What are the effects of rent control policies on housing market dynamics and tenant stability?

Rent control policies yield mixed results, decreasing rents in controlled units by 4-47% and extending tenant stays by up to six years, while simultaneously reducing housing supply and increasing eviction filings, with effects varying by policy design and local market conditions.

Abstract

Rent control policies yield mixed effects on housing market dynamics and tenant stability. In regulated markets, studies report rent declines ranging from 4% to 47% in controlled units while some analyses note rent increases in uncontrolled or post‐decontrol sectors. In one San Francisco study, rents rose concurrently with a 15% reduction in housing supply and a 20% drop in tenant mobility. Other research documents tenants staying an extra six years under tighter regulation, although reports of 83–127% higher eviction filings suggest displacement risks in certain settings.

Separate analyses show shifts in market composition. For example, one study cited annual rent subsidies of about US$2440 (roughly 27% of income), and another observed reduced racial disparities accompanied by increased minority presence. These findings, based on quasi‐experimental and econometric approaches across diverse jurisdictions, indicate that the impacts of rent control vary with policy design and local market conditions.

Methods

We analyzed 40 sources from an initial pool of 989, using 8 screening criteria. Each paper was reviewed for 5 key aspects that mattered most to the research question. More on methods

Papers identified with Elicit search

• n = 989
• Papers screened using: Intervention Type, Outcome Measures, Study Design, Geographic Context, Public/Social Housing Focus, Housing Voucher/Assistance Focus, Empirical Data, Comparison Groups
• n = 989
• Papers screened out
• n = 949
• Papers included for extraction
• n = 40

Paper search

Using your research question “What are the effects of rent control policies on housing market dynamics and tenant stability?”, we searched across over 126 million academic papers from the Semantic Scholar corpus. We retrieved the 989 papers most relevant to the query.

Screening

We screened in sources based on their abstracts that met these criteria:

• Intervention Type: Does this study examine rent control, rent stabilization, or rent regulation policies?
• Outcome Measures: Does this study measure at least one of the following: housing market outcomes (rental supply, housing prices, construction rates, property maintenance, market competition) OR tenant stability outcomes (residential mobility, displacement rates, tenure length, eviction rates, housing security)?
• Study Design: Is this study one of the following: randomized controlled trial, quasi-experimental design, natural experiment, longitudinal study, cross-sectional study with comparison groups, systematic review, or meta-analysis?
• Geographic Context: Was this study conducted in urban or metropolitan areas with rental housing markets?
• Public/Social Housing Focus: Is this study NOT focused solely on public housing or social housing programs without rent control components?
• Housing Voucher/Assistance Focus: Is this study NOT examining only housing voucher or rental assistance programs without rent regulation?
• Empirical Data: Is this study NOT purely theoretical or modeling without empirical data?
• Comparison Groups: Is this study NOT a case study or descriptive study without comparison groups or control conditions?

We considered all screening questions together and made a holistic judgement about whether to screen in each paper.

Data extraction

We asked a large language model to extract each data column below from each paper. We gave the model the extraction instructions shown below for each column.

• Study Design Type:
  Identify the primary research design used in the study. Look in the methods section for explicit description of the study design.

Possible design types include:

• Difference-in-differences
• Quasi-experimental
• Empirical analysis
• Econometric study
• Cross-sectional analysis

If multiple design elements are used (e.g., difference-in-differences with discontinuity design), list all relevant approaches. Be precise about the specific methodological approach.
If the design type is not clearly stated, review the analytical methods and statistical techniques used to infer the most appropriate design classification.

• Geographic Setting and Context:
  Extract the specific geographic location(s) where the study was conducted. Include:
• Country
• City/metropolitan area
• Specific neighborhoods or regions (if applicable)

If multiple geographic areas are studied, list all of them. Note any specific contextual details about the housing market that are relevant to understanding the rent control policy (e.g., housing density, urban vs. suburban, economic conditions).

If geographic context is not explicitly stated, check methods, data sources, and results sections for implicit geographic information.

• Rent Control Policy Details:
  Extract comprehensive details about the rent control policy:

• Year of policy implementation

• Specific type of rent control (first-generation, second-generation, etc.)

• Key policy mechanisms (e.g., price caps, exemptions)

• Scope of application (which housing units are covered)

Look in introduction, methods, and policy description sections. If multiple policy aspects are discussed, provide a comprehensive summary.
If policy details are complex, create a bulleted list to capture nuanced information. Note any explicit exceptions or special conditions in the policy.

• Policy Impact Outcomes: Identify and extract the specific outcomes measured related to rent control policy:
• Rental prices (regulated and unregulated sectors)
• Housing supply
• Land values
• Maintenance investments
• Tenant stability
• Demolition rates
• Housing market dynamics

Extract quantitative values where available. If multiple outcomes are measured, list all with their specific measurements and statistical significance.

Prioritize outcomes directly addressing rental prices, housing supply, and market dynamics. Look in results and discussion sections for comprehensive outcome reporting.

• Key Quantitative Findings: Extract the primary quantitative results, focusing on:
• Magnitude of effects
• Statistical significance
• Confidence intervals or standard errors (if provided)
• Directional impact of rent control policy

Prioritize results that directly answer the research question about housing market dynamics and tenant stability.

If multiple statistical models or analyses are presented, extract results from the primary or most comprehensive analysis. Include specific numeric values and percentage changes where available.

Ensure extracted findings are directly quoted or paraphrased from the results section, maintaining the original statistical context.

