Research Roundup

Links and summaries to my Mercatus papers

I have another paper scheduled to come out at Mercatus later this year. But, this seems like a good time to provide a full set of links to the research paper series that I just finished up.

Series of Four Recent Papers

Each of the four papers included at least one substack post, summarizing the findings, with an accompanying twitter feed.

Paper #1: Rising Home Prices are Mostly from Rising Rents

• Post Link. In this paper, I establish the underappreciated empirical evidence that rising rents basically explain all of the increases in home prices over the past 20 years, both over time and cross-sectionally. This discusses some basic points: Price/rent ratios rise when rents rise. All of the excess real estate value has been in cities with elevated rents. Low end rents have increased more than high end rents. Rent/income ratios have been rising where incomes are low. Stop focusing on distractions like interest rates. It’s the rents. And, the reason it’s the rents is because it’s about supply constraints.

  • Here is the twitter thread.

Paper #2: Price Is the Medium Through Which Housing Filters Up and Down: A Proposal for Price/Income as an Indicator of Housing Supply Elasticity

This paper is the conceptual linchpin of the four paper series. If you compare the price/income ratio of housing across a city, it is much more volatile in parts of the city where incomes are low than it is where incomes are high. I describe how this quantifiable measure of a city’s housing stock (the affordability of a home in a neighborhood with lower incomes compared to the affordability of a home in a neighborhood with higher incomes) provides real-time feedback on the adequacy of local housing supply, and supports the existing literature on filtering, chains of sale, and distressed migration trends.

• Post #1. Inadequate supply (even "luxury" supply) hurts poor families. Full Stop. In short filtering (trickle down, if you will) is the whole game. I walk through how distressed migration within and between metropolitan areas creates price differentials in housing. The poorest families in housing deprived cities are harmed the most. They are forced to move away from housing deprived cities, which raises the average income of the families that remain, and so, statistically, they creates a pattern where housing is most expensive for the poorest families in the richest cities. Obstructed housing is responsible for most of those patterns.

  • Twitter thread.

• Post #2. Housing deprivation is driving high real estate values. The only way to raise housing costs in the way that we have is through inertia - the willingness of families to pay exorbitant housing expenses when regional displacement is their only other option. One way to misinterpret these trends is to attribute them to ever more extreme cyclical bubbles. The other way is to infer that the housing deprived cities are just so special that, of course, they are really expensive. I point to some of the recent papers that are increasingly documenting how high costs and migration patterns are the result of housing deprivation.

  • Twitter thread.

• Post #3. “in a normal market, with some supply elasticity, home prices are generally bounded by the cost of construction, rent, and discount rates on future rents. It is a static analysis. If prices rise above the cost of construction, new homes are built until rents decline to bring the market back into balance.

  In cities with a vertical supply curve, it is not a static analysis. The market is determined by flows. How quickly will residents migrate and segregate. The local housing market doesn’t find equilibrium because rents decline to a relatively stable cost of construction. It finds equilibrium because the incomes of the tenants increase as families segregate under duress.”

  • Twitter thread.

• Post #4. “In short, in-migration must trigger either more homes or rising costs, and if it triggers rising costs, those costs induce outmigration.

  One complaint NIMBYs have about new homes is that they will simply attract more newcomers to a city, and just make the displacement worse. These regressions provide at least a speculative result that suggests they are wrong. Mostly what new homes do is keep local costs down so that locals are not displaced. If a city permits an additional house, the city is likely to grow by about 2.9 residents, but those are likely existing residents that now won’t be displaced.”

  • Twitter thread.

Paper #3: Reassessing the Role of Supply and Demand on Housing Bubble Prices

In this paper, I use the “price/income slope” (the difference in home prices between rich and poor parts of each city) to more comprehensively control for metropolitan area differences, which allows me to analyze a much larger portion of price changes than traditional methods of regional controls allow and to include supply constraints as an independent variable along with demand-side variables like credit access and speculative activity.

