# Greenbelts Help Cars

A number of major cities, most notably London, have designated areas around their built-up areas as green belts, in which development is restricted, in an attempt to curb urban sprawl. The towns within the green belt are not permitted to grow as much as they would in an unrestricted setting, where the built-up areas would merge into a large contiguous urban area. Seeking access to jobs in the urban core, many commuters instead live beyond the greenbelt and commute over long distances. There has been some this policy’s effect on housing prices, for example in Ottawa and in London by YIMBY. In the US, this policy is less common than in Britain and Canada, but exists in Oregon in the form of the urban growth boundaries (UGBs), especially around Portland. The effect has been the same, replacing a continuous sprawling of the urban area with discontinuous suburbanization into many towns; the discontinuous form is also common in Israel and the Netherlands. In this post, I would like to explain how, independently of issues regarding sprawl, such policies are friendlier to drivers than to rail users.

Let us start by considering what affects the average speed of cars and what affects that of public transit. On a well-maintained freeway without traffic, a car can easily maintain 130 km/h, and good cars can do 160 or more on some stretches. In urban areas, these speeds are rarely achievable during the day; even moderate traffic makes it hard to go much beyond 110 or 120. Peak-direction commutes are invariably slower. Moreover, when the car gets off the freeway and onto at-grade arterial roads, the speed drops further, to perhaps 50 or less, depending on density and congestion.

Trains are less affected by congestion. On a well-maintained, straight line, a regional train can go at 160 km/h, or even 200 km/h for some rolling stock, even if headways are short. The busiest lines are typically much slower, but for different reasons: high regional and local traffic usually comes from high population density, which encourages short stop spacing, such that there may not be much opportunity for the train to go quickly. If the route is curvy, then high density also makes it more difficult to straighten the line by acquiring land on the inside of the curves. But by and large, slowdowns on trains come from the need to make station stops, rather than from additional traffic.

Let us now look at greenbelts of two kinds. In the first kind, there is legacy development within the greenbelt, as is common around London. See this example:

The greenbelt is naturally in green, the cities are the light blue circles with the large central one representing the big city, and the major transportation arteries (rail + freeway) are in black. The towns within the greenbelt are all small, because they formed along rail stops before mass motorization; the freeways were built along the preexisting transportation corridors. With mass motorization and suburbanization, more development formed right outside the greenbelt, this time consisting of towns of a variety of sizes, typically clustering near the freeways and railways for best access to the center.

The freeways in this example metro area are unlikely to be very congested. Their congestion comes from commuters into the city, and those are clustered outside the greenbelt, where development is less restricted. Freeways are widened based on the need to maintain a certain level of congestion, and in this case, this means relatively unimpeded traffic from the outside of the green belt right up until the road enters the big city. Under free development, there would be more suburbs closer to the city, and the freeway would be more congested there; travel times from outside the greenbelt would be longer, but more people would live closer to the center, so it would be a wash.

In contrast, the trains are still going to be slowed down by the intermediate stops. The small grandfathered suburbs have no chance of generating the rail traffic of larger suburbs or of in-city stops, but they still typically generate enough that shutting them down to speed traffic is unjustified, to say nothing of politically impossible. (House prices in the greenbelt are likely to be very high because of the tight restrictions, so the commuters there are rich people with clout.) What’s more, frequency is unlikely to be high, since demand from within the greenbelt is so weak. Under free development, there might still be more stops, but not very many – the additional traffic generated by more development in those suburbs would just lead to more ridership per stop, supporting higher frequency and thus making the service better rather than worse.

Let us now look at another greenbelt, without grandfathered suburbs, which is more common in Canada. This is the same map as before, with the in-greenbelt suburbs removed:

In theory, this suburban paradigm lets both trains and cars cruise through the unbuilt area. Overall commutes are longer because of the considerable extra distance traveled, but this distance is traversed at high speed by any mode; 120 km/h is eminently achievable.

