Rent control in all its forms is government’s attempt to reduce rental costs and help those who struggle to find housing they can afford. While the policies themselves are made with the best of intentions, the end result is not as kind. In fact, research finds that rent control ultimately drives a market that favors certain renters over others, puts more power in the hands of landlords, appears to slow increases in rental unit supply, incentivizes landlords to convert controlled units to owner-occupied units, contributes to higher rents in uncontrolled units, and reduces landlord investment back into rent-controlled apartments.
While the targeted beneficiaries of rent control often experience savings in the short term, the policies over time offer greater benefits to higher-income earners—a group not intended to reap the rewards.
This paper examines the difference in the rental unit supply between 113 cities with and without rent control regulations from 2010 to 2018 in California. The results support the theory that rent control results in less rental unit supply, showing a 2% decrease in rental unit growth in rent-controlled cities compared to non-rent-controlled cities. To test whether this interesting result was independent of housing generally, the same test was done with owner-occupied units (like houses or condos). No significant difference was found among the two groups. In sum, these results support the theory that rent control restricts rental unit supply.
While America’s housing market has become slower acting and more expensive, millions of Americans are facing higher housing costs. The answer to improving this situation isn’t more government interference, but the free market, innovation, and less restriction. For example, reforms such as the Goldwater Institute’s Permit Freedom Act and Property Ownership Fairness Act signal the burden of unnecessary regulations to legislators and help eventually alleviate these regulations.
Introduction to Modern Rent Control Regulations in the United States
Price control policies, which are nearly as old as democracy itself, are found in ancient texts like the Hammurabi Code and the writings of Roman rulers such as Diocletian. Price controls are government-established minimum or maximum prices that private firms may charge for a product or service. This paper examines a common price control, specifically rent control. Although there are different types of rent controls—first generation spawning from early 20th century America and a newer and less pervasive second generation—the main theory is consistent: They cap the amount a landlord may charge for rent.
Rent controls often arise after some crisis or event causes a rapid but temporary increase in rents—war, famine, and economic depression, for example—putting political pressure on legislators to curb public outrage about a lack of “affordable housing.” The very concept of “affordable” is of course subjective, because what is affordable to one person may be unaffordable to the next regardless of income.
The birth of large-scale first generation rent control in America dates back to a cataclysmic event—World War II (note that rent control did exist in some municipalities prior to the war). During the onset of war, masses of young American servicemen were deployed overseas, leaving their wives at home. In response, many of these young women either moved in together or returned to their parents’ home. Simultaneously, the nation’s production efforts shifted away from housing and other construction to focus on wartime supplies, creating a demand for employment in nontraditional manufacturing roles and a cessation of housing supply. Women and other workers began moving into industrialized cities to aid in the war effort. These new workers enjoyed greater independence and higher incomes, generating demand for city living. Temporarily unable to keep up with supply, the price per rental unit rose.
Increased rents and a fear of price gauging and other seemingly exploitive behaviors from landlords was on the rise as well, leading President Franklin Roosevelt to push for legislation to stop such occurrences from damaging the “civilian morale.” The Emergency Price Control Act was eventually passed, placing nearly 80 percent of U.S. municipalities under rent control by 1943, capping the amount landlords could charge.
Before assessing what impacts rent control had and still has today through second generation rent control policies, it is important to note the logic of rent control. Increased rents are due to a shortage in rental unit supply. To curb the increased prices, rent control addresses the prices themselves, not the decreased supply. In fact, as we’ll see, rent control has a host of results that actually make shortages worse.
Although well intentioned, capping rents during World War II had unintended consequences, namely conversion of rental units to owner-occupied units. In fact, conversion of rentals to owner-occupied units is part of the rapid 10 percentage-point increase in homeownership rates from 1940 to 1950 controlling for other variables, with estimates concluding nearly 3 million rental units having been converted to owner-occupied units.
During the same period, evidence of reduced supply can also be found in New York City’s low vacancy rates after the enactment of rent control (an industrialized city utilized during the war). Because New York’s rent control has remained in place ever since, so too have low vacancy rates. These consequences made affordable housing less available to tenants, not only in the years during and immediately following the war, but for years to come.
