Market Urbanism https://marketurbanism.com Liberalizing cities | From the bottom up Thu, 22 Feb 2024 19:54:09 +0000 en-US hourly 1 https://wordpress.org/?v=5.1.1 https://i2.wp.com/marketurbanism.com/wp-content/uploads/2017/05/cropped-Market-Urbanism-icon.png?fit=32%2C32&ssl=1 Market Urbanism https://marketurbanism.com 32 32 3505127 Poor People Move Too https://marketurbanism.com/2024/02/20/poor-people-move/ https://marketurbanism.com/2024/02/20/poor-people-move/#respond Tue, 20 Feb 2024 20:44:58 +0000 http://marketurbanism.com/?p=81984 It is well known that rent control is not particularly effective in controlling rents; cities like New York and San Francisco have rent control and yet are quite expensive. Supporters of rent control, however, often argue that rent control is valuable for a different reason: it makes housing more stable, by making it more difficult […]

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It is well known that rent control is not particularly effective in controlling rents; cities like New York and San Francisco have rent control and yet are quite expensive. Supporters of rent control, however, often argue that rent control is valuable for a different reason: it makes housing more stable, by making it more difficult for a tenant to be evicted for nonpayment of rent.

But it seems to me that there’s an assumption hidden behind this idea: that the neediest people are the ones who are ordinarily most stable, and thus do not suffer from rising housing costs as long as they are protected by rent control or similar measures. For example, law professor Richard Schragger complains that pro-housing zoning reform will “redound to the benefits of investors and developers and not to those residents with limited resources who seek to afford to remain in place.” (emphasis added) In the next sentence, he adds that “those in the market for housing- including middle-class families, recent college graduates, and young families– are often priced out of high-cost urban markets. But reforms should be careful not to equate their interests with those of the working class and especially minority poor…” (emphasis added)* In other words, the “working class” and “minority poor” and people “in the market for housing” are somehow two separate groups.

This assumption might be persuasive if poor people moved less often than other people. But neither common sense nor data support this idea. If you are poor, you might be less likely to have steady employment, which means that your income is likely to be unstable. Thus, you are more likely than other Americans to be evicted or to move voluntarily even if rents are stable. Even if you rely on government transfer payments, you are at risk for bureaucrats questioning your eligibility.

What do the data show? Census Table S0701 shows that over the five year period between 2017 and 2022, 10.6 percent of persons with incomes below the poverty level moved recently within the same county, as opposed to only 6.1 percent of persons with incomes at or above 150 percent of the poverty level. 7 percent of poor Americans switched counties or states, as opposed to 4.7 percent of persons with incomes over 150 percent of the poverty level. Thus, a total of 13.1 percent of the poor moved, as opposed to 10.8 percent of the nonpoor. This is not a new development: between 2011 and 2016, 14.6 percent of the poor moved within a county and 7.2 percent switched counties or states, as opposed to 6.9 percent and 4.4 percent for persons with incomes over 150 percent of the poverty level.

What about in cities with extensive rent control? In New York City, everyone moved less, but poor people still move more. 10 percent of the poor moved within a county or switched counties or states, as opposed to 8.5 percent of persons with incomes over 150 percent of the poverty level. In San Francisco, 15.9 percent of the poor moved, and 13.6 percent of the nonpoor. (These statistics only include people who move into these cities, not people forced out by rising rents).

*My quotes are from page 129 of this article.

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Milton’s Zoning Referendum https://marketurbanism.com/2024/02/19/miltons-zoning-referendum/ https://marketurbanism.com/2024/02/19/miltons-zoning-referendum/#respond Mon, 19 Feb 2024 15:58:38 +0000 http://marketurbanism.com/?p=81865 “Wow!” the reporter said, “I knew you from Milton, but I didn’t know you were from East Milton. Tell me what it feels like?” Well, until last week it was not that dramatic. East Milton is an old railroad-commuter neighborhood favored by affluent Boston Irish. It’s separated from the City of Boston by the Neponset […]

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“Wow!” the reporter said, “I knew you from Milton, but I didn’t know you were from East Milton. Tell me what it feels like?”

Sport sites in East Milton: Sgroiball and sledding

Well, until last week it was not that dramatic. East Milton is an old railroad-commuter neighborhood favored by affluent Boston Irish. It’s separated from the City of Boston by the Neponset River estuary and from the rest of Milton by a sunken interstate highway that makes it more congested and big-city than the rest of town.

Divided East Milton Square, with downtown Boston on the horizon (Photo: Howard Stein Hudson)

MBTA Communities

In January 2021, Massachusetts passed the first transit-oriented upzoning law of the YIMBY era, now called “MBTA Communities,” “MTBA-C”, or “Section 3A”. Implementing regulations assigned a multifamily zoning capacity to each town.

Milton was always going to be one of the toughest cases for MBTA Communities. The northern edge of town is served by the Mattapan Trolley, which John Adams rode to the Boston Tea Party links up to the Red Line at Ashmont. The trolley makes Milton a “rapid transit community”, which means it has to zone for multifamily units equal to 25% of its housing stock. Among the dozen towns in the rapid transit category, Milton is the only one where less than a quarter of current housing units are multifamily; it also has few commercial areas to upzone.

