Uncertainty and Learning in Pharmaceutical Demand

Posted: 1 Nov 2005

See all articles by Gregory S. Crawford

Gregory S. Crawford

University of Zurich - Department of Economics

Matthew Shum

Johns Hopkins University - Department of Economics

Abstract

Exploiting a rich panel data set on anti-ulcer drug prescriptions, we measure the effects of uncertainty and learning in the demand for pharmaceutical drugs. We estimate a dynamic matching model of demand under uncertainty in which patients learn from prescription experience about the effectiveness of alternative drugs. Unlike previous models, we allow drugs to have distinct symptomatic and curative effects, and endogenize treatment length by allowing drug choices to affect patients' underlying probability of recovery. We find that drugs' rankings along these dimensions differ, with high symptomatic effects for drugs with the highest market shares and high curative effects for drugs with the greatest medical efficacy. Our results also indicate that while there is substantial heterogeneity in drug efficacy across patients, learning enables patients and their doctors to dramatically reduce the costs of uncertainty in pharmaceutical markets.

Keywords: Uncertainty, learning, pharmaceutical demand, matching, dynamic discrete choice

JEL Classification: D83, I11, L15

Suggested Citation

Crawford, Gregory S. and Shum, Matthew, Uncertainty and Learning in Pharmaceutical Demand. Econometrica, Vol. 73, No. 4, pp. 1137-1173, July 2005, Available at SSRN: https://ssrn.com/abstract=829284

Gregory S. Crawford (Contact Author)

University of Zurich - Department of Economics ( email )

Schönberggasse 1
Zürich, CH-8001
Switzerland

HOME PAGE: http://www.econ.uzh.ch/faculty/groupcrawford.html

Matthew Shum

Johns Hopkins University - Department of Economics ( email )

3400 Charles Street
Baltimore, MD 21218-2685
United States
410-516-8828 (Phone)

HOME PAGE: http://www.econ.jhu.edu/people/shum/

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