Seeking to lower rents to benefit low-income residents is a noble and universal goal among housing regulation supporters and opponents alike. Rent control regulations, however, are not the best step in accomplishing this goal.
Government as the Cause of, Not the Solution to, Housing Unaffordability
Before exploring whether government rent-control policies effectively lower rents, let’s first look at why costs increase. California is a good example to illustrate this concept.
Income is both a symptom and cause of rising costs. As a symptom, California’s net outgoing migration is not equal among income levels. In fact, a vast discrepancy exists between low-income households and higher-income households. Nearly 75% of the 800,000 residents that left California between 2000 and 2015 had annual incomes below $50,000. However, as a cause, net migration increased for some—namely those households with annual incomes between $100,000 and $200,000. As a result, more and more residents are willing to pay top-dollar in these areas, increasing housing prices overall.
Heightened land-use regulation drives up construction costs. Such regulations make it difficult for developers to build new housing and keep pace with rapid upticks in demand, and they simultaneously destabilize the steady flow of state construction, adding unpredictability. In fact, research has shown that strict land-use regulation is associated with increased real average housing prices in 36 states. Local governments impose high costs for new-owner and renter-occupied housing. Impact fees—the payments local governments require during new complex and home construction for future public services—can make affordable housing development out of reach for developers and homeowners alike, and they are especially onerous when not used for their intended purpose of alleviating burdens on local residents. In Fremont, California, these fees alone can range up to $77,000. Municipalities in California also employ discretionary review, a process that requires consent from public groups before rental and other housing is built. And to top it off, environmental review by the California Environmental Quality Act may also be required. It is no surprise that rental complex construction has been stalled or canceled because of these measures, which require hearings, committee approvals, and other time-consuming processes. Such regulations increase the cost and risk of building new rental housing, and combined are responsible for nearly a quarter of new housing development costs. 
Inadequate housing supply is one of the largest factors in increased home and rental housing costs. In San Francisco, California, employment and population growth are rapidly rising. Housing development, however, is not. From 2010 to 2015, San Francisco added 531,000 jobs, dwarfing the number of housing permits issued—only some 82,000. The city is currently adding about six new jobs per every housing unit constructed. Housing-density rules—such as minimum lot sizes, requirements for a certain amount of space per family, and limits on how many units in a given defined area—can dramatically increase housing costs. Such regulations may come in seemingly discrete regulatory packages like building height limits or floor-area ratio rules.
Using Rent Control to Mitigate Housing Shortages and Costs
Rent control policies are one of the few topics on which economists of all political persuasions largely agree, deeming them ineffective, inefficient, and inequitable. Economist Assar Lindbeck went so far as to label rent control the best alternative to destroy a city “except for bombing.”  Although many rent control regulations today are not as harsh as those during World War II, they have similar effects, albeit slower acting and more discrete. Existing research covers a wide range of consequences but most confirms that rent control indeed restricts rental-housing supply and encourages conversion of rental units to owner-occupied units. Rather than sufficiently benefiting those it intends to help, rent control contributes to higher rents in uncontrolled units and reduces landlord reinvestment into the complex.
Rent control on rental units has important consequences for landlords, especially in cities where rent is consistently high due to the causes mentioned earlier. Because of these regulations, the profit (assuming there is one) for each additional unit in a housing complex is substantially reduced. When these units are then placed under a rent control ordinance, this revenue is further depleted, often to such a degree that revenue per unit is not enough to cover costs. Even if revenues do exceed costs, landlords have an increased incentive to convert their rental units to owner occupied or condominiums to avoid these regulations, thereby reducing rental unit supply. Research confirms this cause and effect.
When some units become rent-controlled, overall supply drops, causing prices to initially increase for non-rent-controlled units. However, this effect decreases for noncontrolled units over time—a period between 20 to 30 years—because landlords and investors are still willing to build units free of rent control, boosting supply. Controlled units, however, remain restricted and, if anything become less numerous due to a slowdown in new building and general avoidance of the regulations by developers.