East Milton dissents

East Milton voters went to the polls on Wednesday and led a referendum rebuke of the plan. In Ward 7, it wasn’t close: 82% opposed the rezoning.
The Boston Globe offered a helpful breakdown of the surprisingly varied voting:

There are several hypotheses as to why the neighborhood went against rezoning so hard, all probably played a role.

  • East Milton was assigned more than half the net new
    multifamily zoning capacity despite lacking good transit access.
  • The neighborhood has been in a contentious, multiyear planning/suing process, so at least some residents were defensive and organized at the outset.
  • It’s a very townie neighborhood. Growing up, I took it as a given that anybody who lived near me was Irish Catholic. Not being one myself, I didn’t quite belong. As a whole, the town is 16% Black, but East Milton is just rounding-error Black.

These reasons do not excuse East Milton. Its net multifamily zoning addition is so large because it has allowed so little multifamily housing in the past. The paucity of Black residents certainly suggests that prospective movers feel unwelcome.

Eliot Street YIMBYS

The real man-bites-dog story in Wednesday’s vote isn’t in East Milton. It’s along the street named for the Puritan apostle, which parallels the trolley tracks. The town’s plan (map, ordinance) put as much of the upzoning as possible into commercial or already-multifamily parcels. What was left was absorbed by Eliot Street and Blue Hills Parkway, plus some side streets.

The Neponset River in this section divides a 70% white census tract from a 95% non-white one surrounding Mattapan station. In my teen years, I remember a desultory movement to have the Capen Street trolley stop closed out of concern for crime. I expected these residents to vote no: theirs were the only houses being rezoned, and they live at the bleeding edge of a stark color and culture line.

Zoning plan excerpt (Town of Milton)

The plan rezoned these single-family neighborhoods to allow 3 units per 7,500 square foot lot, up to 2.5 stories. Few, if any houses would be worth scraping, but some might be subdivided.

On Wednesday, the ward including Eliot Street voted 67%-33% in favor. The wards on each side of Blue Hills Parkway were also in favor. I don’t have a theory of the case. One person I spoke to pointed out that it’s a more progressive neighborhood. Another obvious aspect is that people here bought a home along a trolley line – they knew they were living in a city.

Who is the town?

Despite Eliot Street, “the town” failed to abide by MBTA-C. But who, exactly, failed? Is the town its staff? They worked exceptionally hard to comply. Is it the elected council, the Select Board? It complied. Or the representative town meeting members? They voted for the compliant plan 158-76.

But a state law allows voters to appeal the decision of a representative town meeting if they gather enough signatures. They did. In the resulting referendum, “the town” rejected “the town’s” decision.

Show me a hero, and I’ll write you a tragedy

I recently finished Lisa Belkin’s Show Me a Hero. You can take it as a tale about the racism or classism run amok, depending on which side you take. But I see it as a story about local democracy. The ruling in United States v. City of Yonkers didn’t just deconcentrate public housing, it also delegitimized a local democracy. The judge refused to make the hard decisions himself – he forced the city’s elected council to do so.

Whatever you may think of Milton, it is one of the world’s oldest continually-functioning democracies (362 years). It maintained its own militia and welfare system a century before the Declaration of Independence.

Democracies – local or sovereign – should not be omnipotent. Constitutional checks are vital at the top; hierarchical checks put guardrails around locals. Some areas of law are rightly outside local jurisdiction and the state can overrule a town.

But as Attorney General Andrea Campbell decides how to punish Milton for its failure to comply, she should keep in mind that no individual voter or representative should be forced to change his vote. The town can be overruled, but its democracy should not be mocked.

East Milton Square during the construction of the Central Artery (Milton Historical Society)

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Houston as an Affordability Model https://marketurbanism.com/2024/01/15/houston-as-an-affordability-model/ Tue, 16 Jan 2024 03:10:43 +0000 http://marketurbanism.com/?p=81157 In December, I was asked to testify at a House Subcommittee on Housing and Insurance hearing on government barriers to housing construction and affordability. I provided examples of reforms to land regulations that have facilitated increased housing supply, particularly relatively low-cost types of housing, including multifamily, small-lot single-family, and accessory dwelling units. Following the hearing, […]

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In December, I was asked to testify at a House Subcommittee on Housing and Insurance hearing on government barriers to housing construction and affordability. I provided examples of reforms to land regulations that have facilitated increased housing supply, particularly relatively low-cost types of housing, including multifamily, small-lot single-family, and accessory dwelling units.

Following the hearing, I received a good question from Congresswoman Sylvia Garcia. She points out that, as in the country as a whole, the share of cost burdened renters has increased in recent years in Houston, in spite of land use liberalization. She asked what local policymakers could do to improve affordability for low-income residents.

When market-oriented housing researchers point to Houston’s relatively light-touch land use regulations as a model for other U.S. localities to learn from, its declining affordability may cause skepticism. Houston, however, has fared better than many other cities in housing affordability for both renters and homebuyers.