In practice, why would there be a modern commuter line on any of these arteries? Commuter rail modernization is historically a piecemeal program, proceeding line by line, prioritizing the highest-trafficked corridors. In Paris, the first commuter line to be turned over to the Metro for operation compatible with city transit, the Ligne de Sceaux, has continuous urban development for nearly its entire length; a lightly-trafficked outer edge was abandoned shortly after the rest of the line was electrified in 1938. If the greenbelt was set up before there was significant suburbanization in the restricted area, it is unlikely that there would have been any reason to invest in a regional rail line; at most there may be a strong intercity line, but then retrofitting it to include slower regional traffic is expensive. Nor is there any case for extending a high-performing urban transit line to or beyond a greenbelt. Parts of Grand Paris Express, namely Lines 14 and 11, are extended from city center outward. In contrast, in London, where the greenbelt reduces density in the suburbs, high investment into regional rail focuses on constructing city-center tunnels in Crossrail and Crossrail 2 and connecting legacy lines to them. In cities that do not even have the amount of suburban development of the counties surrounding London, there is even less justification for constructing new transit.

The overall picture in which transit has an advantage over cars at high levels of density is why high levels of low-density sprawl are correlated with low transit usage. But I stress that even independently of sprawl, greenbelts are good for cars and bad for transit. A greenbelt with legacy railway suburbs is going to feature trains going at the normal speed of a major metro area, and cars going at the speed of a more spread out and less populated region. Even a greenbelt without development is good urban geography for cars and bad one for transit.

As a single exception, consider what happens when a greenbelt is reserved between two major nodes. In that specific case, an intercity line can more easily be repurposed for commuting purposes. The Providence Line is a good example: while there’s no formal greenbelt, tight zoning restrictions in New England even in the suburbs lead to very low density between Boston and Providence, which is nonetheless served by good infrastructure thanks to the strength of intercity rail travel. The MBTA does not make good use of this infrastructure, but that’s beside the point: there’s already a high-speed electrified commuter line between the two cities, with widely spaced intermediate stops allowing for high average speeds even on stopping trains and overtakes that are not too onerous; see posts of mine here and here. What’s more, intercity trains can be and are used for commutes from Providence to Boston. For an analogous example with a true greenbelt, Milton Keynes plays a role similar to Providence to London’s Boston.

However, this exception is uncommon. There aren’t enough Milton Keyneses on the main intercity lines to London, or Providences on the MBTA, to make it possible for enough transit users to suburbanize. In cities with contiguous urban development, such as Paris, it’s easier. The result of a greenbelt is that people who do not live in the constrained urban core are compelled to drive and have poor public transportation options. Once they drive, they have an incentive to use the car for more trips, creating more sprawl. This way, the greenbelt, a policy that is intended to curb sprawl and protect the environment, produces the exact opposite results: more driving, more long-distance commuting, a larger urban footprint far from the core.

# A Theory of Zoning and Local Decisionmaking

This weekend there’s a conference in the US, YIMBY 2016, by a national network of activists calling for more housing. I am not there, but I see various points raised there via social media. One is a presentation slide that says “NIMBYism is a collective action problem: no single neighborhood can lower prices by upzoning; might still be in everyone’s interest to upzone at city/state level.” I think this analysis is incorrect, and in explaining why, I’d like to talk about a theory of how homeowners use zoning to create a housing shortage to boost their own property values, and more generally how long-time residents of a city use zoning to keep out people who are not like them. In this view,zoning is the combination of a housing cartel, and a barrier to internal migration.

For years, I’ve had trouble with the housing cartel theory, because of a pair of observations. The first is that, contra the presentation at YIMBY, zoning is driven by homeowners rather than by renters; for an overview, see the work of William Fischel. The second is that restrictive zoning typically correlates with local decisionmaking, such as in a neighborhood or small city, while lax zoning typically correlates with higher-level decisionmaking, such as in a city with expansive municipal boundaries or in an entire province or country; see below for more on this correlation. These two observations together clash with the housing cartel theory, for the inverse of the reason in the above quote from the YIMBY presentation: it’s more effective to create a housing shortage in a large area than in a small one.

