Removing Specification Errors from the Usual Formulation of Binary Choice Models

P.A.V.B. Swamy, I-Lok Chang, Jatinder S. Mehta, William Greene, Stephen Hall and George Tavlas
Additional contact information
P.A.V.B. Swamy: Federal Reserve Board (Retired), Washington, DC 20551, USA
I-Lok Chang: Department of Mathematics (Retired), American University, Washington, DC 20016, USA
Jatinder S. Mehta: Department of Mathematics (Retired), Temple University, Philadelphia, PA 19122, USA

Econometrics, 2016, vol. 4, issue 2, 1-21

Abstract: We develop a procedure for removing four major specification errors from the usual formulation of binary choice models. The model that results from this procedure is different from the conventional probit and logit models. This difference arises as a direct consequence of our relaxation of the usual assumption that omitted regressors constituting the error term of a latent linear regression model do not introduce omitted regressor biases into the coefficients of the included regressors.

Keywords: binary choice models; specification errors; stochastic coefficients (search for similar items in EconPapers)
JEL-codes: B23 C C00 C01 C1 C2 C3 C4 C5 C8 (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Working Paper: Removing Specification Errors from the Usual Formulation of Binary Choice Models* (2016)
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