Redundancies in an industry in transition: who gets fired and why? Evidence from one consumer-goods industry in Russia

Rinaldi, Gustavo (2007): Redundancies in an industry in transition: who gets fired and why? Evidence from one consumer-goods industry in Russia.

Abstract

Does employee productivity explain why during a period of crisis firms fired relatively more blue-collar than white-collar workers and why, when conditions improved, they began to hire relatively more blue collars? Are redundancies targeted towards the least productive workers? Was firms’ behaviour profit maximising? These questions are investigated in the extreme circumstances of the footwear industry in Russia in the period 1994-2000. Firms in this industry underwent a major upheaval in these years. Part of their response was to downsize the blue-collar workforce more severely than the whitecollars. Was this because (a) white collar employees had higher marginal productivity or (b) because the technical rate of substitution of white collar labour with blue collar labour was greater than the factor price ratio of these two inputs If it turns out that the marginal productivity of white collar employees was the higher, we could conclude that they were embodying more human capital (Becker, 1962); if they were no more productive than blue collars, this could mean that they had been privileged during downsizing for some institutional reasons, e.g. a prior commitment towards higher-ranking staff (Lazear, 1979; Lazear and Rosen, 1981). If it turns out that the technical rate of substitution of white collar labour with blue collar labour was greater than their factor price ratio, this would suggest that the firms’ downsizing policies were consistent with profit-maximising precepts. Russian footwear is a suitable industry for investigation because there are many units, which use a standard technology, and with relatively little political interference. The paper uses Translog and Cobb Douglas production functions with ordinary least squares, two-step least squares and stochastic frontier analysis, both in a panel and in a cross-section setting. Results show that white collar employees were not only more productive than blue collar employees but also the technical rate of substitution of white collar labour with blue collar labour was greater than the factor price ratio of these two inputs. This suggests that even in a turbulent period and with a Soviet heritage, the firms behaved as profit-maximising agents. Institutional factors may also have operated, but they do not need to be invoked in explaining the data.

• Item Type: MPRA Paper
• Language: English
• Keywords: Productivity, blue collars, white collars, transition, footwear
• Subjects: J - Labor and Demographic Economics > J2 - Demand and Supply of Labor > J24 - Human Capital ; Skills ; Occupational Choice ; Labor Productivity

References

•Angelucci, M., Bevan, A., Estrin, S., Fennema, J.A., Kuznetsov, B., Mangiarotti, G., Schaffer, M. E, 2002, The determinants of privatized enterprise performance in Russia, Discussion Paper, N. 3193, CEPR, London.

•Beatson, M., 1995, Labour Market Flexibility (Employment department- London).

•Becker, G., 1962, Investment in human capital: a theoretical analysis, The journal of political economy, Vol. 70 (5) part 2, pp. 9-49.

•Becker, G., 1964, Human capital: a theoretical and empirical analysis, with special reference to education, NBER.

•Berndt, E.R., Christensen, L., 1974, Testing for the existence of a consistent aggregate index of labor inputs, The American economic review, Vol. 64(3), pp. 391-404.

•Blakemore, A.E., Hoffman, D.L., 1989, Seniority rules and productivity: an empirical test, Economica, Vol. 56, 359-71.

•Brown, J.D., Earle, J.S., 2000, Competition geography and firm performance: lessons from Russia, CEPR/WDI Annual international conference on transition economics, Moscow 2-5 July 2000.

•Chiang, A., C., 1984, Fundamental methods of mathematical economics, Mc Graw-Hill International Editions.

•Devereux, P.J., 2000, Task assignment over business cycle, Journal of labour economics, Vol. 18(1), pp. 98-124.

•Goskomstat Rossij, 1999b, Trud y Zanyatost v Rossij (Work and employment in Russia ), Moscow.

•Goskomstat Rossij, 1999c, Maloe Predprinimatelstvo v Rossij (Small business in Russia ), Moscow.

•Greene,W., 1990, A Gamma distributed stochastic frontier model, Journal of econometrics, Vol. 46 (1/2), pp. 141-64.

•Greene, W., 2003, Econometric analysis, Prentice hall, Upper Saddle River, NJ.

•Greene, W., 2003a, LIMDEP Version 8, Econometric modeling guide and reference guide, Econometric software Inc., Plainview, NY.

•Greene, W., 1997, Frontier production functions. In Pesaran and Schmidt(eds), Handbook of applied econometrics: Vol. II: Microeconomics, Blackwell publishers, London.

•Idson, T.L., Valletta, R.G., 1996, Seniority, sectoral decline, and employee retention: an analysis of layoff unemployment spells, Journal of labour economics, Vol. 14(4), pp. 654-676.

•Kumbhakar, S.C., Knox Lovell, C.A., 2000, Stochastic frontier analysis, Cambridge university press, Cambridge.

•Lazear, E.P., 1979, Why is there mandatory retirement?, Journal of political economy, Vol. 87(6), pp. 1261-84 .

•Lazear, E.P., Rosen, S., 1981, Rank-order tournaments as optimum labor contracts, Journal of political economy, Vol. 89(5), pp. 841-64.

•Lichtenberg F.R., Siegel, D., 1990, The effect of ownership changes on the employment and wages of central office and other personnel, Journal of Law and Economics, Vol. 33 (2), pp. 383-408.

•Mickiewicz, T., Zalewska, A., 2002, Deindustrialization. Lessons from the structural outcomes of post communist transition, Working paper, N. 383, William Davidson Institute, The University of Michigan business school, Ann Arbour, MI.

•Oi, W., 1962, Labor as a quasi fixed factor, Journal of political economy, Vol. 70, pp. 538-55.

•Tirole, J., 1986, Hierarchies and bureaucracies: on the role of collusion in organizations, Journal of law, economics, & organization, Vol. 2, (2), pp. 181-214.

•Varian, H., 2006, Intermediate micro economics, W.W. Norton & Company, New York – London.

•Wang, H., Lall, S., (1999), Valuing Water for Chinese Industries: A Marginal Productivity Assessment ,World Bank Working Paper Series 2236

•Woolridge, J.M., 2002, Econometric analysis of cross section and panel data, The MIT press, Cambridge, MA.