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Inference in Censored Models with Endogenous Regressors

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  • Elie Tamer

    (Princeton University)

Abstract

This paper analyzes the linear regression model y = xb+e with a conditional median assumption Med( e | z)=0 where z is a vector of instruments. Added complication arises due to the censoring of the outcome y. We treat the censored model as a model with interval-observed outcome thus obtaining interval restrictions on conditional median regressions. This allows us to use the framework introduced by Manski and Tamer (2000) to analyze the information contained in these inequality restrictions. We first show identification of the parameter b in the absence of censoring and introduce a consistent estimator based on the minimum distance method. We then give conditions for global identification of b in the model above with censored y and endogenous x. We provide a consistent estimator that is based on a modified minimum distance method.

Suggested Citation

  • Elie Tamer, 2000. "Inference in Censored Models with Endogenous Regressors," Econometric Society World Congress 2000 Contributed Papers 1815, Econometric Society.
    • Handle: RePEc:ecm:wc2000:1815
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    References listed on IDEAS

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    1. Powell, James L., 1984. "Least absolute deviations estimation for the censored regression model," Journal of Econometrics, Elsevier, vol. 25(3), pages 303-325, July.
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    6. Honore, Bo E, 1992. "Trimmed LAD and Least Squares Estimation of Truncated and Censored Regression Models with Fixed Effects," Econometrica, Econometric Society, vol. 60(3), pages 533-565, May.
    7. Powell, James L & Stock, James H & Stoker, Thomas M, 1989. "Semiparametric Estimation of Index Coefficients," Econometrica, Econometric Society, vol. 57(6), pages 1403-1430, November.
    8. Charles F. Manski & Elie Tamer, 2002. "Inference on Regressions with Interval Data on a Regressor or Outcome," Econometrica, Econometric Society, vol. 70(2), pages 519-546, March.
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