Cities With the Worst Rent

photo by Alex Lozupone

Realtor.com quoted me in Cities With the Worst Rent: Is This How Much You’re Coughing Up? It opens,

Sure, rents are too dang high just about everywhere, but people living in Los Angeles really have a right to complain: New analysis by Forbes has found that this city tops its list of the Worst Cities for Renters in 2018.

To arrive at these depressing results, researchers delved into rental data and found that people in L.A. pay an average of $2,172 per month.

Granted, other cities have higher rents—like second and third on this list, San Francisco (at $3,288) and New York ($3,493)—but Los Angeles was still deemed the worst when you consider how this number fits into the bigger picture.

For one, Los Angeles households generally earn less compared with these other cities, pulling in a median $63,600 per year. So residents here end up funneling a full 41% of their income toward rent (versus San Franciscans’ 35%).

Manhattanites, meanwhile, fork over 52% of their income toward rent, but the saving grace here is that rents haven’t risen much—just 0.4% since last year. In Los Angeles, in that same time period, rent has shot up 5.7%.

So is this just a case of landlords greedily squeezing tenants just because they can? On the contrary, most experts say that these cities just aren’t building enough new housing to keep up with population growth.

“It is fundamentally a problem of supply and demand,” says David Reiss, research director at the Center for Urban Business Entrepreneurship at Brooklyn Law School. “Certain urban centers like Los Angeles, San Francisco, and New York are magnets for people and businesses. At the same time, restrictive local land use regulations keep new housing construction at very low levels. Unless those constraints are loosened, hot cities will face housing shortages and high rents no matter what affordable housing programs and rent regulation regimes are implemented to help ameliorate the situation.”

The Economics of Housing Supply


chart by Smallman12q

Housing economists Edward L. Glaeser and Joseph Gyourko have posted The Economic Implications of Housing Supply to SSRN (behind a paywall but you can find a slightly older version of the paper here). The abstract reads,

In this essay, we review the basic economics of housing supply and the functioning of US housing markets to better understand the distribution of home prices, household wealth and the spatial distribution of people across markets. We employ a cost-based approach to gauge whether a housing market is delivering appropriately priced units. Specifically, we investigate whether market prices (roughly) equal the costs of producing the housing unit. If so, the market is well-functioning in the sense that it efficiently delivers housing units at their production cost. Of course, poorer households still may have very high housing cost burdens that society may wish to address via transfers. But if housing prices are above this cost in a given area, then the housing market is not functioning well – and housing is too expensive for all households in the market, not just for poorer ones. The gap between price and production cost can be understood as a regulatory tax, which might be efficiently incorporating the negative externalities of new production, but typical estimates find that the implicit tax is far higher than most reasonable estimates of those externalities.

The paper’s conclusions, while a bit technical for a lay audience, are worth highlighting:

When housing supply is highly regulated in a certain area, housing prices are higher and population growth is smaller relative to the level of demand. While most of America has experienced little growth in housing wealth over the past 30 years, the older, richer buyers in America’s most regulated areas have experienced significant increases in housing equity. The regulation of America’s most productive places seems to have led labor to locate in places where wages and prices are lower, reducing America’s overall economic output in the process.

Advocates of land use restrictions emphasize the negative externalities of building. Certainly, new construction can lead to more crowded schools and roads, and it is costly to create new infrastructure to lower congestion. Hence, the optimal tax on new building is positive, not zero. However, there is as yet no consensus about the overall welfare implications of heightened land use controls. Any model-based assessment inevitably relies on various assumptions about the different aspects of regulation and how they are valued in agents’ utility functions.

Empirical investigations of the local costs and benefits of restricting building generally conclude that the negative externalities are not nearly large enough to justify the costs of regulation. Adding the costs from substitute building in other markets generally strengthens this conclusion, as Glaeser and Kahn (2010) show that America restricts building more in places that have lower carbon emissions per household. If California’s restrictions induce more building in Texas and Arizona, then their net environmental could be negative in aggregate. If restrictions on building limit an efficient geographical reallocation of labor, then estimates based on local externalities would miss this effect, too.

