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State of the City 2020

Renters and Recovery


As New York City enters the second year of the COVID-19 crisis, the well-being of New York City renters, a group disproportionately affected by both the virus1 and the economic effects of the shutdown,2 remains a central concern. Despite this, little is known about the actual rent owed by households after a year of unprecedented economic upheaval. While protections like eviction moratoria have helped shield many affected tenants in the short term,3 those safeguards do not address accumulating tenant rental arrears nor lost rental income for property owners. Additionally, while emergency rental assistance has been made available by the federal government, it is not yet reaching households at scale. The COVID-19 pandemic has made clear the need for detailed, real-time, and accurate rent payment data to better understand the challenges faced by tenants and landlords in the current crisis, as well as in better times. Without a clear view of the financial health of renter households, policymakers are left guessing about risk levels for key outcomes like housing stability and the financial viability of the rental stock. 

In this report, we seek to fill a critical piece of this knowledge gap by building an understanding of the experiences of renters in affordable housing in New York City, and by extension, the landlords that house them. We draw on detailed data from primarily affordable housing portfolios, collected in partnership with the New York State Association for Affordable Housing (NYSAFAH), to examine how rent payment and rental arrears changed over the first year of the COVID-19 crisis. We begin by looking at household-level rent payment trends to understand how rental debt levels have changed for renters in our sample of predominantly affordable housing. Tracing payment rates and vacancy rates across the sample sheds light on how those two factors overlapped to affect revenue streams for owners. Owners typically manage finances at the property level, so we next examine the property-level and geographic distribution of changes in payment rates and rent debt to better understand the extent to which properties and neighborhoods were impacted during the pandemic. Finally, to outline which types of properties fared better amidst the economic shutdown, we consider the relationship between rent payment and two key characteristics: property size and the share of subsidized units.

This report surfaces the following key findings about rent payment trends within our sample of primarily affordable housing portfolios in New York City over the first year of the COVID-19 crisis:

Household-Level Analysis: How have rental payments, rental arrears, and vacancies changed in the affordable housing stock in New York City during the pandemic?

Property-Level Analysis: How have payment rates and rental balances changed within properties? Where were properties with the lowest 12-month payment rates located? What type of properties experienced the largest declines in payment rates?

In order to provide aid as effectively as possible, policymakers need detailed information on rental arrears, including the scale of the issue, and how it varies across households and properties. This section seeks to inform the efforts of policymakers and stakeholders working to target rental assistance, counseling, and other eviction prevention efforts by examining the experience of a subset of renters and property owners during the pandemic. Our dataset was designed to provide insight into the status of primarily affordable portfolios and the typically low-income households that live in those apartments. As such, this work mainly sheds light on this population and stock. As we watch the rollout of vaccines and anticipate a safer future, this analysis suggests that even among our sample of affordable properties, this population may need deep support to overcome the lasting effects of a devastating year. 

Background and Context

Prior to the COVID-19 pandemic, the New York State Legislature expanded protections for tenants with the Housing Stability and Tenant Protections Act, passed in June 2019. Tenants in rent stabilized units particularly benefited from the law changes, including provisions that limited rent increases and pathways to an eviction. Over a year into the COVID-19 pandemic and subsequent economic crisis, myriad federal and state policies have attempted to shield renters from the worst of the pandemic’s economic fallout–particularly as it concerns housing and rental payments. Policy interventions have included expanded eligibility and periods of enhanced Unemployment Insurance,4 various eviction moratoria,5 three rounds of direct stimulus checks,6 as well as the allocation of close to $50 billion in rental assistance, which has not yet been widely distributed.7 As elaborate as the COVID-induced safety net has become, many warn of an impending eviction “tsunami.”8 The treatment of past arrears in eviction court will be an important determinant of future eviction rates and the bargaining positions of landlords and tenants. If tenants accumulated high levels of rental debt during the economic shutdown, they may be more vulnerable to eviction once protections are lifted.9 Without the aforementioned financial assistance, landlords’ abilities to cover mortgage and maintenance costs may also be extremely limited.10 While policymakers seek to assist tenants (and property owners), little is known about trends in actual rent payment and the current scale of rental debt.

