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Testing for Structural Breaks in Small Samples

Author

Listed:
  • Sergei Antoshin
  • Andrew Berg
  • Marcos R Souto

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.

Suggested Citation

  • Sergei Antoshin & Andrew Berg & Marcos R Souto, 2008. "Testing for Structural Breaks in Small Samples," IMF Working Papers 08/75, International Monetary Fund.
  • Handle: RePEc:imf:imfwpa:08/75
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    Cited by:

    1. Belke, Angar & Gros, Daniel & Osowski, Thomas, 2017. "The effectiveness of the Fed’s quantitative easing policy: New evidence based on international interest rate differentials," Journal of International Money and Finance, Elsevier, vol. 73(PB), pages 335-349.
    2. repec:eco:journ2:2017-05-6 is not listed on IDEAS
    3. Chris Papageorgiou & Andrew Berg & Catherine A Pattillo & Nikola Spatafora, 2010. "The End of An Era? the Medium- and Long-Term Effects of the Global Crisison Growth in Low-Income Countries," IMF Working Papers 10/205, International Monetary Fund.
    4. Berg, Andrew & Ostry, Jonathan D. & Zettelmeyer, Jeromin, 2012. "What makes growth sustained?," Journal of Development Economics, Elsevier, vol. 98(2), pages 149-166.

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