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Empirical likelihood inference for monotone index model

Otsu, Taisuke, Takahata, Keisuke and Xu, Mengshan (2023) Empirical likelihood inference for monotone index model. Japanese Journal of Statistics and Data Science, 6 (1). pp. 103-114. ISSN 2520-8756

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Identification Number: 10.1007/s42081-023-00195-1

Abstract

This paper proposes an empirical likelihood inference method for monotone index models. We construct the empirical likelihood function based on a modified score function developed by Balabdaoui et al. (Scand J Stat 46:517–544, 2019), where the monotone link function is estimated by isotonic regression. It is shown that the empirical likelihood ratio statistic converges to a weighted chi-squared distribution. We suggest inference procedures based on an adjusted empirical likelihood statistic that is asymptotically pivotal, and a bootstrap calibration with recentering. A simulation study illustrates usefulness of the proposed inference methods.

Item Type: Article
Official URL: https://www.springer.com/journal/42081
Additional Information: © 2023 The Authors
Divisions: Economics
Subjects: H Social Sciences > HA Statistics
Date Deposited: 07 Feb 2023 12:03
Last Modified: 28 Feb 2024 00:05
URI: http://eprints.lse.ac.uk/id/eprint/118123

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