Don't Ask, Don't Tell: The Impact of Real Estate Agents on House Prices Near Environmental Disamenities

Abstract

The purpose of this paper is to determine the impact of real estate agents on the price of houses that are located close to an environmental disamenity using Rosen's (1974) hedonic price model. Our main hypothesis is that real estate agents obtain higher prices than those theoretically expected when the houses are located closer to an environmental disamenity. We attribute this result to differences in information about the presence of the environmental disamenity between buyers, sellers, and their real estate agent, that ultimately have an impact on their bargaining position. Our analysis is based on 2,967 transactions involving houses located close to four landfills in Franklin County, Ohio, in 1990. Using an estimated hedonic price model, we predict house values for transactions made with and without a real estate agent, and calculate their percentage differences at various distance intervals from the landfills. On average, results suggest that at distances less than 1 mile away from the landfills, the percentage increase in the house price obtained by a real estate agent is greater than the commission rate. For example, the weighted predicted rent for transactions made through a real estate agent at an interval distance of 0.75 miles away from the landfills is $7,680.37, while the predicted rent for transactions made without an agent is $6,780.71. The difference between these two predicted house values is 13.27 percent. For an average real estate commission rate of 7 percent, real estate brokered sales results in surplus for houses closer to landfills. This effect erodes as distance away from the landfill is increased. These findings are consistent with theoretical expectations about differences between prices obtained by real estate agents and prices obtain by individual house sellers. In addition to the effects that real estate agents may have on house prices, results of this paper may be of interest to individuals using multiple listing service (MLS) data alone for hedonic studies. That is, our paper provides evidence that estimating hedonic price models with MLS data can downwardly bias estimated impacts of an environmental disamenity.