Today I’m going to write about something I know almost nothing about, as opposed to my usual essays in which I write about something I know very little about.
It is well-known that rents in major cities in the U.S. are extremely high relative to income, particularly for low wage workers (in other words, the rent “floor” is higher than the income floor, which is the minimum wage). It is less well-known that the problem is actually not confined to major cities:
There is not a single state, county or metropolitan area in the U.S. where a minimum-wage worker can afford a modest two-bedroom rental without spending more than 30% of their income. And full-time minimum-wage workers cannot afford to rent a modest one-bedroom home in 95% of U.S. counties.
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The report calculates a “housing wage,” which is the minimum a full-time worker must earn in order to afford to rent a modest one- or two-bedroom home without spending more than 30% of their income. Above that percentage, they are considered cost-burdened and therefore vulnerable to unexpected financial pressures. This vulnerability is exacerbated for the almost 8 million renters in America who spend more than 50% of their income on housing costs. Considered severely cost-burdened, they are forced to choose between housing and other basic needs, such as food, transportation and child care.
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To afford a modest two-bedroom rental, according to the report, a full-time worker needs to earn $23.96 an hour, which is $16.71 above the federal minimum wage of $7.25. For a modest one-bedroom rental, a full-time worker must earn $19.56, or $12.31 above the federal minimum wage.
Some states have higher minimum wages, but even taking these into account, the average minimum wage worker would need to work nearly 97 hours a week (equivalent to more than two full-time jobs) to afford a two-bedroom rental, and 79 hours a week to affordably rent a one-bedroom.
But let’s stick to major cities for now, and, in particular, my city of New York. There are, broadly speaking, two schools of thought when it comes to housing affordability. One relies on market forces; the other seeks to oppose them. By “market forces”, I mean “supply and demand”; here, “supply” denotes supply of apartments/housing, while “demand” refers to the population of renters seeking accommodations. Here’s a representative argument from the pro-market crowd, from libertarian Reason Magazine (October 2020):
The country’s priciest cities are seeing massive declines in rents as people who are now free to work remotely and unable to enjoy the typical amenities of urban living decamp for less expensive metros.
Tucked away in this trend is a lesson for cities: Building more housing is the key to solving affordability problems.
San Francisco has also seen the largest price declines. Rents for studio apartments there have declined by 31 percent year over year there, according to a new report from Realtor.com. Rents for one- and two-bedroom units declined by 24 percent and 20 percent respectively.
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In Manhattan, rents have declined by 15 percent for studios and 10 percent for one-bedroom apartments. Washington, D.C., and Boston both also report double-digit rent drops.
The trend, if not the individual figures, matches reports from other listing websites. A recent report from Apartment List found median rents had declined 20 percent year over year in San Francisco, 12 percent in New York City, and 9 percent in Seattle.
The logic is not too hard to follow. As demand for housing in major cities declines, driven by the ability of these individuals to work remotely, rents have dropped correspondingly. Hence, the laws of supply and demand apply to the rental market. And, furthermore, this implies that increasing the supply of housing would have the same effect. (The remainder of the article goes on to explain how cities should increase housing supply through deregulation, naturally.)
Let’s try to work from first principles here in the same way that one might in an economics class. I was in the market for an apartment in June 2020. I had a set of requirements that were inviolable: I was looking for a one-bedroom apartment in Brooklyn that was within a 30 minute subway commute of my office in Chelsea. (This was back when I believed, optimistically, that I would return to commuting by the end of the year.) I had a maximum rent I was willing to pay. Below that maximum, I was willing to trade some level of comfort for lower rent: a smaller bedroom, a longer walk to the subway, a basement apartment, a shower that was barely tall enough to fit me, and a bathroom without a sink. (Those last two aren’t made up, by the way: I was very close to signing on the former, and actually did sign on the latter.)
We might abstract these notions by assigning each individual in the market a set of “constraints” that cannot be violated and a “utility” function that should be maximized. The utility function involves the aforementioned factors: geography, apartment size, monthly rent, amenities, etc. This reformulation converts each individual’s housing search into the language of “constrained optimization” — again, assuming that everyone acts rationally and self-interestedly. (There are actually additional complications here, mostly related to the temporal nature of the search. These make the problem a bit more like the “secretary problem”, in optimal stopping theory, but I’ll ignore those complications here.)
On the other side, each landlord has a corresponding set of constraints and a utility function. There is likely a minimum rent below which they will be unwilling to participate. They require certain things out of the tenant: a minimum income, a minimum credit score, evidence of utilities paid, evidence of a steady job, etc. Their utility is much simpler to compute: it is simply monotonically related to the monthly rent. Even so, there are complications, such as the broker’s fee (which favors a renter that they expect will not turnover quickly), or the prospect of concessions (landlords tend to favor concessions, like giving one free month’s rent, that reduce the effective rent but not the nominal rent).
So we imagine a collection of individuals in each group of this two-sided marketplace, each with their own idiosyncratic constraints and utilities. How does “supply and demand”, as vague and abstruse as that concept sounds, interact with these ideas?
Supply and demand obviously operate at the very small, “micro” scale. Again, ignoring the temporal nature of the problem, each apartment opening can be thought of as an auction. A single landlord opens up her apartment for viewing and accepts applications from renters. Renters apply only if the apartment satisfies their constraints. Renters are disqualified if their application does not satisfy the landlord’s constraints. Eventually the pool is whittled down to a set of renters for whom the dual constraints are mutually satisfied. Then, each renter submits their bid: normally, this is the same as the listed price, but, when I was applying, I asked for a concession of $100/month. (The opposite can happen too; in earlier years, when the rental market was hotter, I was often outbid by someone who was willing to pay more than the listed price.) Whether the demand is actually conceded depends, of course, on the “supply” of other individuals participating in this “auction”. It seems incontrovertible that if more renters participate in an auction, the probability the rent is higher than the listed rent should go up, and, conversely, if fewer participate, the probability of the opposite outcome increases. In my own search, I was successful at extracting the concession I sought because the demand from similar individuals had fallen.