If the welfare and output gains from reducing regulation of housing construction are large, then why don’t we see more policy interventions to permit more building in markets such as San Francisco? The great challenge facing attempts to loosen local housing restrictions is that existing homeowners do not want more affordable homes: they want the value of their asset to cost more, not less. They also may not like the idea that new housing will bring in more people, including those from different socio-economic groups.

There have been some attempts at the state level to soften severe local land use restrictions, but they have not been successful. Massachusetts is particularly instructive because it has used both top-down regulatory reform and incentives to encourage local building. Massachusetts Chapter 40B provides builders with a tool to bypass local rules. If developers are building enough formally-defined affordable units in unaffordable areas, they can bypass local zoning rules. Yet localities still are able to find tools to limit local construction, and the cost of providing price-controlled affordable units lowers the incentive for developers to build. It is difficult to assess the overall impact of 40B, especially since both builder and community often face incentives to avoid building “affordable” units. Standard game theoretic arguments suggest that 40B should never itself be used, but rather work primarily by changing the fallback option of the developer. Massachusetts has also tried to create stronger incentives for local building with Chapters 40R and 40S. These parts of their law allow for transfers to the localities themselves, so builders are not capturing all the benefits. Even so, the Boston market and other high cost areas in the state have not seen meaningful surges in new housing development.

This suggests that more fiscal resources will be needed to convince local residents to bear the costs arising from new development. On purely efficiency grounds, one could argue that the federal government provide sufficient resources, but the political economy of the median taxpayer in the nation effectively transferring resources to much wealthier residents of metropolitan areas like San Francisco seems challenging to say the least. However daunting the task, the potential benefits look to be large enough that economists and policymakers should keep trying to devise a workable policy intervention. (19-20)

Silicon Valley’s Housing Crisis

photo by Smitha Murthy

Drop in the Bucket?

Realtor.com quoted me in Could There Really Be Relief Ahead for Silicon Valley’s Housing Crisis? It opens,

Finally! A glimmer of hope has appeared in Silicon Valley’s housing crisis. Amid gloomy and downright terrifying stories about astronomical home prices and tighter-than-tight inventories forcing well-paid tech workers to live in vans, pay $2 million for a tear-down shack, or ponder commuting to work from Las Vegas, there seems to be some good news for a change: City Council members in Mountain View, CA, approved plans to build 10,250 new homes in the area.

Given that Mountain View has only about 32,000 homes total, this will increase its housing inventory by a whopping 32%—all purportedly within “walking distance” (possibly a bit of a long walk) of tech giant Google, which has long been lobbying on this front and will no doubt break out the Champagne once developers break ground. Sure, it may be years before these homes become a reality, but even the idea of them may have many locals (or those moving there) daring to dream. Might this new influx of housing cause home prices to drop within reasonable reach?

As logical as this renewed optimism about Silicon Valley’s housing market might seem, experts aren’t so sure home prices will budge all that much.

“This news in itself will not drive down prices much,” says David Reiss, research director at the Center for Urban Business Entrepreneurship at Brooklyn Law School. “While a 10,000-unit commitment is significant, Silicon Valley as a whole has about 3 million people living there.”

So if you consider the population of the entire area—many of whom would likely kill to move to Mountain View—10,000 new houses would house only 0.3% of these people. For you math-challenged, that’s less than a measly half-percent! 

And even though the number of homes may be edging upward, so are the number of people moving there.

“Silicon Valley remains a booming economy, so it’s likely that the population will continue to grow, further driving up prices,” Reiss continues.

As further evidence that more homes doesn’t necessarily lead to cheaper home prices, Florida Realtor® Cara Ameer points to another historically hot market: New York City.

“In New York, more new buildings has had no impact on housing prices or rents,” she says. If anything, the only change New Yorkers noticed is their neighborhood got a lot more cramped. The same will likely be true for picture-perfect Mountain View.

“The biggest thing people will see is increased congestion,” says Amer, “with many more residents, cars, and the need for schools and additional services.”

