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

Daisuke Yamazaki; Eiji Kurozumi

doi:10.1016/j.jspi.2015.05.002

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

Daisuke Yamazaki, Eiji Kurozumi

Research output: Contribution to journal › Article › peer-review

3 Citations (Scopus)

Abstract

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.

Original language	English
Pages (from-to)	144-173
Number of pages	30
Journal	Journal of Statistical Planning and Inference
Volume	167
DOIs	https://doi.org/10.1016/j.jspi.2015.05.002
Publication status	Published - Dec 1 2015
Externally published	Yes

All Science Journal Classification (ASJC) codes

Statistics and Probability
Statistics, Probability and Uncertainty
Applied Mathematics

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10.1016/j.jspi.2015.05.002

Cite this

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abstract = "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.",

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ER -

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

Abstract

All Science Journal Classification (ASJC) codes

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