We propose generalised DWH specification tests which simultaneously compare three or more likelihood-based estimators of conditional mean and variance parameters in multivariate conditionally heteroskedastic dynamic regression models. Our tests are useful for GARCH models and in many empirically relevant macro and finance applications involving VARs and multivariate regressions. To design powerful and reliable tests, we determine the rank deficiencies of the differences between the estimators' asymptotic covariance matrices under the null of correct specification, and take into account that some parameters remain consistently estimated under the alternative of distributional misspecification. Finally, we provide finite sample results through Monte Carlo simulations.
Specification tests for non-Gaussian maximum likelihood estimators, Centre for Economic Policy Research DP12934, ISSN: 0265-8003 / Gabriele Fiorentini; Enrique Sentana. - ELETTRONICO. - (2018), pp. 1-70.
Specification tests for non-Gaussian maximum likelihood estimators, Centre for Economic Policy Research DP12934, ISSN: 0265-8003
Gabriele Fiorentini;
2018
Abstract
We propose generalised DWH specification tests which simultaneously compare three or more likelihood-based estimators of conditional mean and variance parameters in multivariate conditionally heteroskedastic dynamic regression models. Our tests are useful for GARCH models and in many empirically relevant macro and finance applications involving VARs and multivariate regressions. To design powerful and reliable tests, we determine the rank deficiencies of the differences between the estimators' asymptotic covariance matrices under the null of correct specification, and take into account that some parameters remain consistently estimated under the alternative of distributional misspecification. Finally, we provide finite sample results through Monte Carlo simulations.File | Dimensione | Formato | |
---|---|---|---|
CEPR-DP12934.pdf
accesso aperto
Descrizione: Articolo
Tipologia:
Pdf editoriale (Version of record)
Licenza:
Tutti i diritti riservati
Dimensione
557.41 kB
Formato
Adobe PDF
|
557.41 kB | Adobe PDF |
I documenti in FLORE sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.