Relative Error Accurate Statistic Based on Nonparametric Likelihood

Lorenzo Camponovo, Yukitoshi Matsushita, Taisuke Otsu

研究成果: Article査読

抄録

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 both in normal and large deviation regions. Numerical results illustrate the accuracy of the proposed TET statistic. Our results cover both just- A nd overidentified 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.

本文言語English
ページ(範囲)1214-1237
ページ数24
ジャーナルEconometric Theory
37
6
DOI
出版ステータスPublished - 2021 12月 1
外部発表はい

ASJC Scopus subject areas

  • 社会科学(その他)
  • 経済学、計量経済学

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