Estimation of hedonic price functions with incomplete information

Existence of persistent price dispersion suggests that some buyers find lower prices through search and information acquisition, while some sellers charge higher prices by gathering information on potential buyers. If buyers are not fully informed of the lowest price available in the market they end up paying a price higher than if they had full information. Similarly, if sellers are not fully informed about the highest price they could charge, they too suffer by receiving a price lower than had they had full information. This paper develops a hedonic price model that incorporates the effects of incomplete information on both sides of the market and obtains estimates of the discrepancies between market prices and buyers' maximum willingness to pay and sellers' minimum willingness to accept. Correlates of such price discrepancies are also explored. We apply the technique to a data set constructed from the American Housing Survey, and find that incomplete information has had a significant impact on housing prices.