PRICE LEVELS AND DISPERSION WITH ASYMMETRIC INFORMATION

In the extensive literature on price dispersions that exists to date, there is a gap in the analysis of how market structure affects prices as well as the degree of dispersion in prices. Specifically, the literature is deficient in analyzing how price levels and price dispersion are affected by the number of firms operating in a market. I use secondary data to look at the prices of prescription drugs at the retail level in nine hundred and seventy pharmacies across one hundred and sixty five markets in Maryland and compare price dispersion across these brick and mortar pharmacies as well as across a separate set of pharmacies that only operate online. I compare online versus offline price dispersion, as well as price dispersion in purely offline markets from the structure of the market’s context. Stahl’s (1989) theoretical model is used to formulate and test the hypotheses that an increase in the proportion of positive search cost consumers in a market will cause price levels to rise and price dispersion to initially increase and then decrease. Furthermore, in markets with the proportion of positive search cost consumers above a threshold level, an increase in the number of firms will also lead price levels to rise and price dispersion to initially increase and then decrease. Conversely, in markets with positive search cost consumers below the threshold level, an increase in the number of firms will lead to lower price levels, i.e. the competitive outcome. For the analysis, I look at prices at the pharmacy level and price dispersion at the market level and determine the proportion of high search cost consumers for a specific pharmacy or a specific market relative to the other pharmacies and markets in the dataset. I find that a significant part of the differences in prices for a homogeneous prescription drug can be attributed to asymmetric information and that price dispersion is higher in markets with a greater number of firms, and price levels are higher in low income neighborhoods.