ENDOGENEITY IN COUNT DATA MODELS: AN APPLICATION TO DEMAND FOR HEALTH CARE (replication data)

DOI

The generalized method of moments (GMM) estimation technique is discussed for count data models with endogenous regressors. Count data models can be specified with additive or multiplicative errors. It is shown that, in general, a set of instruments is not orthogonal to both error types. Simultaneous equations with a dependent count variable often do not have a reduced form which is a simple function of the instruments. However, a simultaneous model with a count and a binary variable can only be logically consistent when the system is triangular. The GMM estimator is used in the estimation of a model explaining the number of visits to doctors, with as a possible endogenous regressor a self-reported binary health index. Further, a model is estimated, in stages, that includes latent health instead of the binary health index.

Identifier
DOI https://doi.org/10.15456/jae.2022313.1256434475
Metadata Access https://www.da-ra.de/oaip/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai:oai.da-ra.de:776398
Provenance
Creator WINDMEIJER, F. A. G.; SILVA, J. M. C. SANTOS
Publisher ZBW - Leibniz Informationszentrum Wirtschaft
Publication Year 1997
Rights Creative Commons Attribution 4.0 (CC-BY); Download
OpenAccess true
Contact ZBW - Leibniz Informationszentrum Wirtschaft
Representation
Language English
Resource Type Collection
Discipline Economics