While Houston is the only major U.S. city without use zoning, it does have land use regulations that appear in zoning ordinances elsewhere, including minimum lot size, setback, and parking requirements. These rules drive up the minimum cost of building housing in Houston. However, Houston has been a nationwide leader in reforming these exclusionary rules over the past 25 years. Houston policymakers have enacted rule changes to enable small-lot development and, in parts of the city, they have eliminated parking requirements. In part as a result, Houston’s affordability is impressive compared to peer regions.

As the chart below shows, Houston has the lowest share of cost-burdened renter households among comparable Sun Belt markets for households earning 81% to 100% of the area median income. Only San Antonio and Austin have lower rates of rent burden among households earning 51% to 80% of the area median income.

Source: National Low Income Housing Coalition, The Gap: A Shortage of Affordable Rental Homes (database), accessed January 3, 2023, https://nlihc.org/gap.

At the least-well-off end of the income spectrum, Houston has the lowest rate of homelessness among major U.S. cities, due in part to its relative abundance of housing and in part to well-administered public and nonprofit services for formerly homeless residents.

The next chart shows that at the other end of the spectrum, homeownership is also more attainable to residents earning the region’s median income compared to the same group of Sun Belt metros shown in the chart above.

Source: Zillow Research, Housing Data (database), “ZHVI All Homes Time Series ($),” accessed March 24, 2023, https://www.zillow.com /research/data/; US Census Bureau, American Community Survey (ACS) (database), accessed March 24, 2023, https://www.census.gov/programs ?surveys/acs.

While Houston is a model of relative affordability, its housing market cannot serve its least-well-off residents without aid. As I interpret the evidence, the best way to improve housing affordability and housing quality for households that cannot afford adequate market-rate housing is with housing vouchers or other forms of income assistance targeted to the renter households most in need. The Housing Choice Voucher program improves important outcomes for the households that receive them. Compared to eligible households that do not receive vouchers, those that do suffer less food insecurity, less domestic violence, fewer child separations, and much less housing instability.

Dedicating resources toward vouchers allows dollars to go further relative to dollars dedicated toward new, subsidized housing construction because new-construction housing is generally the most expensive type. Relative to new construction that is fully or partially dedicated to residents of a specific income, vouchers open up opportunities for recipients to live in many different types of housing.

Policymakers in cities like Houston could provide a similar, locally-administered aid for extremely-low-income residents who are not receiving federal Housing Choice Vouchers. However, fiscal constraints and tax competition across local and state borders present challenges for providing this type of aid at the subnational level.

Due in part to the fiscal difficulties in providing costly aid at the local level, local policymakers tend to turn instead to policies to mandate income-restricted housing through programs that appear costless. Increasingly, local policymakers are implementing “inclusionary zoning” programs that require housing developers to set aside a portion of new-construction units as income-restricted. I’ve studied inclusionary zoning in the Baltimore-Washington region, which has the country’s longest history with these mandates. I find that in this case, localities that have adopted mandatory inclusionary zoning programs have seen greater increases in their median house prices relative to what they could have expected without these programs.

Inclusionary zoning can provide large benefits for the few residents who win lotteries for the units that they produce. However, inclusionary zoning provides a very small number of units relative to the number of households that qualify for them based on their income. Further, as I find, these programs can actually make housing affordability worse for the households that don’t specifically benefit from them.

The name “inclusionary zoning” implies that these programs are a reversal of the exclusionary zoning rules that exclude people from neighborhoods and localities on the basis of their income. In fact, inclusionary zoning depends on continued exclusionary zoning in order to function. These programs are typically paired with density bonuses that are intended to fully or partially offset the cost of providing income-restricted units. Without exclusionary zoning, these density bonuses would have no value, and inclusionary zoning would be a clear tax on housing construction.

Even in a city at the far end of land use liberalization, like Houston, the housing market may not adequately serve low-income residents. There is a role for policymakers to provide aid to extremely-low-income households. Expanding the Housing Choice Voucher program is one way to make progress toward improved housing affordability that carries fewer risks than programs that require market-rate housing construction to subsidize income-restricted housing.

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Resources for Reformers: Houston’s minimum lot sizes https://marketurbanism.com/2024/01/11/resources-for-reformers-houstons-minimum-lot-sizes/ Thu, 11 Jan 2024 19:33:56 +0000 http://marketurbanism.com/?p=75440 Updated 1/11/24 to add 3 new papers, Wegmann, Baqai, and Conrad (2023), Dobbels & Tavakalov (2023), and Hamilton (2024). The original post was published 3/14/23. A concerted research effort has brought minimum lot sizes into focus as a key element in city zoning reform. Boise is looking at significant reforms. Auburn, Maine, and Helena, Montana, […]

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Updated 1/11/24 to add 3 new papers, Wegmann, Baqai, and Conrad (2023), Dobbels & Tavakalov (2023), and Hamilton (2024). The original post was published 3/14/23.

