The last decade has witnessed an explosive growth in the use of the internet. Not only the number of users has dramatically increased, but also the amount and quality of the information displayed online has improved. The information available to web users is limited mostly by technological constraints and will be significantly less restrictive in the next decade. These technological changes foreseen for the future should affect buyer's and seller's behavior in many electronic markets (e-markets). One can think of two elements that determine the importance of e-markets: a) the number of consumers who have internet access, and b) the amount and quality of the information that internet marketplaces provide to consumers. Clearly, changes in each of these elements should affect the e-markets differently, and we are not aware of any previous study that has attempted to separate these effects. In our research paper, we attempt to explain how improvements in the information technology affect buyer's and seller's behavior in online markets. We focus our attention on the Real Estate Market (REM) for several reasons. First, housing units, in the majority of cases, are advertised through the internet. Second, buyers incur remarkable high offline search costs in the REM. Third, online housing sites have notably improved the amount of information they display by incorporating pictures and virtual tours to the existing Multiple Listing Services, and important improvements are forecasted for the near future. Finally, the housing market is one of the largest and most important in the US economy. We specify and estimate an equilibrium two-sided search model that depicts many of the REM’s real-life features. The theoretical model modifies the framework of existing equilibrium search models in the labor literature to capture the unique nature of the REM. To our knowledge, it is the first attempt in the literature to model in an equilibrium context five very important characteristics of the REM: a) buyers' and sellers' search behavior, b) heterogeneity in agents' motivation to trade, c) transaction costs, d) a trading mechanism with posting prices and bargaining, and e) the availability of an online advertising technology. To estimate our theoretical model, we follow the growing literature on estimation of equilibrium search models and use maximum likelihood methods. The data used for estimation consists of Multiple Listing Services data for real estate transactions in Charlottesville City and Albemarle County (VA) during the years 2000 through 2002. Our estimates suggest that only 3% of the relevant information that home-buyers collect before making a purchase decision is obtained through on-line ads. Furthermore, we use the estimated model to conduct counterfactual experiments and find that, improvements in online information displayed by Real Estate ads decrease equilibrium prices but increase the time that a property stays on the market.
