The Impact of a New Rent Control Law on Tenants and Owners

By | October 3, 2022

Rental housing is one of the most important sectors in the economy. According to the US Census, in 2019, out of 123 million housing units in the United States, 44 million units, or 36%, were occupied by renters. The median household spent 35% of its income on rent, while 22% of households spent more than 50% of their income on rent. Moreover, rents are increasing at a record pace. In February 2022, the CoreLogic single-family rent index grew by 13.1% year-over-year, the fastest increase in almost two decades. 

Rental housing is also highly regulated, from zoning laws to building codes and subsidies. One of the most impactful regulations is rent control. As housing becomes more expensive, rent control is increasingly being considered by state and local governments. Starting in 2019, new rent control laws have been enacted in cities across the country, including areas with no history of rent control, such as Maine and Minnesota. For the first time in 70 years, rent control has been enacted at the state level in Oregon and California, and state legislatures are debating similar laws in New York, Illinois, and Massachusetts. Given the importance of housing for consumption inequality and wealth accumulation, understanding the economic consequences of these new rent control laws is imperative for policymakers, practitioners, and voters. 

In our recent paper, we investigate two of the most important consequences of rent control: changes in property values and the redistribution of wealth. While basic economic analysis indicates that the outcomes of rent control include reduced supply, deadweight loss, and a transfer of wealth from property owners to renters; it is challenging to establish the causal effect of rent control on these outcomes. First, landlords may endogenously respond to rent control by evading the law, neglecting maintenance, or removing properties from the rental market (Autor et al., 2004, Diamond et al., 2019). Second, deteriorating housing quality and evasion of laws are difficult to observe directly and occur gradually over many years. Similarly, a city’s rent control law may evolve slowly over time. Studying market values offers a potential solution to these challenges. Because market prices are forward-looking and incorporate new information, they offer the opportunity to observe the long-run and endogenous impacts of rent control immediately. 

Thus, to provide new evidence on the effects of rent control on property values and wealth transfers, we study the effects on property prices of the enactment of rent control in St. Paul, Minnesota, in November 2021. In general, the setting is ideal because (1) there was little anticipation of the law, and no other confounding laws were passed at the same time; (2) when passed, St. Paul’s new law had simple, though extreme, provisions: annual rental growth was capped at 3% year-over-year, with no inflation-adjustment and no provision to allow rental prices to be reset to market prices upon vacancy, and all residential properties were covered by the law, with very few exceptions; (3) the real estate located outside of St. Paul’s city limits provides a similar control sample for comparison; and (4) St. Paul is a relatively large, diverse city that allows us to study the heterogeneous impact of rent control across different property types, locations, tenants, and owners.  

To summarize our main results, we find that the introduction of rent control caused property values in St. Paul to decline by about 6%, on average, over the following three months. Rental properties declined by about 12%.  This loss in value is driven by lower future rents, which benefits current renters. Using the losses in property value as a measure of the transfer of wealth from owners to renters, we find that the transfers were largest in neighborhoods where renters had higher incomes and owners had lower incomes, opposite of the law’s goal of benefiting lower-income neighborhoods.  

We first provide more details on the historical context of St. Paul’s rent control law and then present a discussion of our main results. 

Historical Context of Rent Control 

Rent control laws in the United States have historically been implemented in a small number of states, most notably New York, New Jersey, and California. The federal government enacted the so-called first generation of rent control laws during World War II as a temporary method to stabilize rental markets during a period of relocation and economic uncertainty. During the post-War housing boom, rents declined, and the temporary rent control laws were not renewed, except in New York City. 

The second generation of rent control laws was enacted in the 1970s in response to growing inflation and as part of a general regulatory practice of price controls. New laws were passed in Massachusetts, Washington DC, and California. These second-generation laws were less restrictive than the first generation of rent control laws. They allowed landlords to pass some costs on to tenants; rents to be set to market rates upon vacancies; exemptions for new construction and small landlords; and rent increases to be tied to the rate of inflation.  

Following the second wave, there was a regulatory backlash to rent control laws, and many states passed laws that banned or limited rent control at the local level, including Massachusetts (1989), California (1995), and Illinois (1997). This trend continued in recent years in a wide range of states, including Colorado (2010), Georgia (2010), Mississippi (2013), Indiana (2017), Iowa (2017), and Florida (2018). By 2019, 37 states had passed laws that preempted rent control at the local level. 

