Template-Type: ReDIF-Paper 1.0
Series: Tinbergen Institute Discussion Papers
Creation-Date: 2014-03-04
Revision-Date: 2017-10-23
Number: 14-029/III
Author-Name: Francisco Blasques
Author-Workplace-Name: VU University Amsterdam
Author-Name: Siem Jan Koopman
Author-Workplace-Name: VU University Amsterdam
Author-Name: Andre Lucas
Author-Workplace-Name: VU University Amsterdam
Title: Maximum Likelihood Estimation for Score-Driven Models
Abstract: We establish the strong consistency and asymptotic normality of the maximum likelihood estimator for time-varying parameter models driven by the score of the predictive likelihood function. We formulate primitive conditions for global identification, invertibility, strong consistency, and asymptotic normality under both correct specification and mis-specification of the model. A detailed illustration is provided for a conditional volatility model with disturbances from the Student's t distribution.
Classification-JEL: C13, C22, C12
Keywords: score-driven models, time-varying parameters, Markov processes, stationarity, invertibility, consistency, asymptotic normality
File-Url: https://papers.tinbergen.nl/14029.pdf
File-Format: application/pdf
File-Size: 767933 bytes
Handle: RePEc:tin:wpaper:20140029