Policies that encourage the provision of low-cost housing have the potential to improve the well-being of city residents as a whole, despite the widespread recognition of the limitations of such programs.
When Covid struck and millions of people were suddenly forced to work from home, many people predicted that a silver lining might be a mass exodus to the suburbs and countryside, which would help to tame buoyant home prices in cities. When Covid hit, millions of people were suddenly forced to work from home. They could not have been more incorrect in their assumptions.
Prices of homes have skyrocketed, surpassing the rise in people’s incomes, across the majority of the world’s major countries, thanks to ultra-low interest rates, an abundance of cash, and a craving for larger accommodations. The surge has been slightly tempered by rate hikes this year, but it is anticipated that around 1.6 billion people would be without appropriate housing by the year 2025.
Rent control has been implemented in major metropolitan centers across the United States and Europe, including Berlin, Paris, and Dublin, with varied degrees of success. In Europe, national and municipal governments are responsible for implementing rent control. Yet, the policies frequently exacerbate existing tensions, pitting renters against landlords and investors and, in the case of Sweden, even leading to the removal of the country’s prime minister.
In light of the importance of the issue at hand, economists have analyzed the effects of rent control and stabilization policies. According to studies, these restrictions discourage landlords and investors from joining the market, which leads to a decrease in the availability of property and, paradoxically, an increase in prices and rental rates. For this reason, housing industry experts typically advocate for supply-side initiatives, such as the development of high-rise apartment buildings, in order to raise the overall number of affordable housing options.
Instead than focusing on the availability of homes, we should prioritize well-being.
On the other hand, the majority of these research concentrate on how different rent rules affect the market. In addition, the prevalent option of boosting the supply of housing benefits not just the poor but also the affluent, whereas the poor would gain more from targeted initiatives, particularly in places with high levels of inequality.
What if, instead of evaluating rent policy measures based on their effect on the housing market, they were evaluated based on their effect on a more basic criterion such as well-being? Because of this, my co-authors* and I developed a model to simulate and evaluate housing affordability policies in any given location. These policies can range from rent stabilization (RS), which is a cap on yearly rents rises, to housing vouchers. The model can simulate and evaluate any policy.
We examined actual data from the New York metropolitan area and came to the conclusion that the policies improve average well-being when measured in terms of annual consumption of goods and housing. This is due in large part to the fact that the policies ensure residents with lower incomes have a roof over their heads. The prior research has shown that there are misallocations in both the labor and housing markets, but the net welfare gains created by policies to make housing more affordable are strong enough to overcome these problems.
Our methodology is innovative because it takes into account the precariousness and danger of revenue. To put it another way, affordable housing laws that assist individuals in maintaining their houses are beneficial if they live in major cities, where the unpleasant reality is that many people struggle with uncertain earnings or live in constant fear of being laid off from their employment. This is especially true when one considers that the majority of individuals avoid taking risks, meaning that they do not appreciate being forced to make changes to their housing usage, such as moving into a smaller apartment.
The rent regulation system and the city
Cities provide a variety of employment and educational options, in addition to a wide range of cultural and leisure attractions, which attract individuals from all walks of life. My co-authors and I built a model to capture essential aspects of the housing market, such as house prices, rents, construction, labor supply and output, income, wealth inequality, and the location decisions of households, so that we could understand the effects that affordable housing policies have on diverse urban populations. When given the appropriate data, the model may be used to the investigation of any city.
After running five separate tests, we were able to successfully calibrate our model to the New York metropolitan region. In the first step, we raised the number of RS houses, which are defined as residences whose rents are restricted from increasing by more than a few percentage points annually. In actuality, RS accounts for up to one third of the apartments in New York City, with another third being sold at prices determined by the market and the last third being inhabited by their respective owners. Our model demonstrates that there will be an increase in the number of low-income families who have access to stable housing if the total square footage of RS housing is raised by fifty percent. As a consequence of this, the general standard of living of New Yorkers will improve by an impressive 0.91 percent.
Yet, there are expenses associated with this strategy. RS housing units are often older, smaller, and assigned without doing means testing. This implies that they are occasionally given to persons who really have the financial capability to live in non-RS housing that is larger. Reducing rents unavoidably has the effect of lessening the incentives to build and maintain housing, while simultaneously pushing up the cost of market-rent apartments. As a consequence of this, there is a possibility that some professionals and highly educated employees may be compelled to reside in the more affordable suburbs, forcing them to spend their time traveling into the city center.
After that, we conducted tests on two other metrics that had the potential to compensate for the misallocations described earlier. The first strategy is a more focused method that regularly checks the income of each Section 8 tenant in order to guarantee that a greater number of Section 8 units are allocated to persons who really need them. Yet, our research showed that income testing discourages people from working since it makes it possible for them to be disqualified for housing assistance if they earn too much money. And while some long-term RS renters are replaced by new tenants who have a greater need, the average subsidy is lower because new RS tenants get much smaller rent reductions. This results in a lower number of RS residents overall. Overall, the implementation of this strategy resulted in significant improvements to the welfare of 0.66 percent of the population.
The subsequent policy simulation moves all RS housing outside of the city itself and into the surrounding suburbs. Naturally, this has led to the gentrification of the city center, which has resulted in fewer people with higher incomes, bigger flats, and an increase in the number of people who own their own homes. When seen in a positive sense, this indicates that more high-skilled and high-productivity families will be able to dwell in the core of New York City, contributing more to the output of the city than lower-productivity households would.
The other side of this coin is that families with low incomes are forced farther out into the suburbs. Not only does this result in segregation between those who have and those who do not have, but it also causes a substantial portion of the population to be unable to access the attractions that are exclusively accessible in the city center, such as museums and theaters. Overall, there is a little smaller gain in average welfare, amounting to 0.25 percent.
The goal of our fourth attempt at experimenting with public policy is to expand the supply of housing that is accessible to everyone, not just those with lower incomes, by relaxing the land-use or height limits that have been placed on house building in the central business district. As a consequence of this, rents have decreased generally. Yet, since this policy only produces a little improvement in the predicament of low-income families, the aggregate wellbeing of the population only increases by 0.11 percent as a result of its implementation.
Read more: How to Find Happiness by Going Down a Step
Using their actions as a kind of voting
It is interesting to note that according to our model, there is no increase in social welfare produced by providing low-income families with an extra US$800 million worth of housing vouchers, which are basically cash transfers. Any advantage that may be created is cancelled out by the authorities’ decision to raise taxes in order to pay for the expenditures. This results in the departure of some inhabitants with high incomes, which necessitates the imposition of even higher taxes to fund the same spending, which, in turn, results in the departure of even more rich residents, and so on. The outflow, on the other hand, causes a decline in the housing supply, which in turn leads to an increase in rent prices.
Our model has the potential to serve as a helpful instrument for policymakers who are researching the advantages and costs of a variety of rent control schemes for their respective cities. Even though there is no single answer that will work in every situation, there is one thing that can be said for certain: rent control policies have the potential to be a net positive for the average well-being in unequal cities like New York and Seoul, after the associated risks and efficiencies have been accounted for (though perhaps less so in more equal cities with vast social safety nets). These kinds of regulations eventually offer more than they take away since they make it possible for individuals in insecure financial situations to maintain their home stability over the long run.