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Semiparametric Estimation Of Nonstationary Censored Panel Data Models With Time Varying Factor Loads

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  • Chen, Songnian
  • Khan, Shakeeb

Abstract

We propose an estimation procedure for a semiparametric panel data censored regression model in which the error terms may be subject to general forms of nonstationarity. Specifically, we allow for heteroskedasticity over time and a time varying factor load on the individual specific effect. Empirically, estimation of this model would be of interest to explore how returns to unobserved skills change over time—see, e.g., Chay (1995, manuscript, Princeton University) and Chay and Honoré (1998, Journal of Human Resources 33, 4–38). We adopt a two-stage procedure based on nonparametric median regression, and the proposed estimator is shown to be null -consistent and asymptotically normal. The estimation procedure is also useful in the group effect setting, where estimation of the factor load would be empirically relevant in the study of the intergenerational correlation in income, explored in Solon (1992, American Economic Review 82, 393–408; 1999, Handbook of Labor Economics , vol. 3, 1761–1800) and Zimmerman (1992, American Economic Review 82, 409–429).

Suggested Citation

  • Chen, Songnian & Khan, Shakeeb, 2008. "Semiparametric Estimation Of Nonstationary Censored Panel Data Models With Time Varying Factor Loads," Econometric Theory, Cambridge University Press, vol. 24(05), pages 1149-1173, October.
  • Handle: RePEc:cup:etheor:v:24:y:2008:i:05:p:1149-1173_08
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    Cited by:

    1. Khan, Shakeeb & Ponomareva, Maria & Tamer, Elie, 2016. "Identification of panel data models with endogenous censoring," Journal of Econometrics, Elsevier, vol. 194(1), pages 57-75.
    2. Evans, Mary F. & Schaur, Georg, 2010. "A quantile estimation approach to identify income and age variation in the value of a statistical life," Journal of Environmental Economics and Management, Elsevier, vol. 59(3), pages 260-270, May.
    3. Carlos A. Flores & Alfonso Flores-Lagunes & Dimitrios Kapetanakis, 2014. "Lessons From Quantile Panel Estimation of the Environmental Kuznets Curve," Econometric Reviews, Taylor & Francis Journals, vol. 33(8), pages 815-853, November.
    4. Genya Kobayashi & Hideo Kozumi, 2012. "Bayesian analysis of quantile regression for censored dynamic panel data," Computational Statistics, Springer, vol. 27(2), pages 359-380, June.
    5. Li, Tong & Oka, Tatsushi, 2015. "Set identification of the censored quantile regression model for short panels with fixed effects," Journal of Econometrics, Elsevier, vol. 188(2), pages 363-377.

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