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ROOT-N CONSISTENCY OF INTERCEPT ESTIMATORS IN A BINARY RESPONSE MODEL UNDER TAIL RESTRICTIONS

Published online by Cambridge University Press:  02 November 2017

Lili Tan
Affiliation:
Yunnan University
Yichong Zhang*
Affiliation:
Singapore Management University
*
*Address correspondence to Yichong Zhang, School of Economics, Singapore Management University, Singapore; e-mail: yczhang@smu.edu.sg.
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Abstract

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The intercept of the binary response model is not regularly identified (i.e., $\sqrt n$ consistently estimable) when the support of both the special regressor V and the error term ε are the whole real line. The estimator of the intercept potentially has a slower than $\sqrt n$ convergence rate, which can result in a large estimation error in practice. This paper imposes additional tail restrictions which guarantee the regular identification of the intercept and thus the $\sqrt n$-consistency of its estimator. We then propose an estimator that achieves the $\sqrt n$ rate. Last, we extend our tail restrictions to a full-blown model with endogenous regressors.

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Copyright
Copyright © Cambridge University Press 2017 
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