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Semiparametric Binary Choice Panel Data Models without Strictly Exogeneous Regressors

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Author Info

  • Bo E. Honore

    (Princeton University)

  • Arthur Lewbel

    ()
    (Boston College)

Abstract

Previous estimators of binary choice panel data models with fixed effects require strong parametric error asumptions, strictly exogeneous regressors, or both. This is because nonlinearity of the model precludes the use of the "moment conditions on differences" based estimators that are generally employed for linear models without strictly exogeneous regressors. Based on the cross section binary choice estimator in Lewbel (2000a), we show how discrete choice panel data models with fixed effects can be estimated with only predetermined regressors. The estimator is semiparametric in that the error distribution is not specified, it allows for some general forms of heteroskedasticity, and converges at rate root n.

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Bibliographic Info

Paper provided by Boston College Department of Economics in its series Boston College Working Papers in Economics with number 455.

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Length: 16 pages
Date of creation: 15 Nov 1998
Date of revision: 22 Sep 2001
Handle: RePEc:boc:bocoec:455

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Keywords: panel data; fixed effects; binary choice; semiparametric; latent variable; predetermined regressors; lagged dependent variable;

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References

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  1. Newey, Whitney K, 1994. "The Asymptotic Variance of Semiparametric Estimators," Econometrica, Econometric Society, vol. 62(6), pages 1349-82, November.
  2. Adams, Robert M & Berger, Allen N & Sickles, Robin C, 1999. "Semiparametric Approaches to Stochastic Panel Frontiers with Applications in the Banking Industry," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(3), pages 349-58, July.
  3. Maurin, Eric, 2002. "The impact of parental income on early schooling transitions: A re-examination using data over three generations," Journal of Public Economics, Elsevier, vol. 85(3), pages 301-332, September.
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  5. Arthur Lewbel & Oliver Linton & Daniel McFadden, 2001. "Estimating features of a distribution from binomial data," CeMMAP working papers CWP07/01, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  6. Arellano, Manuel & Carrasco, Raquel, 2003. "Binary choice panel data models with predetermined variables," Journal of Econometrics, Elsevier, vol. 115(1), pages 125-157, July.
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  8. Newey, Whitney K. & McFadden, Daniel, 1986. "Large sample estimation and hypothesis testing," Handbook of Econometrics, in: R. F. Engle & D. McFadden (ed.), Handbook of Econometrics, edition 1, volume 4, chapter 36, pages 2111-2245 Elsevier.
  9. repec:cup:etheor:v:10:y:1994:i:2:p:372-95 is not listed on IDEAS
  10. Heckman, James J & Macurdy, Thomas E, 1980. "A Life Cycle Model of Female Labour Supply," Review of Economic Studies, Wiley Blackwell, vol. 47(1), pages 47-74, January.
  11. Yongmiao Hong & Halbert White, 2005. "Asymptotic Distribution Theory for Nonparametric Entropy Measures of Serial Dependence," Econometrica, Econometric Society, vol. 73(3), pages 837-901, 05.
  12. Manski, Charles F, 1987. "Semiparametric Analysis of Random Effects Linear Models from Binary Panel Data," Econometrica, Econometric Society, vol. 55(2), pages 357-62, March.
  13. Joseph G. Altonji & Rosa L. Matzkin, 2001. "Panel Data Estimators for Nonseparable Models with Endogenous Regressors," NBER Technical Working Papers 0267, National Bureau of Economic Research, Inc.
  14. Sherman, Robert P., 1994. "U-Processes in the Analysis of a Generalized Semiparametric Regression Estimator," Econometric Theory, Cambridge University Press, vol. 10(02), pages 372-395, June.
  15. Powell, James L & Stock, James H & Stoker, Thomas M, 1989. "Semiparametric Estimation of Index Coefficients," Econometrica, Econometric Society, vol. 57(6), pages 1403-30, November.
  16. Arthur Lewbel, 2000. "Asymptotic Trimming for Bounded Density Plug-in Estimators," Boston College Working Papers in Economics 479, Boston College Department of Economics, revised 30 Oct 2000.
  17. Arthur Lewbel, 1999. "Semiparametric Qualitative Response Model Estimation with Unknown Heteroskedasticity or Instrumental Variables," Boston College Working Papers in Economics 454, Boston College Department of Economics.
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