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Testing for joint significance in nonstationary ordered choice model

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  • Xu, Peng

Abstract

This paper studies the test of joint significance for the ordered choice model with multiple explanatory variables following integrated processes. The results show that for the widely used logit and probit models, when the true parameter vector of explanatory variables is zero, the classical Wald statistic is still useful and has a Chi-squared limiting distribution.

Suggested Citation

  • Xu, Peng, 2015. "Testing for joint significance in nonstationary ordered choice model," Economics Letters, Elsevier, vol. 130(C), pages 5-8.
    • Handle: RePEc:eee:ecolet:v:130:y:2015:i:c:p:5-8
    DOI: 10.1016/j.econlet.2015.02.020
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    References listed on IDEAS

    as
    1. Phillips, Peter C.B. & Jin, Sainan & Hu, Ling, 2007. "Nonstationary discrete choice: A corrigendum and addendum," Journal of Econometrics, Elsevier, vol. 141(2), pages 1115-1130, December.
    2. Joon Y. Park & Peter C. B. Phillips, 2000. "Nonstationary Binary Choice," Econometrica, Econometric Society, vol. 68(5), pages 1249-1280, September.
    3. Hu, Ling & Phillips, Peter C. B., 2004. "Nonstationary discrete choice," Journal of Econometrics, Elsevier, vol. 120(1), pages 103-138, May.
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    More about this item

    Keywords

    Ordered 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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