A concerted research effort has brought minimum lot sizes into focus as a key element in city zoning reform. Boise is looking at significant reforms. Auburn, Maine, and Helena, Montana, did away with minimums in some zones. And even state legislatures are putting a toe in the water: Bills enabling smaller lots have been introduced [in 2023] in Arizona, Massachusetts, Montana, New York, Texas, Vermont, and Washington. The bipartisan appeal of minimum lot size reform is reflected in Washington HB 1245, a lot-split bill carried by Rep. Andy Barkis (R-Chehalis). It passed the Democratic-dominated House of Representatives by a vote of 94-2 and has moved on to the Senate.

City officials and legislators are, reasonably, going to have questions about the likely effects of minimum lot size reductions. Fortunately, one major American city has offered a laboratory for the political, economic, and planning questions that have to be answered to unlock the promise of minimum lot size reforms.

Problem, we have a Houston

Houston’s reduced minimum lot sizes from 5,000 to 1,400 square feet in 1998 (for the city’s central area) and 2013 (for outer areas). This reform is one of the most notable of our times – and thus has been studied in depth.

To bring all the existing scholarship into one place, I’ve compiled this annotated bibliography covering the academic papers and some less-formal but informative articles that have studied Houston’s lot size reform. Please inform me of anything I’m missing – I’ll add it.

Political economy of Houston’s reform

M. Nolan Gray & Adam Millsap (2020). Subdividing the Unzoned City: An Analysis of the Causes and Effects of Houston’s 1998 Subdivision Reform. Journal of Planning Education and Reform.

Jake Wegmann (2020). Bayou City Townhouse Boom: Does Houston Have Something to Teach Us About Pro-Climate Urban Transformation? Platform,
The University of Texas at Austin School of Architecture.

NuNu Chang (2018). Planning the Houston Way, Part II: Special Minimum Lot Size. Rice Design Alliance.

Jake Wegmann, Aabiya Noman Baqai, and Josh Conrad (2023). Here Come the Tall Skinny Houses: Assessing Single-Family to Townhouse Redevelopment in Houston, 2007–2020. Cityscape.

Big ideas

  • HOA deed restrictions & opt-out options enabled the broad reform of Houston’s lot-size mandates.
  • The reform slowed gentrification in low-income neighborhoods, concentrating rather in middle-income neighborhoods.
  • Builders took advantage of reform to build “Houston townhouses”, which are not attached to neighboring houses and are usually 3 stories tall with a “tuck-under” garage.
  • Normal fee simple ownership is a key to townhouse success. Nobody wanted condo-ownership townhouses.
  • Wegmann and co-authors argue from tax data that relatively few Houston townhouses replaced single-family homes. But Dobbels and Takavalov (below) claim that 59% of townhouses are on old single family lots. This contradiction remains to be resolved.

Discussion

Third Ward townhomes (Google Maps, via Guajardo 2021)

History and geography of Houston townhomes

Stephen Fox (2000). The Houston Townhouse. Cite: The Architecture and Design Magazine of Houston.

John Park, Luis Guajardo, Kyle Shelton, Steve Sherman, and William Fulton (2021). Re-Taking Stock: Understanding How Trends in the Housing Stock and Gentrification are connected in Houston and Harris County. Kinder Institute for Urban Research, Rice University.

Big ideas

  • The unique “detached townhouse” is a new concept, probably owing to the 1999 regulatory reform.
    • As of 2000, Fox makes no mention of detached townhomes.
    • In 2005, Houston had about 12,000 detached townhomes and 31,000 attached townhomes.
    • From 2005 to 2018, Houston added 34,000 detached townhomes against 5,000 attached townhomes.
  • Detached townhomes are common in inner neighborhoods undergoing redevelopment; greenfield development is almost entirely traditional single family and large-scale multifamily.
  • Construction and demolition are more frequent in affluent and already-gentrified core neighborhoods than gentrifying ones, as shown in Figure 4.
Figure 4 (Park et al 2021): Demolitions are concentrated in Houston’s affluent west

Discussion

Who benefits from small lots?

Mike Mei (2022). House Size and Household Size: The Distributional Effects of the Minimum Lot Size Regulation. Working paper.

Gregory Dobbels and Suren Tavakalov (2023). Not in My Back Yard: The Local Political Economy of Residential Land-Use Regulations. Working paper.

Big ideas

  • From Mei:
    • Small lots result in smaller houses. The average new house size in Houston declined by 10 to 15 percent when small lots were legalized.
    • A simplified model shows that smaller, lower-income families and those who have not yet bought a house are big winners. Most existing homeowners took small losses (See Figure 15).
    • The lot size reform was equivalent to a one-time gift of $18,000 to every Houston household living in a single-family home (the model doesn’t incorporate apartment dwellers). That adds up to about $8 billion.
Figure 15 (Mei 2022): Renters (who are future buyers) gain a lot, homeowners lose a little
  • From Dobbels & Tavakalov:
    • If the authors’ “revealed preference” approach is correct, most incumbent homeowners dislike added density on their block. They estimate that the subdivision of 2 old houses into 4 townhouses creates a $6,900 amenity cost for each other house on a block.
    • But incumbents value the profitable sale opportunity even more. The typical homeowner comes out about $2,300 ahead.
    • 16% of eligible blocks took the “special minimum lot size” opt-out and kept the old 5,000 square foot minimum. The opt outs were more likely affluent and white.
Table 4, Dobbels & Tavakalov, showing the costs and benefits of lot size reform to incumbents

Discussion

Front yards, Kaler Rd (Google Maps)

Yard space isn’t highly valued

Salim Furth (2021). Foundations and Microfoundations: Building Houses on Regulated Land. Mercatus Center Working Paper.

