TY - JOUR
T1 - Improving the finite sample performance of tests for a shift in mean
AU - Yamazaki, Daisuke
AU - Kurozumi, Eiji
N1 - Publisher Copyright:
© 2015 Elsevier B.V.
PY - 2015/12/1
Y1 - 2015/12/1
N2 - 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.
AB - 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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U2 - 10.1016/j.jspi.2015.05.002
DO - 10.1016/j.jspi.2015.05.002
M3 - Article
AN - SCOPUS:84945489275
SN - 0378-3758
VL - 167
SP - 144
EP - 173
JO - Journal of Statistical Planning and Inference
JF - Journal of Statistical Planning and Inference
ER -