GLS Bias Correction for Low Order ARMA models
AbstractWe study the problems of bias correction in the estimation of low order ARMA(p, q) time series models. We introduce a new method to estimate the bias of the parameters of ARMA(p, q) process based on the analytical form of the GLS transformation matrix of Galbraith and Zinde-Walsh (1992). We show that the resulting bias corrected estimator is consistent and asymptotically normal. We also argue that, in the case of an MA(q) model, our method may be considered as an iteration of the analytical indirect inference technique of Galbraith and Zinde-Walsh (1994). The potential of our method is illustrated through a series of Monte Carlo experiments.
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Bibliographic InfoPaper provided by Departement d'Economique de la Faculte d'administration à l'Universite de Sherbrooke in its series Cahiers de recherche with number 07-19.
Length: 34 pages
Date of creation: 2007
Date of revision:
ARMA; bias correction; GLS;
Find related papers by JEL classification:
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
This paper has been announced in the following NEP Reports:
- NEP-ALL-2007-09-30 (All new papers)
- NEP-ECM-2007-09-30 (Econometrics)
- NEP-ETS-2007-09-30 (Econometric Time Series)
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- Patrick Richard, 2009. "Improving the accuracy of the analytical indirect inference estimator for MA models," Economics Bulletin, AccessEcon, vol. 29(4), pages 2795-2802.
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