M. Nolan Gray and Salim Furth (2019). Do Minimum-Lot-Size Regulations Limit Housing Supply in Texas? Mercatus Center Research Paper.

Big ideas

  • Houston area homebuyers are happy to pay more for bigger houses – but they don’t place much value on larger yards.
  • In suburbs of Dallas and Austin with large minimum lot sizes, most house lots are built very close to the minimum lot size (or below it via various exceptions). See Figure 4.
    • But in Pearland, with many small lots available in nearby Houston, suburbanites are happy to buy larger-than-mandated lots.
Figure 4 (Gray and Furth 2019): Few people in Pflugerville want such a large lot.

Discussion

“Free tacos with purchase” – Montrose, Houston (Salim Furth)

Did Lot Size Reform Change Property Values?

Joseph Shortell (2022). The Effect of a Minimum Lot Size Reduction on Residential Property Values: The Case of Houston. Universitat de Barcelona master’s thesis.

Emily Hamilton (2024) addresses the same question by comparing land price growth in areas where minimum lot sizes were lowered in 2013 to areas where it had been lowered in 1999.

Big ideas

  • In theory, lowering lot size mandates ought to raise the price of land while lowering the price of existing structures.
  • Comparing Houston lots (which benefited from reform) to those outside the city, Shortell finds that the price of land definitely rose and the price of existing structures may have fallen (but the evidence is less clear).
  • With an all-city sample, however, Hamilton finds that minimum lot size reform had either no effect or a negative effect on assessed land values.

Discussion

Nobody has critiqued or dissected Shortell (2022) yet. It is an excellent master’s thesis, but readers should bear in mind that it is student work and has not undergone peer review. Given the disagreement between these two papers – which both rely on assessment data – more research may be needed.

Hurricane Harvey
(U.S. Air National Guard photo by Staff Sgt. Daniel J. Martinez)

How does small lot development handle stormwater?

Samuel Brody, Russell Blessing, Antonia Sebastian & Philip Bedient (2012). Examining the impact of land use/land cover characteristics on flood losses. Journal of Environmental Planning and Management.

Big ideas

  • The authors examined the Clear Creek watershed, in Houston’s southeastern suburbs. It’s not directly a study of Houston small-lot development, though.
  • They found a mixed relationship between impervious cover and flood losses. An area surrounded by “medium” coverage development (50 to 79 percent covered) fared best, even better than one surrounded by “developed open space” (0 to 20 percent).
    • The authors guess this is because denser development is usually accompanied by better infrastructure.
    • The worst-performing category was “low” coverage (20 to 49 percent).

Discussion

  • Houston planners have noted that impact fees from small-lot infill development have helped fund stormwater improvements and sidewalks. Houston incentivizes shared courtyards in part because they handle stormwater better. Further research is needed on the fiscal consequences of small lot reform.
  • Phil Magness offers a quick history of Houston flooding.
  • Nolan Gray notes the irrelevance of zoning to flood damage.

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Hopefully, AI will create a perpetual housing crisis https://marketurbanism.com/2023/12/12/hopefully-ai-will-create-a-perpetual-housing-crisis/ Tue, 12 Dec 2023 12:30:42 +0000 http://marketurbanism.com/?p=80644 I don’t know how successful artificial intelligence will be. But let’s agree, for the moment, to consider a reasonably optimistic case where AI delivers significant productivity gains across a broad range of tasks – but not in a way that radically alters our Newtonian constraints. What would happen to housing economics and, consequently, housing politics? […]

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I don’t know how successful artificial intelligence will be. But let’s agree, for the moment, to consider a reasonably optimistic case where AI delivers significant productivity gains across a broad range of tasks – but not in a way that radically alters our Newtonian constraints. What would happen to housing economics and, consequently, housing politics?

TL;DR

  • Construction won’t be much affected by AI.
  • Consumers will be richer and spend a bigger share of their incomes on housing.
  • The stakes around housing policy will only grow.
Single-pen log house, Indiana (nyttend)

Inscriptibility

Karl Marx divided the economic world into capital and labor. More recent economists have frequently (and self-regardingly) divided labor into low-skill and high-skill. In an AI world, we need to start talking about inscriptible and uninscriptible labor. I’m using a circular definition on purpose – AI will replace inscriptible labor because inscriptible labor is the type that AI is good at replacing – because I have only a fuzzy idea what AI will be good at.

(A diversion)

(Why inscriptible rather than legible, in a James C. Scott sense? I thank Bard for the suggestion. Think about visual art – AI is probably no better than humans at guessing what nuances a human artist intended, but it can produce human-quality visual art rich with nuance. Since AI’s value is partly predicated on repetition speed, it will thrive in arenas where failures are costless. Thus, AI may be formulating 99% of new drugs in a few years even if nobody trusts it to perform a simple surgery. That’s an inscriptibility difference, not a legibility difference.

