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Simple Estimators for Binary Choice Models with Endogenous Regressors

Listed author(s):
  • Yingying Dong

    ()

    (Department of Economics, University of California-Irvine)

  • Arthur Lewbel

    ()

    (Department of Economics, Boston College)

This paper provides simple estimators for binary choice models with endogenous or mismeasured regressors. 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 also 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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File URL: https://www.economics.uci.edu/files/docs/workingpapers/2011-2012/dong-04.pdf
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Paper provided by University of California-Irvine, Department of Economics in its series Working Papers with number 111204.

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Length: 30 pages
Date of creation: Feb 2012
Handle: RePEc:irv:wpaper:111204
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Web page: http://www.economics.uci.edu/

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