Shouldn’t we measure the effect of rent control by its effects on renters? The outcomes for them aren’t much better. Rent stabilization is found to decrease rents for a small minority of renters, but even those tenants may not be better off in the long run. Because rent control drives rents in uncontrolled units above market prices, renters in controlled units have even fewer options than before if they must seek other non-regulated housing that better meets their needs. The net benefits to a renter in a controlled unit, therefore, is negative. In other words, rent control favors certain renters over others—less mobile, longtime residents tend to benefit, while families, migrants, and youth likely lose the most in the short term. Over time, however, landlords of controlled units can be choosy with the tenants they approve, preferring mobile tenants so they can hike prices in between current tenants and the next. The ultimate result is a rental market that favors certain renters over others and places greater power in the hands of landlords.
Landlords’ investment back into rent-controlled units has also been found to decrease over time, even when economic conditions are favorable for investment, leading to deterioration of controlled housing quality. Research has also confirmed that when landlord reinvestment is lacking, upkeep is deferred to tenants. In the absence of this upkeep, unit living quality decreases.
Rent control also does a poor job of targeting benefits to those it intends to help. Research has shown that while initial beneficiaries of rent control are typically stationary, lower-income individuals, minorities, and the elderly, they reap the benefits for only a short time. Ultimately, the policies prove to be a greater asset for higher-income earners. Other research has concluded that modern rent stabilization policies similarly help only a minority of the targeted population with many benefits going to higher-income renters and households. The reason the benefits to low-income renters seem to diminish over time is the impact of rent control and stabilization on supply: Landlords have the ability to be choosy with the tenants they allow.26 In other words, landlords prefer tenants who in the end do not benefit from rent control—mobile tenants.
Let’s look at an example. A landlord who has three rent-controlled units available for rent and four potential renters will probably look for applicants who ultimately allow for increased revenue. In this case, suppose one of the tenants is elderly—a group that is likely to be stationary—while the other three renters are students, a group more likely to relocate soon after moving in. Because the landlord has the upper hand on a commodity that suffers from a shortage, they will likely choose the students, allowing a rent increase after those tenants move out.
Rent control and zoning regulations are more than a simple issue of supply and demand. Most current argumentation focuses only on restrictions of supply below market demand and the subsequent shortages due to rent controls. But this is simply scratching the surface because it ignores existing problems with housing supply and the difference in alternatives that tenants and landlords have. Addressing these concerns is key to addressing housing costs.
Cities in California that implement rent control often have long-term elasticity issues as well—that is, even when prices rise, there isn’t much additional housing construction in response.
Data enforces this claim. Coastal California cities have some of the lowest elasticities in the country, well below the national average. In fact, in San Francisco, where elasticity of supply is extremely low at .04 (according to index number statistics from 1996 to 2006): Housing prices have increased a massive 290%, while the increase in housing stock has been a mere 12.3%.
Compare this to Las Vegas, a city with relatively high elasticity of supply at 1.17: Housing stock increased 87.8% from 1996 to 2016, while housing prices climbed 75.2%. Compared to San Francisco, Las Vegas’s housing elasticity is much higher, meaning that in contrast to San Francisco, Las Vegas is able to produce enough housing to meet increasing demand.
Regulation in the housing market and an inflated bureaucracy are a primary contributor to low housing elasticities because landlords cannot increase the supply of housing to keep up with demand when they must spend over 10 months just to obtain a building permit, as is the case in San Francisco.
Tenants get the worst of government’s restrictive policies. While landlords have other alternatives—they can build in a new city, build different kinds of housing, or simply shift their investments into other products—tenants have one goal that is not replaceable: finding a place to live. Rent control is not a good solution to this issue, and may indeed make the problem much worse by further restricting new building. In fact, if it is true that elasticity is extremely low, rent control does not necessarily cause a large short-term shortage, but it does restrict building over time, causing long-term problems.
How Rent Control Affects Growing Cities—A California Case Study
California’s cities serve as a good case study to test the assumptions and economic theory behind the effects of rent control laws. The cities are diverse, in close proximity, and have a range of rent control regulations, as well as other characteristics that lend themselves to comparison. Because rent control is intended to lower rents, Goldwater’s research explores whether rent control is a good policy tool for lowering rents over time, based on data from 2012 to 2018.
