<p>We propose a test of the hypothesis of stochastic monotonicity. This hypothesis is of interest in many applications. Our test is based on the supremum of a rescaled U-statistic. We show that its asymptotic distribution is Gumbel. The proof is difficult because the approximating Gaussian stochastic process contains both a stationary and a nonstationary part and so we have to extend existing results that only apply to either one or the other case.</p>
Authors
![Sokbae "Simon" Lee](/sites/default/files/styles/square_desktop/public/2022-07/Simon%20Lee.jpg?itok=J8PnQSbc)
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](/sites/default/files/styles/square_desktop/public/2022-06/IFS-person-graphic.png?itok=hWCtTSrz)
Oliver Linton
![Person graphic](/sites/default/files/styles/square_desktop/public/2022-06/IFS-person-graphic.png?itok=hWCtTSrz)
SNU
Report details
- Publisher
- STICERD
Suggested citation
S, Lee and O, Linton and Y, Whang. (2006). Testing for stochastic monotonicity. London: STICERD. Available at: https://ifs.org.uk/publications/testing-stochastic-monotonicity (accessed: 30 June 2024).
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