This paper develops tests for inequality constraints of nonparametric regression functions. The test statistics involve a one-sided version of Lp-type functionals of kernel estimators (1≤p∞). Drawing on the approach of Poissonization, this paper establishes that the tests are asymptotically distribution free, admitting asymptotic normal approximation. In particular, the tests using the standard normal critical values have asymptotically correct size and are consistent against general fixed alternatives. Furthermore, we establish conditions under which the tests have nontrivial local power against Pitman local alternatives. Some results from Monte Carlo simulations are presented.

    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

    Song, Kyungchul

    Journal article details

    DOI
    10.1016/j.jeconom.2012.08.006
    Publisher
    Elsevier
    Issue
    Volume 172, Issue 1, January 2013

    Suggested citation

    S, Kyungchul and S, Lee and Y, Whang. (2013). 'Testing functional inequalities' 172(1/2013)

    More from IFS

    Understand this issue

    Row of houses

    How is tax damaging the housing market?

    podcast

    We discuss how taxes like capital gains, stamp duty, and council tax impact the housing market, affecting affordability, renting, and homeownership.

    18 December 2024

    Policy analysis

    Academic research