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.
|Number of pages||30|
|Journal||Journal of Statistical Planning and Inference|
|Publication status||Published - Dec 1 2015|
All Science Journal Classification (ASJC) codes
- Statistics and Probability
- Statistics, Probability and Uncertainty
- Applied Mathematics