The most inscriptible human tasks are presumably those that simpler software replaced long ago, usually called “routine.” The big surprise of 2023 AI was the advances that software made with tasks we have considered creative. The “routine” concept was valuable as long as physical and informational machines advanced at comparable paces. But with informational machines far outpacing physical ones, it now seems that routine tasks handling physical materials are likely to be assigned to humans longer than non-routine tasks handling information.

Will any capital be replaced by AI? Other software and some intellectual property, sure. But most capital is buildings and vehicles.

Mixed-materials house, Seoul

Construction

Construction, especially low-rise residential construction, relies heavily on uninscriptible labor – individual workmen solving physical problems on a site-by-site basis.

To be sure, there have been and ought to be more productivity increases. But promising changes remain just out of reach. Factory-built housing is the Brazil of construction. And AI adds almost nothing to the relevant mid-20th century factory techniques. Besides, richer consumers (we’ll get to that) will want bespoke, not standardized, homes.

Looking upstream – softwood lumber growing and harvesting, Portland cement manufacture – one sees few obvious gains from better software.

Construction will gain a bit from the “ripple effect”: as people leave sectors where labor demand declines, more will enter construction.

But overall, construction productivity will be a laggard in an era of potentially – hopefully – high productivity growth. Any argument for a big AI effect in construction (e.g., via inventions) must admit even larger effects in most other fields. The robots will eat plumbers last.

Apartment interior, Stockholm

Consumer mindset

In our hypothesized future, most workers will be more productive than they are today. (Some – I think of drivers – will experience so much productivity increase that they lose their jobs.) As consumers, most will face a world of higher wages (or, equivalently, lower prices).

This popular graphic shows how price levels have changed in 20 years. Overall inflation came in just below the price of housing over this period; average wages grew a bit more. AI, in our optimistic scenario, takes a big bite out of the eds-and-meds inflation near the top of the graph.

That’s great – but it will leave housing even more exposed as a productivity laggard.

So what do deep-pocketed consumers do when they have more money, fewer college loans, and lower medical expenses?

They spend more on housing!

Economists have spent lots of time studying what happens to housing expenditures when people have more money. There are a range of estimates, each with its own nuance. A solid starting point is that the average share of income spent on housing is mostly constant across time and place, implying an income-expenditure elasticity of 1.0 (Davis & Ortalo-Magne 2011). A more optimistic estimate of that elasticity is 2/3 (Albouy, Ehrlich, and Liu 2016). A related estimate of the income-home price elasticity finds a U.S. average of 0.81, but with wide variation between cities (Oikarinen et al 2018).

Once we split rental and ownership costs out, it’s obvious that interest rates and timing luck for purchasers can move observed “affordability” metrics drastically:

Speculating, I predict that housing expenditure as a share of income will rise around these choppy trends. There’s no deep reason why it should be constant. If other major categories are cheaper (and the categories are complements), then expenditures should rise. The services we derive from “shelter” are also growing – a nice house today includes not only a home office but what could only be described to a 1960s family as a miniature cinema.

Obviously, there are two ways to spend more on housing: Buy more or better housing, or bid up the per-quality-adjusted-square-foot price. Oikarinen et al found what market urbanists expect: the home price elasticity was smaller in cities with a less constrained housing supply.

Higher per-square-foot housing prices are obviously going to hurt whoever is on the outside of this boom. And even higher-quality housing stock has historically made housing concerns more salient. I’ve illustrated this article with pictures of old houses. They’re cute, but they are far below modern legal and cultural standards.

Painted plaster houses, Tangier (Christopher RASCLE)

YIMBY forever

In their short Mercatus book on high prices and Baumol’s cost disease, Eric Helland and Alex Tabarrok note that having a few high cost sectors is a price worth paying for progress:

There is nothing wrong with a future world in which consumers spend most of their income on live musical performances.

But people in 2040 or 2080 are no more likely than our own generation to be complacently grateful for their material abundance relative to the past. Our own YIMBY movement, after all, arose not from poverty but from constrained affluence. As I’ve pointed out elsewhere, the oddest thing about the “abundance agenda” moment is that it’s occurring at the most materially-abundant time in history (so far).

AI success will not extinguish the motives and causes of YIMBY v. NIMBY politics. Rather, it will deepen them. An AI-enabled world will produce even more people who fit the profile of YIMBY recruits. And, by raising the share of expenditure on housing, it will raise the stakes for both sides.

Among those left behind by productivity growth, housing will be – even more than it is now – the clearest outward signal of income inequality. The political and ethical stakes of the housing debate are going to rise, not fall.

Build accordingly.

Historic wooden houses, Bangkok (shankar s.)

