Lag length selection for unit root tests in the presence of nonstationary volatility

G. Cavaliere, P.C.B. Phillips, S. Smeekes, A.M.R. Taylor

Research output: Contribution to journalArticleAcademicpeer-review

5 Citations (Scopus)

Abstract

A number of recent papers have focused on the problem of testing for a unit root in the case where the driving shocks may be unconditionally heteroskedastic. These papers have, however, taken the lag length in the unit root test regression to be a deterministic function of the sample size, rather than data-determined, the latter being standard empirical practice. We investigate the finite sample impact of unconditional heteroskedasticity on conventional data-dependent lag selection methods in augmented Dickey-Fuller type regressions and propose new lag selection criteria which allow for unconditional heteroskedasticity. Standard lag selection methods are shown to have a tendency to over-fit the lag order under heteroskedasticity, resulting in significant power losses in the (wild bootstrap implementation of the) augmented Dickey-Fuller tests under the alternative. The proposed new lag selection criteria are shown to avoid this problem yet deliver unit root tests with almost identical finite sample properties as the corresponding tests based on conventional lag selection when the shocks are homoskedastic.
Original languageEnglish
Pages (from-to)512-536
Number of pages25
JournalEconometric Reviews
Volume34
Issue number4
Early online date7 Nov 2014
DOIs
Publication statusPublished - 21 Apr 2015

Keywords

  • C15
  • C22
  • Nonstationary volatility
  • Lag selection
  • Information criteria
  • Wild bootstrap
  • Unit root test
  • TIME-SERIES MODELS
  • AUTOREGRESSIVE MODELS
  • INITIAL CONDITION

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