To a good approximation, land value equals (housing price – housing construction cost)*allowed density. If a small municipality upzones, then as in the quote, housing price doesn’t change much, but allowed density grows, raising the price a homeowner can get by selling their house to developers who’d build an apartment building. In contrast, if a large municipality upzones then housing prices will fall quite a bit as supply grows, and depending on the price elasticity, land value might well go down. If x = housing price/housing construction cost and e = price elasticity for housing, i.e. price is proportional to density^(-1/e), then maximum land value occurs when x = e/(e-1), provided e > 1; if e < 1 then maximum value occurs when x is arbitrarily large. Price elasticity is much higher in a small municipality, since even a large increase in local housing supply has a small effect on regional supply, limiting its ability to reduce prices. This implies that, to maximize homeowner value, small municipalities have an incentive to set density limits at a higher level than large municipalities, which will be seen in faster housing growth relative to population growth.

What we see is the exact opposite. Consider the following cases, none a perfect natural experiment, but all suggestive:

1. In the Bay Area, we can contrast San Francisco (a medium-size urban municipality), San Jose and generally Santa Clara County (San Jose is medium-size for a central city and very large for a suburb), and San Mateo County (comprising small and medium-size suburbs). San Mateo County is by far the stingiest of the three about permitting housing: over the last three years it’s averaged 1,000 new housing units per year (see here); in 2013, the corresponding figures elsewhere in the Bay Area were 2,277 new housing units in San Francisco and 5,245 in Santa Clara County. Per thousand people (not per housing unit), this is 2.63 in San Francisco, 2.73 in Santa Clara, and 1.31 in San Mateo. In Alameda County, comprising medium-size cities and suburbs, with a less hot housing market because of the distance from Silicon Valley jobs, growth was 2,474 units, 1.51 per 1,000 people. In small rich Silicon Valley municipalities like Palo Alto and Menlo Park, NIMBYs have effectively blocked apartment construction; in much larger and still rich San Jose, the city has a more pro-growth outlook.

2. Among the most important global cities – New York, Paris, London, and Tokyo – Tokyo has by far the fastest housing stock growth, nearly 2% a year; see article by Stephen Smith. In Japan, key land use decisions are made by the national government, whereas in Paris, London, and New York, decision is at a lower level. London builds more than New York and Paris; its municipal limit is much looser than Paris’s, with 8.5 million people to Paris’s 2.2 million even though their metro areas have similar populations. New York has a fairly loose limit as well, but the development process empowers lower-level community boards, even though the city has final authority.

3. Canada has a relatively permissive upzoning process, and in Ontario, the planning decisions are made at the provincial level, resulting in about 1.3% annual housing growth in Toronto in the previous decade; in the same period, San Jose’s annual housing growth was about 1% and San Francisco’s was 0.9%.

4. France has recently made a national-level effort to produce more housing in the Paris region, especially social housing, due to very high housing prices there. Last decade, housing production in Ile-de-France was down to about 30,000-35,000 per year, averaging to 2.6 per 1,000 people, similar to San Francisco; see PDF-pp. 4-5 here and the discussion here. With the new national and regional effort at producing more social housing, plans appear to be on track to produce 30,000 annual units of social housing alone in the next few years; see PDF-p. 6 here. With 7,000 annual units within city limits, Paris expects to build somewhat more per capita than the rest of the region.

In France, the combination of a national focus on reducing housing burden and the observation that higher-level decisionmaking produces more housing makes sense. But elsewhere, we need to ask how come homeowners aren’t able to more effectively block construction.

