Hostname: page-component-77c78cf97d-hf2s2 Total loading time: 0 Render date: 2026-04-25T02:36:25.835Z Has data issue: false hasContentIssue false
  • English
  • Français

BIAS REDUCTION FOR DYNAMIC NONLINEAR PANEL MODELS WITH FIXED EFFECTS

Published online by Cambridge University Press:  31 May 2011

Jinyong Hahn  and
Guido Kuersteiner
Jinyong Hahn
Affiliation:
UCLA
Guido Kuersteiner*
Affiliation:
Georgetown University
*
*Address correspondence to Guido Kuersteiner, Georgetown University, Department of Economics, ICC 572, 37th and O Streets, Washington, D.C. 20057; e-mail: gk232@georgetown.edu
Get access Rights & Permissions [Opens in a new window]

Abstract

The fixed effects estimator of panel models can be severely biased because of well-known incidental parameter problems. It is shown that this bias can be reduced in nonlinear dynamic panel models. We consider asymptotics where n and T grow at the same rate as an approximation that facilitates comparison of bias properties. Under these asymptotics, the bias-corrected estimators we propose are centered at the truth, whereas fixed effects estimators are not. We discuss several examples and provide Monte Carlo evidence for the small sample performance of our procedure.

Information

Type
ARTICLES
Information
Econometric Theory , Volume 27 , Issue 6 , December 2011 , pp. 1152 - 1191
Copyright
Copyright © Cambridge University Press 2011