Unlike household mortgage payments, there is no uniform reporting and tracking of rental payments. Without consistent, detailed, national data on rent payments, researchers have attempted to estimate the scope of rental debt incurred over the course of the pandemic using other sources. One approach has been to survey property owners. For example, a July 2020 survey of the National Association of Hispanic Real Estate Professionals found that close to 60 percent of respondents saw rent collections drop compared to the previous quarter.11 The National Multifamily Housing Council has been surveying approximately 12 million units of market-rate rental properties since April 2019, finding that rent payment rates dipped to their lowest point compared to the prior year in January 2021.12 Finally, based on a survey of roughly 40,000 of its members’ units (owners and operators of rent-regulated housing), the Community Housing Improvement Program (CHIP) estimated $1.1 billion in rental arrears including an average rent balance of about $6,000.13 Those who respond to surveys typically provide estimates on overall trends in their portfolios, and not the underlying unit-level data itself. 

An alternative approach is to use information on the employment impact of the pandemic to infer changes in rental payments. Earlier in the pandemic, our June 2020 analysis drew on Unemployment Insurance claims data and American Community Survey (ACS) microdata to estimate the total rental assistance needed for New York City renters given the crisis’ economic impact.14 Combining data from the Bureau of Labor Statistics and the ACS, the Urban Institute simulated the impact of job loss on renter households by industry and estimated the amount that would be necessary to return all renter households to pre-pandemic rent-to-income ratios.15

By contrast, this report relies on detailed rent ledger data on rents charged and paid.16 These granular, unit-level data allow us to trace individual transactions to analyze payment histories and cash flows for current tenants, as well as to track vacancies, providing insight into tenant payments and rental arrears, as well as property revenues from the perspective of property owners. While our data are limited to largely affordable properties, they nonetheless present a detailed picture of the stakes of the economic crisis in those properties–a topic critical to New York City’s recovery. Ultimately, we hope that this research will contribute to the public conversation and inform policymakers as they respond to the ever-shifting economic crisis.

Summary Statistics

How does our sample compare to New York City Low Income Housing Tax Credit (LIHTC) properties?

For this analysis, we draw on rent data during the first year of the COVID-19 crisis and the year prior for properties in New York City. The granularity of the rent ledger data allows us to take a more detailed look at the distribution of arrears and identify characteristics of tenants or properties that fared better during the pandemic.

Our sample differs from the general pool of New York City’s rental properties in important ways, including its focus on affordable properties. The firms that provided rent ledger data are large in size and primarily operate properties financed using Low-Income Housing Tax Credits (LIHTC), which require that rents be affordable to low-income households (those with incomes at or below 50% or 60% of Area Median Income). To qualify for LIHTC units, households must fall within designated income bands at the time of application. Some of the households also have additional tenant- or unit-based rental subsidies that adjust according to income, such as Section 8. Later in this analysis, we identify those households using notes in the rent ledger data, and consider how additional, adjusting subsidies may protect households from an economic shock like the shutdown.17 We also estimate vacancy rates using the share of empty units in each month. Given the design of our sample, our findings are most pertinent to affordable housing properties and the lower income households that reside in them, and not necessarily generalizable to the broader pool of rental units in New York City.

Compared to the stock of LIHTC properties, the properties in our sample are more likely to be larger and located in the Bronx.

The 128 properties in our sample are less likely to be between 2 and 9 units (4.7% of the sample compared to 18% of properties in New York City), and more likely to be larger in size than the full universe of LIHTC properties in New York City (Table 1). Our sample properties are also more likely to be located in the Bronx and considerably less likely to be in Manhattan when compared LIHTC properties across the city.

Table 1: Summary Statistics: NYSAFAH Sample and NYC LIHTC Properties

Summary Statistics
NYSAFAH Sample and NYC LIHTC Properties
Characteristic NYSAFAH Sample, N = 1281 NYC LIHTC, N = 2,0831
Total Number of Units 13,163 178,360
Total Number of Properties 128 2,083
Property Size
2-9 Unit Property 6 (4.7%) 369 (18%)
10-19 Unit Property 12 (9.4%) 246 (12%)
20-49 Unit Property 32 (25%) 505 (24%)
50-99 Unit Property 42 (33%) 503 (24%)
100-199 Unit Property 19 (15%) 274 (13%)
200+ Unit Property 17 (13%) 186 (8.9%)
Bronx 58 (45%) 579 (28%)
Brooklyn 38 (30%) 657 (32%)
Manhattan 26 (20%) 767 (37%)
Queens 6 (4.7%) 54 (2.6%)
Staten Island 0 (0%) 26 (1.2%)
Sources: HUD National LIHTC Database, NYC Department of City Planning, 2015-2019 5-year American Community Survey, NYU Furman Center

1 n (%)


Properties in our sample are primarily located in the Bronx and north Brooklyn, with a smaller number scattered throughout Queens and Manhattan.

Our sample of primarily affordable buildings is concentrated in the south Bronx and north Brooklyn, as well as part of Manhattan and Queens. None of the properties in our sample are located in Staten Island (Figure 1).

