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State dependence in work-related training participation among British employees: A comparison of different random effects probit estimators

  • Panos, Sousounis

This paper compares three different estimation approaches for the random effects dynamic panel data model, under the probit assumption on the distribution of the errors. These three approaches are attributed to Heckman (1981), Wooldridge (2005) and Orme (2001). The results are then compared with those obtained from generalised method of moments (GMM) estimators of a dynamic linear probability model, namely the Arellano and Bond (1991) and Blundell and Bond (1998) estimators. A model of work-related training participation for British employees is estimated using individual level data covering the period 1991-1997 from the British Household Panel Survey. This evaluation adds to the existing body of empirical evidence on the performance of these estimators using real data, which supplements the conclusions from simulation studies. The results suggest that for the dynamic random effects probit model the performance of no one estimator is superior to the others. GMM estimation of a dynamic LPM of training participation suggests that the random effects estimators are not sensitive to the distributional assumptions of the unobserved effect.

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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 14261.

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Date of creation: Jul 2008
Date of revision: Mar 2009
Handle: RePEc:pra:mprapa:14261
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  1. Arellano, M. & Honore, B., 2000. "Panel Data Models: Some Recent Developments," Papers 0016, Centro de Estudios Monetarios Y Financieros-.
  2. Mundlak, Yair, 1978. "On the Pooling of Time Series and Cross Section Data," Econometrica, Econometric Society, vol. 46(1), pages 69-85, January.
  3. Chamberlain, Gary, 1984. "Panel data," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 2, chapter 22, pages 1247-1318 Elsevier.
  4. M. Ruth & K. Donaghy & P. Kirshen, 2006. "Introduction," Chapters, in: Regional Climate Change and Variability, chapter 1 Edward Elgar.
  5. Avery, Robert B & Hansen, Lars Peter & Hotz, V Joseph, 1983. "Multiperiod Probit Models and Orthogonality Condition Estimation," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 24(1), pages 21-35, February.
  6. Blundell, R. & Bond, S., 1995. "Initial Conditions and Moment Restrictions in Dynamic Panel Data Models," Economics Papers 104, Economics Group, Nuffield College, University of Oxford.
  7. David Roodman, 2009. "How to do xtabond2: An introduction to difference and system GMM in Stata," Stata Journal, StataCorp LP, vol. 9(1), pages 86-136, March.
  8. J. Breitung & M. Lechner, 1995. "GMM-Estimation of Nonlinear Models on Panel Data," SFB 373 Discussion Papers 1995,67, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
  9. Wooldridge, Jeffrey M., 1995. "Selection corrections for panel data models under conditional mean independence assumptions," Journal of Econometrics, Elsevier, vol. 68(1), pages 115-132, July.
  10. M Arellano & O Bover, 1990. "Another Look at the Instrumental Variable Estimation of Error-Components Models," CEP Discussion Papers dp0007, Centre for Economic Performance, LSE.
  11. Arulampalam, W., 1998. "A Note on Estimated Coefficients in Random Effects Probit Models," The Warwick Economics Research Paper Series (TWERPS) 520, University of Warwick, Department of Economics.
  12. Bo E. Honoré & Ekaterini Kyriazidou, 2000. "Panel Data Discrete Choice Models with Lagged Dependent Variables," Econometrica, Econometric Society, vol. 68(4), pages 839-874, July.
  13. Douglas Holtz-Eakin & Whitney K. Newey & Harvey S. Rosen, 1989. "Implementing Causality Tests with Panel Data, with an Example from LocalPublic Finance," NBER Technical Working Papers 0048, National Bureau of Economic Research, Inc.
  14. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-54, July.
  15. Arellano, Manuel & Bond, Stephen, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," Review of Economic Studies, Wiley Blackwell, vol. 58(2), pages 277-97, April.
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