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Bootstrap Tests Based on Goodness-of-Fit Measures for Nonnested Hypotheses in Regression Models

Author

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  • Jeong, Jinook

Abstract

This paper utilizes the bootstrap to construct tests using the measures for goodness-of-fit for nonnested regression models. The bootstrap enables us to compute the statistical significance of the differences in the measures and to formally test on nonnested regression models. The bootstrap tests that this paper proposes are expected to show better finite sample properties since they do not have accumulated errors in the computation process. Moreover, the bootstrap tests remove the possibility of inconsistent test results that the previous tests suffer from. Because the bootstrap tests only evaluate if a model has a significantly higher explanatory power than the other model, there is no possibility for inconsistent results. This study presents Monte Carlo simulation results to compare the finite sample properties of the proposed tests with the previous tests such as Cox test and J-test.

Suggested Citation

  • Jeong, Jinook, 2006. "Bootstrap Tests Based on Goodness-of-Fit Measures for Nonnested Hypotheses in Regression Models," MPRA Paper 9789, University Library of Munich, Germany, revised Mar 2007.
    • Handle: RePEc:pra:mprapa:9789
    as

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    File URL: https://mpra.ub.uni-muenchen.de/9789/1/MPRA_paper_9789.pdf
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    References listed on IDEAS

    as
    1. Kinal, Terrence & Lahiri, Kajal, 1984. "A Note on "Selection of Regressors."," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 25(3), pages 625-629, October.
    2. Mizon, Grayham E & Richard, Jean-Francois, 1986. "The Encompassing Principle and Its Application to Testing Non-nested Hypotheses," Econometrica, Econometric Society, vol. 54(3), pages 657-678, May.
    3. Ebbeler, Donald H, 1975. "On the Probability of Correct Model Selection Using the Maximum R2 Choice Criterion," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 16(2), pages 516-520, June.
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    Cited by:

    1. Hilda Osafo Hounkpatin & Alex Wood & Gordon Brown & Graham Dunn, 2015. "Why does Income Relate to Depressive Symptoms? Testing the Income Rank Hypothesis Longitudinally," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 124(2), pages 637-655, November.
    2. Tobias Schlueter & Soenke Sievers, 2014. "Determinants of market beta: the impacts of firm-specific accounting figures and market conditions," Review of Quantitative Finance and Accounting, Springer, vol. 42(3), pages 535-570, April.

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    More about this item

    Keywords

    nonnested regression models; bootstrap; goodness-of-fit measures;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General

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