Nonparametric selection of regressors: The nonnested case

P. Lavergne, Quang Vuong

    Research output: Contribution to journalArticle

    Abstract

    We propose a consistent and directional testing procedure for discriminating between two sets of regressors without specifying the functional form of the regressions or the distribution of the residuals. Our test statistic uses the empirical mean square error from a nonparametric (kernel) regression.

    Original languageEnglish (US)
    Pages (from-to)207-219
    Number of pages13
    JournalEconometrica
    Volume64
    Issue number1
    StatePublished - 1996

    Fingerprint

    Kernel Regression
    Nonparametric Regression
    Mean square error
    Test Statistic
    Regression
    regression
    testing procedure
    Testing
    statistics
    Form
    Test statistic
    Kernel regression
    Functional form

    ASJC Scopus subject areas

    • Economics and Econometrics
    • Mathematics (miscellaneous)
    • Statistics and Probability
    • Social Sciences (miscellaneous)

    Cite this

    Lavergne, P., & Vuong, Q. (1996). Nonparametric selection of regressors: The nonnested case. Econometrica, 64(1), 207-219.

    Nonparametric selection of regressors : The nonnested case. / Lavergne, P.; Vuong, Quang.

    In: Econometrica, Vol. 64, No. 1, 1996, p. 207-219.

    Research output: Contribution to journalArticle

    Lavergne, P & Vuong, Q 1996, 'Nonparametric selection of regressors: The nonnested case', Econometrica, vol. 64, no. 1, pp. 207-219.
    Lavergne, P. ; Vuong, Quang. / Nonparametric selection of regressors : The nonnested case. In: Econometrica. 1996 ; Vol. 64, No. 1. pp. 207-219.
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