Full Citation

Title: Tests of Stochastic Monotonicity with Improved Power

Citation Type: Journal Article

Publication Year: 2018

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Abstract: We develop improved statistical procedures for testing stochastic monotonicity. While existing tests use a fixed critical value to set the limiting rejection rate equal to nominal size at the least favorable case, we use a bootstrap procedure to raise the limiting rejection rate to nominal size over much of the null. This improves power against relevant local alternatives. To show the validity of our approach we draw on recent results on the directional differentiability of the least concave majorant operator, and on bootstrap inference when smoothness conditions sufficient to apply the functional delta method for the bootstrap are not satisfied.

Url: https://www.sciencedirect.com/science/article/pii/S0304407618301179

User Submitted?: No

Authors: Seo, Juwon

Periodical (Full): Journal of Econometric

Issue:

Volume: 207

Pages: 53-70

Data Collections: IPUMS USA

Topics: Labor Force and Occupational Structure, Methodology and Data Collection, Other

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