Recently, as housing costs increase, the pendulum appears to have swung back in favor of rent control. Many states are revisiting their laws that preempt rent control or have enacted state-level rent control. Cities are also exploring options for enacting rent control, including Minneapolis and St. Paul. Though the Minnesota state legislature preempted rent control at the local level in 1984 in response to a proposed rent cap in Minneapolis, the state statute had a provision that allowed local governments to enact rent control if approved in a general election. On November 2, 2021, Minneapolis and St. Paul residents voted on two separate rent control measures. St. Paul’s ballot measure was a vote for a specific rent control law that capped rental increases at 3% per year, with few exemptions. The law passed with a 53% to 47% split. Minneapolis’s ballot measure was an amendment to the city charter allowing for the possibility of introducing a new, unspecified rent control law in the future. This provision was also approved with a 53% to 47% split. 

St. Paul’s Rent Control Ordinance 

St. Paul’s rent control ordinance is unique in its stringency. First, unlike most rent control laws which include vacancy decontrol provisions, rent increases in St. Paul are limited to 3% regardless of whether a property becomes vacant and is re-rented to new tenants. This means there is no mechanism for rents to be adjusted to market prices. Second, unlike most rent controls that exempt new construction to encourage increases in supply, there is no exemption for new construction in St. Paul. All residential rental property is under the jurisdiction of the law. Similarly, there are no exemptions for small landlords or properties with few units; no provisions for owner-occupants; and no provision for inflation adjustments, as are common in other rent control laws. This means that rent increases in St. Paul could be capped below inflation rates indefinitely. Thus, because St. Paul’s rent control is possibly the strictest in the country, it offers the chance to provide new evidence around the impact of rent control. 

In contrast to St. Paul’s stringent rent control, Minneapolis’s ballot measure did not create any new laws. Because no law was actually enacted, we cannot know what market participants anticipate about future provisions. Historically, Minneapolis and St. Paul tend to enact similar laws (e.g., minimum wages, COVID masking policies, and paid employee leave), so we might imagine that if Minneapolis were to adopt rent control in the future, it would be similar to the policy in St. Paul. However, the mayor of Minneapolis, who was re-elected in November, has been a vocal opponent of rent control. Thus, the future of rent control in Minneapolis is unclear. For these reasons, our paper focuses on St. Paul’s rent control law. 

It is important to note that St. Paul and Minneapolis did not have excessive rent before the passage of rent control. According to Census Bureau estimates, the median gross rent as a percentage of household income in the Minneapolis-St. Paul metro area was 28.4% in 2019, which places it at the 47th percentile in a sample of over 900 metro and micro-Census areas. In addition, we find that the median inflation-adjusted rent for a two-bedroom unit in St. Paul remained roughly the same from January 2019 to November 2021, when rent control was approved.  

St. Paul’s final rent control policy is uncertain as of the time of writing. In February 2022, the city formed a community working group to help decide how to implement the law, which would go into effect in May 2022. The Department of Safety and Inspections also solicited comments from the public in April on its proposed rules. On April 29, 2022, the city issued a set of rules that substantially weakened the terms under which the law was passed in November 2021. In particular, the new rules would allow landlords to increase rent to maintain an inflation-adjusted constant net operating income based on the property’s operating income in 2019. Any rent increase below 8% per year could be self-certified by the landlord, with the possibility of an audit. Increases between 8% and 15% would need to be approved by the city. The maximum allowable rent increase in one year would be 15%, but increases above 15% could be deferred to future years. The legal uncertainty continues as the mayor of St. Paul is pursuing an exemption for new construction and the Minnesota Senate approved a bill that would retroactively ban rent control, even if passed in a ballot measure.  


Using a sample of nearly 150,000 real estate transactions from January 2018 to January 2022 in the five counties surrounding St. Paul, we estimate the effect of St. Paul’s rent control on property values. These difference-in-difference tests identify the change in residential real estate transaction prices in St. Paul following the passage of rent control relative to the change in prices during the same period in cities adjacent to St. Paul. The tests control for common time-series variation in prices in the greater St. Paul area, cross-sectional variation in prices across granular geographic regions, property-level attributes, including building age and size, and whether the property is a multi-unit or single-family residence.  

We find that the introduction of rent control caused an economically and statistically significant decline of 6-7% in the value of real estate in St. Paul and show that these results are not driven by seasonal changes caused by declining volume in the winter months. Second, we run additional tests to account for changing preferences for suburbs over city centers using transactions from five midwestern cities comparable to St. Paul. Comparing differences between city centers versus suburbs in St. Paul and the other midwestern cities, we still find that rent control caused an abnormal 6-8% decline in property values in St. Paul. Third, we find that rental properties in St. Paul experienced an additional 6% decline in value compared to owner-occupied properties in St. Paul, for a total loss of about 12%. These results imply that the value loss is caused by rent control rather than a spurious variable that affected rentals and non-rentals equally. Finally, we verify that our results are unlikely to be caused by changes in the composition of houses sold before and after the reform. 

