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Blockwise empirical entropy tests for time series regressions

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Publication details

JournalJournal of Time Series Analysis
DatePublished - Mar 2005
Issue number2
Volume26
Number of pages25
Pages (from-to)185-210
Original languageEnglish

Abstract

This paper shows how the empirical entropy (also known as exponential likelihood or non-parametric tilting) method can be used to test general parametric hypothesis in time series regressions. To capture the weak dependence of the observations, the paper uses blocking techniques which are also used in the bootstrap literature on time series. Monte Carlo evidence suggests that the proposed test statistics have better finite-sample properties than conventional test statistics such as the Wald statistic.

    Research areas

  • alpha-mixing, blocking techniques, empirical likelihood, mixed-form hypothesis, Wald statistic, GENERALIZED-METHOD, LIKELIHOOD, INFORMATION, HYPOTHESIS, ESTIMATORS, BOOTSTRAP, MODELS, HETEROSKEDASTICITY, VARIANCE

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