This special topic poll sought the views of New York City residents on rent control and rent stabilization regulations in New York City. Those queried were asked for their opinions on government regulation of the prices that businesses can charge for goods and services and to comment on rent control systems in New York City, including whether these laws should be changed, whether rent controls should be abandoned when a tenant's income rises above a certain level, whether the controls should be abandoned when a tenant moves out of the apartment, and whether renters in the city were paying too much or too little in rent. Those queried were asked what they believed would happen if the rent controls were abolished, including a possible rise in rental costs, and construction of apartment buildings in the city. A series of additional questions addressed the topic of men's and women's bathing suits. Topics covered whether modern bathing suits were too revealing, whether the respondent intended to wear a bathing suit in public during the summer, how the respondent would describe his/her appearance while wearing a bathing suit, and whether women should be allowed to go topless at public beaches. Background information on respondents includes age, race, ethnicity, sex, education, political party, family income, and whether the respondent owned or rented his/her residence.

Using a 1994 law change, we exploit quasi-experimental variation in the assignment of rent control in San Francisco to study which types of landlords bear the burden of decreased rental payments versus substitute away from supplying rent-controlled housing. We find rent control leads to a long-run decrease in the supply of rental housing. This effect is more pronounced among properties managed by corporate landlords versus individual landlords. Raising revenue for rental subsidies through rent control appears to be regressive, since corporations can evade the tax burden of rent control more easily, likely due to their superior access to capital.

A. SUMMARY Beginning in 2022, the law requires owners of residential housing units in San Francisco to report certain information about their units to the San Francisco Rent Board on an annual basis. For units (other than condominium units) in buildings of 10 residential units or more, owners were required to begin reporting this information to the Rent Board by July 1, 2022, with updates due on March 1, 2023 and every March 1 thereafter. For condominium units and units in buildings with less than 10 residential units, reporting began on March 1, 2023 with updates due every March 1 thereafter. Owners are also required to inform the Rent Board within 30 days of any change in the name or business contact information of the owner or designated property manager. The Rent Board uses this information to create and maintain a “housing inventory” of all units in San Francisco that are subject to the Rent Ordinance.

B. HOW THE DATASET IS CREATED The Rent Board has developed a secure website portal that provides an interface for owners to submit the required information (The Housing Inventory). The Rent Board uses the information provided to generate reports and surveys, to investigate and analyze rents and vacancies, to monitor compliance with the Rent Ordinance, and to assist landlords and tenants and other City departments as needed. The Rent Board may not use the information to operate a “rental registry” within the meaning of California Civil Code Sections 1947.7 – 1947.8.

C. UPDATE PROCESS The Housing Inventory is continuously updated as it receives submissions from the public. The portal is available to the public 24/7. The Rent Board Staff also makes regular updates to the data during regular business hours, and the data is shared to DataSF every 24 hours.

D. HOW TO USE THIS DATASET It is important to note that this dataset contains information submitted by residential property owners and tenants. The Rent Board does not review or verify the accuracy of the data submitted. Please note that historical data is subject to change.

Notes for Analysis - Addresses have been anonymized to the block level - Latitude & Longitude are the closest mid-block point to the unit - Each row is a unit. To count total units, first select a year then count unique ids. Do not sum unit count.

In accordance with Rules and Regulations Section 1.12 (https://www.sf.gov/reports--rent-board-rules-and-regulations), the Rent Board sets the annual allowable rent increase for rent controlled units. The new rates are effective every year on March 1. The amount is based on 60% of the percentage increase in the Consumer Price Index (CPI) for All Urban Consumers in the San Francisco-Oakland-San Jose region for the 12-month period ending October 31, as posted in November by the Bureau of Labor Statistics.

Bearing some similarities to other cities' "rent control" programs, the City administers the Rent Stabilization Ordinance (RSO) to protect tenants from excessive rent increases while allowing apartment owners a reasonable return on their investments.

This replication package is prepared for the paper “Does Rent Control Increase Tenant Unemployment?”, accepted for publication in the Journal of Urban Economics.

