Multivariate INAR(1) Regression Models Based on the Sarmanov Distribution

Lluís Bermúdez and Dimitris Karlis
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Lluís Bermúdez: Departament de Matemàtica Econòmica, Financera i Actuarial, Riskcenter-IREA, University of Barcelona, Av. Diagonal, 690, 08034 Barcelona, Spain
Dimitris Karlis: Department of Statistics, Athens University of Economics and Business, 2, Troias, Kimolou & Spetson Str., 113 62 Athens, Greece

Mathematics, 2021, vol. 9, issue 5, 1-13

Abstract: A multivariate INAR(1) regression model based on the Sarmanov distribution is proposed for modelling claim counts from an automobile insurance contract with different types of coverage. The correlation between claims from different coverage types is considered jointly with the serial correlation between the observations of the same policyholder observed over time. Several models based on the multivariate Sarmanov distribution are analyzed. The new models offer some advantages since they have all the advantages of the MINAR(1) regression model but allow for a more flexible dependence structure by using the Sarmanov distribution. Driven by a real panel data set, these models are considered and fitted to the data to discuss their goodness of fit and computational efficiency.

Keywords: multivariate longitudinal data; time dependence; cross dependence; motor insurance (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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