In fact, fears of overcrowding might even galvanize current homeowners in the area to show up en force at future City Council meetings to fight the greenlighting of additional developments—that is, unless they’re out-muscled by employee-hungry firms such as Google.

“As key businesses realize that the lack of housing is hurting their ability to recruit and retain good employees, it is possible that Mountain View’s decision is a harbinger for more pro-development decisions throughout Silicon Valley,” Reiss explains. “Current homeowners, called ‘homevoters,’ tend to make their anti-growth views known to local officials, but once the interests of local businesses focus on the lack of workforce housing, it can change the dynamics.

“These are powerful companies. The result is that those decisions can become more pro-growth than is typical for suburban communities.”

Economic Factors That Affect Housing Prices

photo by TaxRebate.org.uk

S&P has posted a paper on Economic Factors That Affect Housing Prices. This is, of course, an important topic, albeit one that is an art as well as a science. While S&P undertook this analysis more for mortgage-backed securities investors than for anyone else, it certainly is of use to the rest of us. The paper opens,

The U.S. domestic housing market has experienced a 23% price increase since the beginning of the housing recovery in 2011. Many local housing markets are now close to or above their peak levels of 2006, which leads us to investigate whether the pace of home price appreciation (HPA) can continue at its current pace. In this paper, we (1) examine the economic factors that influence HPA and (2) forecast HPA for numerous geographic regions assuming various economic conditions over the next five years. While the aggregate national pattern in housing prices is an important reference, we need to examine housing prices at a more granular geographic level in order to understand regional housing market dynamics and learn how these are affected by local macroeconomic factors. This paper demonstrates that several economic variables are needed to predict average home price movements for each of 48 different U.S. metropolitan statistical areas (MSAs).

*     *      *

Factors that influence HPA can be difficult to predict. Therefore, residential mortgage backed securities (RMBS) investors frequently use a range of HPA projections to estimate their potential bond returns. With that in mind, for each MSA, we considered five separate hypothetical economic scenarios, ranging from an “Upside” forecast to an extreme “Stress 3” case. Interestingly, our Stress 3 case forecasts a 28% decline in HPI at the national level over the next five years, which corresponds roughly to the decline experienced in the last recession. Our “base case” scenario leads to forecasts at the national level of a 26% increase in HPI over five years. This represents what we believe to be the most likely economic forecast. (1-2)

S&P’s key findings include:

  • Movement in HPA is primarily influenced by up to five variables, depending on the MSA: housing affordability, changes in shadow inventory, the unemployment rate, the TED spread [a measure of distress in the credit markets], and population growth.
  • HPA in many MSAs has momentum, meaning that it depends on its level in the previous quarter of observation.
  • The mortgage rate generally appears to have little predictive power in connection with home prices.
  • Chicago, Houston, Boston, and San Francisco are projected to appreciate at a greater pace (45%, 40%, 27%, and 36%, respectively) than the 26% forecast for the nation as a whole over the next five years, and New York at a slower pace (21%). Columbus led all MSAs with a projected five-year HPA of 50%.
  • Under our most pessimistic (Stress 3) scenario, Chicago is forecast to experience a greater decline in HPI (34%) over the next five years than the nation as a whole (29%), while New York, Boston, Houston, and San Francisco are projected to experience declines that are less severe than that of the nation (19%, 3%, 17%, and 16%, respectively). Markets that have been vulnerable in the past (Las Vegas, Phoenix, and Riverside) are projected to experience the greatest five-year declines under our Stress 3 scenario (66%, 68%, and 68%). The markets that show the greatest movements are the most sensitive to the five factors and frequently show the greatest upside and downside. (2-3, emphasis in the original)

I found the first and third bullet points to be the most interesting, as many pundits weigh in on the factors that affect housing prices. It will be interesting to see if further research confirms S&P’s findings.

What Makes NYC Crowded

"Manhattan from Weehawken, NJ" by Dmitry Avdeev

NewsDocVoices quoted me in What Makes NYC Become More and More Crowded. It reads, in part,

Yuqiao Cen, a graduate engineering student at NYU, makes sure to shower before 10pm every night, otherwise she is criticized for making too much noise in her apartment. She lives with her landlord and his family of five in a 3-bedroom apartment on 11th Avenue in Brooklyn.

