the model of union employment bargaining. Note that the reduced form for employment under
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the efficient contracts model has predictions for the interaction terms between union power and the effects of technology id^N/d^dA = sign{3^N/9^aa>> = -R /A
N
[ d + g) J
< 0 (if i//>l). This implies that innovation effects on employment are increasing with union power which is exactly what we appear to find. The absence of alternative wage effects in the employment equations may well be due to one of the problems alluded to in Chapter 2 (e.g. weak separability of the union utility function). Alternatively, the fact that this interactive effect exhibits a complex dynamic pattern may imply that all unions are doing is temporarily preventing the firm from adjusting to its desired level of employment. The innovation terms were allowed to take a longer lag structure and a representative regression is in column (5) where effects are allowed up to four years later. The essential pattern remains; for example a firm with 100% density has an average long-run innovations effect of 0.3376 whereas one with 25% density has a long-run mean effect of only 0.0162. On this reading of the data the effect of unions is not merely a short-run phenomena.Column (6) offers a possible defense of the Labour Demand Model. 33
Interacting own wages with firm density revealed that the implied demand elasticity was greater in firms with higher density. Thus one could argue that larger innovation effects would be expected in these firms under a labour demand model. We remain a little unhappy with this explanation, despite the fact it ties up with our earlier conclusions. One would expect that unions can achieve higher wage gains when labour demand elasticities are
^^Differentiate (5.6) with respect to 13. 33
Density was also interacted with the other right hand side variables, in particular the alternative wage, but they were never significantly different from the linear term.
lower and this gives individuals greater incentives to join unions to share these gains (Table 5.3 shows that average wages are higher in firms with high density). On the other hand, this argument may be more true for recognition than density. Conditional on recognition, a few writers have found investment to be increasing with density (e.g. Denny and Nickell, 1992) and it is these increases which may be the source of wage gains rather than
34 demand inelasticity .
Given the doubts about accepting a model based on interactive terms only, our conclusion that the Labour Demand model best describes the data still holds. Nonetheless, there is a need to look at these interactions more closely, especially with regard to wages, which is what will be done in the next chapter.
VI Co n c lu s io n s
The main message from the analysis presented in this chapter is that innovations have a large positive effect on employment at the firm level raising it by up to 13% in union firms over the long haul. The positive effect is robust across all our main datasets to a wide variety of respecifications. It was argued that this should not come as a surprise as similar results have emerged from other careful studies using very different measures of innovative success. The theoretical prediction that technical change is associated with greater employment when labour demand elasticity is greater than unity is also broadly corroborated by our results.
On the subject of union models the absence of significant impacts of
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One alternative means is to look at profitability equations again and ask the question: do unions reduce the rate of return to an innovation. The raw correlations in the data gave a positive answer to this question, but when subjected to a more rigorous examination they could not be sustained.
union power and the alternative wage in our employment equations implies that the labour demand model best describes the data for union firms. Things are less clear in the non-union sector, but there are a few signs that efficiency wage considerations may be of some importance. An unresolved issue is how to reconcile our main conclusions with the finding that firms with high union density enjoyed the greatest positive effects from innovation. Although consistent with unions spreading technological rents into higher employment it is also the case that demand elasticities seem higher in these firms and we would expect them to have greater increases in employment under a labour demand model too.
An obvious criticism of this study is that a short panel was used covering the 1979-83 period of severe recession and one must be cautious in generalising from this particular experience. However, this period is of particular interest both on the Schumpeterian grounds that the essential character of capitalist economies is often revealed during recessions and on the more specific grounds that it was a fascinating period of economic history. Our analysis suggests that the firms who emerged from the slump were not reducing employment on a large scale because of technological
innovât ions but for for entirely different reasons (e.g. low demand, attacks
on union ’ over-manning’,etc).
The eventual outcome of new technologies may well be greater economy wide unemployment, yet the spillover and survivor biases are more likely to cause an underestimation of the benefits of new technology on major innovations. The statistical picture detailed in this chapter is that major innovations create jobs and this is especially so when these firms have strong unions.