Suchergebnisse

We generate the first cross-city panel dataset of land-use reforms that increase or decrease allowed housing density and estimate their association with changes in housing supply and rents. To generate reform data, we use machine-learning algorithms to search US newspaper articles between 2000 and 2019, then manually code them to increase accuracy. We merge these data with US Postal Service information on per-city counts of addresses and Census data on demographics, rents, and units affordable to households of different incomes. We then estimate a fixed-effects model with city specific time trends to examine the relationships between land-use reforms and the supply and price of rental housing. We find that reforms that loosen restrictions are associated with a statistically significant 0.8% increase in housing supply within three to nine years of reform passage, accounting for new and existing stock. This increase occurs predominantly for units at the higher end of the rent price distribution; we find no statistically significant evidence that additional lower-cost units became available or moderated in cost in the years following reforms. However, impacts are positive across the affordability spectrum and we cannot rule out that impacts are equivalent across different income segments. Conversely, reforms that increase land-use restrictions and lower allowed densities are associated with increased median rents and a reduction in units affordable to middle-income renters.