Identification of Panel Data Models with Endogenous Censoring

Shakeeb Khan, Maria Ponomareva and Elie Tamer

No 11-07, Working Papers from Duke University, Department of Economics

Abstract: This paper analyzes the identification question in censored panel data models, where the censoring can depend on both observable and unobservable variables in arbitrary ways. Under some general conditions, we derive the tightest sets on the parameter of interest. These sets (which can be singletons) represent the limit of what one can learn about the parameter of interest given the model and the data in that every parameter that belongs to these sets is observationally equivalent to the true parameter. We consider two separate sets of assumptions, motivated by the previous literature, each controlling for unobserved heterogeneity with an individual specific (fixed) effect. The first imposes a stationarity assumption on the unobserved disturbance terms, along the lines of Manski (1987), and Honore (1993). The second is a nonstationary model that imposes a conditional independence assumption. For both models, we provide sufficient conditions for these models to point identify the parameters. Since our identified sets are defined through parameters that obey first order dominance, we outline easily implementable approaches to build confidence regions based on recent advances in Linton et.al.(2010) on bootstrapping tests of stochastic dominance. We also extend our results to dynamic versions of the censored panel models in which we consider lagged observed, latent dependent variables and lagged censoring indicator variables as regressors.

Keywords: panel data; partial identification; endogenous censoring (search for similar items in EconPapers)
JEL-codes: C23 C24 C32 (search for similar items in EconPapers)
Pages: 43
Date: 2011
References: Add references at CitEc
Citations: View citations in EconPapers (6)

Downloads: (external link)
http://ssrn.com/abstract=1831402 main text

Related works:
Journal Article: Identification of panel data models with endogenous censoring (2016)
Working Paper: Identification of Panel Data Models with Endogenous Censoring (2011)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:duk:dukeec:11-07

Access Statistics for this paper

More papers in Working Papers from Duke University, Department of Economics Department of Economics Duke University 213 Social Sciences Building Box 90097 Durham, NC 27708-0097.
Bibliographic data for series maintained by Department of Economics Webmaster ().