• Post #1. I was somewhat surprised that when I analyzed the effect of credit access on home prices from 2002 to 2006 in a regression that included my supply variable, I found more of an effect from credit access. The effect was stronger than the existing literature has found. But, the effect was much less than the effect of obstructed supply. There was a small credit boom that coincided with a huge supply bust and distressed migration event. The existing literature has primarily focused on the small credit boom, and even though the boom they have documented wasn’t particularly large, they did not have a developed counterargument that could replace it.

• Post #2. Here, I go into controlling for regional differences. The way researchers like Mian & Sufi control for regional differences gives them biased results. And, you can see how the conclusions in the existing literature are strongly driven by their presumptions that the variables they are looking at are the important price drivers. Mian & Sufi write, “If the expansion of mortgage credit supply to marginal households was purely a function of house price growth expectations, why did such an expansion occur even in elastic housing supply cities with no house price growth?” So, they conclude that increased credit supply wasn’t driven by price expectations, but where prices increased, credit supply was the cause (which could only happen where supply was inelastic). In this post, I show how my framework helps to highlight the biases that led them to that conclusion. In short, “where other cities experienced high price appreciation and active lending markets, there wasn’t much income-sensitive price appreciation. It’s only in the Closed Access cities… The income-sensitive price appreciation that Mian & Sufi took as confirmation that credit to buyers with lower incomes was driving prices higher only shows up in cities that were bleeding low-income families at a massive rate.” More details on the regressions are at the post.

• Post #3. Here, I go through regressions regarding price changes from 2002 to 2006, and show how my new variables help to isolate the effects of supply and demand more accurately. “In summary, I have found apparently important effects on home price appreciation from 2002 to 2006 from credit access. However, in order of importance, prices were correlated with (1) metro area differences, (2) supply constraints, (3) factors outside the model, (4) credit access, and (5) speculation and trend continuation. And each of those factors affected distinctly different parts of the market in interesting and perplexing ways, which I will discuss soon.”

• Post #4. Here I go over a paradox in my findings. I find that mortgage access had a positive effect on home prices from 2002 to 2006, but, oddly, once the interactions with the other variables are accounted for, the ZIP codes where mortgage access was most important were the ZIP codes where prices were the most moderate! “Credit access was associated with rising home prices in places where home prices weren’t rising that much!… There’s an old saying that you can’t reason someone out of something they weren’t reasoned into, and I think there is a version of that here. In the conventional story, there’s a mish-mash story of home buyers with double-digit price/income ratios in Los Angeles and of an increase of subprime borrowing in Detroit, which serves to explain the subsequent collapse in both cities. There are anecdotes of predatory lending in both contexts. But, these are very different stories. There is evidence of a lending boom in Detroit and Atlanta. There is little evidence of a housing bubble in Detroit and Atlanta. But, questioning the analytical evidence for a housing bubble in Detroit or Atlanta doesn’t go very far when the conventional wisdom is so dependent on anecdotes. ‘I saw lenders handing out loans to buyers who had no business taking on a mortgage’ might be a factually accurate statement in a large number of cases, but the mish-mash story became canon without carefully connecting those anecdotes to local rates of housing construction or price appreciation. If the canon was written without that careful connection, it isn’t going to be easily re-written if that connection is retroactively reexamined and found wanting.”

• Post #5. The housing bust was not particularly a reversal of the housing boom. In 2010, prices across Los Angeles, for example, were about 40% higher than they had been in 2002. In most other cities, the change from 2002 to 2010 was largely income-sensitive. Poor neighborhoods lost 20-40% of value compared to rich neighborhoods. Erdmann Housing Tracker readers will be familiar with this point. The boom and bust was a one-two punch. Price appreciation driven by local supply constraints and related regional migration surges was followed by price decreases driven by a collapse of that migration and severe mortgage suppression.

  • Twitter thread.

• Post #6. “Homes across the country and homes with existing Fannie Mae mortgages lost value. But the average price of homes getting new Fannie Mae mortgages shot up, so that by 2009, prices of homes getting new Fannie Mae mortgages were, on average, around 60% higher than existing homes that had received Fannie Mae mortgages in the past.

