Binary choice models with endogenous regressors
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 (J. Econometrics, 2000). `Control function' methods such as Stata's ivprobit are generally only valid when endogenous regressors are consistent. The estimators proposed here can be used with limited, censored, continuous or discrete endogenous regressors, and have significant advantages over alternatives such as maximum likelihood and 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 post-estimation features.
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