Figure 1: Properties in Sample by ZIP Code, Feb 2021

Map of Properties in the Sample by ZIP Code

Household-Level Analysis

We begin by analyzing two-year trends in rent payment rates, rental arrears, and vacancy rates for all units in our sample. In reviewing rent payment rates, we estimate the monthly rent paid as a share of monthly rent owed to assess whether current tenants are covering their full rent in each month. In calculating rental arrears, we estimate the amount of rental debt accruing to households in occupied units, and how this changed during the crisis. This captures one source of lost revenue for owners. We also examine the share of units that were vacant each month, as increasing vacancy rates would represent a second source of lost revenue for landlords. Finally, to shed light on the change in trends during the first year of the pandemic, we compare the 12 months preceding the COVID-19 shutdown (March 2019 to February 2020) to the first year of the pandemic period (March 2020 to February 2021) instead of comparing calendar years.18

How have rental payments, rental arrears, and vacancies changed in this sample of New York City affordable housing during the pandemic?

During the first year of the COVID-19 crisis, the payment rate fell below that of the previous year in every month except June and July.

We find that monthly payment rates were lower after the start of the COVID crisis than they were before (Figure 2). The average monthly payment rate in the first year of the pandemic was 94.7 percent, almost four percentage points lower than the prior year average of 98.1 percent. Payment rates were particularly low in April of 2020, just after the beginning of the crisis, as well as in August of 2020, after the extended federal employment benefits expired in July. While an average payment rate of 95 percent may seem high, any payment rate below 100 percent contributes to increased rental arrears that accumulate over time.

Figure 2: Monthly Rent Paid as a Share of Monthly Rent Charged

Line graph of payment rates across the sample// over time.

While rental arrears were increasing before COVID-19, they more than doubled between February 2020 and 2021.

In the first year of the pandemic (March 2020 to February 2021), the total accumulated rental arrears owed by tenants of all properties increased by 108.4 percent (Figure 3). Rental arrears increased during the prior year, too, but at a notably lower rate (43.0%). Focusing on the pandemic period, total rental arrears increased most dramatically immediately after the economic shutdown in April and May 2020, as well as after the expiration of expanded federal unemployment benefits in August. 

Figure 3: Total Accumulated Rental Arrears

Line graph showing total accumulated rental arrears across// portfolios over time.

The share of tenant households with any rental arrears increased by five (5) percentage points between the year prior to COVID and the first year of the pandemic.

Overall, a higher proportion of households owed some amount of rent to their landlords during the first year of the pandemic than the prior year. The household rent debt ranges from relatively small amounts to extreme arrears. The share of households owing any rent increased by 4.9 percentage points, from an average of 49.9 percent between March 2019 and February 2020 to an average of 54.8 percent the following year (Figure 4). The greatest monthly increase in the share of indebted households occurred at the beginning of the crisis, between March and April of 2020. The share of households with any arrears decreased in July 2020, before rising again. Notably, the share of indebted households was increasing between March 2019 and February 2020, even before the pandemic. 

Figure 4: Share of Tenant Households with Any Rental Arrears

Line graph showing Share of Tenant Households with Any Rental Arrearsover time.

The dollar amount owed by households with any rent arrears deepened dramatically: the average rental debt increased by 65.7 percent between February 2020 and 2021.

While the increase in the share of households with rental debt increased by five percentage points in the first year of COVID-19 compared to the prior year, the average rent owed by those households increased more dramatically (Figure 5). Between February 2020 and the following year, average rental debt among those who owed any rent increased by 65.7 percent, from $2,073 to $3,435. In contrast, between February 2019 and 2020, the average rental debt increased at a much lower rate of 25.3 percent. 

Figure 5: Average Rent Owed by Households in Rental Arrears 

Bar graph showing Average Rent Owed by Households in Arrears for February 2019, 2020, and 2021.

The share of tenant households owing more than $3,000 rose to 15.8 percent by February 2021, six percentage points higher than in February 2020.

The above analysis considers tenants with any rent owed, including those with very small amounts of arrears that may well be paid off in the near term. Landlords tend to file nonpayment eviction cases at or around the time a tenant has significant arrears, typically around 2 months of rent.19 Using $3,000 as a proxy for that threshold,20 we see that the share of tenant households at or above that level of debt increased by more than six percentage points over the initial year of the pandemic, from 9.5 percent in February 2020 to 15.8 percent in February 2021 (Figure 6). As of February 2021, this group owed on average more than $10,000 per household ($10,154). The deepening of debt particularly accelerated between March and May 2020, as the economic shutdown first went into effect. 

