Robust Covariance Matrix Estimation in Time Series: A Review

Masayuki Hirukawa

Econometrics and Statistics, 2023, vol. 27, issue C, 36-61

Abstract: In the analysis of economic, financial and other time series, long-run variance estimators play an important role in estimating model parameters more efficiently and drawing more accurate statistical inference on the parameters. A non-technical review of long-run variance estimation is provided. Both parametric and nonparametric estimators are discussed. Kernel methods are dominant among all estimation procedures, and therefore recent developments in kernel-smoothed estimators and related inference are presented. The information given can help practitioners decide on a suitable long-run variance estimator.

Keywords: Bandwidth; Generalized method of moments; Heteroskedasticity and autocorrelation robust inference; Kernel; Long-run variance; Positive semi-definite (search for similar items in EconPapers)
JEL-codes: C12 C13 C22 C32 (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecosta:v:27:y:2023:i:c:p:36-61

DOI: 10.1016/j.ecosta.2021.12.001

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