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A Simple Estimator for Binary Choice Models with Endogenous Regressors

Listed author(s):
  • Yingying Dong

    (California State University, Fullerton)

  • Arthur Lewbel

    ()

    (Boston College)

This paper provides a few variants of a simple estimator for binary choice models with endogenous or mismeasured regressors, or with heteroskedastic errors. Unlike control function methods, which are generally only valid when endogenous regressors are continuous, the estimators proposed here can be used with limited, censored, continuous, or discrete endogenous regressors, and they allow for latent errors having heteroskedasticity of unknown form, including random coefficients. The variants of special regressor based estimators we provide are numerically trivial to implement. We illustrate these methods with an empirical application estimating migration probabilities within the US.

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Paper provided by Boston College Department of Economics in its series Boston College Working Papers in Economics with number 604.

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Date of creation: 31 Aug 2004
Date of revision: 15 Jun 2012
Publication status: published, Econometric Reviews, 2015, 34, 1-2, 82-105.
Handle: RePEc:boc:bocoec:604
Note: Previously circulated as "Simple Estimators for Binary Choice Models with Endogenous Regressors"
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