Similar to Cen, Yanjun Wu, a newly admitted graduate student at Fordham University, barely stays in his living room because she feels uneasy wearing pajamas while her male roommates are around. She lives with 4 roommates in a 4-bedroom apartment on the Upper West Side.

Cen and Wu are not the only ones forced to share an apartment. Many of their classmates and friends living in New York are also doing the same thing. In fact, a recent study conducted by the New York City Comptroller Office suggested that NYC has become much more crowded in the past 10 years with the crowding rate being more than two and a half times the national average.

The study “Hidden Households” was conducted by Scott Stringer, New York City Comptroller, highlighting the growing crowding rate in housing in NYC. According to the study, New York City’s crowding rate has rose from 7.6 percent in 2005 to 8.8 percent in 2013. The number of crowded housing units grew from 228,925 in 2005 to 272,533 in 2013, representing an increase of 19 percent.

The increase in the crowding rate is city-wide. The Comptroller’s study indicates that the proportion of crowded dwelling units increased in all of the five boroughs except Staten Island during this time period. Brooklyn has the largest increase with 28.1 percent, Queens has 12.5 percent and 12.3 percent in the Bronx.

*     *     *

“Fundamentally, this is a story about supply and demand,” said David Reiss, professor of Law in Brooklyn Law School, and research director of Center for Urban Business Entrepreneurship. “The increase of the housing supply has been very slow, while the increase of the population was very fast, and that is the recipe for crowding. Because people can’t afford to live where they want to live, their choices would be continuing to live where they want to live and be crowded, or to switch to location with more space for your dollar.”

The data confirm Reiss’s observation. According to the U.S. Census Bureau, NYC’s population in 2013 was 8.43 million, increasing from t8.2 million in 2005. However, the 2014 Housing Supply Report, conducted by New York City Rent Guidelines Board, also indicates that the number of permits issued for new construction of residential units had reached its peak – 34,000 in 2008, but the number decreased greatly to 6,000 in 2009. Although the number kept gradually going up, and reached to 18,000 in 2013, the market is no longer as hot as before the financial crisis of 2008.

Contrary to common belief, income does not in itself drive crowding. Although “Hidden Households” shows that 23.6 percent of crowded households reported household incomes in the City’s bottom quartile, it also revealed that 18.5 percent of crowded households have incomes in the City’s top quartile and 5.2 percent of crowded households have incomes in the 90th percentile or higher.

In the beginning of apartment hunting, Wu and her roommates wanted to rent a five-bedroom apartment so that everyone could have their own private space. “The market is too busy in New York,” said Wu. “Once we were going to pay the [lease] for an apartment on Roosevelt Island, but someone was ahead of us by just a few minutes.”

After weeks of apartment hunting, Wu and her roommates decided to make a compromise – two of them would have to share a bedroom, in order to get a decent apartment at an acceptable price – $4,900 per month, with neither an elevator nor a laundry room.

“Land is very expensive, and there is not much left for residential development but a tremendous number of people want to live in New York,” said Albert Goldson, Executive Director of Indo-Brazilian Associates LLC, A NYC-based global advisory firm. “Real estate prices started to go up, so you have people who are middle class or who have modest salaries who can no longer afford [to pay a] mortgage. And what many of them would have done, either single people or a family, was ‘double up’. Like single people who bring in a roommate, now have several roommates in a unit.”

Most experts in the urban planning industry believe that the underlying cause of the growing crowding rate is the affordability of housing. Goldson argues that the city needs to be more available for middle-class people who are actually working here and potentially leaving the city if it is too small or uncomfortable to live here anymore.

From Reiss’ perspective, the way to solve affordability of housing is to amend its zoning code to encourage the construction of housing. Vertical construction is a trend and a solution to the crowding situation. But in the meantime, with more people living in taller buildings, the density would definitely increase. “If the city is really committed to increasing the affordability of housing, you have to be committed to increase the housing density as well,” said Reiss.