Testing for joint significance in nonstationary binary choice model

This paper investigates the test of joint significance for binary choice model with multiple integrated explanatory variables. It is found that for the widely used logit and probit models, even though the estimators have a different convergence rate under null hypothesis compared with the case under alternative, the commonly used Wald statistic is still useful, and asymptotically chi-squared.

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Year of publication:	2014
Authors:	Mao, Guangyu
Published in:	Economics Letters. - Elsevier, ISSN 0165-1765. - Vol. 122.2014, 2, p. 311-313
Publisher:	Elsevier
Subject:	Binary choice model \| Nonstationarity \| Significance test

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Type of publication:	Article
Classification:	C12 - Hypothesis Testing ; C25 - Discrete Regression and Qualitative Choice Models
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10010743738