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Critical Values for the Cusumsq Statistic in Medium and Large Sized Samples

Listed author(s):
  • Edgerton, David
  • Wells, Curt

Data series containing more than 200 observations are common in financial economics. The usefulness of the cusumsq test in such medium-sized samples has been hampered by the lack of tabulated confidence bounds and by the inaccuracy of asymptotic approximations. In this paper, the authors extend Durbin's table to encompass all practical sample sizes. They have empirically calculated asymptotic limits, which prove to be extremely accurate for sample sizes greater than sixty. A convenient algorithm for calculating P-values, which is useful even in small samples, is also referred to. Copyright 1994 by Blackwell Publishing Ltd

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Article provided by Department of Economics, University of Oxford in its journal Oxford Bulletin of Economics & Statistics.

Volume (Year): 56 (1994)
Issue (Month): 3 (August)
Pages: 355-365

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Handle: RePEc:bla:obuest:v:56:y:1994:i:3:p:355-65
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References listed on IDEAS
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  1. Zeileis, Achim & Leisch, Friedrich & Hornik, Kurt & Kleiber, Christian, 2001. "Strucchange: An R package for testing for structural change in linear regression models," Technical Reports 2001,26, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
  2. Kramer, Walter & Schotman, Peter, 1992. "Range vs. maximum in the OLS-based version of the CUSUM test," Economics Letters, Elsevier, vol. 40(4), pages 379-381, December.
  3. Ploberger, Werner & Kramer, Walter, 1992. "The CUSUM Test with OLS Residuals," Econometrica, Econometric Society, vol. 60(2), pages 271-285, March.
  4. Kramer, Walter & Ploberger, Werner & Alt, Raimund, 1988. "Testing for Structural Change in Dynamic Models," Econometrica, Econometric Society, vol. 56(6), pages 1355-1369, November.
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