Contains buyout declarations and buyout agreements filed at the Rent Board. Rent Ordinance Section 37.9E, effective March 7, 2015, is a new provision that regulates "buyout agreements" between landlords and tenants under which landlords pay tenants money or other consideration to vacate their rent-controlled rental units. For more information, please see: http://sfrb.org/new-ordinance-amendment-regulating-buyout-agreements

Contains buyout declarations and buyout agreements filed at the Rent Board. Rent Ordinance Section 37.9E, effective March 7, 2015, is a provision that regulates "buyout agreements" between landlords and tenants under which landlords pay tenants money or other consideration to vacate their rent-controlled rental units. For more information, please see: https://www.sf.gov/information/buyout-agreements

Data includes eviction notices filed with the San Francisco Rent Board per San Francisco Administrative Code 37.9(c). A notice of eviction does not necessarily indicate that the tenant was eventually evicted, so the notices below may differ from actual evictions. Notices are published since January 1, 1997.

This indicator presents information on key aspects of regulation in the private rental sector, mainly collected through the OECD Questionnaire on Affordable and Social Housing (QuASH). It presents information on rent control, tenant-landlord relations, lease type and duration, regulations regarding the quality of rental dwellings, and measures regulating short-term holiday rentals. It also presents public supports in the private rental market that were introduced in response to the COVID-19 pandemic. Information on rent control considers the following dimensions:  the control of initial rent levels, whether the initial rents are freely negotiated between the landlord and tenants or there are specific rules determining the amount of rent landlords are allowed to ask; and  regular rent increases – that is, whether rent levels regularly increase through some mechanism established by law, e.g. adjustments in line with the consumer price index (CPI).

Data includes eviction notices filed with the San Francisco Rent Board per San Francisco Administrative Code 37.9(c). A notice of eviction does not necessarily indicate that the tenant was eventually evicted, so the notices below may differ from actual evictions. Notices are published since January 1, 1997. Please note that there are blank values for neighborhoods that could not be automatically assigned. These counts are automatically derived and there could be errors, please check the source to verify accuracy. The neighborhood boundaries used in this dataset correspond to these: https://data.sfgov.org/d/p5b7-5n3h

This dataset contains the replication package for the article "Do giving voice and social information help in revising a misconception about rent-control?" Data were collected through a randomized experimental trial to test the effectiveness of different communication formats in debunking a misconception about rent controls. Three communication formats were tested against a benchmark condition, a refutational video (RV): a refutational video with voice (RVV), a refutational video with voice and social information type 1 (RVVS1), a refutational video with voice and social information type 2 (RVVS2).

Abstract

The purpose of the SEPHER data set is to allow for testing, assessing and generating new analysis and metrics that can address inequalities and climate injustice. The data set was created by Tedesco, M., C. Hultquist, S. E. Char, C. Constantinides, T. Galjanic, and A. D. Sinha.

Methodology

SEPHER draws upon four major source datasets: CDC Social Vulnerability Index, FEMA National Risk Index, Home Mortgage Disclosure Act, and Evictions datasets. The data from these source datasets have been merged, cleaned, and standardized and all of the variables documented in the data dictionary.

CDC Social Vulnerability Index

CDC Social Vulnerability Index (SVI) dataset is a dataset prepared for the Centers for Disease Control and Prevention for the purpose of assessing the degree of social vulnerability of American communities to natural hazards and anthropogenic events. It contains data on 15 social factors taken or derived from Census reports as well as rankings of each tract based on these individual factors, groups of factors corresponding to four related themes (Socioeconomic, Household Composition & Disability, Minority Status & Language, and Housing Type & Transportation) and overall. The data is available for the years 2000, 2010, 2014, 2016, and 2018.

FEMA National Risk Index

The National Risk Index (NRI) dataset compiled by the Federal Emergency Management Agency (FEMA) consists of historic natural disaster data from across the United States at a tract-level. The dataset includes information about 18 natural disasters including earthquakes, tsunamis, wildfires, volcanic activity and many others. Each disaster is detailed out in terms of its frequency, historic impact, potential exposure, expected annual loss and associated risk. The dataset also includes some summary variables for each tract including the total expected loss in terms of building loss, human loss and agricultural loss, the population of the tract, and the area covered by the tract. It finally includes a few more features to characterize the population such as social vulnerability rating and community resilience.

