Confidence Sets for the Date of a Single Break in Linear Time Series Regressions

Graham Elliott () and Ulrich K. Muller

University of California at San Diego, Economics Working Paper Series from Department of Economics, UC San Diego

Abstract: We consider 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 he currently standard method in econometrics to construct such intervals has a coverage rate far below nominal levels when breaks are of moderate magnitude. Given that such breaks are a theoretically and empirically highly relevant phenomenon, we proceed to develop an appropriate alternative. We suggest constructing confidence sets by inverting a sequence of tests. Each test maintains a specific break date under the null hypothesis, and rejects when a break occurs elsewhere. By inverting a certain variant of a modified 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.

Keywords: Test Inversion; Coverage Control; Locally Best Test (search for similar items in EconPapers)
Date: 2004-08-01
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Related works:
Journal Article: Confidence sets for the date of a single break in linear time series regressions (2007)
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