Economic theory asserts that increases in price are the result of a reduction in the supply of housing accompanied with increased demand. This hypothesis is tested by analyzing the change in rental housing growth from 2010 to 2018 between controlled and noncontrolled cities, then comparing this result to a placebo group—owner-occupied housing. Below is a summary table. Research methodologies and suggestions for future research are discussed later.
This research also looks at the long-term change in renter-occupied units in both rent-controlled and noncontrolled cities. The greater the difference between renter-occupied units in 2018 and in 2010 indicates a greater supply of rental units overall. In this case, it appears as though the variable used to indicate rent control versus non-rent-control is inversely related to the difference in renter-occupied units between 2018 and 2010. In other words, the closer the rent control variable “Bi” gets to 1 (indicating rent control), the smaller the difference in renter-occupied units between 2018 and 2010. The opposite is also true. This effect is statistically significant at the 95% confidence level—indicating that if we change the rent control variable “Bi” from 0 (noncontrol) to 1 (rent control), we decrease the difference in renter-occupied units in a given city by roughly 2%.
To truly get a sense of whether this discrepancy exists between controlled and noncontrolled cities independent of factors that may also decrease the supply of owner-occupied housing in rent-controlled cities, a placebo group—owner-occupied housing—was analyzed as well. The results indicate a positive relationship between rent controlled cities and the difference in owner-occupied housing between 2018 and 2010, although this value is not statistically significant. This suggests that the difference between renter-occupied units in rent controlled versus non-rent-controlled cities occurs independently from other factors that may generally influence homebuilding (both renter and owner occupied). 
This research indicates an association between rent-controlled cities and reduced growth in the rental unit supply without significantly lowering rents. Rather than rent control, California cities may make housing much more affordable over the long run by implementing policy tools that attack the state’s elasticity problem. While price elasticities typically increase over time in the housing market because of the additional alternatives for current and prospective tenants, if a city has restrictive policies that prevent new building, it will find itself with rapidly increasing costs without any meaningful increases in housing supply, just as California cities have. In other words, these solutions are intended to be universal and do not apply only to California, but to cities in many states across the country.
Increasing the supply of housing should be a first priority for cities. One of the best ways to do this is by making it quicker and easier for builders to build. The Goldwater Institute’s Permit Freedom Act is a state law that requires government to approve or deny permits within a defined timeframe, provide clear criteria for whether the permit will be granted or denied, and provide permit applicants with independent judicial review when their permits are denied.
State legislatures and governing bodies should also implement laws that speed up the permitting process. Land use regulations are one of the main contributors to a lagging housing supply from slow permit approval processes. Therefore, it comes as no surprise that San Francisco and Los Angeles—infamous for their tight land use regulations—have exceedingly slow permit approval processes that no doubt contribute to their lack of housing.14
Knowing the burden that land use and zoning regulations can impose on the building permit process, it should be another area of concern for legislatures if a locality’s zoning ordinances are unnecessarily restrictive.
Zoning regulations come in a variety of packages like maximum building height restrictions, occupancy restrictions, minimum lot sizes, and single-family housing designations. While these regulations may appear useful for increasing property values or maintaining safe distances between schools and certain businesses, they often are the result of aesthetic or “not in my back yard” philosophies, or sometimes nefarious purposes like blocking certain “undesirables” from one’s neighborhood. Relieving these often unnecessary regulations—especially in densely populated cities—would enable greater investment in rental housing construction and supply, and decrease the distance between work and home. It would also encourage more dynamic and productive working environments, and reduce housing segregation. Another Goldwater Institute reform, the Property Ownership Fairness Act, requires government to pay owners when it takes their property rights away. This helps lawmakers understand and weigh the costs and benefits of regulations. If the regulation is too expensive for the government, then it should not be imposed on the property owner.
