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Testing parameter stability : a wild bootstrap approach

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  • Karl Whelan

Abstract

Unknown-breakpoint tests for possible structural change have become standard in recent years, with the most popular being the so-called Sup-F tests, whose asymptotic distribution was derived by Andrews (1993). We highlight two problems that lead to poor performance when testing for structural breaks in dynamic time series models using the Andrews critical values: High persistence of explanatory variables and heteroskedasticity. We propose a so-called "wild bootstrap" approach to generating critical values for the Sup-F statistic and report that this approach performs well across a wide variety of possible data generating processes, including those with large coeffients on lagged dependent variables and heteroskedasticity.

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  • Karl Whelan, 2005. "Testing parameter stability : a wild bootstrap approach," Open Access publications 10197/225, School of Economics, University College Dublin.
    • Handle: RePEc:ucn:oapubs:10197/225
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    Cited by:

    1. Peter Tillmann, 2010. "The changing nature of inflation persistence in Switzerland," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 37(4), pages 445-453, November.
    2. Gerlach, Stefan & Tillmann, Peter, 2012. "Inflation targeting and inflation persistence in Asia–Pacific," Journal of Asian Economics, Elsevier, vol. 23(4), pages 360-373.
    3. Peter Tillmann, 2013. "Inflation Targeting and Regional Inflation Persistence: Evidence from Korea," Pacific Economic Review, Wiley Blackwell, vol. 18(2), pages 147-161, May.
    4. Lee, Taewook & Baek, Changryong, 2020. "Block wild bootstrap-based CUSUM tests robust to high persistence and misspecification," Computational Statistics & Data Analysis, Elsevier, vol. 150(C).

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