Analysis of multinomial counts with joint zero-inflation, with an application to health economics

Alpha Oumar Diallo (1, 2) , Aliou Diop (1) , Jean-François Dupuy (2, 1)

1 UGB - Université Gaston Berger de Saint-Louis Sénégal
2 IRMAR - Institut de Recherche Mathématique de Rennes

Zero-inated regression models for count data are often used in health economics to analyse demand for medical care. Indeed, excess of zeros often aects health-care utilization data. Much of the recent econometric literature on the topic has focused on univariate health-care utilization measures, such as the number of doctor visits. However, health service utilization is usually measured by a number of dierent counts (e.g., numbers of visits to dierent health-care providers). In this case, zero-ination may jointly aect several of the utilization measures. In this paper, a zero-inated regression model for multinomial counts with joint zero-ination is proposed. Maximum likelihood estimators in this model are constructed and their properties are investigated, both theoretically and numerically. We apply the proposed model to an analysis of health-care utilization.

Mots clés: multinomial logit; health-care utilization; excess zeros

Domaines: Méthodologie [stat.ME]

Alpha Oumar Diallo, Aliou Diop, Jean-François Dupuy. Analysis of multinomial counts with joint zero-inflation, with an application to health economics. Journal of Statistical Planning and Inference, 2018, 194, pp.85-105. ⟨10.1016/j.jspi.2017.09.005⟩. ⟨hal-01379903⟩