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An Exponential Class of Dynamic Binary Choice Panel Data Models with Fixed Effects

  • Majid M. Al-Sadoon
  • Tong Li
  • M. Hashem Pesaran

This paper develops a model for dynamic binary choice panel data that allows for unobserved heterogeneity to be arbitrarily correlated with covariates. The model is of the exponential type. We derive moment conditions that enable us to eliminate the unobserved heterogeneity term and at the same time to identify the parameters of the model. We then propose GMM estimators that are consistent and asymptotically normally distributed at the root-N rate. We also study the conditional likelihood approach, which can only identify the effect of state dependence in our case. Monte Carlo experiments demonstrate the finite sample performance of our GMM estimators.

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Paper provided by CESifo Group Munich in its series CESifo Working Paper Series with number 4033.

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Date of creation: 2012
Date of revision:
Handle: RePEc:ces:ceswps:_4033
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  1. Thierry Magnac, 2003. "Panel Binary Variables and Sufficiency: Generalizing Conditional Logit," Research Unit Working Papers 0308, Laboratoire d'Economie Appliquee, INRA.
  2. Richard Blundell & Steve Bond, 1995. "Initial conditions and moment restrictions in dynamic panel data models," IFS Working Papers W95/17, Institute for Fiscal Studies.
  3. Jeffrey M. Wooldridge, 2005. "Simple solutions to the initial conditions problem in dynamic, nonlinear panel data models with unobserved heterogeneity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(1), pages 39-54.
  4. Carro, Jesus M., 2007. "Estimating dynamic panel data discrete choice models with fixed effects," Journal of Econometrics, Elsevier, vol. 140(2), pages 503-528, October.
  5. Arellano, Manuel & Carrasco, Raquel, 2003. "Binary choice panel data models with predetermined variables," Journal of Econometrics, Elsevier, vol. 115(1), pages 125-157, July.
  6. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-54, July.
  7. Arellano, Manuel & Bover, Olympia, 1995. "Another look at the instrumental variable estimation of error-components models," Journal of Econometrics, Elsevier, vol. 68(1), pages 29-51, July.
  8. Gary Chamberlain, 2010. "Binary Response Models for Panel Data: Identification and Information," Econometrica, Econometric Society, vol. 78(1), pages 159-168, 01.
  9. M. Hashem Pesaran & Allan Timmermann, 2006. "Testing Dependence among Serially Correlated Multi-category Variables," CESifo Working Paper Series 1770, CESifo Group Munich.
  10. Francesco Bartolucci & Valentina Nigro, 2010. "A Dynamic Model for Binary Panel Data With Unobserved Heterogeneity Admitting a √n-Consistent Conditional Estimator," Econometrica, Econometric Society, vol. 78(2), pages 719-733, 03.
  11. Anderson, T. W. & Hsiao, Cheng, 1982. "Formulation and estimation of dynamic models using panel data," Journal of Econometrics, Elsevier, vol. 18(1), pages 47-82, January.
  12. David Roodman, 2009. "A Note on the Theme of Too Many Instruments," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(1), pages 135-158, 02.
  13. 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.
  14. Bo Honoré, 2002. "Nonlinear Models with Panel Data," CAM Working Papers 2002-02, University of Copenhagen. Department of Economics. Centre for Applied Microeconometrics.
  15. Magnac, Thierry, 2000. "Subsidised Training and Youth Employment: Distinguishing Unobserved Heterogeneity from State Dependence in Labour Market Histories," Economic Journal, Royal Economic Society, vol. 110(466), pages 805-37, October.
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