The Impact of Minimum Lot Size Regulations On House Prices in Eastern Massachusetts

There has been an increasing focus on exclusionary zoning; particularly in suburban areas, as a cause of the high house prices in many metropolitan areas in the United States. Most of the recent evidence, though, is indirect given the difficulty of isolating the direct causal impact of zoning on house prices. One main problem to overcome is that zoning is not exogenous but is rather the result of economically rational behavior on the part of residents. Another problem is the lack of good data on land use regulations. One further complication is that the ability of a town to sustain a price increase from zoning depends on its monopoly zoning power; that is, the lack of towns that are close substitutes. This study seeks to bridge this gap by investigating the regulatory price effect of minimum lot size zoning on house prices through the use of several excellent data sources which provide parcel level housing and geocoded regulatory data. We have data on all transactions of single-family homes in the greater Boston area from 1987 to 2006, unit characteristics, and changes in minimum lot size zoning over this period. We estimate a model of house prices that include changes in minimum lot size at the zoning-district level, variables that account for possible spillover effects in the same town and in nearby towns, and zoning district fixed effects. The latter will control, to a large extent, the endogeneity bias due to land use regulations. We also account for monopoly zoning power through the use of town fixed effects. We find that the price effect is highly nonlinear in monopoly zoning power with price increases of more that 20% at the upper tail of the monopoly power distribution. We also find evidence of significant spillover effects within and across towns; though not as large as those in the zoning districts where the minimum lot size changes. Finally, we find that the impact increases over time. We would like to thank the MIT Center for Real Estate and the Warren Group for providing us with the data.