How New York is Protecting Affordable Apartments with Analytics

By Chris Bousquet • February 28, 2018

It’s seemingly impossible to find an affordable apartment in New York City. In spring of 2017, the average one-bedroom in the city went for $2,940 a month. Subtract that from the median household income—just over $55,000 a year, around $4,500 per month—and there’s not a lot leftover for other necessities. And, if you make below the median income or need a bigger apartment to accommodate your family, the prospects are even slimmer.

To its credit, New York has made efforts to ensure its housing stock is more accessible to residents. Two of the most important tools offered by the city are housing vouchers and rent regulations. While vouchers subsidize resident income to meet the high prices of the market, rent regulations set limits on prices for certain “rent-regulated” units to ensure available affordable housing.

However, some of New York’s landlords have earned a reputation for disrespecting these policies. While some landlords refuse to accept housing vouchers, others harass rent-regulated residents in an effort to get them to leave, as property owners are often able to significantly raise the rent after a tenant moves out of a rent-regulated unit.

The NYC Mayor’s Office of Data Analytics (MODA) has partnered with operational agencies to combat these practices and ensure that New York residents are able to get into and stay in affordable apartments. As the city’s civic intelligence center, MODA seeks to enable city departments to use data and analytics to resolve critical issues. At the Summit on Data-Smart Government, MODA special advisor Craig Campbell chronicled the office’s efforts to address voucher discrimination and tenant harassment.


Housing discrimination has been an ugly feature of American life from the days of Jim Crow to the present. However, while blatant acts of racial and religious discrimination have significantly declined over the last decade, a new type of discrimination has become more and more prominent: income discrimination. As housing vouchers have become an increasingly important resource for low-income renters, landlords have begun denying applications from prospective renters who indicate they want to use these vouchers. In some cases, these practices may be a guise for racial discrimination, while in others, landlords may simply not want to go through the reimbursement process.

In either case, housing voucher discrimination is explicitly prohibited by New York City law. The NYC Human Rights Law, Title 8 of the Administrative Code of the City of New York, prohibits discrimination based on a number of protected classes, including race, gender, and religion, and also protects against income-based discrimination.

And yet, the city was still hearing from residents that had experienced voucher discrimination. “There was a lot of anecdotal evidence of people who would come to the commission and make a complaint that they had come to a landlord, said that they were eager to rent, and the landlord said that there was availability. Then, when they went to pay with their LINC or Section 8 voucher, they were refused,” said Campbell.

In an effort to curb this type of discrimination, the Commission on Human Rights (CHR) teamed up with MODA. The Commission had already made efforts to transform this complaint-based system into a proactive one, working with the Fair Housing Justice Center to investigate potential violators. By partnering with MODA, CHR wanted to use analytics to decide where to send these investigators, determining areas in which landlords were most likely to be turning away tenants with housing vouchers. However, beyond prosecuting proven violators, the city wanted to discourage landlords across the city from discriminating in the first place. With this in mind, MODA set out to help the Commission and Fair Housing Justice Center crack down first on offending landlords with the largest amount of citywide property “with the idea that getting to the largest offenders first would set an example and create a chilling effect for smaller potential offenders,” said Campbell.

To accomplish this, MODA first analyzed Neighborhood Tabulation Areas (NTAs) most likely to be experiencing income discrimination. The agency pinpointed areas with available housing, high-performing schools, and little crime, but suspiciously low use of housing vouchers. Given their assets, these areas were likely in high demand, meaning that limited voucher use might reflect discrimination rather than a lack of interest. Specifically, MODA looked for areas that boasted eight or more rental buildings, a lower than median felony crime rate, and higher than median average student achievement score, and yet which were in the bottom quarter of NTAs for housing voucher use. “The incentives of good education, low crime, and available housing stock should drive holders here, yet these NTAs remain in the bottom quarter of the distribution in terms of voucher count,” MODA explained on its website.

After examining New York’s 195 neighborhoods looking for these characteristics, analysts landed on 24 NTAs most likely to be experiencing income discrimination. To identify the largest potential discriminators, analysts then cross-referenced this data with information on the landlords that owned the most properties in those areas. Often, landlords attempt to keep their portfolios secret by using different names for different properties. To overcome this challenge, MODA built ownership profiles for buildings in the 24 neighborhoods, grouping properties based on common characteristics—for instance, mailing addresses for tax bills—in order to identify clusters of buildings belonging to the same landlords.

But all of this data only points to potential discrimination. In order to ascertain whether these landlords were actually guilty of discriminatory behavior, the city has been sending testers to these locations. These testers carry out matched paired tests, in which two testers apply for an apartment using matching application information, except one attempts to use housing vouchers to pay and the other does not. If only the tester using the voucher is denied, the city has good reason to believe the landlord is discriminatory.