My theory is that the answer involves internal migration. Consider the situation of Palo Alto: with Stanford and many tech jobs, it is prime location, and many people want to move there. The homeowners are choosing the zoning rule that maximizes their ability to extract rents from those people, in both the conventional sense of the word rent and the economic sense. Now consider decisionmaking at the level of the entire state of California. California can raise housing prices even more effectively than Palo Alto can by restricting development, but unlike Palo Alto, California consists not just of residents of rich cities, but also of residents of other cities, who would like to move to Palo Alto. In the poorer parts of the state, there’s not much point in restrictive zoning, because there isn’t that much demand for new housing, except perhaps from people who cannot afford San Francisco or Los Angeles and are willing to endure long commutes. On the contrary, thanks to the strength of internal migration, a large fraction of prospective residents of Palo Alto live elsewhere in California. Nor do people in poor areas, where houses aren’t worth much as investments, gain much from raising house prices for themselves; the ability to move to where the good jobs are is worth more than raising housing prices by a few tens of thousands of dollars. This means that the general interest in California is to make Palo Alto cheaper rather than more expensive. The same is true of Japan and Tokyo, or France and Paris, or Ontario and Toronto.

While superficially similar to the point made in the presentation quoted at the beginning of this post, my theory asserts the opposite. The issue is not that individual municipalities see no benefit in upzoning since it wouldn’t reduce rents by much. It’s that they see net harm from upzoning precisely because it would reduce rents. It is not a collective action problem: it is a problem of disenfranchisement, in which the people who benefit from more development do not live in the neighborhoods where the development would be taking place. High-level decisionmaking means that people who would like to move to a rich area get as much of a vote in its development policy as people who already live there and have access to its amenities, chief of which is access to work. It disempowers the people who already have the privilege of living in these areas, and empowers the people who don’t but would like to.

Individual rich people can be virtuous. Rich communities never are. They are greedy, and write rules that keep others out and ruthlessly eliminate any local effort to give up their political power. They will erect borders and fences, exclude outsiders, and demagogue against revenue sharing, school integration, and upzoning. They will engage in limited charity – propping up their local poor (as San Francisco protects low-income lifelong San Franciscans via rent control), and engaging in symbolic, high-prestige giving, but avoid any challenge to their political power. Upzoning is not a collective action problem; it is a struggle for equal rights and equal access to jobs regardless of which neighborhood, city, or region one grew up in.

# Modeling Anchoring

Jarrett Walker has repeatedly called transit agencies and city zoning commissions to engage in anchoring: this means designing the city so that transit routes connect two dense centers, with less intense activity between them. For example, he gives Vancouver’s core east-west buses, which connect UBC with dense transit-oriented development on the Expo Line, with some extra activity at the Canada Line and less intense development in between; Vancouver has adopted his ideas, as seen on PDF-page 15 of a network design primer by Translink. In 2013, I criticized this in two posts, making an empirical argument comparing Vancouver’s east-west buses with its north-south buses, which are not so anchored. Jarrett considers the idea that anchoring is more efficient to be a geometric fact, and compared my empirical argument to trying to empirically compute the decimal expansion pi to be something other than 3.1415629… I promised that I would explain my criticism in more formal mathematical terms. Somewhat belatedly, I would like to explain.

First, as a general note, mathematics proves theorems about mathematics, and not about the world. My papers, and those of the other people in the field, have proven results about mathematical structures. For example, we can prove that an equation has solutions, or does not have any solutions. As soon as we try to talk about the real world, we stop doing pure math, and begin doing modeling. In some cases, the models use advanced math, and not just experiments: for example, superstring theory involves research-level math, with theorems of similar complexity to those of pure math. In other cases, the models use simpler math, and the chief difficulty is in empirical calibration: for example, transit ridership models involve relatively simple formulas (for example, the transfer penalty is a pair of numbers, as I explain here), but figuring out the numbers takes a lot of work.

With that in mind, let us model anchoring. Let us also be completely explicit about all the assumptions in our model. The city we will build will be much simpler than a real city, but it will still contain residences, jobs, and commuters. We will not deal with transfers; neither does the mental model Jarrett and TransLink use in arguing for anchoring (see PDF-p. 15 in the primer above again to see the thinking). For us, the city consists of a single line, going from west to east. The west is labeled 0, the east is labeled 1, and everything in between is labeled by numbers between 0 and 1. The city’s total population density is 1: this means that when we graph population density on the y-axis in terms of location on the x-axis, the total area under the curve is 1. Don’t worry too much about scaling – the units are all relative anyway.

