We specify and estimate a computationally tractable stationary equilibrium model of the housing market. The model is rich and incorporates many of its unique features: buyers' and sellers' simultaneous search behavior, heterogeneity in their motivation to trade, transaction costs, a trading mechanism with posting prices and bargaining, and the availability of an exogenous advertising technology that induces endogenous matching. Estimation is conducted using Maximum Likelihood methods and Multiple Listing Services data. The estimated model is used to simulate housing market outcomes when a) the amount of information displayed on real estate listings increases and b) real estate agent's commission rates change.