If you’ve lived in New York City, you know that finding an apartment is no easy task. And once you find your abode, staying put is sometimes even harder. Many of you have felt that dreaded feeling when your lease is about to expire and you wait for the new lease-renewal-rate, wondering if you’ll be able to afford the new rent or be forced out to a new neighborhood or smaller apartment

But then there are the people that are not left completely in the dark- those with rent-stabilized apartments. In those units, rents can only be raised at regulated amounts each year, giving tenants added security that they can probably stay put for much longer.



The funny thing about rent stabilization is that raw data on it is hard to access. Where can you find rent-stabilized apartments? How many are in each building? Our government lists the names of buildings that are stabilized, but gives us no indication of the number of units in each building that are stabilized. This oddly leaves us all in the dark about how many affordable units there are in any specific area of our city.

Enter John Krauss, (the man behind the NYPD Crash Data Bandaid I’ve covered before). After hearing through a FOIL request that it would cost the city $50,000 to deliver the building-by-building data (which implies that the city itself does have the data readily available), John, and some peers at BetaNYC, went about scraping the tax bills for NYC buildings to get the rent stabilization information out of PDFs. This is presumably a much harder task than it would have been for New York State’s Division of Housing and Community Renewal (DHCR), since the State has raw numbers in a database. Nonetheless, John was able to pull it off and build a beautiful map of every rent stabilized building in NYC. And being the good open data steward he is, he also posted the accompanying parsed raw data from the tax bills for us all to see.

And with that, amazingly for the very first time in our city’s history, we have some transparency on rent stabilization data at the individual unit level!

This is exactly what open data is good for. Now New Yorkers and government officials alike can really see what is happening at a granular level in their neighborhoods.

Given that the data is now free from the favorite anti-open format–the PDF– I set about aggregating some of the raw statistics to find out where in the city we are losing rent stabilized apartments the fastest. (Note there are a few different ways that stabilized apartments become destabilized, like for example when they become vacant and the legal rent exceeds $2,500–commonly referred to as vacancy decontrol. For more background see DHCR’s FAQ on destabilization).

For each City Council district (using 2014 boundaries), I mapped out the percent change in affordable housing from 2007 - 2014, with red indicating larger drops. (Clicking on any single district will give you its stats.)

Leading the way in rent stabilized losses was Ben Kallos’ District 5 in the Upper East Side, which the data shows has lost an astounding 31% of its rent stabilized housing units in just eight years, going from a little under 30,000 to just above 20,000 in that period of time. That’s 10,000 units lost in just one council district. The Upper West Side’s Council District 6 (Helen Rosenthal’s district) did not do much better, losing 7,500 units or just about 23 percent of them over this period. The fact that these neighborhoods faced the biggest losses in rent stabilized is unsurprising, with rents surely climbing well above the $2,500 mark. But the magnitude of the loss in recent years is what is striking. By contrast, the district with the largest net gain in units was Carmen Arroyo’s District 17 in the South Bronx, which added a comparably small 3,600 units.

I also created a table of the top ten gaining and losing districts by percentage from 2007 to 2014.



Since Council Districts cut across many neighborhoods, looking at this data on a neighborhood level provides an even more detailed look at where we are losing (and gaining) rent stabilized housing.

At a neighborhood level, we see that the largest drop in number of rent stabilized units took place in the Upper West Side, which saw a drop from about 26,000 to 19,000, or about a 27% loss. Yorkville and Lenox Hill-Roosevelt Avenue are number two and three on this list.

Interestingly, some neighborhoods have seen their counts go up. Stuyvesant Town/Cooper Village had the largest net increase, adding 3,200 units after a lawsuit reclassified many of the units in that area. Rent-stabilized housing also increased in neighborhoods where development was on the rise, like Battery Park City and DUMBO, as developers added rent stabilized units in exchange for tax credits (though these stabilized units traditionally face expiration dates).

Mapping out the city’s loss in affordable housing reveals an interesting trend. The data shows that we are losing units much faster than they can be replaced, and we know that most of the increases reported through new construction are only temporarily affordable. There is a fair bit of irony in the fact that renters are losing protection in some of our most affluent neighborhoods, as those are precisely the neighborhoods where they may need it the most.

The only borough that seems to have seen modest increases in rent-stabilized housing over the last eight years is the Bronx, (though again, those increases may not provide the permanent affordability that one would hope for.) Overall the city has lost about 50,000 units- about 35,000 of them in Manhattan alone.

If the de Blasio administration is as serious about affordable housing as they say they are, it’s time for some transparency on this issue, either by the City’s Department of Finance, which has access to the data, or the state which collects it and is responsible for rent regulation in New York. In this new era of open data, you should not need to know how to write a PDF scraper to find a reasonably priced place to live, or discover where you are about to lose one.

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Tax Data from here.

Council and Neighborhood Shape Files here.

Important Note: We are all much more prone to errors when we have to use back door methods to access data. In this case, we relied on data from the Dept. of Finance reported out by landlords and then scraped from PDFs, though there are surely other agencies that are more directly responsible for collecting and analyzing this data. I look forward to their data releases in the future to help us all paint a clearer picture.