A Classification of Observation-Driven State-Space Count Models for Panel Data

Autor:	Ahn, Jae Youn, Jeong, Himchan, Lu, Yang, Wüthrich, Mario V.
Rok vydání:	2023
Předmět:	Statistics - Methodology Mathematics - Statistics Theory Statistics - Applications 62M10 G.3
Druh dokumentu:	Working Paper
Popis:	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. Comment: 28 pages, 2 figures
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2308.16058 Zobrazit plný text záznamu View this record from Arxiv