Finite sample performance of a long run variance estimator based on exactly (almost) unbiased autocovariance estimators

DOI10.1016/j.econlet.2018.01.023zbMath1401.62179OpenAlexW2788550222MaRDI QIDQ1787421

Jingjing Yang, Timothy J. Vogelsang

Publication date: 5 October 2018

Published in: Economics Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.econlet.2018.01.023

zbMATH Keywords

hypothesis testingbias correctionfixed-\(b\) asymptoticsHAC estimatorlong run varianceParzen bias

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10)

Related Items (3)

Correcting the bias of the sample cross‐covariance estimator ⋮ Nearly unbiased estimation of sample skewness ⋮ A simple nearly unbiased estimator of cross‐covariances

Cites Work

• Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation
• Exactly/Nearly Unbiased Estimation of Autocovariances of a Univariate Time Series With Unknown Mean
• On Consistent Estimates of the Spectrum of a Stationary Time Series
• A NEW ASYMPTOTIC THEORY FOR HETEROSKEDASTICITY-AUTOCORRELATION ROBUST TESTS
• Fixed-b asymptotic approximation of the sampling behaviour of nonparametric spectral density estimators
• A Simple, Positive Semi-Definite, Heteroskedasticity and Autocorrelation Consistent Covariance Matrix
• Simple Robust Testing of Regression Hypotheses
• HETEROSKEDASTICITY-AUTOCORRELATION ROBUST TESTING USING BANDWIDTH EQUAL TO SAMPLE SIZE
• ASYMPTOTICALLY UNBIASED ESTIMATION OF AUTOCOVARIANCES AND AUTOCORRELATIONS WITH LONG PANEL DATA
• Optimal Bandwidth Selection in Heteroskedasticity–Autocorrelation Robust Testing

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