Unconditional Demand for Curative Health Inputs
Does Selection on Health Status Matter in the Long Run?
Download eBook for Free
|PDF file||2.3 MB||
Use Adobe Acrobat Reader version 10 or higher for the best experience.
Healthy people are routinely ignored when analyzing curative health inputs. This practice overlooks people's long-term ability to affect their chances of falling sick, and may have perverse effects on welfare analyses. A dynamic model implies that input demand estimates conditioned on current illness can only be interpreted as short-run effects, in contrast to the long-run nature of unconditional estimates. In addition, conditional estimates may be biased from both sample-selection, and self-reporting of health status. By jointly modeling discrete choices for health inputs and health outcomes, a test for selection bias is derived using the multinomial probit. In data from Cote d'Ivoire, it is found that the usual short-run demand estimates do not suffer from selection bias. However, these conditional estimates differ from the easily estimated long-run unconditional effects, which are often the more relevant policy parameters.
This report is part of the RAND Corporation Draft series. The unrestricted draft was a product of the RAND Corporation from 1993 to 2003 that represented preliminary or prepublication versions of other more formal RAND products for distribution to appropriate external audiences. The draft could be considered similar to an academic discussion paper. Although unrestricted drafts had been approved for circulation, they were not usually formally edited or peer reviewed.
This research in the public interest was supported by RAND, using discretionary funds made possible by the generosity of RAND's donors, the fees earned on client-funded research, and independent research and development (IR&D) funds provided by the Department of Defense.
This document and trademark(s) contained herein are protected by law. This representation of RAND intellectual property is provided for noncommercial use only. Unauthorized posting of this publication online is prohibited; linking directly to this product page is encouraged. Permission is required from RAND to reproduce, or reuse in another form, any of its research documents for commercial purposes. For information on reprint and reuse permissions, please visit www.rand.org/pubs/permissions.
The RAND Corporation is a nonprofit institution that helps improve policy and decisionmaking through research and analysis. RAND's publications do not necessarily reflect the opinions of its research clients and sponsors.