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The estimation of reservation wages: A simulation-based comparison

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  • Leppin, Julian Sebastian

Abstract

This paper examines the predictive power of different estimation approaches for reservation wages. It applies stochastic frontier models for employed workers and the approach from Kiefer and Neumann (1979b) for unemployed workers. Furthermore, the question of whether or not reservation wages decrease over the unemployment period is addressed. This is done by a pseudo-panel with known reservation wages which uses data from the German Socio-Economic Panel as a basis. The comparison of the estimators is carried out by a Monte Carlo simulation. The best results are achieved by the cross-sectional stochastic frontier model. The Kiefer-Neumann approach failed to predict the decreasing reservation wages correctly. --

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Bibliographic Info

Paper provided by Hamburg Institute of International Economics (HWWI) in its series HWWI Research Papers with number 124.

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Date of creation: 2012
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Handle: RePEc:zbw:hwwirp:124

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Keywords: job search theory; Monte Carlo simulation; reservation wages; stochastic wage frontiers;

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References

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  1. Devine, Theresa J. & Kiefer, Nicolas M., 1991. "Empirical Labor Economics: The Search Approach," OUP Catalogue, Oxford University Press, number 9780195059366.
  2. Kate Antonovics & Robert Town, 2004. "Are All the Good Men Married? Uncovering the Sources of the Marital Wage Premium," American Economic Review, American Economic Association, vol. 94(2), pages 317-321, May.
  3. Kiefer, Nicholas M & Neumann, George R, 1979. "An Empirical Job-Search Model, with a Test of the Constant Reservation-Wage Hypothesis," Journal of Political Economy, University of Chicago Press, vol. 87(1), pages 89-107, February.
  4. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
  5. Kumbhakar,Subal C. & Lovell,C. A. Knox, 2003. "Stochastic Frontier Analysis," Cambridge Books, Cambridge University Press, number 9780521666633, November.
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  10. Gert G. Wagner & Joachim R. Frick & Jürgen Schupp, 2007. "The German Socio-Economic Panel Study (SOEP) – Scope, Evolution and Enhancements," Schmollers Jahrbuch : Journal of Applied Social Science Studies / Zeitschrift für Wirtschafts- und Sozialwissenschaften, Duncker & Humblot, Berlin, vol. 127(1), pages 139-169.
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  12. Ritter, C. & Simar, L., . "Pitfalls of normal-gamma stochastic frontier models," CORE Discussion Papers RP -1272, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  13. Robert Webb & Duncan Watson & Tim Hinks, 2003. "Testing for Wage Overpayment in UK Financial Services: A Stochastic Frontier Approach," The Service Industries Journal, Taylor & Francis Journals, vol. 23(5), pages 123-136, November.
  14. Battese, George E. & Coelli, Tim J., 1988. "Prediction of firm-level technical efficiencies with a generalized frontier production function and panel data," Journal of Econometrics, Elsevier, vol. 38(3), pages 387-399, July.
  15. Jondrow, James & Knox Lovell, C. A. & Materov, Ivan S. & Schmidt, Peter, 1982. "On the estimation of technical inefficiency in the stochastic frontier production function model," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 233-238, August.
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Cited by:
  1. Hohenleitner, Ingrid & Hillmann, Katja, 2012. "Impact of Benefit Sanctions on Unemployment Outflow - Evidence from German Survey Data," Annual Conference 2012 (Goettingen): New Approaches and Challenges for the Labor Market of the 21st Century 66055, Verein für Socialpolitik / German Economic Association.
  2. Vöpel, Henning, 2013. "A Zidane clustering theorem: Why top players tend to play in one team and how the competitive balance can be restored," HWWI Research Papers 141, Hamburg Institute of International Economics (HWWI).

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