Finite sample properties of tests based on prewhitened nonparametric covariance estimators

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  • David Preinerstorfer

We analytically investigate size and power properties of a popular family of procedures for testing linear restrictions on the coefficient vector in a linear regression model with temporally dependent errors. The tests considered are autocorrelation-corrected F-type tests based on prewhitened nonparametric covariance estimators that possibly incorporate a data-dependent bandwidth parameter, e.g., estimators as considered in Andrews and Monahan (1992), Newey and West (1994), or Rho and Shao (2013). For design matrices that are generic in a measure theoretic sense we prove that these tests either suffer from extreme size distortions or from strong power deficiencies. Despite this negative result we demonstrate that a simple adjustment procedure based on artificial regressors can often resolve this problem.

Original languageEnglish
JournalElectronic Journal of Statistics
Pages (from-to)2097-2167
Number of pages71
Publication statusPublished - 2017

    Research areas

  • Autocorrelation robustness, prewhitening, size distortion, power deficiency, artificial regressors, AUTOCORRELATION ROBUST-TESTS, MATRIX ESTIMATION, HETEROSKEDASTICITY, SIZE, SELECTION, SERIES, POWER

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