  The scale of that shift is insane. And it’s even more insane that this happened without much notice or objection! This was not a reversal of any lending changes that happened from 2002 to 2006. And it led to price patterns that also weren’t reversals of patterns from 2002 to 2006, which is why my regression has those odd residuals from 2006 to 2010.

  …the existing literature has a … fundamental omitted variable problem in that they completely ignore this massive, novel change in underwriting. It is a quite obvious alternative explanation for many of the trends in housing since 2007 to the explanations given in the existing literature.

  It is common for research papers on the period to interpret the extra drop in prices from 2006-2010 as a confirmation of their preferred explanation for rising prices in 2002-2006, based on process-of-elimination logic. This massive change in the types of homes and borrowers served by our dominant mortgage institutions is never one of the eliminated alternative explanations.”

Paper #4: Home Price Trends Point to a Worsening Lack of Supply

This is the most recent paper, which continues to develop the evidence that pre-2008 housing costs were driven by local supply constraints (that make population growth negatively correlated with local housing production), and that the suppression of mortgage access has constrained housing supply across the country since 2008.

• Post #1. This post walks through how population growth could be negatively correlated with housing production, and why that peculiar outcome is a sign of distressingly low housing supply.

  • Twitter thread.

• Post #2. This post walks through the peculiar post-Great Recession US housing market, where prices were pushed down, rents subsequently increased, and construction was stifled, and all of these trends were highly income sensitive.

  • Twitter thread.

• Post #3. This post argues that suppressed mortgage access is the most reasonable explanation for the peculiar housing market patterns that I highlighted in part 2.

  • Twitter thread.

Earlier Work

Here are some links to earlier work that has been a foundation for these papers, plus a couple of links to other related old pieces.

Here are two older papers:

• Here is one I co-authored with Scott Sumner, which basically gives an overview of his market monetarist view of the Great Recession and my view of how housing fits into that, and connects the two narratives.

  • Here is the Twitter thread.

• Here is a paper, “Build More Houses” on housing supply in the 2000s. To my knowledge, even though an over-supply of housing is a key presumption throughout the literature on housing, mortgage regulation, and monetary policy during the financial crisis, there is only one other paper, that I know of, that attempted any thorough macro-level review of housing supply during that period. I wrote of that paper:

In their introductory paragraphs, they wrote, “While it is now clear that too much housing was built in the US in the boom phase, identifying how much and where overbuilding occurred remain important issues.” Yet at the time of their writing, little empirical research on the scale of pre-recession building had been published.

Unfortunately, the answer “There wasn’t too much housing.”, which, it turns out is the correct answer to the question “Was there too much housing before the Great Recession?” lies outside the possible set of answers to the question “How much overbuilding occurred?”. My paper was an attempt to ask the broader question.

Here is the twitter thread for “Build More Houses”. In this paper I showed that many of the homes identified as excessive supply by 2006 were in the Closed Access cities (LA, San Francisco, etc.), which had negative population growth, negligible vacancies, and pitiful housing production. This was an initial empirical step toward the point in my most recent paper that the housing constrained cities have population growth rates now that are negatively correlated with housing production. It is understandable that this would throw analysts and academics off. We have created a peculiar market context where an increase in homes/household is a signal of a destabilizing lack of adequate homes. Urban planning departments have turned the economy upside-down.

I have 2 books:

• “Shut Out”, which pushes back against the housing bubble thesis, highlights the lack of evidence that there was a spike in unqualified home ownership before the Great Recession, details some of the problems caused by inadequate housing, and introduces the conclusion that misguided policy responses to undersupplied housing were responsible for the Great Recession.

• “Building from the Ground Up” digs into the details of the boom and bust timeline and describes how those macroeconomic policy choices were wrong and what damage they caused.

Finally, here are a couple of other links of interest.

• Here is a link to a series of 16 short conceptual articles at Mercatus about housing affordability.

• Here is a link to a paper where I suggest a mortgage amortization that has a relatively fixed repayment schedule that might capture some of the benefits of fixed rate, fixed amortization mortgages while reducing some of the downsides.