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# Semiparametric Estimation of Nonstationary Censored Panel Data Models with Time Varying Factor Loads

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 dc.contributor.author Chen, Songnian en_US dc.contributor.author Khan, Prof Shakeeb en_US dc.date.accessioned 2010-06-28T18:50:06Z dc.date.available 2010-06-28T18:50:06Z dc.date.issued 2008 en_US dc.identifier.uri http://hdl.handle.net/10161/2554 dc.description.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 $\sqrt{n}$-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). en_US dc.format.extent 503397 bytes dc.format.mimetype application/pdf dc.language.iso en_US dc.publisher Econometric Theory en_US dc.subject censored regression model en_US dc.subject latent regression function en_US dc.title Semiparametric Estimation of Nonstationary Censored Panel Data Models with Time Varying Factor Loads en_US dc.type Journal Article en_US dc.department Economics