In this paper we examine the issue of detecting explosive behaviour in economic and fi nancial time series when an explosive episode is both ongoing at the end of the sample, and of fi nite length. We propose a testing strategy based on the sub-sampling method of Andrews (2003), in which a suitable test statistic is calculated on a fi nite number of end-of-sample observations, with a critical value obtained using sub-sample test statistics calculated on the remaining observations. This approach also has the practical advantage that, by virtue of how the critical values are obtained, it can deliver tests which are robust to, among other things, conditional heteroskedasticity and serial correlation in the driving shocks. We alsoexplore modi fications of the raw statistics to account for unconditional heteroskedasticity using studentisation and a White-type correction. We evaluate the finite sample size and power properties of our proposed procedures, and fi nd that they offer promising levels of power, suggesting the possibility for earlier detection of end-of-sample bubble episodes compared to existing procedures.
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Sam Astill, David Harvey, Stephen Leybourne and Robert Taylor
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School of EconomicsUniversity of Nottingham University Park Nottingham, NG7 2RD
lorenzo.trapani@nottingham.ac.uk