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The Demographics of Labour Turnover: A Comparison of Ordinal Probit and Censored Count Data Models

Published online by Cambridge University Press:  17 August 2016

Lucie Merkle  and
Klaus F. Zimmermann
Lucie Merkle
Affiliation:
Universität München
Klaus F. Zimmermann
Affiliation:
Universität München & CEPR, London
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Summary

As has been found in previous studies, the labor market performance of individuals is often affected by demographic determinants like cohort size, age, marriage status and family size. While most of this analysis was studied for earnings, the paper investigates the issue for labor mobility. Mobility is measured here by the number of new employers and the frequency of unemployment of an individual in a particular period. Given the discrete nature of the data, the ordinal probit model and the censored Poisson as the censored negative binomial model was estimated. Since the choice of the statistical model is not clear a priori, various model comparisons are carried out and some new pseudo-R2 measures are proposed and used in the analysis. Results indicate that demographic determinants matter for labor mobility.

Résumé

Résumé

Il est bien connu que la performance des individus sur le marché du travail est souvent affectée par des déterminants démographiques tels que la taille de la cohorte, l'âge, l'état civil et la taille de la famille. Alors que la plupart des études se sont intéressées aux rémunérations, cet article se concentre sur le problème de la mobilité des travailleurs. Celle-ci est mesurée ici par le nombre d'employeurs et la fréquence des périodes de chômage sur un intervalle de temps donné. Étant donné la nature discrète des données, on a estimé le modèle probit ordinal avec une distribution de Poisson tronquée à la place du modèle à distribution binomiale négative tronquée. Comme le choix d'un modèle n'est pas évident à priori, de nombreuses comparaisons de modèles différents ont été effectués et de nouvelles mesures du pseudo R2 proposées. Les résultats indiquent que les déterminants démographiques influencent la mobilité du travail.

Keywords

C25J60C25J60
Type
Part I: Labour Demand and Supply
Information
Recherches Économiques de Louvain/ Louvain Economic Review , Volume 58 , Issue 3-4: Output and Employment Fluctuations , 1992 , pp. 283 - 306
Copyright
Copyright © Université catholique de Louvain, Institut de recherches économiques et sociales 1992 

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Footnotes

(*)

Financial support from the German Science Foundation (DFG) is gratefully acknowledged. Preliminary versions of this paper were presented at the 1990 meeting of the European Society for Population Economics (ESPE) in Istanbul, and in seminars given in the University of Amsterdam and in the Section Population Economics of the German Economic Association. We wish to thank seminar participants and Anders M. Klevmarken, Christoph M. Schmidt and Rainer Winkelmann as the referees for valuable comments. The study has also benefited from the second author's visit to CentER, Tilburg University, in 1990.

References

REFERENCES

Aldrich, J.H., and Nelson, F.D. (1989), Linear Probability, Logit, and Probit Models, Beverly Hills: Sage University Press.Google Scholar
Amemiya, T. (1981), Qualitative Response Models: A Survey, Journal of Economic Literature, Vol. 19, pp. 1483–1536.Google Scholar
Benham, L. (1974), Benefits of Women's Education within Marriage, in Schultz, T. W., Economics of the Family. Chicago & London: The University of Chicago Press, pp. 375–389.Google Scholar
Ben-porath, Y. (1988), Market, Government, and Israel's Muted Baby Boom, in Lee, R. D., Arthur, W. B. and Rogers, G., Economics of Changing Age Distributions in Developed Countries, Oxford: Clarendon Press, pp. 12–38.Google Scholar
Bishop, J. H. (1990), Job Performance, Turnover, and Wage Growth, Journal of Labor Economics, Vol. 8, pp. 363–386.Google Scholar
Burdett, K. (1978), A Theory of Employee Job Search and Quit Rates, American Economic Review, Vol. 68, No. 1, pp. 212–220.Google Scholar
Burgess, S. M., and Nickell, S. (1990), Labour Turnover in UK Manufacturing, Economica, Vol. 57, pp. 295–317.Google Scholar
Cameron, A. C., and Trivedi, P. K. (1986), Econometric Models Based on Count Data: Comparisons and Applications of some Estimators and Tests, Journal of Applied Econometrics, Vol. 1, pp. 29–53.Google Scholar
Cameron, A. C., and Trivedi, P. K. (1990), Regression-Based Tests for Overdispersion in the Poisson Model, Journal of Econometrics, Vol. 46, pp. 347–364.Google Scholar
Cramer, J. C. (1980), The Effects of Fertility on Husband's Activity: Evidence from Static, Dynamic, and Nonrecursive Models, Research in Population Economics, Vol. 2, pp 151–182.Google Scholar
Easterlin, R. A. (1987), Birth and Fortune, The Impact of Numbers on Personal Welfare (Second Edition), Chicago, London: The University of Chicago Press.Google Scholar
Fienberg, S. E. (1977), The Analysis of Cross-Classified Categorical Data, Cambridge, London: MIT Press.Google Scholar
Hall, R. E. (1972), Turnover in the Labor Force, Brookings Papers on Economic Activity, Vol. 3, pp. 709–764.Google Scholar
Kenny, L. W. (1983), The Accumulation of Human Capital During Marriage By Males, Economic Inquiry, Vol. 11, pp. 223–231.Google Scholar
Light, A., and Ureta, M. (1990), Gender Differences in Wages and Job Turnover Among Continuously Employed Workers, American Economic Review, Vol. 80, No. 2, pp. 293–297.Google Scholar
Maddala, G. S. (1983), Limited-dependent and Qualitative Variables in Econometrics, Cambridge: Cambridge University Press.Google Scholar
McCormick, B. (1988), Quit Rates over Time in a Job-rationed Labour Market: the British Manufacturing Sector, 1971-1983, Economica, Vol. 55, pp. 81–94.Google Scholar
McFadden, D., Puig, C., and Kirschner, D. (1977), Determinants of the Longrun Demand for Electricity, Proceedings of the American Statistical Association (Business and Economics Section), pp. 109–117.Google Scholar
McKelvey, R., and Zavoina, W. (1975), A Statistical Model for the Analysis of Ordinal Level Dependent Variables, Journal of Mathematical Sociology, Vol. 4, pp. 103–120.Google Scholar
McLaughun, K. J. (1991), A Theory of Quits and Layoffs with Efficient Turnover, Journal of Political Economy, Vol. 99, No. 1, pp. 1–29.Google Scholar
Terza, J. V. (1985), A Tobit-Type Estimator for the Censored Poisson Model, Economics Letters, Vol. 18, pp. 361–365.Google Scholar
Veall, M. R., and Zimmermann, K. F. (1992a), Pseudo-R 2 in the Ordinal Probit Model, Journal of Mathematical Sociology, Vol. 16, pp. 333–342.Google Scholar
Veall, M. R. and Zimmermann, K. F. (1992b), Performance Measures from Prediction-Realization Tables, Economics Letters, vol. 39, pp. 129–134.Google Scholar
Zimmermann, K. F. (1986), Multivariate Micro Prediction Analysis of Qualitative Models, in: Beckmann, M. J., Gaede, K. W.. Ritter, K. and Schneeweiss, H. (Eds.), Methods of Operations Research, 53, pp. 683–696.Google Scholar