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Testing for heteroskedasticity and predictive failure in linear regression models

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JournalOxford Bulletin of Economics and Statistics
DatePublished - Jun 2008
Issue number3
Volume70
Number of pages15
Pages (from-to)415-429
Original languageEnglish

Abstract

It is argued that, when researchers wish to carry out a Chow test of the significance of prediction errors, it is necessary to assume homoskedasticity because standard results on heteroskedasticity-robust tests are not available. The effects of heteroskedasticity on the Chow prediction error test are examined. The implementation of tests for heteroskedasticity is discussed, with the case in which the regressors include dummy variables for prediction error tests receiving special attention. Monte Carlo results are reported.

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M1 - 3

    Research areas

  • HETEROSCEDASTICITY, GLEJSER

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