Pre and post break parameter inference

Graham Elliott, Ulrich K. Müller

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)141-157
Number of pages17
JournalJournal of Econometrics
Volume180
Issue number2
DOIs
StatePublished - Jun 2014

All Science Journal Classification (ASJC) codes

  • Economics and Econometrics

Keywords

  • Asymptotic efficiency of tests
  • Convergence of experiments
  • Structural breaks
  • Time varying parameters

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