<p><p>This paper develops tests for inequality constraints of nonparametric regression functions. The test statistics involve a one-sided version of L<sub>p</sub>-type functionals of kernel estimators. Drawing on the approach of Poissonization, this paper establishes that the tests are asymptotically distribution free, admitting asymptotic normal approximation. Furthermore, the tests have nontrivial local power against a certain class of local alternatives converging to the null at the rate of n<sup>-1/2</sup>. Some results from Monte Carlo simulations are presented. </p><p></p><p></p></p>

    Authors

    Sokbae "Simon" Lee
    Sokbae (Simon) Lee

    Research Fellow Columbia University

    Sokbae is an IFS Research Fellow and a Professor at Columbia University, with an interest in Econometrics, Applied Microeconomics and Statistics.

    Person graphic

    Kyungchui (Kevin) Song

    Working Paper details

    DOI
    10.1920/wp.cem.2011.1211
    Publisher
    IFS

    Suggested citation

    S, Lee and K, Song and Y, Whang. (2011). Testing functional inequalities. London: IFS. Available at: https://ifs.org.uk/publications/testing-functional-inequalities (accessed: 13 January 2025).

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