Figure 6: Share of Tenant Households Owing More than $3,000 

Line graph showing share of tenants owing more than $3,000 for each month of the year, separately for pre- and post-covid.

The number of households that owed more than $10,000 in rental arrears increased by 140 percent between February 2020 and 2021.

Focusing on the increase in households with sizable rental arrears, the number of households that owed more than $3,000 increased by 65.5 percent between February 2020 and February 2021 (1,244 and 2,059 households). This group may be particularly at risk for future eviction. The number of households in extreme rental debt (owing more than $10,000) increased by 140 percent during the same time period (280 and 672 households, respectively). Further underscoring the expansion of extreme rent debt during the crisis, the share of all rent debt that is owed by households in extreme debt rose from 34.3 percent in February 2020 to 52.4 percent the following year.

Figure 7: Number of Units With Rental Arrears Greater Than $3,000 and Greater Than $10,000

Bar graph showing number of Units With Rental Arrears  greater Than $3,000 and Greater Than $10,000 for Feb 2020 and Feb 2021

While vacancy rates increased slightly during the first year of the pandemic, they remained relatively low in our sample, averaging 2.2 percent during that year.

The overall vacancy rate between March 2020 to February 2021 slightly outstripped the vacancy rate the year prior (averaging 2.2% and 2.0%, respectively) but was quite low in both years (Figure 8). Low vacancy rates may not be surprising for this sample of primarily affordable properties, which typically have low turnover and long waiting lists to occupy newly available units. Indeed, affordable housing in New York City has historically had extremely low vacancy rates.21 The slight increase in vacancy rates is in addition to increasing rental arrears among occupied units (as shown above).22

Figure 8: Vacancy Rate, Pre-COVID and First Year of COVID

Line graph showing monthly vacancy rates between// 3/2019 and 2/2021

Property-Level Analysis

In this section, we review payment rates and average household balances at the property level. While our data consists of a set of portfolios of properties, each owned or managed by one entity, financial management of these assets is mostly performed by property. The revenue and costs at the property level may be most important in determining the financial health of a property.23 For that reason, we investigate rent payment trends at the property level to consider to what extent individual properties experienced large changes in payment and rent debt, and which types of properties fared better during the first year of the pandemic.

How have payment rates and balances changed within properties?

The share of properties with rental payment rates below 95 percent increased from 23 percent before COVID to 59 percent during COVID. 

The distribution of properties’ rental payment rates in the year prior to and during the crisis exhibits a clear leftward shift as a larger number of properties experienced lower payment rates. The median property’s payment rate dropped by 4.3 percentage points (from 98.0% to 93.7%) between the year preceding the pandemic and the first year of the shutdown (Figures 9a and 9b). Similarly concerning, during the first year of COVID-19, the share of properties with payment rates below 95 percent (a typical standard for multifamily affordable housing underwriting24) increased from 23.4 percent prior to the crisis to 59.4 percent. The share of properties with very low payment rates (below 90%), also nearly tripled, increasing from 7.8 percent to 21.1 percent. Between the pre-COVID year and the first year of COVID, 76.6 percent of properties saw a decline in payment rates. Even prior to COVID, however, there was a notable amount of variation in property-level payment rates.

Figure 9a: Monthly Rent Paid as a Share of Monthly Rent Charged, March 2019 - February 2020 

Bar graph showing the distribution of property-level payent ratesestimated between March 2019 - February 2020.

Figure 9b: Monthly Rent Paid as a Share of Monthly Rent Charged, March 2020 - February 2021

Bar graph showing the distribution of property-level payent ratesestimated between March 2020 - February 2021.

Between February 2020 and February 2021, 93.0 percent of properties experienced an increase in average rental balance per occupied unit.

Examining properties’ average unit rental balances—which are estimated across all occupied units in the property, not just among those that owe rent as in figure 5 above—provides insight into how lower payment rates affect owner residential rent revenue at the property level.25 In almost all of the properties in our sample, the average household balance increased over the course of the first year of the crisis (Figure 10). For the 7 percent of properties with a drop in average unit balance, the decline was comparatively small. There is also a great deal of variation among properties. The average increase in household balances for the 25 percent of properties with the smallest increases (or even decreases) was $90 per unit, compared to $1,967 for the 25 percent of properties with the largest increases. The distribution of change in average household balances has a long right tail, with three outlying properties that saw average balances increase by more than $3,500 between February 2020 and 2021. 

