A Classification of Observation-Driven State-Space Count Models for Panel Data
Methodology
2023-08-31 v1 Statistics Theory
Applications
Statistics Theory
Abstract
State-space models are widely used in many applications. In the domain of count data, one such example is the model proposed by Harvey and Fernandes (1989). Unlike many of its parameter-driven alternatives, this model is observation-driven, leading to closed-form expressions for the predictive density. In this paper, we demonstrate the need to extend the model of Harvey and Fernandes (1989) by showing that their model is not variance stationary. Our extension can accommodate for a wide range of variance processes that are either increasing, decreasing, or stationary, while keeping the tractability of the original model. Simulation and numerical studies are included to illustrate the performance of our method.
Keywords
Cite
@article{arxiv.2308.16058,
title = {A Classification of Observation-Driven State-Space Count Models for Panel Data},
author = {Jae Youn Ahn and Himchan Jeong and Yang Lu and Mario V. Wüthrich},
journal= {arXiv preprint arXiv:2308.16058},
year = {2023}
}
Comments
28 pages, 2 figures