Richard T. Baillie, Francis X. Diebold, George Kapetanios, Kun Ho Kim, Aaron Mora
arXiv 8 Mar 2022 · Econometrics · publishedEconometrics Journal (2024) · 7 citations (OpenAlex)
arXiv:2203.04080 · PDF · DOI · OpenAlex · Extracted main text
Least squares regression with heteroskedasticity consistent standard errors ("OLS-HC regression") has proved very useful in cross section environments. However, several major difficulties, which are generally overlooked, must be confronted when transferring the HC technology to time series environments via heteroskedasticity and autocorrelation consistent standard errors ("OLS-HAC regression"). First, in plausible time-series environments, OLS parameter estimates can be inconsistent, so that OLS-HAC inference fails even asymptotically. Second, most economic time series have autocorrelation, which renders OLS parameter estimates inefficient. Third, autocorrelation similarly renders conditional predictions based on OLS parameter estimates inefficient. Finally, the structure of popular HAC covariance matrix estimators is ill-suited for capturing the autoregressive autocorrelation typically present in economic time series, which produces large size distortions and reduced power in HAC-based hypothesis testing, in all but the largest samples. We show that all four problems are largely avoided by the use of a simple and easily-implemented dynamic regression procedure, which we call DURBIN. We demonstrate the advantages of DURBIN with detailed simulations covering a range of practical issues.
appendix boundary found by appendix_command · 84% 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 | Durbin (1970) Testing for Serial Correlation in Least-Squares Regression when some of the Regressors are Lagged Dependent Variables, Econometr… | 0.928 | 4 | 3 | 100% |
| 2 | Hansen and Hodrick (1980) Forward Exchange Rates as Optimal Predictors of Future Spot Rates: An Econometric Analysis, Journal of Political Economy\/, 88,… | 0.928 | 4 | 3 | 100% |
| 3 | Lazarus, Lewis, Stock, and Watson (2018) HAR Inference: Recommendations For Practice, Journal of Business and Economic Statistics\/, 36, 541–559 | 0.811 | 4 | 2 | 100% |
| 4 | Andrews (1991) Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation, Econometrica\/, 817–858 | 0.737 | 3 | 2 | 100% |
| 5 | Perron and González-Coya (2022) Feasible GLS for Time Series Regression, Manuscript, Department of Economics, Boston University | 0.737 | 3 | 2 | 100% |
| 6 | Andrews and Monahan (1992) An Improved Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimator, Econometrica\/, 60, 953–966 | 0.644 | 2 | 2 | 100% |
| 7 | Hannan and Deistler (1988) The Statistical Theory Of Linear Systems\/, Wiley | 0.644 | 2 | 2 | 100% |
| 8 | Kiefer and Vogelsang (2002) Heteroskedasticity-Autocorrelation Robust Standard Errors using the Bartlett Kernel without Truncation, Econometrica\/, 70, 2093… | 0.644 | 2 | 2 | 100% |
| 9 | Müller (2014) HAC Corrections for Strongly Autocorrelated Time Series, Journal of Business and Economic Statistics\/, 32, 311–322 | 0.644 | 2 | 2 | 100% |
| 10 | Newey and West (1987) A Simple, Positive Semi-Definite, Heteroskedasticity and Autocorrelation Consistent Covariance Matrix, Econometrica\/, 55, 703–708 | 0.644 | 2 | 2 | 100% |
Showing the top 10 of 28 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.