Uni-Logo
Sie sind hier: Startseite Seminar Christian Gourieroux

Christian Gourieroux

— abgelegt unter:

Generalized Covariance Estimator

Was
  • FDM-Seminar
Wann 27.01.2023
von 12:00 bis 13:30
Wo HSII (Alberstr.23b)
Termin übernehmen vCal
iCal

Abstract:

We consider a class of semi-parametric dynamic models with iid errors, including the nonlinear mixed causal-noncausal Vector Autoregressive (VAR), Double-Autoregressive (DAR) and stochastic volatility models. To estimate the parameters characterizing the (nonlinear) serial dependence, we introduce a generic Generalized Covariance (GCov) estimator, which minimizes a residual-based multivariate portmanteau statistic. In comparison to the standard methods of moments, the GCov estimator has an interpretable objective function, circumvents the inversion of high-dimensional matrices, and achieves semi-parametric efficiency in one step. We derive the asymptotic properties of the GCov estimator and show its semi-parametric efficiency. We also prove that the associated residual-based portmanteau statistic is asymptotically chi-square distributed. The finite sample performance of the GCov estimator is illustrated in a simulation study. The estimator is then applied to a dynamic model of commodity futures.

Christian Gourieroux & Joann Jasiak (2022) Generalized Covariance Estimator, Journal of Business & Economic Statistics, DOI: 10.1080/07350015.2022.2120486

 

« Mai 2024 »
Mai
MoDiMiDoFrSaSo
12345
6789101112
13141516171819
20212223242526
2728293031
Benutzerspezifische Werkzeuge