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Testing for joint significance in nonstationary binary choice model

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  • Mao, Guangyu

Abstract

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.

Suggested Citation

  • Mao, Guangyu, 2014. "Testing for joint significance in nonstationary binary choice model," Economics Letters, Elsevier, vol. 122(2), pages 311-313.
    • Handle: RePEc:eee:ecolet:v:122:y:2014:i:2:p:311-313
    DOI: 10.1016/j.econlet.2013.12.012
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    References listed on IDEAS

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    1. Joon Y. Park & Peter C. B. Phillips, 2000. "Nonstationary Binary Choice," Econometrica, Econometric Society, vol. 68(5), pages 1249-1280, September.
    2. Guerre, Emmanuel & Moon, Hyungsik Roger, 2002. "A note on the nonstationary binary choice logit model," Economics Letters, Elsevier, vol. 76(2), pages 267-271, July.
    3. Park, Joon Y. & Phillips, Peter C.B., 1999. "Asymptotics For Nonlinear Transformations Of Integrated Time Series," Econometric Theory, Cambridge University Press, vol. 15(3), pages 269-298, June.
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    More about this item

    Keywords

    Binary choice model; Nonstationarity; Significance test;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities

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