Informational content of special regressors in heteroskedastic binary response models

Songnian Chen, Shakeeb Khan and Xun Tang

Journal of Econometrics, 2016, vol. 193, issue 1, 162-182

Abstract: We quantify the informational content of special regressors in heteroskedastic binary response models with median-independent or conditionally symmetric errors. Based on Lewbel (1998), a special regressor is additively separable in the latent payoff and conditionally independent from the error term. We find that with median-independent errors a special regressor does not increase the identifying power by a criterion in Manski (1988) or lead to positive Fisher information for the coefficients, even though it does help recover the average structural function. With conditionally symmetric errors, a special regressor improves the identifying power, and the information for coefficients is positive under mild conditions. We propose two estimators for binary response models with conditionally symmetric errors and special regressors.

Keywords: Binary response; Heteroskedasticity; Identification; Information; Median independence; Conditional symmetry (search for similar items in EconPapers)
JEL-codes: C14 C21 C25 (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (12)

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Working Paper: Informational Content of Special Regressors in Heteroskedastic Binary Response Models (2013)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:193:y:2016:i:1:p:162-182

DOI: 10.1016/j.jeconom.2015.12.018

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