Mixed INAR(1) Poisson regression models: Analyzing heterogeneity and serial dependencies in longitudinal count data

Ulf Böckenholt

doi:10.1016/S0304-4076(98)00069-4

Mixed INAR(1) Poisson regression models: Analyzing heterogeneity and serial dependencies in longitudinal count data

Ulf Böckenholt^*

^*Corresponding author for this work

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36 Scopus citations

Abstract

This paper presents finite mixture versions of integer-valued autoregressive (INAR) Poisson regression models for investigating regularity and predictability of purchase behavior over time. The approach facilitates the analysis of heterogeneity and serial correlation effects as well as conditional and marginal analyses of the effects of covariates. An application to scanner panel data of detergents yields substantive insights into sources of autodependencies in individual category purchases.

Original language	English (US)
Pages (from-to)	317-338
Number of pages	22
Journal	Journal of Econometrics
Volume	89
Issue number	1-2
DOIs	https://doi.org/10.1016/S0304-4076(98)00069-4
State	Published - Nov 26 1998

Keywords

Autoregression
Binomial thinning
Count data
Finite mixture

ASJC Scopus subject areas

Economics and Econometrics

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title = "Mixed INAR(1) Poisson regression models: Analyzing heterogeneity and serial dependencies in longitudinal count data",

abstract = "This paper presents finite mixture versions of integer-valued autoregressive (INAR) Poisson regression models for investigating regularity and predictability of purchase behavior over time. The approach facilitates the analysis of heterogeneity and serial correlation effects as well as conditional and marginal analyses of the effects of covariates. An application to scanner panel data of detergents yields substantive insights into sources of autodependencies in individual category purchases.",

keywords = "Autoregression, Binomial thinning, Count data, Finite mixture",

author = "Ulf B{\"o}ckenholt",

note = "Funding Information: The author is grateful to Bill Dillon, Eijte Foekens, Peter Leeflang and two anonymous reviewers for helpful comments and suggestions. This research was partially supported by the National Science Foundation grant SBR-9409531. ",

year = "1998",

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AU - Böckenholt, Ulf

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PY - 1998/11/26

Y1 - 1998/11/26

N2 - This paper presents finite mixture versions of integer-valued autoregressive (INAR) Poisson regression models for investigating regularity and predictability of purchase behavior over time. The approach facilitates the analysis of heterogeneity and serial correlation effects as well as conditional and marginal analyses of the effects of covariates. An application to scanner panel data of detergents yields substantive insights into sources of autodependencies in individual category purchases.

AB - This paper presents finite mixture versions of integer-valued autoregressive (INAR) Poisson regression models for investigating regularity and predictability of purchase behavior over time. The approach facilitates the analysis of heterogeneity and serial correlation effects as well as conditional and marginal analyses of the effects of covariates. An application to scanner panel data of detergents yields substantive insights into sources of autodependencies in individual category purchases.

KW - Autoregression

KW - Binomial thinning

KW - Count data

KW - Finite mixture

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