Estimating Incentive and Selection Effects in the Medigap Insurance Market: An Application with Dirichlet Process Mixture Model (replication data)

DOI

This paper presents an empirical study of endogenous treatment effects in the presence of heterogeneous responses. We estimate the incentive and selection effects of having prescription drug coverage on total drug expenditures using a sample from the Medicare Current Beneficiary Survey (MCBS). A Dirichlet process mixture (DPM) model is used to model the heterogeneity in treatment effects. Rather than estimating a finite mixture model with a fixed number of components, we specify a DP prior on the parameters, thus allowing the data and prior knowledge to determine the number of components. Endogeneity is modeled by the covariance of the error terms of the selection and the outcome equations in a two-equation selection model. We find that there are strong incentive and advantageous selection effects, with the average treatment effect and the average treatment effect for the treated estimated at $1132 and $858, respectively. Substantial heterogeneity is found to exist in the selection effects, particularly for those having lower drug expenditures.

Identifier
DOI https://doi.org/10.15456/jae.2022321.0724964366
Metadata Access https://www.da-ra.de/oaip/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai:oai.da-ra.de:775572
Provenance
Creator Hu, Xuequn; Munkin, Murat K.; Trivedi, Pravin K.
Publisher ZBW - Leibniz Informationszentrum Wirtschaft
Publication Year 2015
Rights Creative Commons Attribution 4.0 (CC-BY); Download
OpenAccess true
Contact ZBW - Leibniz Informationszentrum Wirtschaft
Representation
Language English
Resource Type Collection
Discipline Economics