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Testing parameter stability : a wild bootstrap approach
Author(s)
Date Issued
2005-12
Date Available
2008-06-11T15:56:51Z
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.
Type of Material
Technical Report
Publisher
Central Bank of Ireland
Series
Central Bank of Ireland Research Technical Paper
8/RT/05
Copyright (Published Version)
2005 Copyright Central Bank of Ireland
Subject – LCSH
Bootstrap (Statistics)
Asymptotic distribution (Probability theory)
Language
English
Status of Item
Not peer reviewed
This item is made available under a Creative Commons License
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