Real estate agents typically charge a 6 percent commission, regardless of the price of the house sold. As a consequence, the commission fee from selling a house will differ dramatically across cities depending on the average price of housing, although the effort necessary to match buyers and sellers may not be that different. We use a simple economic model to show that if barriers to entry are low, the entry of real estate agents in cities with high housing prices is socially inefficient. Consistent with our model, we find that when the average price of land in a city increases, (1) the fraction of real estate brokers in a city increases, (2) the productivity of an average real estate agent (houses sold per hour worked) falls, and (3) the real wage of a typical real estate agent remains unchanged. We cannot completely rule out the alternative explanation that these results reflect unmeasured differences in the quality of broker services. However, we present evidence that as the average price of housing in a city increases, there is only a small increase in the amount of time a buyer spends searching for a house, and the average time a house for sale stays on the market falls.

We quantify agglomeration spillovers by comparing changes in total factor productivity (TFP) among incumbent plants in "winning" counties that attracted a large manufacturing plant and "losing" counties that were the new plant's runner-up choice. Winning and losing counties have similar trends in TFP prior to the new plant opening. Five years after the opening, incumbent plants' TFP is 12 percent higher in winning counties. This productivity spillover is larger for plants sharing similar labor and technology pools with the new plant. Consistent with spatial equilibrium models, labor costs increase in winning counties, indicating that profits ultimately increase less than productivity.