Abstract
This paper considers the problem of constructing confidence sets for the date of a single break in a linear time series regression. We establish analytically and by small sample simulation that the current standard method in econometrics for constructing such confidence intervals has a coverage rate far below nominal levels when breaks are of moderate magnitude. Given that breaks of moderate magnitude are a theoretically and empirically relevant phenomenon, we proceed to develop an appropriate alternative. We suggest constructing confidence sets by inverting a sequence of tests. Each of the tests maintains a specific break date under the null hypothesis, and rejects when a break occurs elsewhere. By inverting a certain variant of a locally best invariant test, we ensure that the asymptotic critical value does not depend on the maintained break date. A valid confidence set can hence be obtained by assessing which of the sequence of test statistics exceeds a single number.
Original language | English (US) |
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Pages (from-to) | 1196-1218 |
Number of pages | 23 |
Journal | Journal of Econometrics |
Volume | 141 |
Issue number | 2 |
DOIs | |
State | Published - Dec 2007 |
All Science Journal Classification (ASJC) codes
- Economics and Econometrics
Keywords
- Coverage control
- Locally best test
- Test inversion