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Relative error accurate statistic based on nonparametric likelihood

Camponovo, Lorenzo, Matsushita, Yukitoshi and Otsu, Taisuke (2020) Relative error accurate statistic based on nonparametric likelihood. Econometric Theory. ISSN 1469-4360 (In Press)

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Abstract

This paper develops a new test statistic for parameters defined by moment conditions that exhibits desirable relative error properties for the approximation of tail area probabilities. Our statistic, called the tilted exponential tilting (TET) statistic, is constructed by estimating certain cumulant generating functions under exponential tilting weights. We show that the asymptotic p-value of the TET statistic can provide an accurate approximation to the p-value of an infeasible saddlepoint statistic, which admits a Lugannani–Rice style adjustment with relative errors of order n −1 both in normal and large deviation regions. Numerical results illustrate the accuracy of the proposed TET statistic. Our results cover both just- and over-identified moment condition models. A limitation of our analysis is that the theoretical approximation results are exclusively for the infeasible saddlepoint statistic, and closeness of the p-values for the infeasible statistic to the ones for the feasible TET statistic is only numerically assessed.

Item Type: Article
Official URL: https://www.cambridge.org/core/journals/econometri...
Additional Information: © 2020 Cambridge University Press
Divisions: Economics
Subjects: H Social Sciences > HB Economic Theory
H Social Sciences > HA Statistics
Date Deposited: 27 Nov 2020 11:09
Last Modified: 01 Dec 2020 14:42
URI: http://eprints.lse.ac.uk/id/eprint/107521

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