Using MODA’s analytics process and this matched paired practice, the Council on Human Rights has prosecuted a number of prominent landlords and management companies. In fact, in 2016, CHR filed 120 income discrimination complaints against landlords, the most income discrimination complaints in its history, and issued a record high $100,000 civil penalty against Best Apartments Inc. In January of 2017, CHR made headlines after charging five large landlords and brokers controlling 20,000 units for repeatedly denying apartments to prospective tenants and testers attempting to use housing vouchers. And CHR gained attention later that year after fining a Brooklyn management company $33,000 that had left a 74-year-old woman homeless for two months by rejecting her housing voucher. The city hopes that these highly visible penalties will discourage others from discriminating based on income.


This past December, prominent New York City property owner Steven Croman paid $8 million to settle a lawsuit for forcing tenants out of rent-regulated apartments. Croman was alleged to have sent intimidating investigators to his properties to accuse rent-regulated residents of living in their homes illegally, aiming to incite panic and get these tenants to leave so he could raise the rent for the next residents.

This practice of harassing tenants to move out of rent-regulated apartments has become a problem in New York. “There is an incentive for landlords who own rent-regulated units to remove tenants from those units so that then they can get a market rate for those properties,” explained Campbell. In certain cases, when a tenant leaves, landlords can convert rent-regulated units to regular market price units, and in others, landlords can raise prices for rent-regulated units by 20 percent. In order to drive out renters to make more money, landlords have resorted to a number of shady practices, from starting disruptive and dangerous construction projects to sending cronies to intimidate renters. “Some landlords will make a living situation unbearable in order to get people to move out,” said Campbell.

In response, New York formed the Tenant Harassment Prevention Task Force (THPT) in 2015. Comprised of representatives from the Departments of Housing Preservation and Development (HPD), Health and Mental Hygiene (HMH), Buildings (DOB), and the Office of State Attorney General, the Task Force set out to identify cases of harassment and prosecute landlords that violate New York tenants’ rights.

The initial problem facing the task force was determining how to identify landlords that were harassing their tenants. At first, an HPD analyst was in charge of determining where inspections would happen using only HPD complaints and violations data, and inspectors routed investigations in an ad hoc way.

Intent on finding a better way to spot violators, the task force tapped MODA. MODA started with a list of buildings that had a high number of rent-regulated units, scraped from publicly available city tax bills. Then, examining data from a number of city departments including the Departments of Finance (DOF), Housing Preservation and Development, and Buildings, as well as 311 requests, MODA sought to determine those factors most correlative with harassment. Indicators under consideration included recently sold buildings, sold buildings followed by intense construction, illegal construction, resident complaints, large differences between market and rent-regulated prices, and landlords taking tenants to court.

To understand the most important predictors, MODA then cross-referenced this data with information on loss of rent-regulated units, a good proxy for harassment. The agency found that the best predictor was the number of dust or asbestos complaints from tenants. Buildings with dust or asbestos complaints were 4-7 times more likely to lose rent-regulated units in the following year compared to a random rent-regulated building. Other predictors included illegal work complaints, sales followed by construction, 311 requests related to construction, and 311 service requests for air quality. Based on this information, MODA created a list of buildings with one or more significant indicators and developed a scoring system to estimate risk of tenant harassment.

The city has begun using this list to prioritize inspections for tenant harassment. Teams go to areas of highest risk and issue violations, fire watch, and vacate orders, as well as pursue litigation in criminal cases.

The $8 million suit against Steven Croman is only one of a number of examples of how analytics has improved response to tenant harassment. Other prominent cases include a $500,000 tenant harassment settlement with Icon Realty Management over unsafe living conditions including collapsed ceilings, water leaks, and thick layers of construction dust in common areas, as well a $132,000 settlement with landlords Gregory and Graham Jones for offering tenants illegal buyouts. By identifying more landlords harassing tenants, the city can prosecute violators and ensure that residents are able to stay in affordable homes.


MODA’s effectiveness in combating income discrimination and tenant harassment reflects a couple of the agency’s critical strengths. The first is MODA’s ability to deliberate thoughtfully on policy goals before deploying analytics projects. In the income discrimination use case, MODA realized that the Commission's goal was not a traditional optimization to target the largest number of bad actors, but rather to identify the worst cases and leverage those to discourage discriminatory practices among other landlords. MODA understood that the city would never have the bandwidth to address all potential cases of discrimination, but by targeting the largest players, the Council on Human Rights could make the biggest dent.

These cases also reflect MODA’s ability to gather data and stakeholders together from across city government. In both the income discrimination and tenant harassment cases, MODA amassed data from a number of city departments that the supervising agencies—CHR and HPD—may have been less likely to access. Using this information, MODA and these agencies were able to make more accurate predictions.

These two cases are a testament to MODA’s capacity to help agencies shape policy and deliver operations in a way that has a profound influence on resident lives. The ability to use housing vouchers or maintain rent-regulated units can be the difference between homelessness and a comfortable apartment for many New Yorkers. Even the best intentioned policies—like housing vouchers or rent regulations—require effective enforcement to have any real teeth, and agencies like MODA have a unique ability to ensure these policies work the way they should.

About the Author

Chris Bousquet

Chris Bousquet is a PhD student in philosophy at Syracuse University. Prior to that, Chris was a Research Assistant/Writer for Data-Smart City Solutions. Chris holds a bachelor’s degree from Hamilton College.