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Selection of regressors in econometrics: parametric and nonparametric methods selection of regressors in econometrics

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  • Pascal Lavergne

Abstract

The present paper addresses the selection-of-regressors issue into a general discrimination framework. We show how this framework is useful in unifying various procedures for selecting regressors and helpful in understanding the different strategies underlying these procedures. We review selection of regressors in linear, nonlinear and nonparametric regression models. In each case we successively consider model selection criteria and hypothesis testing procedures.

Suggested Citation

  • Pascal Lavergne, 1998. "Selection of regressors in econometrics: parametric and nonparametric methods selection of regressors in econometrics," Econometric Reviews, Taylor & Francis Journals, vol. 17(3), pages 227-273.
    • Handle: RePEc:taf:emetrv:v:17:y:1998:i:3:p:227-273
    DOI: 10.1080/07474939808800415
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    References listed on IDEAS

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    1. Lavergne, Pascal, 2001. "An equality test across nonparametric regressions," Journal of Econometrics, Elsevier, vol. 103(1-2), pages 307-344, July.
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    Cited by:

    1. Maslov, Alexander, 2010. "Функция «Производство-Потребление» Как Методологическое Обоснование Эффективности Региональной Господдержки (На Примере Юфо) [Function "production-consumption" as methodological substanti," MPRA Paper 42767, University Library of Munich, Germany.
    2. El Ghouch, Anouar & Genton, Marc G. & Bouezmarni , Taoufik, 2012. "Measuring the Discrepancy of a Parametric Model via Local Polynomial Smoothing," LIDAM Discussion Papers ISBA 2012001, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    3. Christophe Bontemps & Grayham E. Mizon, 2008. "Encompassing: Concepts and Implementation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 70(s1), pages 721-750, December.
    4. Anouar El Ghouch & Marc G. Genton & Taoufik Bouezmarni, 2013. "Measuring the Discrepancy of a Parametric Model via Local Polynomial Smoothing," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 40(3), pages 455-470, September.

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    More about this item

    Keywords

    Selection of regressors; Discrimination; JEL Classification: Primary C52: Secondary C20;
    All these keywords.

    JEL classification:

    • C20 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - General

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