A substantial body of economic research has warned about potential negative efficiency consequences to limiting rent increases below market rates, including overconsumption of housing by tenants of rent-controlled apartments, misallocation of heterogeneous housing to heterogeneous tenants, negative spillovers onto neighboring housing, and neglect of required maintenance. Yet, due to incomplete markets, in the absence of rent control many tenants are unable to insure themselves against rent increases. A variety of affordable-housing advocates have argued that tenants greatly value these insurance benefits, which allow them to stay in neighborhoods they have lived in for many years and in which they feel invested.
Using a unique 1994 local San Francisco ballot initiative, we find tenants covered by rent control do place a substantial value on the benefit, as revealed by their migration patterns. However, landlords of properties impacted by the law change respond over the long term by substituting to other types of real estate, in particular by converting to condos and redeveloping buildings so as to exempt their properties from rent control. This substitution toward owner-occupied and high-end new construction rental housing likely fueled the gentrification of San Francisco, as these types of properties cater to higher-income individuals. Indeed, the combination of more gentrification and helping rent-controlled tenants remain in San Francisco has led to a higher level of income inequality in the city overall.
The 1994 San Francisco ballot initiative created rent control protections for small multifamily housing built prior to 1980. This led to rent control expansion based on whether the multifamily housing was built prior to or post-1980. To examine rent control’s effects on tenant migration and neighborhood choices, we use address-level migration decisions and housing characteristics of adults living in San Francisco in the early 1990s. We define our treatment group as renters living in small apartment buildings built prior to 1980 and our control group as renters living in small multifamily housing built between 1980 and 1990. Using our data, we follow each of these groups over time up until the present, regardless of where they migrate to.
On average, we find that in the medium to long term, the beneficiaries of rent control are between 10 percent and 20 percent more likely to remain at their 1994 address relative to the control group. These effects are significantly stronger among older households and among households that have already spent a number of years at the same address. This is consistent with the fact that both of these populations are less mobile in general, allowing them to accrue greater insurance benefits.
On the other hand, for households with only a few years at a rent-controlled address, the impact of rent control can be negative. Perhaps even more surprisingly, the impact is only negative in census tracts that had the highest rate of ex-post rent appreciation. This evidence suggests that landlords actively try to remove their tenants in those areas where the reward for resetting to market rents is greatest. In practice, landlords have a few possible ways of removing tenants. First, landlords could move into the property themselves, known as move-in eviction. The Ellis Act also allows landlords to evict tenants if they intend to remove the property from the rental market, for instance, in order to convert the units to condos. Finally, landlords are legally allowed to offer their tenants monetary compensation for leaving. In practice, these transfer payments from landlords are quite common and can be quite large. Moreover, consistent with the empirical evidence, it seems likely that landlords would be most successful at removing tenants with the least built-up neighborhood capital — that is, tenants who have not lived in the neighborhood for long.
To understand the impact of rent control on rental supply, we merge historical parcel data from the San Francisco Assessor’s Office, which allows us to observe parcel splits and condo conversions. We find that rent-controlled buildings were almost 10 percent more likely to convert to a condo or a tenancy in common than buildings in the control group, representing a substantial reduction in the supply of rental housing. Consistent with these findings, we also find a 15 percent decline in the number of renters living in these buildings and a 25 percent reduction in the number of renters living in rent-controlled units compared to the control group, relative to 1994 levels. This gap is driven by landlords demolishing their old housing and building new rental housing. New construction is exempt from rent control.
In order to evaluate the welfare impacts of these effects, we construct and estimate a model of neighborhood choice. We find that rent control offered large benefits to impacted tenants during the 1995–2012 period, averaging between $2,300 and $6,600 per person each year, with aggregate benefits totaling over $214 million annually and $2.9 billion in present discounted value terms. These effects are counterbalanced by landlords reducing supply in response to the introduction of the law. We conclude that this led to a citywide rent increase of 5.1 percent. This has a present discounted cost of $2.9 billion dollars to tenants. Further, we find 42 percent of these losses are paid by future residents of San Francisco, while incumbent residents at the time of the law change bear the other 58 percent. On net, incumbent San Francisco residents appear to come out ahead, but this is at the great expense of welfare losses from future inhabitants. These substantial welfare losses due to decreased housing supply might be mitigated if insurance against large rent increases was provided as a form of government social insurance, instead of a regulated mandate on landlords.
NOTE:
This research brief is based on Rebecca Diamond, Timothy McQuade, and Franklin Qian, “The Effects of Rent Control Expansion on Tenants, Landlords, and Inequality: Evidence from San Francisco,” National Bureau of Economic Research Working Paper no. 24181, January 2018, http://www.nber.org/papers/w24181.
