This paper addresses the issue on estimating semiparametric time series models specified by their conditional mean and conditional variance. We stress the importance of using joint restrictions on the mean and variance. This leads to take into account the covariance between the mean and the variance and the variance of the variance, that is the skewness and kurtosis. We establish the direct links between the usual parametric estimation methods, namely the QMLE, the GMM and the M-estimation. The usual univariate QMLE is, under non-normality, less efficient than the optimal GMM estimator. However, the bivariate QMLE based on the dependent variable and its square is as efficient as the optimal GMM one. A Monte Carlo analysis confirms the relevance of our approach, in particular the importance of skewness.
Cet article s'intéresse à l'estimation des modèles semiparamétriques de séries temporelles définis par leur moyenne et variance conditionnelles. Nous mettons en exergue l'importance de l'utilisation jointe des restrictions sur la moyenne et la variance. Ceci amène à tenir compte de la covariance entre la moyenne et la variance ainsi que de la variance de la variance, autrement dit la skewness et la kurtosis. Nous établissons les liens directs entre les méthodes paramétriques usuelles d'estimation, à savoir l'EPMV (Estimateur du Pseudo Maximum de Vraisemblance), les GMM et les M-estimateurs. L'EPMV usuel est, dans le cas de la non-normalité, moins efficace que l'estimateur GMM optimal. Néanmoins, l'EPMV bivarié basé sur le vecteur composé de la variable dépendante et de son carré est aussi efficace que l'estimateur GMM optimal. Une analyse Monte Carlo confirme la pertinence de notre approche, en particulier l'importance de la skewness.
Download Info
To download:
If you experience problems downloading a file, check if you have the
proper application to
view it first. Information about this may be contained
in the File-Format links below. 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.
References listed on IDEAS 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.:
Hansen, Bruce E, 1994.
"Autoregressive Conditional Density Estimation,"
International Economic Review,
Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 35(3), pages 705-30, August.
[Downloadable!] (restricted)
Other versions:
Did you know? You can import bibliographic info in various formats into you bibliographic tool, or just into your word processor. See under "publisher info" on each abstract page.