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Handling endogeneity and nonnegativity in correlated random effects models: Evidence from ambulatory expenditure
Author(s) -
Maruotti Antonello,
Raponi Valentina,
Lagona Francesco
Publication year - 2016
Publication title -
biometrical journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.108
H-Index - 63
eISSN - 1521-4036
pISSN - 0323-3847
DOI - 10.1002/bimj.201400121
Subject(s) - endogeneity , econometrics , context (archaeology) , statistics , mathematics , parametric statistics , medical expenditure panel survey , random effects model , skewness , mixture model , economics , medicine , paleontology , health care , meta analysis , health insurance , biology , economic growth
We describe a mixed‐effects model for nonnegative continuous cross‐sectional data in a two‐part modelling framework. A potentially endogenous binary variable is included in the model specification and association between the outcomes is modeled through a (discrete) latent structure. We show how model parameters can be estimated in a finite mixture context, allowing for skewness, multivariate association between random effects and endogeneity. The model behavior is investigated through a large‐scale simulation experiment. The proposed model is computationally parsimonious and seems to produce acceptable results even if the underlying random effects structure follows a continuous parametric (e.g. Gaussian) distribution. The proposed approach is motivated by the analysis of a sample taken from the Medical Expenditure Panel Survey. The analyzed outcome, that is ambulatory health expenditure, is a mixture of zeros and continuous values. The effects of socio‐demographic characteristics on health expenditure are investigated and, as a by‐product of the estimation procedure, two subpopulations (i.e. high and low users) are identified.