Testing for Structural Breaks in Small Samples

Sergei Antoshin, Andrew Berg () and Marcos Souto

No 2008/075, IMF Working Papers from International Monetary Fund

Abstract: In a recent paper, Bai and Perron (2006) demonstrate that their approach for testing for multiple structural breaks in time series works well in large samples, but they found substantial deviations in both the size and power of their tests in smaller samples. We propose modifying their methodology to deal with small samples by using Monte Carlo simulations to determine sample-specific critical values under the each time the test is run. We draw on the results of our simulations to offer practical suggestions on handling serial correlation, model misspecification, and the use of alternative test statistics for sequential testing. We show that, for most types of data generating processes in samples with as low as 50 observations, our proposed modifications perform substantially better.

Keywords: WP; Prob k; serial correlation; autocorrelation coefficient; sample size (search for similar items in EconPapers)
Pages: 27
Date: 2008-03-01
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Citations: View citations in EconPapers (19)

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