Nonparametric significance testing

Pascal Lavergne, Quang Vuong

    Research output: Contribution to journalArticlepeer-review


    A procedure for testing the significance of a subset of explanatory variables in a nonparametric regression is proposed. Our test statistic uses the kernel method. Under the null hypothesis of no effect of the variables under test, we show that our test statistic has an nhp2/2 standard normal limiting distribution, where p2 is the dimension of the complete set of regressors. Our test is one-sided, consistent against all alternatives and detects local alternatives approaching the null at rate slower than n-1/2 h-p2/4. Our Monte-Carlo experiments indicate that it outperforms the test proposed by Fan and Li (1996, Econometrica 64, 865-890).

    Original languageEnglish (US)
    Pages (from-to)576-601
    Number of pages26
    JournalEconometric Theory
    Issue number4
    StatePublished - 2000

    ASJC Scopus subject areas

    • Social Sciences (miscellaneous)
    • Economics and Econometrics


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