Dynamic Cost-offsets of Prescription Drug Expenditures : Panel Data Analysis Using a Copula-based Hurdle Model
Partha Deb, Pravin K. Trivedi, David M. Zimmer
This paper presents a new multivariate copula-based modeling approach for analyzing cost-offsets between drug and nondrug expenditures. Estimates are based on panel data from the Medical Expenditure Panel Survey (MEPS) with quarterly measures of medical expenditures. The approach allows for nonlinear dynamic dependence between drug and nondrug expenditures as well as asymmetric contemporaneous dependence. The specification uses the standard hurdle model with two significant extensions. First, it is adapted to the bivariate case. Second, because the cost-offset hypothesis is inherently dynamic, the bivariate hurdle framework is extended to accommodate dynamic relationships between drug and nondrug spending. The econometric analysis is implemented for six different groups defined by specific health conditions. There is evidence of modest cost-offsets of expenditures on prescribed drugs
Year of publication: |
July 2009
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Authors: | Deb, Partha |
Other Persons: | Zimmer, David M. (contributor) ; Trivedi, Pravin K. (contributor) |
Institutions: | National Bureau of Economic Research (contributor) |
Publisher: |
Cambridge, Mass : National Bureau of Economic Research |
Subject: | Arzneimittel | Pharmaceuticals | Privater Konsum | Private consumption | Gesundheitskosten | Health care costs | Multivariate Verteilung | Multivariate distribution | Privater Haushalt | Household | Panel | Panel study |
Saved in:
freely available
Extent: | 1 Online-Ressource |
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Series: | NBER working paper series ; no. w15191 |
Type of publication: | Book / Working Paper |
Language: | English |
Notes: | Mode of access: World Wide Web System requirements: Adobe [Acrobat] Reader required for PDF files Hardcopy version available to institutional subscribers. |
Other identifiers: | 10.3386/w15191 [DOI] |
Source: | ECONIS - Online Catalogue of the ZBW |
Persistent link: https://www.econbiz.de/10012463458