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The weird D.C. housing grift that’s sending a former FBI agent to jail https://marketurbanism.com/2023/12/08/the-weird-d-c-housing-grift-thats-sending-a-former-fbi-agent-to-jail/ Fri, 08 Dec 2023 16:14:09 +0000 http://marketurbanism.com/?p=80595 WASHINGTON – David Paitsel, 42, a former FBI agent, and Brian Bailey, 53, a D.C. real estate developer were sentenced today on bribery and conspiracy charges for their role in schemes involving confidential information held by the D.C. Department of Housing and Community Development United States Attorney’s office There are plenty of housing laws you […]

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WASHINGTON – David Paitsel, 42, a former FBI agent, and Brian Bailey, 53, a D.C. real estate developer were sentenced today on bribery and conspiracy charges for their role in schemes involving confidential information held by the D.C. Department of Housing and Community Development

United States Attorney’s office

There are plenty of housing laws you can break. But these grifters were busted only for bribing a city official for information. Otherwise, they used the housing law – the most innocent-sounding of all housing laws – correctly.

Washington DC has a strong Tenant Opportunity to Purchase Act (TOPA). When a landlord sells, tenants have the right to match any offer, conceivably buying their own building. That never happens. But TOPA also allows tenants to sell their rights to literally anyone else. The law treats the new owner of the TOPA rights with the same exaggerated deference as a tenant.

The TOPA grift goes like this: A TOPA shark, like Paitsel and Bailey, approaches tenants whose building is on the market. The “approach”, as I’ve witnessed it, can be a hand-scrawled note placed in the tenants doors or mailboxes. The tenants rarely know the mechanics of buying a house, let alone utilizing an obscure city-specific TOPA scheme that would have to involve collective action among many tenants.

So the sharks offer the tenants a few hundred dollars for their rights. If the offer is accepted, the shark informs the landlord.

Now suppose a prospective buyer comes along and offers $1,200,000 for a D.C. sixplex. The landlord must inform the shark, who now has the right to match any bona fide offer on the property. But the shark has no interest in buying – he just demands ten or twenty thousand dollars to surrender the rights.

If the landlord resists extortion, the shark finds ways to delay the sale until the buyer walks away. If he finds a misspelled address or other technicality in the landlord’s legally required communications, he can add time to the clock. The shark can force the landlord to wait up to 240 days for financing to be approved. Of course, if the landlord does wait all that time, the shark can just decline to purchase…at which point the entire charade begins anew.

More often, the landlord will submit to extortion – if not before the first prospective buyer walks away in frustration, then before the second does the same.

(Patsel and Bailey didn’t get in trouble for extorting landlords. That’s within the letter of the law. Instead, they were busted for trying to make their shakedown operation more efficient, buying the names and addresses of TOPA-notified tenants. The info presumably gave them an edge on their competitors who drive around with sticky notes seeking for-sale signs on small buildings.)

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Unexpected correlation in Census housing data https://marketurbanism.com/2023/11/22/unexpected-correlation-in-census-housing-data/ Wed, 22 Nov 2023 23:16:46 +0000 http://marketurbanism.com/?p=80222 Since 1973, the US Census Bureau has administered the American Housing Survey (AHS) in odd-numbered years. Surveyors ask questions about the quality and value of respondents’ housing, and have a battery of questions for the subset of respondents who moved recently, asking about their search process. The AHS regularly adds new questions and rephrases old […]

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Since 1973, the US Census Bureau has administered the American Housing Survey (AHS) in odd-numbered years. Surveyors ask questions about the quality and value of respondents’ housing, and have a battery of questions for the subset of respondents who moved recently, asking about their search process. The AHS regularly adds new questions and rephrases old ones from year to year. 

Photo by Eugen Kucheruk on Unsplash

In 2021, they rolled out a group of three new questions. One asks recent movers whether they spent more or less than a month searching for their new home. This is the AHS’s first-ever variable dealing with search time. The other two, which are similar to questions asked in previous years, ask about search scope: whether respondents looked for housing in neighborhoods besides the one they ended up moving to, and whether they looked at other housing units in the same neighborhood they moved to.

In analyzing these new questions within the largest 15 metro areas in the US, I found a curious and hard-to-explain relationship. Search time – the binary variable of taking more or less than a month to look for a home – seems to be predicted by the population of a metropolitan area (with r=0.57 and p > |t| = 0.026), whereas search scope in the sense of looking at multiple neighborhoods or multiple units within a neighborhood seems to be predicted by the cost of housing as gathered from 2021 Zillow data (for looking at multiple neighborhoods, r=0.65 and p > |t| = 0.009; for looking at multiple units, r=0.68 and p > |t| = 0.007). 

The inverse set of relationships are much weaker. Price and likelihood of taking over a month to search are positively correlated, but the relationship is not statistically significant; the same is true of the relationship between metro population and likelihood of looking at multiple units within their neighborhood. The relationship between metro population and looking in multiple neighborhoods is even weaker. The strong relationships outlined above are robust to controlling for price and population respectively. It’s possible that the vague definition of “neighborhood” could be pushing down the correlation between looking at multiple neighborhoods and metro population: if people in bigger cities imagine “neighborhoods” as larger units than their counterparts in smaller cities, they’d be more likely to search only within one “neighborhood”.