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Article purchase

Temporarily unavailable

References

REFERENCES

Amemiya, T. (1973) Regression analysis when the dependent variable is truncated normal. Econometrica 41, 997–1016.CrossRefGoogle Scholar
Andrews, D.W.K. (1991) Heteroskedasticity and autocorrelation consistent covariance matrix estimation. Econometrica 59, 817–858.CrossRefGoogle Scholar
Bester, A.C. & Hansen, C. (2009) A penalty function approach to bias reduction in nonlinear panel models with fixed effects. Journal of Business and Economic Statistics 27, 131–148.CrossRefGoogle Scholar
Chay, K.Y. & Hyslop, D.R. (2000) Identification and Estimation of Dynamic Binary Response Panel Data Models: Empirical Evidence Using Alternative Approaches. Unpublished manuscript.Google Scholar
Chintagunta, P., Kyriazidou, E., & Perktold, J. (2001) Panel data analysis of household brand choices. Journal of Econometrics 103, 111–153.CrossRefGoogle Scholar
De Jong, R. & Woutersen, T. (2011) Dynamic time series binary choice. Econometric Theory 27, 623–702.CrossRefGoogle Scholar
Hahn, J. & Kuersteiner, G. (2002) Asymptotically unbiased inference for a dynamic panel model with fixed effects when both n and T are large. Econometrica 70, 1639–1657.CrossRefGoogle Scholar
Hahn, J. & Kuersteiner, G. (2006) Bandwidth Choice for Bias Estimators in Dynamic Nonlinear Panel Models. Unpublished manuscript.Google Scholar
Hahn, J. & Kuersteiner, G. (2010a) Bias Reduction for Dynamic Nonlinear Panel Models with Fixed Effects: Supplementary Appendix. http://www9.georgetown.edu/faculty/gk232/research/Hahn-Kuersteiner-Supp-Appendix2.pdf.Google Scholar
Hahn, J. & Kuersteiner, G. (2010b) Stationarity and mixing properties of the dynamic Tobit model. Economics Letters 107, 105–111.CrossRefGoogle Scholar
Hahn, J. & Newey, W.K. (2004) Jackknife and analytical bias reduction for nonlinear panel models. Econometrica 72, 1295–1319.CrossRefGoogle Scholar
Hall, P. & Heyde, C. (1980) Martingale Limit Theory and Its Application. Academic Press.Google Scholar
Hall, P. & Horowitz, J. (1996) Bootstrap critical values for tests based on generalized-method-of-moments estimators. Econometrica 64, 891–916.CrossRefGoogle Scholar
Han, C., Phillips, P.C.B., & Sul, D. (2010) X-Differencing and Dynamic Panel Model Estimation. Cowles Foundation Discussion Paper No. 1747.CrossRefGoogle Scholar
Hansen, B.E. (1991) Strong laws for dependent heterogenous processes. Econometric Theory 7, 213–221.CrossRefGoogle Scholar
Heckman, J.J. (1978) Simple statistical models for discrete panel data developed and applied to test the hypothesis of true state dependence against the hypothesis of spurious state dependence. Annales de l’INSEE, 227–269.Google Scholar
Heckman, J.J. (1981a) Heterogeneity and state dependence. In Rosen, S. (ed.), Studies in Labor Markets. University of Chicago Press.Google Scholar
Heckman, J.J. (1981b) Statistical models for discrete panel data. In Manski, C. & McFadden, D. (eds.), Structural Analysis of Discrete Data. MIT Press.Google Scholar
Heckman, J.J. & MaCurdy, T.E. (1980) A life cycle model of female labour supply. Review of Economic Studies 47, 47–74.CrossRefGoogle Scholar
Hendel, I. & Nevo, A. (2006) Sales and consumer inventory. RAND Journal of Economics 37, 543–561.CrossRefGoogle Scholar
Honoré, B.E. (1992) Trimmed LAD and least squares estimation of truncated and censored regression models with fixed effects. Econometrica 60, 533–565.CrossRefGoogle Scholar
Honoré, B. & Kyriazidou, E. (2000) Panel data discrete choice models with lagged dependent variables. Econometrica 68, 839–874.CrossRefGoogle Scholar
Hyslop, D.R. (1999) State dependence, serial correlation, and heterogeneity in intertemporal labor force participation of married women. Econometrica 67, 1255–1294.CrossRefGoogle Scholar
Lee, L., Yu, J., & de Jong, R. (2008) Quasi-maximum likelihood estimators for spatial dynamic panel data with fixed effects when both n and T are large. Journal of Econometrics 146, 118–134.Google Scholar
Lee, Y. (2007a) Bias Correction in Dynamic Panels under Time Series Misspecification. Unpublished manuscript.CrossRefGoogle Scholar
Lee, Y. (2007b) Nonparametric Estimation of Dynamic Panel Models with Fixed Effects. Unpublished manuscript.CrossRefGoogle Scholar
Magnus, J. & Neudecker, H. (1988) Matrix Differential Calculus with Applications in Statistics and Econometrics. Wiley.Google Scholar
McLeish, D.L. (1975) A maximal inequality and dependent strong laws. Annals of Probability 3, 829–839.CrossRefGoogle Scholar
Moon, H.R. & Phillips, P.C.B. (2004) GMM estimation of autoregressive roots near unity with panel data. Econometrica 72, 467–522.CrossRefGoogle Scholar
Newey, W.K. & McFadden, D. (1994) Large sample estimation and hypothesis testing. In Engle, R.F. & McFadden, D.L. (eds.), The Handbook of Econometrics, vol. IV, pp. 2111–2245. Elsevier.CrossRefGoogle Scholar
Neyman, J. & Scott, E. (1948) Consistent estimates based on partially consistent observations. Econometrica 16, 1–31.CrossRefGoogle Scholar
Olsen, R.J. (1978) Note on the uniqueness of the maximum likelihood estimator for the Tobit model. Econometrica 46, 1211–1215.CrossRefGoogle Scholar
Phillips, P.C.B. & Sul, D. (2003) Dynamic panel estimation and homogeneity testing under cross section dependence. Econometrics Journal 6, 217–259.CrossRefGoogle Scholar
Robert, M.J. & Tybout, J.R. (1997) The decision to export in Colombia: An empirical model of entry with sunk costs. American Economic Review 87, 545–564.Google Scholar
Van der Vaart, A.W. & Wellner, J.A. (1996) Weak Convergence and Empirical Processes. Springer Verlag.CrossRefGoogle Scholar