Figure 10: Change in Average Unit-level Rental Balance per Property

Bar graph showing number of Units With Rental Arrears  greater Than $3,000 and Greater Than $10,000 for February 2020 and February 2021

Where were properties with the lowest 12-month payment rates located?

Properties in the Bronx were disproportionately likely to have some of the lowest payment rates during COVID.

Properties in some parts of the city saw much greater declines in payment rates during the pandemic than others, providing insight into which tenants and owners saw the greatest changes in rent payment. Within our sample, the properties in the Bronx were disproportionately likely to fall into the lowest third of payment rates during the first year of the pandemic (Table 2). While 45.3 percent of properties in our sample were located in the Bronx, 65.1 percent of the properties with the lowest third of payment rates between March 2020 and February 2021 were located in the borough. Conversely, properties in Manhattan and Queens fared the best out of the sample, and were disproportionately likely to fall in the top two thirds in terms of payment rates after the start of COVID.

Table 2: Sample Characteristics by Borough

Sample Characteristics by Borough
Borough Share of Properties in Borough Share of Properties in Lowest Third for
Payment Rates in the First Year of COVID
Bronx 45.3% 65.1%
Brooklyn 29.7% 30.2%
Manhattan 20.3% 4.7%
Queens 4.7% 0.0%
Source: NYU Furman Center

What type of properties experienced the largest declines in payment rates?

Properties with the largest decline in payment rates had the lowest share of tenants/units that were subsidized, and were also smaller on average than the rest of the sample.

We review changes in payment rates according to property size and the presence of additional subsidies, two characteristics potentially related to rental payment flows and financial health of the property. In terms of subsidies, the programs we track in Table 3 adjust according to household income (e.g., Section 8), and may add an additional layer of protection against economic shocks for owners and tenants, distinct from low or fixed rent levels common across all LIHTC properties. In terms of size, those low-income renters disproportionately likely to be impacted by the economic shutdown26 are also more likely to live in smaller buildings.27 Finally, there are two important caveats to consider when reviewing the findings in Table 3: first, our sample of properties are somewhat larger (in terms of units) than the average LIHTC property in New York City, and so the findings may not be true of LIHTC properties more generally. Second, our sample of properties are within portfolios of larger property owners, so these findings should not be taken to represent the experiences of smaller firms and landlords.

To consider the characteristics of properties that have so far weathered the pandemic better than others, we break our sample of properties into quartiles according to their percentage-point change in payment rate between the year prior to the crisis and the first year of COVID. We see considerable variation across properties in the change in payments rates. While the top quartile experienced a 15.5 percentage point decline in payment rates, the properties in the lowest quartile experienced a 2.8 point increase in payment rates during the first year of the crisis. Large declines in payment rates are fairly concentrated among properties, with half of properties experiencing less than a 1.25 percentage point decline across the two time periods.

In terms of the presence of additional subsidies, properties in the lowest quartile of changes in payment rates also had the highest average share of subsidized tenants or units (62.9%). Conversely, properties in the quartile of largest declines in payment rates had the lowest share of subsidized units on average (35.9%). This is consistent with income-based subsidies adjusting to changes in incomes, providing some protection against economic downturns. The properties hardest hit in terms of declines in payment rates were also slightly smaller on average compared to the rest of the sample—averaging 59 units compared to the lowest quartile’s 75 unit average—but the relationship between size and payment rate quartile was not monotonic as the middle 50 percent of properties were the largest on average.28 Among a few key property characteristics there is one clear relationship: that between resilient payment rates during the pandemic and a higher share of units with additional subsidies.

Table 3: Property Characteristics by Difference in Payment Rate

Property Characteristics by Difference in Payment Rate
(Mar 2019 - Feb 2020, Mar 2020 - Feb 2021)
Payment Rate Count of Properties Point Change in Payment Rate Average Subsidy Rate Average Property Size
Top Quartile: Properties with the Largest Decline in Payment Rate 32 -15.5 35.9 59
Middle-High Quartile: Properties with High-Moderate Decline in Payment Rate 32 -5.4 39.3 153
Middle-Low Quartile: Properties with Low-Moderate Decline in Payment Rate 32 -1.2 55.8 124
Low Quartile: Properties with the Least Decline (or Increase) in Payment Rate 32 2.8 62.9 75
Source: NYU Furman Center


Within our sample of primarily affordable portfolios, we find that rental payments declined and a higher share of households were in rental debt after the first year of the pandemic compared to the year prior. The most dramatic change was in the deepening of rent debt, with a 65.7 percent increase in average rental debt owed among households with rental arrears, and the number of households in extreme arrears more than doubling. While owners contended with lower rent payment rates during the crisis, vacancy rates only increased by a slight margin and remained quite low. The slight spreading and significant deepening of rental debt within households during the pandemic raise concerns about the ability for renters to cover their accumulated rental arrears, even as the economy recovers, and especially when eviction moratoria are lifted. For owners, lower payment rates and lost rental revenue could translate to challenges covering mortgage payments or maintaining buildings over time.