Other restrictive regulations, including excessive historic land/building designations, should also be rolled back or repealed. While historic building designations add to the beauty and allure of cities, when abused they can restrict housing supply. Unfortunately, governments have been known to apply these restrictions without due cause, as in the case of a BP gas station and the New York City Landmarks Preservation Commission, wherein the owner was unable to redevelop the property where the gas station sat. By subjecting historic designations to oversight and appeal or independent judicial review, the burden of proof shifts from citizens to government, where it rightly belongs.
The combination of these suggestions in a policy package should help reduce housing costs, especially rents, over time. While America’s housing market has slowly become slower acting and more expensive, millions of Americans are facing higher housing costs. Government is not the answer to improving this situation; the solution lies with the free market, innovation, and less restriction.
Goldwater gathered data using the U.S. Census Bureau and Census QuickFacts data. Cities were chosen using rent control data from Nolo’s master database of rent controlled cities gathered from Tenants Together website—an advocacy group for rent control measures. Some cities listed in the master database either had only tenant protections or implemented the ordinance after the period in question. For this reason, only cities with rent control measures implemented prior to the period in question, 2018, were selected. Cities in the noncontrolled group were also selected from the Tenants Together website and through random sampling. Total sample size including noncontrolled cities was (n=113).
Cities with large populations have increased housing supply, so population data was gathered to control for this occurrence. The price a landlord is willing to charge is dependent on the price a tenant is willing to pay, ceteris paribus, hence rental prices are dependent on the income of local residents. For this reason, median income data were gathered to control for income discrepancies between cities. If rental unit supply is unable to keep pace with demand, vacancy rate is often low. Vacancy rate, because of this, is a good predictor of rent levels, and is used as a control variable. As time passes, rent-controlled units tend to become less numerous. For this reason, the percent of housing stock built before 1980 was added to control for an estimated percent of housing stock in each city that would be affected by rent control laws.
Ordinary Least Squares (OLS) Regression
Ordinary Least Squares (OLS) log-log regression was used to measure changes in median rent from 2012 to 2018, changes in the number of units renter occupied between 2010 and 2018, and the change in the number of units owner-occupied from 2010 to 2018 as a placebo group. A bivariate dummy variable, Bi (1=controlled, 0=not controlled), was used to distinguish rent-controlled cities from non-rent-controlled cities.
Standard errors were clustered by location to control for unseen variations by region. Two main groups (San Francisco Bay area and Los Angeles metro area) formed the majority of cities with the rest in outlying areas.
To test for multicollinearity, a Variance Inflation Factor (VIF) test was run. Generally, a VIF value of less than 10 is acceptable for variables of interest, indicating an acceptable level of multicollinearity. In this research, all variables of interest have a VIF value less than 10. A detailed chart is included in the appendix. Log values of median rent in 2010, the number of units renter occupied in 2000, and the number of units owner-occupied in 2000 help control for existing housing units and to establish a baseline level of rent.
To control for selection bias, median contract rent and the number of housing units renter occupied were collected in years prior to the year in question. Median contract rent was collected in the years 2010, 2012, and 2018. Similarly, the number of units renter occupied was collected in 2000, 2010, and 2018. These variables were then log transformed to find the percent change from 2012 to 2018 in median rent controlling for median rent in 2010 and the percent change in number of housing units renter occupied between 2010 and 2018 controlling for the number of housing units renter occupied in 2000.
Discussion and Suggestions for Future Research
There were several limitations in this study, most notably selection bias and general difficulty controlling for extraneous variables. A better way to study causal effects of rent control would perhaps utilize a difference-in-difference design wherein baseline levels of contract rent and rental unit supply are standardized prior to treatment (rent control laws being implemented). This design would allow researchers to analyze and compare respective changes due to rent control implementations. Although this research does indicate correlational data that may indicate causal relationships, it does not intend to draw these conclusions. Rather, this research is solely intended to show associations between variables.
VIF Test for Multicollinearity
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 It is important to quickly note that this research focuses on associations and does not necessarily imply causal relationships. However, the research does point to potential causal relationships. More detailed and controlled research would be able to verify the validity of these relationships. This study also has a small sample size, so statistical error should also be considered before drawing concrete conclusions.
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