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Identification of Panel Data Models with Endogenous Censoring

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  • Khan, Shakeeb
  • Ponomareva, Maria
  • Tamer, Elie

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 Honor ́e (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.

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Bibliographic Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 30373.

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Date of creation: 18 Apr 2011
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Handle: RePEc:pra:mprapa:30373

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Keywords: Endogenous Censoring; Conditional Stochastic Dominance; Censored Panel Models.;

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References

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  1. Bester, C. Alan & Hansen, Christian, 2009. "Identification of Marginal Effects in a Nonparametric Correlated Random Effects Model," Journal of Business & Economic Statistics, American Statistical Association, American Statistical Association, vol. 27(2), pages 235-250.
  2. Victor Chernozhukov & Ivan Fernandez-Val & Jinyong Hahn & Whitney Newey, 2009. "Identification and Estimation of Marginal Effects in Nonlinear Panel Models," Boston University - Department of Economics - Working Papers Series, Boston University - Department of Economics wp2009-b, Boston University - Department of Economics.
  3. Rosen, Adam M., 2012. "Set identification via quantile restrictions in short panels," Journal of Econometrics, Elsevier, Elsevier, vol. 166(1), pages 127-137.
  4. Oliver Linton & Kyungchul Song & Yoon-Jae Whang, 2009. "An improved bootstrap test of stochastic dominance," Economics Working Papers we094827, Universidad Carlos III, Departamento de Economía.
  5. Honore, Bo E., 1993. "Orthogonality conditions for Tobit models with fixed effects and lagged dependent variables," Journal of Econometrics, Elsevier, Elsevier, vol. 59(1-2), pages 35-61, September.
  6. Bryan S. Graham & James Powell, 2008. "Identification and Estimation of 'Irregular' Correlated Random Coefficient Models," NBER Working Papers 14469, National Bureau of Economic Research, Inc.
  7. Stefan Hoderlein & Halbert White, 2009. "Nonparametric Identification in Nonseparable Panel Data Models with Generalized Fixed Effects," Boston College Working Papers in Economics, Boston College Department of Economics 746, Boston College Department of Economics.
  8. Khan, Shakeeb & Tamer, Elie, 2007. "Partial rank estimation of duration models with general forms of censoring," Journal of Econometrics, Elsevier, Elsevier, vol. 136(1), pages 251-280, January.
  9. Chen, Songnian & Khan, Shakeeb, 2008. "Semiparametric Estimation Of Nonstationary Censored Panel Data Models With Time Varying Factor Loads," Econometric Theory, Cambridge University Press, Cambridge University Press, vol. 24(05), pages 1149-1173, October.
  10. Bo E. Honoré & Elie Tamer, 2006. "Bounds on Parameters in Panel Dynamic Discrete Choice Models," Econometrica, Econometric Society, Econometric Society, vol. 74(3), pages 611-629, 05.
  11. Honore, Bo E. & Powell, James L., 1994. "Pairwise difference estimators of censored and truncated regression models," Journal of Econometrics, Elsevier, Elsevier, vol. 64(1-2), pages 241-278.
  12. Powell, James L., 1984. "Least absolute deviations estimation for the censored regression model," Journal of Econometrics, Elsevier, Elsevier, vol. 25(3), pages 303-325, July.
  13. Honore, Bo E. & Hu, Luojia, 2004. "Estimation of cross sectional and panel data censored regression models with endogeneity," Journal of Econometrics, Elsevier, Elsevier, vol. 122(2), pages 293-316, October.
  14. Victor Chernozhukov & Sokbae 'Simon' Lee & Adam Rosen, 2009. "Intersection Bounds: estimation and inference," CeMMAP working papers, Centre for Microdata Methods and Practice, Institute for Fiscal Studies CWP19/09, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  15. Honore, Bo & Khan, Shakeeb & Powell, James L., 2002. "Quantile regression under random censoring," Journal of Econometrics, Elsevier, Elsevier, vol. 109(1), pages 67-105, July.
  16. Peter Phillips & Hyungsik Moon, 2000. "Nonstationary panel data analysis: an overview of some recent developments," Econometric Reviews, Taylor & Francis Journals, Taylor & Francis Journals, vol. 19(3), pages 263-286.
  17. Bo E. Honoré & Adriana Lleras-Muney, 2006. "Bounds in Competing Risks Models and the War on Cancer," Econometrica, Econometric Society, Econometric Society, vol. 74(6), pages 1675-1698, November.
  18. Manski, Charles F, 1987. "Semiparametric Analysis of Random Effects Linear Models from Binary Panel Data," Econometrica, Econometric Society, Econometric Society, vol. 55(2), pages 357-62, March.
  19. Stéphane Bonhomme, 2012. "Functional Differencing," Econometrica, Econometric Society, Econometric Society, vol. 80(4), pages 1337-1385, 07.
  20. Charles F. Manski & Elie Tamer, 2002. "Inference on Regressions with Interval Data on a Regressor or Outcome," Econometrica, Econometric Society, Econometric Society, vol. 70(2), pages 519-546, March.
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Citations

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Cited by:
  1. Sokbae 'Simon' Lee & Kyungchul Song & Yoon-Jae Whang, 2014. "Testing for a general class of functional inequalities," CeMMAP working papers, Centre for Microdata Methods and Practice, Institute for Fiscal Studies CWP09/14, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  2. Alan Sule & Honoré Bo E. & Hu Luojia & Leth-Petersen Søren, 2014. "Estimation of Panel Data Regression Models with Two-Sided Censoring or Truncation," Journal of Econometric Methods, De Gruyter, De Gruyter, vol. 3(1), pages 1-20, January.

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