Alessandro Casini, Pierre Perron
arXiv 3 Mar 2021 · Econometrics · publishedJournal of Econometrics (2024) · 7 citations (OpenAlex)
arXiv:2103.02235 · PDF · DOI · OpenAlex · Extracted main text
We introduce a nonparametric nonlinear VAR prewhitened long-run variance (LRV) estimator for the construction of standard errors robust to autocorrelation and heteroskedasticity that can be used for hypothesis testing in a variety of contexts including the linear regression model. Existing methods either are theoretically valid only under stationarity and have poor finite-sample properties under nonstationarity (i.e., fixed-b methods), or are theoretically valid under the null hypothesis but lead to tests that are not consistent under nonstationary alternative hypothesis (i.e., both fixed-b and traditional HAC estimators). The proposed estimator accounts explicitly for nonstationarity, unlike previous prewhitened procedures which are known to be unreliable, and leads to tests with accurate null rejection rates and good monotonic power. We also establish MSE bounds for LRV estimation that are sharper than previously established and use them to determine the data-dependent bandwidths.
appendix boundary found by appendix_command · 47% of the source is main text. Read the extracted text to check this.
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 | Newey, W.K., West, K.D (1987) A simple positive semidefinite, heteroskedastic and autocorrelation consistent covariance matrix | 1.000 | 16 | 3 | 100% |
| 2 | Andrews, D.W.K (1991) Heteroskedasticity and autocorrelation consistent covariance matrix estimation | 0.976 | 28 | 7 | 93% |
| 3 | Andrews, D.W.K., Monahan, J.C (1992) An improved heteroskedasticity and autocorrelation consistent covariance matrix estimator | 0.969 | 11 | 5 | 91% |
| 4 | Giacomini, R., Rossi, B (2009) Detecting and predicting forecast breakdowns | 0.874 | 5 | 2 | 100% |
| 5 | Kiefer, N.M., Vogelsang, T.J., Bunzel, H (2000) Simple robust testing of regression hypotheses | 0.843 | 3 | 3 | 100% |
| 6 | Casini, A (2023) Theory of evolutionary spectra for heteroskedasticity and autocorrelation robust inference in possibly misspecified and nonstati… self | 0.807 | 40 | 7 | 52% |
| 7 | Chan, K.W (2022) Mean-structure and autocorrelation consistent covariance matrix estimation | 0.737 | 3 | 2 | 100% |
| 8 | Lazarus, E., Lewis, D.J., Stock, J.H., Watson, M.W (2018) HAR inference: recommendations for practice | 0.737 | 3 | 2 | 100% |
| 9 | Newey, W.K., West, K.D (1994) Automatic lag selection in covariance matrix estimation | 0.737 | 3 | 2 | 100% |
| 10 | Casini, A., Deng, T., Perron, P (2024) Theory of low frequency contamination from nonstationarity and misspecification: consequences for HAR inference self | 0.721 | 8 | 3 | 38% |
Showing the top 10 of 67 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | Theory of Low Frequency Contamination from Nonstationarity and Misspecification: Consequences for HAR Inference | 0.693 | 5 | 1 |
| 2 | On changepoint detection in functional data using empirical energy distance | 0.644 | 2 | 2 |