Measuring Inefficiency of the Czech Labour Market

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Abstract

This paper aims to quantify the performance of the Czech regional labour markets and to reveal the most influential economic factors standing behind its dynamics in the last fifteen years. Investigated labour markets are described using matching function approach. The successful matches are treated as an output of production process, where the unemployed are paired with vacancies. Efficiency of this matching process plays an important role in determining unemployment outflows. Using stochastic frontier model approach, dynamics of quantified efficiency terms is revealed and differences among regions are evaluated. The model specification includes a fixed effect term, where individual effect terms and inefficiency terms are estimated jointly. The stochastic frontier is estimated using monthly and quarterly regional panel data of 77 districts for the period 1999-2014. Matching efficiency of the Czech regional labour markets is negatively influenced people who have been unemployed for a long time and by the unemployed aged over 50 years. Although all districts were able to operate at their stochastic frontiers of matching, an upward trend in the inefficiency has been found within the investigated period. These tendencies are accompanied by rising disparities among the regions. Low levels of estimated matching inefficiency do not necessary mean the low unemployment in the corresponding districts.

AIGNER, D., LOVELL, C.A.K., SCHMIDT, P. (1977). Formulation and Estimation of Stochastic Frontier Production Function Models. Journal of Econometrics 6, 21-37.

AMSLER, C., LEE, Y. H., SCHMIDT, P. (2009). A Survey of Stochastic Frontier Models and Likely Future Developments. Seoul Journal of Economics 22 (1), 5-27.

ARELLANO, M., BOND, S. (1991). Some tests of specification for panel data: Monte Carlo evidence and an application to employment equation. Review of Economic Studies 58, 277-297.

BATTESE, G. E., COELLI, T. J. (1993). A Stochastic Frontier Production Function Incorporating a Model For Technical Inefficiency Effects. Working Papers in Econometrics and Applied Statistics. No. 69. University of New England.

BATTESE, G. E., COELLI, T. J. (1995). A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data. Empirical Economics 20, 325-332.

Czech National Bank. Public time series database ARAD available at http://www.cnb.cz/docs/ARADY/HTML/index_en.htm.

GALUŠČÁK, K., MÜNICH, D. (2007). Structural and Cyclical Unemployment: What Can Be derived from the Matching Function. Czech Journal of Economics and Finance 57, 102-125.

GORTER, C., NIJKAMP, P., PELS, E. (1997). Vacancy Dynamics and Labor Market Efficiency in the Dutch Labor Market. Growth and Change 28, 173-200.

GREENE, W. H. (2005). Reconsidering heterogeneity in panel data estimators of the stochastic frontier model. Journal of Econometrics 126 (2), 269-303.

ILMAKUNNAS, P., PESOLA, H. (2003). Regional Labour Market Matching Functions and Efficiency Analysis. Labour 17, 413-437.

International Financial Statistics. Database of International Monetary Fund available at http://www.imf.org/external/data.htm.

JONDROW, J., LOVELL, C. A. K., MATEROV, I. S., SCHMIDT, P. (1982): On the Estimation of Technical Inefficiency in the Stochastic Frontier Production Function Model. Journal of Econometrics 19, 233-238.

KALMAN, R. E. (1979): A system-theoretic critique of dynamic economic models. Lecture Notes in Control and Information Sciences 19, 3-24.

Ministry of Labour and Social Affairs. Unemployment statistics (quarterly and monthly) available at http://portal.mpsv.cz/sz/stat/nz

MÜNICH, D., ŠVEJNAR, J., TERELL, K. (1999): Worker-Firm Matching and Unemployment in Transition to a Market Economy: (Why) Are the Czechs More Successful than Others? (January 1999). CERGE-EI Working Paper No. 141. Available at http://dx.doi.org.sci-hub.org/10.2139/ssrn.164555

NĚMEC, D. (2013a). Evaluating labour market flexibility in V4 countries. In Vojáčková, H. (ed.) Proceedings of 31st International Conference Mathematical Methods in Economics. College of Polytechnics Jihlava, Jihlava, 661-666.

NĚMEC, D. (2013b). Investigating Differences between the Czech and Slovak Labour Market Using a Small DSGE Model with Search and Matching Frictions. The Czech Economic Review 7, 21-41.

NĚMEC, D. (2014a). Efficiency of the matching process on the Czech regional labour markets. In Reiff, M., Gežík. P. (eds.) Proceedings of the International Scientific Conference QUANTITATIVE METHODS IN ECONOMICS Multiple Criteria Decision Making XVII. Vydavateľstvo EKONÓM, Bratislava, 188-195. NĚMEC, D. (2014b) Efficiency of the European labour markets: The Case of Czech Republic (A Stochastic frontier model approach). In Talašová, J., Stoklasa, J., Talášek, T. (eds.) 32nd International Conference Mathematical Methods in Economics Conference Proceedings. Palacký University, Olomouc, 703-708.

POLASEK, W., SELLNER, R. (2013): Does Globalization Affect Regional Growth? Evidence for NUTS-2 Regions in EU-27. DANUBE: Law and Economics Review 4 (1), 23-65.

TVRDOŇ, M., VERNER, T. (2012). Regional unemployment disparities and their dynamics: Evidence from the Czech Republic. In Ramík, J., Stavárek, D. (eds.) Proceedings of 30th International Conference Mathematical Methods in Economics. Silesian University in Opava, School of Business Administration in Karviná, 938-943.

WANG, H.-J., HO, C.-W. (2010). Estimating fixed-effect panel stochastic frontier models by transformation. Journal of Econometrics 157, 286-296.

WANG, H.-J., Schmidt, P, (2002). One-step and Two-Step Estimation of the Effects of Exogenous Variables on Technical Efficiency Levels. Journal of Productivity Analysis 18 (20), 1296-144

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CiteScore 2017: 0.42

SCImago Journal Rank (SJR) 2017: 0.153
Source Normalized Impact per Paper (SNIP) 2017: 0.351

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