At the property level, median payment rates dropped and average rental balances increased over the first year of COVID-19. Here too, the largest changes are somewhat concentrated. The lowest payment rates during the pandemic were concentrated in properties in the Bronx, although the geographic scope of our data is limited. Smaller properties fared worse in terms of declines in rent payment rates. Conversely, properties with higher shares of units with additional subsidies, such as Housing Choice Vouchers, appeared to be better protected against the economic crisis. Understanding the distribution of rent payments and rental arrears across properties and their tenants helps us consider which may be in greatest need of targeted rental assistance, and how much assistance may be needed at the unit or property level. This may also raise additional questions about how to design for resilience during future crises.

While New York City’s renters have experienced a devastating year, hundreds of millions of dollars in emergency rental assistance have been allocated directly to the City of New York, with over $2 billion allocated to the State of New York,29 to help cover current and accumulating rental arrears. Policymakers face critical questions about how to apportion this assistance in a way that is effective in stabilizing the most vulnerable households. It is our hope that this analysis underscores the value of detailed rental data by providing key insight into the financial landscape of renters as the city moves towards a recovery.

Technical Appendix

This appendix describes the data and estimates underlying the analysis outlined in this chapter. The data were pulled directly from firms’ property management systems (typically Yardi or Bostonpost) by their own employees and cleaned of any identifying information, including building address and tenant name, before being shared with our team. We then cleaned the data to ensure standardization across different portfolios. More detail on our methodology is provided below.


The data in this analysis combine information from rent ledgers, property directories, and tenant directories from January 2019 to February 2021. The rent ledger data track tenant payments and charges in each occupied unit along with the actual date of the transaction, the overall tenant balance, the post-date-month (or the intended date of the transaction, which can differ from the transaction date), a charge code for the type of transaction, and any related notes. The property directories list the units in each property as well as the property ZIP Code, and the tenant directories list the lease start and end dates, tenant move-in and move-out dates, and sometimes include unit- or tenant-level program information (such as subsidies or tax financing). 

Excluded Records

Commercial Tenants

For this analysis, we use the transaction-level charge codes and notes to identify and exclude any commercial tenants, such as grocery stores or offices, as well as “units” that represent building-level laundry or telecommunications income.

Debt Write-Offs

We also use charge codes to isolate and exclude debt write-offs. According to interviews with our participating firms, when they cannot collect a payment from a tenant, they will write off that charge or range of charges. The write-offs show up in the data as a reversing charge and are typically coded as “bad debt” or “write off charge”. To more accurately reflect the cash flow over time, we drop these debt write-offs and include forgiven debt in the debt totals above. However, we are not able to exclude any debt write-offs that occurred before our data set begins in January 2019. 

Reverse Charges

Reverse charges are also excluded from our analysis. Reverse charges reference charges that could have been made in error and which are subsequently reversed at a later date, transactions related to past tenants that have since left the building and have outstanding balances, or a specific issue related to a subsidy that was suspended. 

Miscellaneous Exclusions

In addition to the aforementioned exclusions, we also remove transactions related to rents for building superintendents. We exclude monthly tenant total balances, and calculate our own accrued balance per tenant. We also remove records for a handful of properties that report very large subsidy payments in one month that are meant to cover transactions throughout a fiscal year, since those anomalous payments distort the sample’s trajectory of payment rates over time. Finally, we removed a few properties from the sample after determining that they were accounts used to track building expenses rather than residential properties.

Constructed Variables

We estimate rent by calculating the median monthly charge during each tenancy. In addition, we calculate balance by summing charges and payments at the end of each month. A positive balance means that a tenant is in arrears, while a negative balance means that a tenant has overpaid. Currently, these charges and payments include tangential fees (like legal fees or key fees) as well as fines and damages levied against the tenant. In future analysis, we hope to unbundle these non-rent related charges.

We estimate monthly vacancy rates by calculating the share of days that units are vacant in each month. We use a balanced panel with this analysis, which protects against skew due to new buildings with high vacancy rates during lease up.

Finally, we identify tenant and/or unit level subsidies based on keywords in the transaction charge codes and notes; if the record contains a matching keyword (e.g. “subsidy” or “HUD”), we classify the tenant as subsidized. Based on high-level estimates from our data providers, we believe that we are undercounting the number of subsidized tenants in certain portfolios. In future iterations of the project, we hope to collect more precise data on subsidies to further refine our analysis.