Let us now graph three possible distributions of population density: uniform (A), center-dominant (B), and anchored (C).

Let us make one further assumption, for now: the distributions of residences and jobs are the same, and independent. In city (A), this means that jobs are uniformly distributed from 0 to 1, like residences, and a person who lives at any point x is equally likely to work at any point from 0 to 1, and is no more likely to work near x than anyone else. In city (B), this means that people are most likely to work at point 0.5, both if they live there and if they live near 0 or 1; in city (C), this means that people are most likely to work at 0 or 1, and that people who live at 0 are equally likely to work near 0 and near 1.

Finally, let us assume that there is no modal splitting and no induced demand: every employed person in the city rides the bus, exactly once a day in each direction, once going to work and once going back home, regardless of where they live and work. Nor do people shift their choice of when to work based on the network: everyone goes to work in the morning peak and comes back in the afternoon peak.

With these assumptions in mind, let us compute how crowded the buses will be. Because all three cities are symmetric, I am only going to show morning peak buses, and only in the eastbound direction. I will derive an exact formula in city (A), and simply state what the formulas are in the other two cities.

In city (A), at point x, the number of people who ride the eastbound morning buses equals the number of people who live to the west of x and work to the right of x. Because the population and job distributions are uniform, the proportion of people who live west of x is x, and the proportion of people who work east of x is 1-x. The population and job distributions are assumed independent, so the total crowding is x(1-x). Don’t worry too much about scaling again – it’s in relative units, where 1 means every single person in the city is riding the bus in that direction at that time. The formula y = x(1-x) has a peak when x = 0.5, and then y = 0.25. In cities (B) and (C), the formulas are:

(B): $y = \begin{cases}2x^2(1 - 2x^2) & \mbox{ if } x \leq 1/2\\ 2(1-x)^2(1 - 2(1-x)^2) & \mbox{ if } x > 1/2\end{cases}$

(C): $y = \begin{cases}(2x-2x^2)(1 - 2x + 2x^2) & \mbox{ if } x \leq 1/2\\ (2(1-x)-2(1-x)^2)(1 - 2(1-x) + 2(1-x)^2) & \mbox{ if } x > 1/2\end{cases}$

Here are their graphs:

Now, city B’s buses are almost completely empty when x < 0.25 or x > 0.75, and city C’s buses fill up faster than city A’s, so in that sense, the anchored city has more uniform bus crowding. But the point is that at equal total population and equal total transit usage, all three cities produce the exact same peak crowding: at the midpoint of the population distribution, which in our three cases is always x = 0.5, exactly a quarter of the employed population lives to the west and works to the east, and will pass through this point on public transit. Anchoring just makes the peak last longer, since people work farther from where they live and travel longer to get there. In a limiting case, in which the population density at 0 and 1 is infinite, with half the population living at 0 and half at 1, we will still get the exact same peak crowding, but it will last the entire way from 0 to 1, rather than just in the middle.

Note that there is no way to play with the population distribution to produce any different peak. As soon as we assume that jobs and residences are distributed identically, and the mode share is 100%, we will get a quarter of the population taking transit through the midpoint of the distribution.

If anything, the most efficient of the three distributions is B. This is because there’s so little ridership at the ends that it’s possible to run transit at lower frequency at the ends, overlaying a route that runs the entire way from 0 to 1 to a short-turn route from 0.25 to 0.75. Of course, cutting frequency makes service worse, but at the peak, the base frequency is sufficient. Imagine a 10-minute bus going all the way, with short-turning overlays beefing frequency to 5 minutes in the middle half. Since the same resources can more easily be distributed to providing more service in the center, city B can provide more service through the peak crowding point at the same cost, so it will actually be less crowded. This is the exact opposite of what TransLink claims, which is that city B would be overcrowded in the middle whereas city C would have full but not overcrowded buses the entire way (again, PDF-p. 15 of the primer).

