Estimation of mis-specified long memory models
AbstractWe study the asymptotic behaviour of frequency domain maximum likelihood estimators of mis-specified models of long memory Gaussian series. We show that even if the long memory structure of the time series is correctly specified, mis-specification of the short memory dynamics may result in estimators of both long- and short-memory parameters that are slower than ãn consistent for the pseudo-true parameter values, which in general differ from the true values. The conditions under which this happens are provided and the asymptotic distribution of the estimators is shown to be non-Gaussian. Conditions under which estimators of the parameters of the mis-specified model have the standard ãn consistency for the pseudo-true values and are asymptotically normal are also provided.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by EconWPA in its series Econometrics with number 0501004.
Length: 24 pages
Date of creation: 11 Jan 2005
Date of revision:
Note: Type of Document - pdf; pages: 24
Contact details of provider:
Web page: http://184.108.40.206
long memory; model mis-specification;
Other versions of this item:
- 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 &bull Diffusion Processes
This paper has been announced in the following NEP Reports:
- NEP-ALL-2005-01-16 (All new papers)
- NEP-ECM-2005-01-16 (Econometrics)
- NEP-ETS-2005-01-16 (Econometric Time Series)
- NEP-FIN-2005-01-16 (Finance)
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.:
- repec:cup:etheor:v:12:y:1996:i:4:p:657-81 is not listed on IDEAS
- Gourieroux, C. & Monfort, A. & Renault, E., 1992.
92.279, Toulouse - GREMAQ.
- Gourieroux Christian & Monfort Alain & Trognon A, 1982.
"Pseudo maximum lilelihood methods : applications to poisson models,"
CEPREMAP Working Papers (Couverture Orange)
- Gourieroux, Christian & Monfort, Alain & Trognon, Alain, 1984. "Pseudo Maximum Likelihood Methods: Applications to Poisson Models," Econometrica, Econometric Society, vol. 52(3), pages 701-20, May.
- Chen, Willa W. & Deo, Rohit S., 2004. "A Generalized Portmanteau Goodness-Of-Fit Test For Time Series Models," Econometric Theory, Cambridge University Press, vol. 20(02), pages 382-416, April.
- Gourieroux, Christian & Monfort, Alain & Trognon, Alain, 1984.
"Pseudo Maximum Likelihood Methods: Theory,"
Econometric Society, vol. 52(3), pages 681-700, May.
- Gallant, A. Ronald & Tauchen, George, 1996.
"Which Moments to Match?,"
Cambridge University Press, vol. 12(04), pages 657-681, October.
- White, Halbert, 1982. "Maximum Likelihood Estimation of Misspecified Models," Econometrica, Econometric Society, vol. 50(1), pages 1-25, January.
- Rohit Deo & Clifford Hurvich & Yi Lu, 2005.
"Forecasting Realized Volatility Using a Long Memory Stochastic Volatility Model: Estimation, Prediction and Seasonal Adjustment,"
- Deo, Rohit & Hurvich, Clifford & Lu, Yi, 2006. "Forecasting realized volatility using a long-memory stochastic volatility model: estimation, prediction and seasonal adjustment," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 29-58.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (EconWPA).
If references are entirely missing, you can add them using this form.