We then decompose the observed value loss into direct capitalization effects and indirect negative externalities. The direct capitalization effects account for future expected cash flows lost by landlords, while negative externalities reflect potential negative indirect effects that rent control may have on the local community (see Autor et al. 2014). We derive a simple model of rent control that allows for random growth rates and probabilistic transitions between owner-occupied and rental housing. Matching the model’s parameters to the St. Paul market, we estimate that capitalization effects drive about two-thirds of the value loss, and one-third is driven by negative externalities. These results suggest the capitalization effects of rent control can greatly impact prices even for owner-occupied properties, despite the relatively small likelihood of switching to the rental market. 

The large decline in property values caused by rent control may have significant consequences for St. Paul’s economy. Assuming that the market transactions observed represent the average residential property in St. Paul, rent control would have caused an aggregated loss of $1.57 billion in property value and a 4% expected shortfall in property tax revenue. Since property taxes are the main form of revenue for the city and the school district, the shortfall in tax revenue will likely lead to tax increases to maintain city services. 

Next, we investigate our second research question: how does rent control redistribute wealth? St. Paul’s rent control intends to reduce the burden of housing costs for low-income renters. To study whether the law achieved its intended goal, we test whether the wealth transfers caused by the law are larger when owners have higher incomes and renters have lower incomes.  

To test this hypothesis, we first show theoretically and empirically that the value losses we observe are driven by transfers from owners to renters rather than deadweight losses from the reduced supply. This allows us to use variation in property value losses to proxy for variation in the size of transfers from owners to renters.  

Next, we use a pricing model to predict the change in property value following rent control for over 60,000 residential parcels in St. Paul. Due to limitations in the administrative data, we focus on properties with three or fewer units owned by small landlords. This accounts for 90% of rental properties and 54% of all rental housing units in St. Paul. Most residential parcels in St. Paul are single-family residences (89% of all parcels), of which 17% are rental properties. Of the rental properties in our sample, 43% are owned by small landlords.  

To measure the traits of renters and owners, we use highly granular Census data. We proxy for the traits of renters based on Census data corresponding to the property address. To proxy for the traits of owners, we collect their addresses from the county assessor’s office. We classify rental property owners as small landlords if their listed address is residential and different from the property address and as large landlords if their listed address is commercial. We proxy for small landlords’ demographic traits using the granular Census data corresponding to their home address.  

To test whether transfers are larger when renters have lower incomes and owners have higher incomes, we create a ‘high disparity’ subsample of properties in which owners have incomes above the median owner’s income, and renters have incomes below the median renter’s income. We also create a ‘low disparity’ subsample in which owners have below-median income and renters have above-median income. The differences between the two subsamples are stark. In the high disparity subsample, the median owner’s income is more than double the median renter’s income, while in the low disparity subsample, owners’ and renters’ median incomes are statistically equivalent. Likewise, the fraction of minority renters is roughly 50% in the high disparity subsample, compared to 25% in the low disparity subsample. Similar variation exists for age and education.  

In contrast to the stated goals of the rent control law, we find that the largest transfer of wealth occurred in the low disparity subsample (8.52%), in which renters are relatively wealthier, while the smallest transfer occurred in the high disparity subsample (0.89%), in which renters are relatively poorer. This pattern persists after controlling for additional factors: wealth transfers are positively related to renters’ income and negatively related to owner’s income.  

We consider possible explanations for the poor targeting of rent control. If properties in neighborhoods with lower-income renters also have lower expected growth in future rents, then rent control would impose a smaller constraint and hence a smaller transfer loss. Using our simple pricing model to help isolate transfers from negative externalities, we find evidence consistent with this hypothesis. In contrast, we find that negative externalities do not vary systematically with renters’ backgrounds, suggesting that the externalities affect city-wide amenities, such as school quality or infrastructure. An alternative, untested explanation is that owners with low-income renters are more likely to be able to evade the law than owners with high-income renters. 


To our knowledge, our results provide the first evidence of new rent control laws in the US since the mid-1990s. This is important because the vast majority of existing empirical evidence on rent control is concentrated on New York City’s historical law, with a few papers studying rent control laws from the 1970s to the 1990s in other locations, including Cambridge, Vancouver, Toronto, Los Angeles, and San Francisco. As housing markets and policies have become more integrated over time and the debate on housing affordability grows, we believe that studying a new rent control mandate in a relatively large city located in an area with no history of rent control may provide important evidence for understanding the future of rent control. 

Kenneth R. Ahern is an Associate Professor of Finance and Business Economics at the USC Marshall School of Business.  

Marco Giacoletti is an Assistant Professor of Finance of Business Economics at the USC Marshall School of Business.  


This post is adapted from their paper, “Robbing Peter to Pay Paul? The Redistribution of Wealth Caused by Rent Control,” available on SSRN 

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