In my empirical critique of anchoring, I noted that the unanchored routes actually perform better than the anchored ones in Vancouver, in the sense that they cost less per rider but also are less crowded at the peak, thanks to higher turnover. This is not an observation of the model. I will note that the differences in cost per rider are not large. The concept of turnover is not really within the model’s scope – the empirical claim is that the land use on the unanchored routes lends itself to short trips throughout the day, whereas on the anchored ones it lends itself to peak-only work trips, which produce more crowding for the same total number of riders. In my model, I’m explicitly ignoring the effect of land use on trips: there are no induced trips, just work trips at set times, with 100% mode share.

Let us now drop the assumption that jobs and residences are identically distributed. Realistically, cities have residential and commercial areas, and the model should be able to account for this. As one might expect, separation of residential and commercial uses makes the system more crowded, because travel is no longer symmetric. In fact, whereas under the assumption the peak crowding is always exactly a quarter of the population, if we drop the assumption the peak crowding is at a minimum a quarter, but can grow up to the entire population.

Consider the following cities, (D), (E), and (F). I am going to choose units so that the total residential density is 1/2 and so is the total job density, so combined they equal 1. City (D) has a CBD on one side and residences on the other, city (E) has a CBD in the center and residences on both sides, and city (F) is partially mixed-use, with a CBD in the center and residences both in the center and outside of it. Residences are in white, jobs are in dark gray, and the overlap between residences and jobs in city (F) is in light gray.

We again measure crowding on eastbound morning transit. We need to do some rescaling here, again letting 1 represent all workers in the city passing through the same point in the same direction. Without computing, we can tell that in city (D), at the point where the residential area meets the commercial area, which in this case is x = 0.75, the crowding level is 1: everyone lives to the west of this point and works to its east and must commute past it. Westbound morning traffic, in contrast, is zero. City (E) is symmetric, with peak crowding at 0.5, at the entry to the CBD from the west, in this case x = 0.375. City (F) has crowding linearly growing to 0.375 at the entry to the CBD, and then decreasing as passengers start to get off. The formula for eastbound crowding is,

(F): $y = \begin{cases}x & \mbox{ if } x < 3/8\\ x(5/2 - 4x) & \mbox{ if } 3/8 \leq x \leq 5/8\\ 0 & \mbox{ if } x > 5/8\end{cases}$

In city (F), the quarter of the population that lives in the CBD simply does not count for transit crowding. The reason is that, with the CBD occupying the central quarter of the city, at any point from x = 0.375 east, there are more people who live to the west of the CBD getting off than people living within the CBD getting on. This observation remains true down to when (for a symmetric city) a third of the population lives inside the CBD.

In city (B), it’s possible to use the fact that transit runs empty near the edges to run less service near the edges than in the center. Unfortunately, it is not possible to use the same trick in cities (E) and (F), not with conventional urban transit. The eastbound morning service is empty east of the CBD, but the westbound morning service fills up; east of the CBD, the westbound service is empty and the eastbound service fills up. If service has to be symmetric, for example if buses and trains run back and forth and make many trips during a single peak period, then it is not possible to short-turn eastbound service at the eastern edge of the CBD. In contrast, if it is possible to park service in the center, then it is possible to short-turn service and economize: examples include highway capacity for cars, since bridges can have peak-direction lanes, but also some peaky commuter buses and trains, which make a single trip into the CBD per vehicle in the morning, park there, and then make a single trip back in the afternoon. Transit cities relies on services that go back and forth rather than parking in the CBD, so such economies do not work well for them.

A corollary of the last observation is that mixed uses are better for transit than for cars. Cars can park in the CBD, so for them, it’s fine if the travel demand graph looks like that of city (E). Roads and bridges are designed to be narrower in the outskirts of the region and wider near the CBD, and peak-direction lanes can ensure efficient utilization of capacity. In contrast, buses and rapid transit trains have to circulate; to achieve comparable peak crowding, city (E) requires twice as much service as perfect mixed-use cities.

