Pre and post break parameter inference

Graham Elliott () and Ulrich K Müller

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

Abstract: Consider inference about the pre and post break value of a scalar parameter in a time series model with a single break at an unknown date. Unless the break is large, treating the break date estimated by least squares as the true break date leads to substantially oversized tests and confidence intervals. To develop a suitable alternative, we first establish convergence to a Gaussian process limit experiment. We then determine a nearly weighted average power maximizing test in this limit experiment, and show how to implement a small sample analogue in GMM time series models. © 2014 Elsevier B.V. All rights reserved.

Keywords: Generic health relevance; Structural breaks; Time varying parameters; Convergence of experiments; Asymptotic efficiency of tests; Statistics; Applied Economics; Econometrics (search for similar items in EconPapers)
Date: 2014-06-01
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Citations: View citations in EconPapers (14)

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Journal Article: Pre and post break parameter inference (2014)
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