Zhihao Xu, Clifford M. Hurvich
arXiv 13 Aug 2021 · Econometrics · publishedEconometrics and Statistics (2023)
arXiv:2108.06093 · PDF · DOI · OpenAlex · Extracted main text
A unified frequency domain cross-validation (FDCV) method is proposed to obtain a heteroskedasticity and autocorrelation consistent (HAC) standard error. This method enables model/tuning parameter selection across both parametric and nonparametric spectral estimators simultaneously. The candidate class for this approach consists of restricted maximum likelihood-based (REML) autoregressive spectral estimators and lag-weights estimators with the Parzen kernel. Additionally, an efficient technique for computing the REML estimators of autoregressive models is provided. Through simulations, the reliability of the FDCV method is demonstrated, comparing favorably with popular HAC estimators such as Andrews-Monahan and Newey-West.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Andrews, D. W (1991) Heteroskedasticity and autocorrelation consistent covariance matrix estimation | 1.000 | 10 | 4 | 100% |
| 2 | Andrews, D. W. and J. C. Monahan (1992) An improved heteroskedasticity and autocorrelation consistent covariance matrix estimator | 1.000 | 10 | 4 | 100% |
| 3 | Hurvich, C. M (1985) Data-driven choice of a spectrum estimate: extending the applicability of cross-validation methods self | 1.000 | 8 | 3 | 100% |
| 4 | Newey, W. K. and K. D. West (1994) Automatic lag selection in covariance matrix estimation | 1.000 | 7 | 4 | 100% |
| 5 | Beltrao, K. and P. Bloomfield (1987) Determining the bandwidth of a kernel spectrum estimate | 0.928 | 4 | 3 | 100% |
| 6 | Den Haan, W. J. and A. Levin (1997) A practitioner's guide to robust covariance matrix estimation | 0.874 | 6 | 2 | 100% |
| 7 | Newey, W. K. and K. D. West (1987) A simple, positive semi-definite, heteroskedasticity and autocorrelation consistent covariance matrix | 0.843 | 3 | 3 | 100% |
| 8 | Wahba, G. and S. Wold (1975) Periodic splines for spectral density estimation: The use of cross validation for determining the degree of smoothing | 0.737 | 3 | 2 | 100% |
| 9 | Cheang, W.-K. and G. C. Reinsel (2000) Bias reduction of autoregressive estimates in time series regression model through restricted maximum likelihood | 0.644 | 2 | 2 | 100% |
| 10 | Chen, W. W. and R. S. Deo (2012) The restricted likelihood ratio test for autoregressive processes | 0.644 | 2 | 2 | 100% |
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