Simulation Based Inference In Moving Average Models
AbstractWe examine several autoregressive-based estimators for the parameters of a moving average process, including the estimators initially proposed by Galbraith and Zinde-Walsh  and Gouriéroux, Monfort and Renault . We also propose over-identified asymptotic-least-squares based variants of the former, and extensions of the latter based on Gallant and Tauchen's  simulated method of moments. The relative performance of these estimators is assessed, with emphasis on the near-uninvertibility region. We find that, although no formal local-to-one arguments are taken into consideration, the Wald-type indirect inference method performs best at the boundary, with practically just one calibration.
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Bibliographic InfoArticle provided by ENSAE in its journal Annals of Economics and Statistics.
Volume (Year): (2003)
Issue (Month): 69 ()
Other versions of this item:
- Ghysels, E. & Khalaf, L. & Vodounou, C., 1995. "Simulation Based Inference in Moving Average Models," Cahiers de recherche 9513, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
- Eric Ghysels & Lynda Khalaf & Cosme Vodounou, 1994. "Simulation Based Inference in Moving Average Models," CIRANO Working Papers 94s-11, CIRANO.
- Ghysels, E. & Khalaf, L. & Vodounou, C., 1995. "Simulation Based Inference in Moving Average Models," Cahiers de recherche 9513, Universite de Montreal, Departement de sciences economiques.
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
- C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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