Background
San Francisco has, by some metrics, the most expensive rental housing in the world. Housing prices continue to rise and much of the city is undergoing or at risk of gentrification or displacement. San Francisco also has rent control, which limits annual rent increases for much of the city’s older housing stock. Tenants with rent control often receive tremendous pressure to move out from landlords, since this allows the owner to increase the rent to the market rate.
There are many ways that landlords try to get rid of rent-controlled tenants, including harassment, not making repairs, and moving into the apartment themselves (or claiming to…). Another is buyout agreements, in which the landlord offers the tenant a lump sum to move out and theoretically find new housing with that money. In response to concerns from tenant advocates that the buyout process was taking advantage of asymmetries in power and information, the San Francisco Rent Board (SFRB) began regulating buyout agreements in March 2015. The ordinance required landlords to file notice of a buyout agreement with SFRB and notify renters of their right to refuse. The Board is also required to maintain a public database of buyout agreements. The following maps utilize this data to understand how this process is playing out in this very high-cost rental market.
How many buyouts?
Since March 2015, SFRB has received filings for 1,945 buyout agreements. This averages to about 65 buyout agreements each month. But how many people are we talking about? The dataset includes the number of tenants being bought out, although only about half of the filings actually reported this. If we take a conservative estimate, however, assuming that each blank value is one tenant, we get to 2,580 tenants bought out over two and a half years. The number is likely higher, due to the presence of larger households and buyouts that are not duly registered with SFRB.
The map below shows the number of buyout agreements by census tract, divided into quintiles. The highest concentrations are in neighborhoods well-known to be experiencing gentrification and/or displacement, including the Mission and the Haight, and to a lesser extent, SoMa and the Marina.
How much are these buyouts?
The next map indicates the average buyout amount by census tract, again divided into quintiles. Unfortunately, this data too is incomplete, with just over one-third of filings including this information. Since the Carto embed did not seem to save the legend, I am including the quintile cutoff points here: $13,500, $25,000, $37,000 and $60,000. The mean was around $38,000. The map uses purple circles to denote buyout amounts over $100,000, the 95th percentile. The highest registered buyout was $310,000 in the Mission. This building is marked on the map with a larger red circle, at the 1000 block of South Van Ness Avenue.
There seems to be a general positive association between the number of buyout agreements in a census tract and the value of those buyouts. Some of the same high-profile neighborhoods appear again. This a very rough connection, however, and more information would be needed on square footage, the number of bedrooms, locational advantages, and the use of lawyers (by tenants or landlords) to understand the range of buyout amounts. The Richmond and Sunset Districts are notable here for having tracts with relatively high buyout values, even though they were not as salient in the previous map.
One of the big questions regarding buyout agreements is how much is fair. $20,000 is a lot of money, especially for lower-income tenants, but does not go very far in the city’s current rental market. It would be useful, then, to overlay this buyout data with rental prices by neighborhood. This could show, for example, where a rent-controlled tenant accepting a buyout in the Mission could move and pay rent for at least one year.
Notes on methodology and data
To map these buyout agreements in Carto, I began by downloading the dataset from San Francisco’s open data portal. At first I had all the points in their exact coordinate position. However, it was messy and difficult to interpret, so I joined this to a TIGER file with the census tracts. This allowed me to count, sum and average different factors at an aggregated, but still very local, scale.
I had some challenges with Carto’s legend, particularly not being able to see where the breaks were in the categories. I ended up using Excel to find these data points. I was also not sure how to bring the legend into WordPress – it kept disappearing when I embedded the Carto link.
Finally, although this SFRB data is tremendously important, it is also incomplete. The lack of information about buyout amounts is particularly concerning, because it sidesteps the affordability question (where can renters who take buyouts go?). I was also surprised to see that there were no registered buyouts in Chinatown or the Financial District and would be curious to understand why that might be.