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SEMI-PARAMETRIC ESTIMATION OF HURDLE REGRESSION MODELS WITH AN APPLICATION TO MEDICAID UTILIZATION

✍ Scribed by SHIFERAW GURMU

Publisher
John Wiley and Sons
Year
1997
Tongue
English
Weight
202 KB
Volume
12
Category
Article
ISSN
0883-7252

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✦ Synopsis

This paper develops a semi-parametric estimation method for hurdle (two-part) count regression models. The approach in each stage is based on Laguerre series expansion for the unknown density of the unobserved heterogeneity. The semi-parametric hurdle model nests Poisson and negative binomial hurdle models, which have been used in recent applied literature. The empirical part of the paper evaluates the impact of managed care programmes for Medicaid eligibles on utilization of health-care services using a key utilization variable, the number of doctor and health centre visits. Health status measures and age seem to be more important in determining health-care utilization than other socio-economic and enrollment variables. The semi-parametric approach is particularly useful for the analysis of overdispersed individual level data characterized by a large proportion of non-users, and highly skewed distribution of counts for users.

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## REFERENCE Kinal, T. and K. Lahiri (1993) , `On the estimation of simultaneous-equations error-components models with an application to a model of developing country foreign trade', Journal of Applied Econometrics, 8, 81Β±92.