A Unified Frequency Domain Cross-Validatory Approach to HAC Standard Error Estimation
نویسندگان
چکیده
A unified frequency domain cross-validation (FDCV) method is proposed to obtain a heteroskedasticity and autocorrelation consistent (HAC) standard error. This enables model/tuning parameter selection across both parametric nonparametric spectral estimators simultaneously. The candidate class for this approach consists of restricted maximum likelihood-based (REML) autoregressive lag-weights with the Parzen kernel. Additionally, an efficient technique computing REML models provided. Through simulations, reliability FDCV demonstrated, comparing favorably popular HAC such as Andrews-Monahan Newey-West.
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ژورنال
عنوان ژورنال: Econometrics and Statistics
سال: 2023
ISSN: ['2452-3062', '2468-0389']
DOI: https://doi.org/10.1016/j.ecosta.2023.06.006