Home Mortgage Disclosure Act

The Home Mortgage Disclosure Act (HMDA) dataset contains loan-level data for home mortgages including information on applications, denials, approvals, and institution purchases. It is managed and expanded annually by the Consumer Financial Protection Bureau based on the data collected from financial institutions. The dataset is used by public officials to make decisions and policies, uncover lending patterns and discrimination among mortgage applicants, and investigate if lenders are serving the housing needs of the communities. It covers the period from 2007 to 2017.

Evictions

The Evictions dataset is compiled and managed by the Eviction Lab at Princeton University and consists of court records related to eviction cases in the United States between 2000 and 2016. Its purpose is to estimate the prevalence of court-ordered evictions and compare eviction rates among states, counties, cities, and neighborhoods. Besides information on eviction filings and judgments, the dataset includes socioeconomic and real estate data for each tract including race/ethnic origin, household income, poverty rate, property value, median gross rent, rent burden, and others.

This statistic shows the share of rental housing stock in New York City in 2017, by property type. In 2017, only one percent of New York City's rental housing stock was rent-controlled.

Researchers employed longitudinal policy surveillance to comprehensively describe state responses to the eviction crisis resulting from the emergence of the COVID-19 pandemic and continuing through the end of substantive state intervention. The study relied on an exhaustive collection of all emergency orders and legislation that controlled the eviction process, related to protections under federal moratoria, or provided support to tenants and that were issued by state governors, courts, and legislative bodies between March 13, 2020 and March 1, 2022. Researchers developed a dynamic, novel dataset consisting of over 50 indicators which captured the temporal and substantive features of these moratoria and renter-supportive measures. To confirm that the dataset was complete, researchers provided state governors and court officials with lists of collected orders from their states and incorporated any needed additions. From this validated dataset, researchers created a time series cross-sectional dataset that tracked changes in a state’s overall eviction moratoria and supportive measures over time. For a complete description of the variables tracked, please see the codebooks included with the dataset.

Housing affordability is a major concern for many Los Angeles County residents. Housing constitutes the single largest monthly expense for most people. Renters are more susceptible than homeowners to high housing costs, especially if they live in a community without rent control or other tenant protection policies. Compared to homeowners, renters are also more likely to experience housing burden or housing instability and have a higher risk for homelessness.For more information about the Community Health Profiles Data Initiative, please see the initiative homepage.

This is a study of tenant attitudes and experiences. The survey included questions on type of residence, persons living with the respondent, monthly rent and what it includes, neighborhood conditions, condition of the residence, relations with owner and manager, respondent's and respondent's family's history of home and property ownership, opinions on rents in the area, opinions on rent control, opinions of landlords in general, problems with present and past landlords, tenant organizations, political participation and ideology, importance of rent control as a local political issue, labor union and other organizational memberships, opinions on how much control a tenant should have, private ownership of housing in general, government actions to help tenants, age, employment, education, income, race, sex, zip code, number of telephones, and language in which interview was conducted. There are 1598 respondents in the Los Angeles file. An additional 500 cases were attempted for the Santa Monica file.

This dataset includes requests for information filed with the San Francisco Rent Board under SF Admin. Code 37.9(i) or (j). Under the Code, residents receiving an eviction notice may claim protected status either due to age and/or disability and length of tenancy or based on length of tenancy and occupancy of a child under the age of 18 during the school year. They need not be filed as estoppels. However, it has become common practice to add the request pursuant to (I) or (j) to estoppels, which is a legal term for limiting a legal action that could normally be taken, e.g. evicting. Data are available starting in January 1999.

This map provides information about apartments in San Jose that are covered by the Rent Stabilization Program, Tenant Protection Ordinance and/or the Ellis Act Ordinance. If you have any questions, please call the Rent Stabilization Program at 408-975-4480.

The Taipei City Rent and Lease Commission handles cases for the year 111.