Measuring Ignorance in the Market: A New Method with an Application to Physician Services
Ever since Stigler's seninal piece on the econcinics of information, a
great deal of research has been done investigatirg equilibrium in markets
with imperfect imformation. While most of this research has been concerned
with theoretically establishing the conditions under which there exists a
distribution of prices in equilibrium, there is a small, but growing, body of
empirical research in this area.
This work has followed the sestion of Stigler ard utilized the
dispersion of prices (usually the variance) as a measure of ignorance about
price. There are two disadvantages to using the variance (or another measure
of dispersion, such as the range) of prices as a measure of ignorance about price. The first reason, recognized by Stigler ard others, is that price can
vary for many reasons other than ignorance. Thus dispersion is not a pure
measure of ignorance about prices. The second reason, which has not been
commonly considered in the empirical literature, is that price dispersion can due to ignorance on the part of both buyers and of sellers.
In this paper we propose a method for measuring ignorance about price in
a market which builds on Stigler's original suggestion to use dispersion as a
measure of ignorance. The innovation is to use a new frontier estiiation
technique containing a three component error term to separate observed price
dispersion into purely random variation, variation due to buyer ignorance,
and variation due to seller ignorance . We apply the technique to the
physicians' service market. This surplies us with quantitative indices of
price ignorance for different services and how the level of ignorance varies
by buyer, seller, and market area characteristics. The results are striking.
Buyer ignorance exceeds seller ignorance by roughly a factor of two in this
market, and this gap is greater for services which are less frequently
purchased, more heavily insured, or accompanied by greater severity of
illness, as predicted by search theory.
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