Do Macroeconomic Conditions Explain Drug Price Variations Across Countries? A Cross-Sectional Analysis

Authors: Tsang K, Wang B, Patel P

Conference: International Society for Pharmacoeconomics and Outcomes Research

Location: Taipei, Taiwan

Year: 2012

Objectives: We examine how much of the cross-country drug price differences can be explained by macroeconomic conditions (real GDP per capita, openness, population, and corruption).

Methods: We use the Pricentric® dataset of drug prices and analyze prices of 13 drug packs across 32 countries at various pack levels in 2009. The sample is selected by requiring each pack having observations for more than 20 countries and each country having observations for more than 20 packs. We gather data on real GDP per capita, openness, and population from the Penn World Table, and the Corruption Perceptions Index by Transparency International. The analysis has two parts. First, for each drug pack, we regress the log prices (ex-factory, public, etc) on the four macroeconomic variables. Second, to achieve better identification, we pool together all data and regress log prices on the macroeconomic variables and drug fixed effects.

Results: For 6 of the 13 packs we find that the four macroeconomic variables can explain the cross-country price variations well (with R-squared over 8%). For the other 7 drugs the fit is worse, but the signs of the coefficients among the 13 packs are in general consistent. The pooled regression shows the same conclusion that the macroeconomic variables have strong explanatory power. For the whole sample, a 1% increase in real GDP per capita correlates with a 0.15% increase in drug price. Openness has little impact, while population has a small but significant positive association. A 1% increase in the corruption index correlates with a 0.3% increase for all prices.

Conclusions: Controlling for drug fixed effects, macroeconomic variables show statistically significant and economically large effects on drug pack prices. In particular, real GDP per capita and corruption perceptions have large positive impacts suggesting drugs cost more in either more developed countries or in more corrupted countries.