In this paper, we propose a simple bias–reduced log–periodogram regression estimator, , of the long–memory parameter, , that eliminates the first– and higher–order biases of the Geweke and Porter–Hudak (1983) (GPH) estimator. The bias–reduced estimator is the same as the GPH estimator except that one includes frequencies to the power 2 for =1,…,, for some positive integer , as additional regressors in the pseudo–regression model that yields the GPH estimator. The reduction in bias is obtained using assumptions on the spectrum only in a neighborhood of the zero frequency.
MLA
Andrews, Donald W. K., and Patrik Guggenberger. “A Bias–Reduced Log–Periodogram Regression Estimator for the Long–Memory Parameter.” Econometrica, vol. 71, .no 2, Econometric Society, 2003, pp. 675-712, https://doi.org/10.1111/1468-0262.00420
Chicago
Andrews, Donald W. K., and Patrik Guggenberger. “A Bias–Reduced Log–Periodogram Regression Estimator for the Long–Memory Parameter.” Econometrica, 71, .no 2, (Econometric Society: 2003), 675-712. https://doi.org/10.1111/1468-0262.00420
APA
Andrews, D. W. K., & Guggenberger, P. (2003). A Bias–Reduced Log–Periodogram Regression Estimator for the Long–Memory Parameter. Econometrica, 71(2), 675-712. https://doi.org/10.1111/1468-0262.00420
We are deeply saddened by the passing of Kate Ho, the John L. Weinberg Professor of Economics and Business Policy at Princeton University and a Fellow of the Econometric Society. Kate was a brilliant IO economist and scholar whose impact on the profession will resonate for many years to come.
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