Panos, Sousounis (2008): State dependence in work-related training participation among British employees: A comparison of different random effects probit estimators.
Download (227Kb) | Preview
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.
|Item Type:||MPRA Paper|
|Original Title:||State dependence in work-related training participation among British employees: A comparison of different random effects probit estimators.|
|Keywords:||state dependence; training; dynamic panel data models|
|Subjects:||C - Mathematical and Quantitative Methods > C2 - Single Equation Models; Single Variables > C23 - Models with Panel Data; Longitudinal Data; Spatial Time Series
C - Mathematical and Quantitative Methods > C2 - Single Equation Models; Single Variables > C25 - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
|Depositing User:||Panos Sousounis|
|Date Deposited:||25. Mar 2009 15:51|
|Last Modified:||15. Feb 2013 04:20|
ARELLANO, M., and S. BOND (1991): "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," The Review of Economic Studies, 58, 277-297.
ARELLANO, M., and O. BOVER (1995): "Another Look at the Instrumental Variable Estimation of Error-Components Models," Journal of Econometrics, 68, 29-51.
ARELLANO, M., and B. E. HONORE (2000): "Panel Data Models: Some Recent Developments," CEMFI Working Paper No. 0016.
ARULAMPALAM, W. (1998): "A Note on Estimated Coefficients in Random Effects Probit Models," The Warwick Economics Research Paper Series (TWERPS).
AVERY, R. B., L. P. HANSEN, and V. J. HOTZ (1983): " Multiperiod Probit Models and Orthogonality Condition Estimation," International Economic Review 24, pp. 21-35.
BALTAGI, B. (1995): Econometric Analysis of Panel Data. New York: John Wiley and Sons.
BLUNDELL, R., and S. BOND (1998): "Initial Conditions and Moment Restrictions in Dynamic Panel Data Models," Journal of Econometrics, 87, 115-143.
BREITUNG, J., and M. LECHNER (1995): "Gmm-Estimation of Nonlinear Models on Panel Data," Sonderforschungsbereich 373, Humboldt Universitaet Berlin.
CHAMBERLAIN, G. (1984): "Panel Data," Handbook of Econometrics, S. Griliches and M. Intriligator (eds), Amsterdam, North-Holland, 1247-318.
CHAY, K. Y., and D. R. HYSLOP (2000): "Identification and Estimation of Dynamic Binary Response Panel Data Models: Empirical Evidence Using Aletrnative Approaches," University of California at Berkeley, Working Paper Series.
HANSEN, L. P. (1982): "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, 50, 1029-1054.
HECKMAN, J. J. (1981a): "Statistical Models for Discrete Panel Data," in C.F. Manski and D. McFadden (eds), Structural Analysis of Discrete Data with Econometric Applications, MIT Press, 114-78.
HOLTZ-EAKIN, D., W. K. NEWEY, and H. S. ROSEN (1989): "Implementing Causality Tests with Panel Data, with an Example from Localpublic Finance," NBER Technical Working Papers, 0048.
HONORE, B. E., and E. KYRIAZIDOU (2000): "Panel Data Discrete Choice Models with Lagged Dependent Variables," Econometrica, 68, 839-874.
— (2000): "Panel Data Discrete Choice Models with Lagged Dependent Variables," Econometrica, 68, 839-874. HSIAO, C. (1986): Analysis of Panel Data. Cambridge UK: Cambridge University Press.
MUNDLAK, Y. (1978): "On the Pooling of Time Series and Cross Section Data," Econometrica, 46, 69-85.
ORME, C. D. (2001): "The Initial Conditions Problem and Two-Step Estimation in Discrete Panel Data Models," mimeo, University of Manchester.
ROODMAN, D. (2006): "How to Do Xtabond2: An Introduction To "Difference" And "System" Gmm in Stata," Working Papers, Center for Global Development.
STEWART, M. B. (2006): "-Redprob- a Stata Program for the Heckman Estimator of the Random Effects Dynamic Probit Model," mimeo, University of Warwick.
— (2007): "The Interrelated Dynamics of Unemployemnt and Low-Wage Employment," Journal of Applied Econometrics, 22, 511-531.
WOOLDRIDGE, J. (2002): "Econometric Analysis of Cross Section and Panel Data," The MIT Press.
WOOLDRIDGE, J. M. (1995): "Selection Corrections for Panel Data Models under Conditional Mean Independence Assumptions," Journal of Econometrics, 68, 115-132.
— (2005): "Simple Solutions to the Initial Conditions Problem in Dynamic, Nonlinear Panel Data Models with Unobserved Heterogeneity," Journal of Applied Econometrics, 20, 39-54.