1 W. Holmes Finch and Maria E. Hernández Finch, Poverty and Covid19: Rates of Incidence and Deaths in the United States During the First 10 Weeks of the Pandemic. Frontiers in Sociology, 2020(5): 47. https://www. frontiersin.org/article/10.3389/fsoc.2020.00047; Matthew A. Raifman, Julia R. Raifman, Disparities in the Population at Risk of Severe Illness from COVID-19 by Race/Ethnicity and Income. American Journal of Preventive Medicine, 2020;59(1):137−139.

2 Kim Parker, Rachel Minkin, and Jesse Bennett, Economic Fallout From COVID-19 Continues To Hit Lower-Income Americans the Hardest. Pew Research Center, (September 24, 2020). https://www.pewsocialtrends.org/2020/09/24/economic-fallout-from-covid-19-continues-to-hit-lower-income-americans-the-hardest/. What are the Housing Costs of Households Most Vulnerable to Job Layoffs? An Initial Analysis. NYU Furman Center (March 30, 2020). https://furmancenter.org/thestoop/entry/what-are-the-housing-costs-of-households-most-vulnerable-to-job-layoffs-an

3  Ryan Brenner. Data Update: Eviction Filings in New York City as Some Renter Protections Expire. The Stoop: NYU Furman Center Blog (December 4, 2020). https://furmancenter.org/thestoop/entry/data-update-eviction-filings-in-new-york-city-as-some-renter-protections-ex. Ryan Brenner. Data Update: Eviction Filings in NYC Since COVID-19. NYU Furman Center (September 29, 2020). https://furmancenter.org/thestoop/entry/data-update-eviction-filings-in-nyc-since-covid-19

4 Coronavirus Aid, Relief, and Economic Security (CARES) Act: What You Need to Know About Filing for Unemployment Insurance During the Pandemic. New York State Department of Labor (nd). https://dol.ny.gov/coronavirus-aid-relief-and-economic-security-cares-act

5 Governor Cuomo Signs the COVID-19 Emergency Eviction and Foreclosure Prevention Act of 2020. New York State, Governor’s Press Office. (December 28, 2020). https://www.governor.ny.gov/news/governor-cuomo-signs-covid-19-emergency-eviction-and-foreclosure-prevention-act-2020

6 Tara Siegel Bernard and Ron Lieber. F.A.Q. on Stimulus Checks, Unemployment and the Coronavirus Plan. New York Times (March 17, 2021). https://www.nytimes.com/article/coronavirus-stimulus-package-questions-answers.html  Zack Friedman. Stimulus Package Released Today—$1,200 Second Stimulus Checks, Unemployment Benefits And Payroll Protection Program. Forbes (July 22, 2020). https://www.forbes.com/sites/zackfriedman/2020/07/22/second-stimulus-checks-new-stimulus/?sh=4a6e4d77879e https://www.nytimes.com/article/coronavirus-stimulus-package-questions-answers.html  Tony Romm. Congress adopts $1.9 trillion stimulus, securing first major win for Biden. The Washington Post (March 10, 2021). https://www.washingtonpost.com/us-policy/2021/03/10/house-stimulus-biden-covid-relief-checks/

7 Emergency Rental Assistance Program. US. Department of the Treasury. https://home.treasury.gov/policy-issues/coronavirus/assistance-for-state-local-and-tribal-governments/emergency-rental-assistance-program?utm_source=NLIHC+All+Subscribers&utm_campaign=4aafde323d-CTA_050721&utm_medium=email&utm_term=0_e090383b5e-4aafde323d-293293665&ct=t(CTA_050721)

8 Spencer Lee. LAS Continues To Warn Against Potential "Tsunami" of Evictions in NYC. The Legal Aid Society (July 13, 2020). https://legalaidnyc.org/news/eviction-tsunami/

9 Matthew Desmond and Carl Gershenson, Who gets evicted? Assessing Individual, Neighborhood, and Network Factors, Social Science Research 2015(1): 16. http://dx.doi.org/10.1016/j.ssresearch.2016.08.017

10 Noah Buhayar, Oshrat Carmiel, and Nic Querolo. Landlords Squeezed Between Missed Rent and Overdue Mortgages. Bloomberg (April 1, 2020). https://www.bloomberg.com/news/articles/2020-04-01/rent-day-arrives-with-u-s-landlords-bracing-for-missed-payments

