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A simple alternative to the linear probability model for binary choice models with endogenous regressors

Author

Listed:
  • Christopher F Baum

    () (Boston College
    DIW Berlin)

  • Yingying Dong

    (University of California Irvine)

  • Arthur Lewbel

    (Boston College)

  • Tao Yang

    (Boston College)

Abstract

Dong and Lewbel have developed the theory of simple estimators for binary choice models with endogenous or mismeasured regressors, depending on a “special regressor” as defined by Lewbel (Journal of Econometrics, 2000). These estimators can be used with limited, censored, continuous, or discrete endogenous regressors and have significant advantages over the linear probability model. These estimators are numerically straightforward to implement. We present and demonstrate an improved version of a Stata routine that provides both estimation and postestimation features, and we give a simple example where the linear probability model fails to estimate any useful quantity.

Suggested Citation

  • Christopher F Baum & Yingying Dong & Arthur Lewbel & Tao Yang, 2012. "A simple alternative to the linear probability model for binary choice models with endogenous regressors," German Stata Users' Group Meetings 2012 02, Stata Users Group.
  • Handle: RePEc:boc:dsug12:02
    as

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    File URL: http://fmwww.bc.edu/repec/dsug2012/desug12_baum.pdf
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    Cited by:

    1. Lin, Wei & Wooldridge, Jeffrey M., 2015. "On different approaches to obtaining partial effects in binary response models with endogenous regressors," Economics Letters, Elsevier, vol. 134(C), pages 58-61.

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