It’s hard to tell a story about this unusual finding, given how new these questions are. Perhaps future iterations of the same variables will firm up the weaker correlations observed in 2021. For that matter, the difference might be just an artifact of region-specific data only being available for the top 15 metro areas. But if years hence it becomes conventional wisdom that people look longer in bigger cities but more widely in more expensive cities, you heard it here first.

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An Autopsy of Hsieh & Moretti (2019)? https://marketurbanism.com/2023/11/13/an-autopsy-of-hsieh-moretti-2019/ Mon, 13 Nov 2023 20:07:55 +0000 http://marketurbanism.com/?p=80094 Update 11/20: Chang-Tai Hsieh counters that Greaney’s critique ignores general equilibrium effects which make labor scale invariant. That doesn’t address the alleged coding errors. We’ll see – and perhaps I wrote an autopsy too early. Thanks to Bryan Caplan for getting Hsieh’s response out to the world. Popular urban econ should be shaken with the […]

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Update 11/20: Chang-Tai Hsieh counters that Greaney’s critique ignores general equilibrium effects which make labor scale invariant. That doesn’t address the alleged coding errors. We’ll see – and perhaps I wrote an autopsy too early. Thanks to Bryan Caplan for getting Hsieh’s response out to the world.

Popular urban econ should be shaken with the revelation that its most famous academic paper had two coding errors, a serious theoretical flaw, and a hypothesized mechanism that – when executed correctly – did not work at all.

Chang-Tai Hsieh and Enrico Moretti’s paper Housing Constraints and Spatial Misallocation noted that “high productivity cities like New York and the San Francisco Bay Area have adopted stringent restrictions to new housing supply, effectively limiting the number of workers who have access to such high productivity” – and used a simple model to estimate how much US growth could have been unlocked by decreasing those restrictions.

Brian Greaney, an assistant professor at the University of Washington, released notes on his replication of The paper gained widespread notice as a 2015 NBER working paper and was published in 2019 in American Economic Journal: Macroeconomics. The paper already has an impressive 813 scholarly citations.

But the paper has problems – fatal problems – and is embarrassingly sloppy. The embarrassment extends beyond the authors to the many referees and editors who missed surface, implementation, architectural, and foundational problems over a four-year period of peer review and discussion.

Surface

Greaney is not the first to find a mistake in Hsieh & Moretti. Bryan Caplan caught a major inconsistency in 2021, one that readers (myself included) and referees should have caught earlier. The authors reported huge annual effects adding up to a merely-large effects over 45 years. He noted a few other arithmetical mistakes and generously concluded, “authors and referees alike focused so intently on the advanced mathematics that they glossed over some elementary yet crucial errors.” This turns out not to have been true.

Implementation

Greaney found two coding errors in Hsieh & Moretti’s publicly-posted Stata code. (Thank goodness for public code requirements!)

If the coding errors (only) were corrected, the headline result would be reversed: “their model predicts that the land-use deregulation experiment they propose would decrease output.” Nobody thinks that this is the right answer – but it’s an answer that would have alerted the authors to a deeper error.

Architecture

Why did correct code yield an unintuitive answer? Because Hsieh and Moretti’s model was scale-dependent. Anyone interested in the math should read Greaney’s brief explanation. This was not hard to fix – Greaney does so, and a diligent referee might have caught the problem.

With the problems fixed, Hsieh and Moretti’s conceptual argument delivers a big nothing: Greaney reports that liberalizing three superstar cities would boost national GDP by just 0.02%.

The nearly-null result is surprising to urbanists – but it isn’t so surprising when you realize the modeling approach that Hsieh and Moretti took to build their idea. They treat each metro area as a separate unit that takes labor as a factor of production with decreasing marginal returns. Thus, lower housing prices in superstar cities attract more migrants, decreasing local wages and increasing wages in the sending areas. Since each migrant decreases wages in one place and boosts them in another, it’s not so surprising that the net effect is near zero.

Foundation

Urban economists Gilles Duranton and Diego Puga offer a much richer treatment of local agglomeration and congestion effects. Their work ought to replace Hsieh and Moretti as the academic anthem for YIMBYism, but there’s still a fundamental problem:

Silicon Valley and Manhattan attract especially productive, high-income people. Even when the absolute number of workers is low, as in Silicon Valley, the concentration of complementary talents can be enough to achieve large agglomeration benefits through selective migration to innovation clusters


Contrary to the models, the next 35 million people to move to the Bay Area would probably not be as tech savvy or as risk loving as the first 5 million. The next 20 million people to move to New York would include a lower proportion of investment bankers willing to work 70-hour weeks.

There’s a vigorous debate in urban economics about the strength of local agglomeration effects. One paper says, “two thirds of the variation in observed wage premiums for working in different CZs is attributable to skill?based sorting.” (In English, that means that most of the difference between local wages arise because different kinds of people chose to live there. You can’t get a big raise by moving.) Another paper finds that the difference is “about half”, not two thirds. Oh wait, it’s the same paper – just a new revision.

These debates are hard enough when all the code and arithmetic are sound – we readers and referees should work harder to ensure that the papers we’re debating are executed correctly.

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