11 How are Smaller Landlords Weathering the COVID-19 Pandemic, FACTSHEET. Terner Center for Housing Innovation at UC Berkeley and National Association of Hispanic Real Estate Professionals (July 2020). https://ternercenter.berkeley.edu/wp-content/uploads/pdfs/NAHREP-Terner-Center-Survey-Factsheet-July-2020.pdf

12 NMHC Rent Payment Tracker. National Multifamily Housing Council (May 2021). https://www.nmhc.org/research-insight/nmhc-rent-payment-tracker/

13 Community Housing Improvement Program. Survey: Rent-Regulated Tenants Owe $1.1 Billion in Arrears. CHIP Press Release. Nd. https://chipnyc.org/survey-rent-regulated-tenants-owe-1-1-billion-in-arrears/

14 NYU Furman Center. Understanding the Potential Magnitude of Rent Shortfalls in New York Due to COVID. The Stoop: NYU Furman Center Blog (June 4, 2020 ). https://furmancenter.org/thestoop/entry/understanding-the-potential-magnitude-of-rent-shortfalls-in-new-york-state

15 Sarah Strochak, Aaron Shroyer, Jung Hyun Choi, Kathryn Reynolds, and Laurie Goodman. How Much Assistance Is Needed to Support Renters through the COVID-19 Crisis? The Urban Institute (June 2020). https://www.urban.org/sites/default/files/publication/102389/how-much-assistance-is-needed-to-support-renters_1_1.pdf

16 For a summary of an early installment of these data through September 2020 see: Hayley Raetz, Daniel Waldinger, and Katherine O’Regan. Rent Payments in a Pandemic: Analysis of Affordable Housing in New York City. NYU Furman Center (March 2021). https://furmancenter.org/files/Rent_Payments_in_a_Pandemic_-_Final.pdf

17 For more detail on categorizing subsidy units, please refer to the technical appendix.

18 While some of the figures below are similar in structure to our previous work on this topic, the sample differs in order to create a balanced panel of properties across the new period of analysis.

19 In a 2019 analysis, we found that the rent amount sought in eviction filings typically fell between 2.5 and 3.0 months of the median gross rent for the sub-borough area and year of the filing. See: Trends in New York City Housing Court Eviction Filings. NYU Furman Center (November, 2019). https://furmancenter.org/files/publications/NYUFurmanCenter_TrendsInHousingCourtFilings.pdf

20 We use this threshold based on our findings in our previous brief that about 60% of our sample were in units that rented for $1,500 or less per month.

21 In 2017, New York City units renting for below $800 had a vacancy rate of 1.15 percent and units renting for between $800 and $999 had a vacancy rate of 2.09 percent. See: Elyzabeth Gaumer. Selected Initial Findings of the 2017 New York City Housing and Vacancy Survey. New York City Department of Housing Preservation and Development (2018).

22 We also examined vacancy rates according to property size, subsidy level, and changes in payment rate and rental balance during the pandemic, but we found similar rates between categories. Vacancy rates appeared to increase more for high rent properties, but those increases were small and rates generally remained low.

23 For example, for most multifamily properties, reserves are held in escrow and debt is paid at the property level, rather than across an owner’s portfolio.

24 For nearly all affordable housing financed in New York City, in order to mitigate risk, lenders typically only recognize 95% of the potential rental revenue for a property when underwriting multifamily loans. The 5% subtraction is a recognition of potential vacancies as well as uncollected rent. In our analysis, we focus only on uncollected rent at the household level.

25 Commercial units also provide revenue for property owners, but those were excluded from this analysis to focus on trends for residential tenants.

26 What are the Housing Costs of Households Most Vulnerable to Job Layoffs? An Initial Analysis. NYU Furman Center (March 30, 2020). https://furmancenter.org/thestoop/entry/what-are-the-housing-costs-of-households-most-vulnerable-to-job-layoffs-an

27 Noah Kazis, COVID-19 and the Rental Market. NYU Furman Center (April 30, 2020). https://furmancenter.org/thestoop/entry/covid-19-and-the-rental-market

28 While we reviewed the change in vacancy rates for each category, there was little difference between the groups.

29  Emergency Rental Assistance Program: Payments to States and Eligible Units of Local Government U.S. Department of the Treasury. (January 26, 2021). https://home.treasury.gov/system/files/136/Emergency-Rental-Assistance-Payments-to-States-and-Eligible-Units-of-Local-Government.pdf.  Emergency Rental Assistance Program: Allocations to States and Eligible Units of Local Government U.S. Department of the Treasury. (May 7, 2021). https://home.treasury.gov/system/files/136/ERA2_Allocations_Eligible_Entities_572021.pdf.