We have, of course, clouded the elegant picture presented at the top of this post. We started with two straight lines, representing supply and demand, intersecting beautifully at the point of mutual benefit. It is not clear, however, that we ended there. Is it true that if supply and demand are true at the “micro” scale, then they are true at the macro scale? This is, I think, the important (and underappreciated) question of housing economics. (And perhaps most branches of economics: it is often very easy to develop clever, game-theoretic models at the scale of a few interacting individuals or entities, but whether these translate directly into a “continuum” of individuals or entities is not always clear.) In basic microeconomics textbooks, the question is usually glossed over. It is usually said that the “aggregate” demand curve is the summation of the individual demand (utility) curves. Is that true in this case?
Probably not. Remember all the constraints I mentioned before: geography, maximum rent, apartment size, etc. And remember the constraints on the landlord’s side: the minimum rent and tenant “quality”. If these mutual constraints fail to intersect in the right way, then prices do not change in the ideal way that is usually depicted. To take some examples: in the “auction” for my current apartment, adding a prospective tenant whose maximum rent is well below the listed rent would not change the outcome. Similarly, adding a prospective tenant whose budget is significantly above the listed rent would likely also not change the outcome. These tenants, because of their constraints, do not constitute effective demand for my apartment. I was able to extract a concession because some workers who had similar constraints and utility functions had left the city. It is their demand that mattered. Low-wage workers in New York by and large have not left. But their demand does not matter to me, for better or worse.
The best counterargument to this train of thought is that I am assuming “non-substitutability,” or that each of these auctions involves a pool of renters who do not participate in other types of auctions. Low-wage renters do not substitute for medium-wage ones; medium-wage ones do not substitute for luxury ones. Even the difficulties associated with defining the terms “low-wage” and “medium-wage” point to a deeper problem: we do not have sharp, non-substitutable clusters; we instead have a continuum of wages across people. At best, we have “imperfect substitutability”. And, therefore, the logic might go: as medium-to-high-wage tenants leave New York, the gains will eventually filter down to low-wage tenants. Each $3000/month renter leaving means that a $2900/month renter will get a better or cheaper apartment; their moving up the scale, in turn, frees up apartment stock for the $2800/month renter, and so on. It might be true that I am not substitutable with a low-wage tenant, but, by a series of these overlapping links, my presence in New York might have some indirect effect on their rents. (In fact, the argument we have constructed also implicates gentrification in making low-end housing unaffordable.) And, taken at a macro scale instead of a micro one, we can see how increasing housing supply, no matter at what income bracket, should make rents overall more affordable.
I honestly don’t know which argument is correct. I would be curious to see how substitutable housing supply and demand are, across a number of dimensions. Does an increase in supply in Williamsburg reduce cost in Bushwick? Does it reduce cost in Queens? Or New Jersey, or Philadelphia, or Phoenix? One can construct an analogous “overlapping link” type of argument for any of these, although it seems more and more tenuous the more physically distant the ends of the chain are. What about substitutability across income brackets? Or substitutability between luxury apartments and non-luxury ones? And what about other factors, like single-family housing vs other types of housing?
It is worth noting, though, that people in the business tend to see the housing market not as a unity, but instead as several fragmented markets, each subject to their own dynamics. Here is one report, from Zillow Research:
As rent overall continues to grow, rents are growing faster across the board among low-end apartments as demand for more affordable rentals stays hot. But rather than build more units at the bottom end of the market to meet this demand, apartment developers have instead focused their efforts on adding more supply at the high end.
On an annual basis, median U.S. rents have risen or remained flat in every month for going on four years now. But there isn’t just one rental market, even within a single given area. There are many submarkets depending on the location, size and price of the apartment sought, and strength in some segments of the market can mask weaknesses in others.
Similar to Zillow’s prior analyses of the for-sale market, we divided the rental market into segments based on the Zillow Rent Index[1] to help determine how apartments at the bottom end of the market have fared relative to more upscale digs.[2]
In all 15 major metro markets analyzed, we found that rents among bottom-tier apartments are growing more quickly than median rents overall. In some California markets, annual rental growth at the low end is exceeding 20 percent per year, including Sacramento (up 32.7 percent), Los Angeles (27. Percent), San Francisco (24.6 percent) and San Diego (up 21.7 percent). This increase is playing a big part indeteriorating rental housing affordability in general, especially for the lowest-income Americans that are more likely to rent. Income growth for those earning the least has been weak or flat for years, and trying to manage what are often double-digit increases in rent can quickly stretch already tight budgets to the breaking point.
It is possible my reasoning is too simplistic, but, if we want to reduce rents for people who cannot find affordable housing, why don’t we build more housing for those people? Instead of waiting for “the market” to build upscale apartments that, through a series of plausible but hard-to-conceive processes, eventually trickle down to everyone else, we could simply circumvent the luxury segment entirely and expedite the trickling down. In other words, in the debate between “pro-market forces” and “anti-market forces”, I fall somewhere in the middle. Supply and demand do matter, but, I think, the crucial issue is supply for whom, and demand by whom.
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