Federico Belotti, Alessandro Casini, Leopoldo Catania, Stefano Grassi, Pierre Perron
arXiv 26 Feb 2021 · Econometrics · publishedEconometric Reviews (2023) · 4 citations (OpenAlex)
arXiv:2103.00060 · PDF · DOI · OpenAlex · Extracted main text
We consider the derivation of data-dependent simultaneous bandwidths for double kernel heteroskedasticity and autocorrelation consistent (DK-HAC) estimators. In addition to the usual smoothing over lagged autocovariances for classical HAC estimators, the DK-HAC estimator also applies smoothing over the time direction. We obtain the optimal bandwidths that jointly minimize the global asymptotic MSE criterion and discuss the trade-off between bias and variance with respect to smoothing over lagged autocovariances and over time. Unlike the MSE results of Andrews (1991), we establish how nonstationarity affects the bias-variance trade-o?. We use the plug-in approach to construct data-dependent bandwidths for the DK-HAC estimators and compare them with the DK-HAC estimators from Casini (2021) that use data-dependent bandwidths obtained from a sequential MSE criterion. The former performs better in terms of size control, especially with stationary and close to stationary data. Finally, we consider long-run variance estimation under the assumption that the series is a function of a nonparametric estimator rather than of a semiparametric estimator that enjoys the usual T^(1/2) rate of convergence. Thus, we also establish the validity of consistent long-run variance estimation in nonparametric parameter estimation settings.
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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 | Casini, A., Deng, T., Perron, P (2021) Theory of low frequency contamination from unaccounted nonstationarity: consequences for HAR inference self | 1.000 | 6 | 4 | 100% |
| 2 | Newey, W.K., West, K.D (1987) A simple positive semidefinite, heteroskedastic and autocorrelation consistent covariance matrix | 1.000 | 5 | 4 | 100% |
| 3 | Andrews, D.W.K (1991) Heteroskedasticity and autocorrelation consistent covariance matrix estimation | 0.894 | 28 | 8 | 71% |
| 4 | Kiefer, N., Vogelsang, T.J., Bunzel, H (2000) Simple robust testing of regression hypotheses | 0.843 | 3 | 3 | 100% |
| 5 | Lazarus, E., Lewis, D.J., Stock, J.H (2020) The size-power tradeoff in HAR inference | 0.843 | 3 | 3 | 100% |
| 6 | Newey, W.K., West, K.D (1994) Automatic lag selection in covariance matrix estimation | 0.843 | 3 | 3 | 100% |
| 7 | Casini, A (2021) Theory of evolutionary spectra for heteroskedasticity and autocorrelation robust inference in possibly misspecified and nonstati… self | 0.815 | 37 | 7 | 54% |
| 8 | Casini, A., Perron, P (2021) b self | 0.769 | 11 | 4 | 45% |
| 9 | Giacomini, R., Rossi, B (2009) Detecting and predicting forecast breakdowns | 0.644 | 4 | 1 | 100% |
| 10 | Cai, Z (2007) Trending time-varying coefficient time series models with serially correlated errors | 0.644 | 2 | 2 | 100% |
Showing the top 10 of 63 scored citations.