Improving the finite sample performance of tests for a shift in mean

Daisuke Yamazaki, Eiji Kurozumi

研究成果: Contribution to journalArticle査読

3 被引用数 (Scopus)

抄録

It is widely known that structural break tests based on the long-run variance estimator, which is estimated under the alternative, suffer from serious size distortion when the errors are serially correlated. In this paper, we propose bias-corrected tests for a shift in mean by correcting the bias of the long-run variance estimator up to O(1/. T). Simulation results show that the proposed tests have good size and high power.

本文言語英語
ページ(範囲)144-173
ページ数30
ジャーナルJournal of Statistical Planning and Inference
167
DOI
出版ステータス出版済み - 12 1 2015
外部発表はい

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Statistics, Probability and Uncertainty
  • Applied Mathematics

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