INAR approximation of bivariate linear birth and death process

Zezhun Chen Chen, Angelos Dassios and George Tzougas

LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library

Abstract: In this paper, we propose a new type of univariate and bivariate Integer-valued autoregressive model of order one (INAR(1)) to approximate univariate and bivariate linear birth and death process with constant rates. Under a specific parametric setting, the dynamic of transition probabilities and probability generating function of INAR(1) will converge to that of birth and death process as the length of subintervals goes to 0. Due to the simplicity of Markov structure, maximum likelihood estimation is feasible for INAR(1) model, which is not the case for bivariate and multivariate birth and death process. This means that the statistical inference of bivariate birth and death process can be achieved via the maximum likelihood estimation of a bivariate INAR(1) model.

JEL-codes: C1 (search for similar items in EconPapers)
Pages: 39 pages
Date: 2023-10-01
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Published in Journal of Applied Statistics, 1, October, 2023, 26(3), pp. 459 - 497. ISSN: 0266-4763

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Persistent link: https://EconPapers.repec.org/RePEc:ehl:lserod:118769

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