Results

Characteristics of Included Studies

Across 40 studies of rent control policies, the following patterns were observed:

Primary Outcomes Measured:

• Rental prices:Measured in 25 studies.
• Housing supply (including new construction and conversions):Measured in 20 studies.
• Tenant stability (including tenure duration, mobility, turnover, and displacement):Measured in 16 studies.
• Maintenance, quality, investment, or renovations:Measured in 9 studies.
• Evictions or eviction filings:Measured in 3 studies.
• Land values, property values, or wealth transfer:Measured in 5 studies.
• Vacancy rates:Measured in 2 studies.
• Market dynamics (including spillovers, misallocation, search/matching costs, and disequilibrium):Measured in 6 studies.
• Rent burden, rent discounts, or rent subsidy:Measured in 4 studies.
• Community composition or segregation:Measured in 2 studies.
• Owner/tenant knowledge, queue time, and income distribution:Each measured in 1 study.
• Other outcomes (such as distribution, race, tenant welfare, and consumption):Found in 5 studies.

Rent Control Policy Type:

• First-generation rent control:Studied in 7 studies.
• Second-generation rent control:Studied in 10 studies.
• Third-generation rent control:Studied in 1 study.
• Rent stabilization:Explicitly labeled in 3 studies.
• No clear specification of policy type:21 studies.
• User value system (other):1 study.

Methodology:

• Quasi-experimental methods (including difference-in-differences, event study, regression discontinuity, interrupted time series, and triple difference):Used in 24 studies.
• Econometric methods (including cross-sectional and empirical econometric analysis):Used in 21 studies.
• Empirical analysis (not otherwise specified):Used in 11 studies.

We did not find mention of some outcomes or policy types for several studies, either due to lack of reporting or lack of access to the full text.

Effects

Effects on Housing Market Dynamics

Across 40 studies, the following patterns were observed in effect direction and statistical significance:

• Decrease in rents:Reported in 11 studies.
• Increase in rents:Reported in 10 studies. Some studies reported both increases and decreases, depending on market segment (for example, regulated versus unregulated units).
• Decrease in supply or construction:Found in 4 studies.
• Increase in supply or construction:Found in 3 studies.
• Increase in tenant stability or tenure:Found in 2 studies.
• Decrease in tenant stability or tenure:Found in 1 study.
• Increase in evictions or displacement:Found in 3 studies.
• Decrease in evictions or displacement:Found in 1 study.
• Increase in property or land values:Found in 1 study.
• Decrease in property or land values:Found in 1 study.
• Increase in vacancy:Found in 2 studies. We did not find studies reporting a decrease in vacancy.
• Increase in rent burden, savings, discounts, or subsidy:Found in 5 studies.
• Mixed, minimal, or no effect:Reported in 5 studies.
• Other outcomes (queue times, demographic changes, misallocation costs):Reported in 2–3 studies.

Statistical significance:

• Explicit statements of statistical significance:Found in 9 studies, based on available full texts or abstracts.
• Explicit statements of non-significance:Found in 2 studies.
• No mention of statistical significance:In the available full texts or abstracts for the remaining 29 studies.

The most common outcome measures were rents or rental prices, supply or construction, tenant stability, tenure or mobility, evictions or displacement, property or land values, and rent burden, savings, or subsidy. We did not find mention of outcome measure information in the available full texts or abstracts for some studies, and some studies reported multiple outcomes.

Effects on Tenant Stability and Demographics

Tenant Composition and Income Distribution

Across these 6 studies:

• Outcome measures:
  • Rent subsidy or discount: 2 studies.
  • Regressive or high-income benefit effects: 2 studies.
  • Minority or racial/ethnic composition or disparity: 2 studies.
  • Rent burden: 1 study.
  • Wealth transfer: 1 study.
  • Some studies covered multiple topics.
• Effect direction:
  • Regressive effects or greater benefits for high-income groups: 2 studies.
  • Positive effect of subsidy on tenure: 1 study.
  • Reduced racial disparity: 1 study.
  • Increased minority presence and decreased poor presence: 1 study.
  • Reduced rent burden with increased Hispanic/foreign-born presence: 1 study.
• Statistical significance:
  • Statistical significance or robustness was reported in 3 studies, based on available full texts or abstracts.
  • We did not find mention of statistical significance in the available full texts or abstracts for the other 3 studies.

Residential Mobility and Tenure Duration

Across these 6 studies:

• Outcome measures:
  • Mobility: 3 studies.
  • Tenancy or tenure duration: 2 studies.
  • Outmigration: 1 study.
• Effect direction:
  • Decrease only (in mobility): 1 study.
  • Increase only (in tenancy/tenure duration): 2 studies.
  • Mixed effects, with both increases and decreases depending on subgroup or context (for example, by income, unit age, or stabilization status): 3 studies.
• Effect sizes:
  • 20% reduction in mobility: 1 study.
  • 5.7% reduction in mobility with a 10% increase in income: 1 study.
  • Increase of 6 years in tenancy duration: 1 study.
  • 1–2% increase in outmigration: 1 study.
• Statistical significance:
  • We did not find mention of statistical significance in the available full texts or abstracts for any of the 6 studies.

Neighborhood Segregation and Community Composition

Across these three studies:

• Outcome measures:
  • Segregation: 1 study.
  • Exclusionary impact: 1 study.
  • Racial disparities: 1 study.
• Effect direction:
  • Increase in the measured outcome (segregation or exclusion): 2 studies.
  • Decrease in disparities: 1 study.
• Statistical significance:
  • Statistical significance was described as “robust” in 1 study.
  • We did not find mention of statistical significance in the available full texts or abstracts for the other 2 studies.