Necessary and sufficient conditions for the identifiability of observation-driven models
Statistics Theory
2020-05-13 v2 Statistics Theory
Abstract
In this contribution we are interested in proving that a given observation-driven model is identifiable. In the case of a GARCH(p, q) model, a simple sufficient condition has been established in [1] for showing the consistency of the quasi-maximum likelihood estimator. It turns out that this condition applies for a much larger class of observation-driven models, that we call the class of linearly observation-driven models. This class includes standard integer valued observation-driven time series, such as the log-linear Poisson GARCH or the NBIN-GARCH models.
Keywords
Cite
@article{arxiv.1904.02893,
title = {Necessary and sufficient conditions for the identifiability of observation-driven models},
author = {François Roueff and Randal Douc and Ois Roueff and Tepmony Sim},
journal= {arXiv preprint arXiv:1904.02893},
year = {2020}
}