The upshot of this model is that the land use that best supports efficient use of public transit is mixed use. Since all rich cities have CBDs, they should work on encouraging more residential land uses in the center and more commercial uses outside the center, and not worry about the underlying distribution of combined residential and job density. Since CBDs are usually almost exclusively commercial, any additional people living in the center will not add to transit crowding, even as they ride transit to work and pay fares. In contrast, anchoring does not have any effect on peak crowding, and on the margins makes it worse in the sense that the maximum crowding level lasts longer. This implies that the current planning strategy in Vancouver should be changed from encouraging anchoring to fill trains and buses for longer to encouraging more residential growth Downtown and in other commercial centers and more commercial growth at suitable nodes outside the center.

# Penn Station Elimination Followup

Several commenters, both here and on Streetsblog, have raised a number of points about my proposal to eliminate above-ground Penn Station and reduce the station to a hole in the ground. A few of those points are things I’d already thought about when I wrote that post and didn’t want to clutter; others are new ideas that I’ve had to wrestle with.

Waiting

On Streetsblog, Mark Walker says, “Getting on a train at Penn is not like using the subway. Instead of a train that runs every five minutes, you’re waiting for a train that runs once per hour (more or less),” implying nicer waiting areas and lounges are needed. My proposal, of course, does not have dedicated waiting areas. (That said, there’s an immense amount of space on the platforms under the escalators, which could be equipped with chairs, tables, and newsstands.)

However, I take exception to the notion that when the train runs every hour, passengers wait an hour. When I lived in Providence, a few trips to Boston, New Haven, and New York taught me the exact amount of time it’d take me to walk from my apartment to the train station: 21 minutes. I learned to time myself to get to the station 2 minutes before the train would leave, and as I recall, I missed the train twice out of maybe 30 trips, and one of those was when I had a lot of luggage and was in a taxi and couldn’t precisely gauge the extra travel time. Walking is that reliable. People who get to Penn Station by subway have to budget some extra time to account for missed subway trains, but from much of the city, including the parts of the CBD not within walking distance from Penn, the required spare time is less than 10 minutes. Moreover, Penn is at its most crowded at rush hour, which is precisely when subway frequency is the highest, and people can reliably time themselves to within less than 5 minutes.

Outlying train stations in Switzerland are deserted except a few minutes before a train shows up, because the connecting transit is all timed to meet the train. This is of course inapplicable at very large stations with many lines, but the modes of transportation that most Penn Station users take to the station are reliable and frequent, if you can even talk of frequency for walking. The result is that the amenities do not need to be extravagant on account of waiting passengers, and do not need to be more than those of a busy subway station in a busy area.

Shelter

Several commenters raised the idea of shelter. One option, raised by James Sinclair, is an arched glass roof over the station, on the model of Milan. This involves above-ground infrastructure, but the arched structure is only supported at the margins of the compound, which means that the primary feature of a hole-in-the-ground station, the lack of anything that the track area must support the weight of, is still true. I do not think it’s a bad idea; I do, however, want to raise three additional options:

Do nothing. A large proportion of the usable area of the platforms would be located under the walkways above, or under the escalators and staircases. Having measured the depth more precisely, through Plate 14 here, I found it is 13 meters from street level to top of rail, or 12 from street level to platform level, translating to 21 meters of escalator length, plus 2.2-2.5 meters on each side for approach (see page 23 here). About 16 of those 21 (18.5 out of 25.7, counting approaches) meters offer enough space for passengers to stand below the escalators, leading to large areas that could be used for shelter, as noted in the waiting section above.

Build a simple shelter. Stockholm-area train stations have cheap corrugated metal roofs over most of the length of their platforms. These provide protection from rain. Of course those roofs require some structural support at the platform, but because they’re not supposed to hold anything except rainwater, those supports are narrow poles, easy to move around if the station is reconfigured.

Build a street-level glass pane. This may be structurally intricate, but if not, it would provide complete shelter from the elements on the track level, greatly improve passenger circulation, and create a new public plaza. But in summer, the station would be a greenhouse, requiring additional air conditioning.

Note that doing nothing or building a simple shelter would not protect any of the track level from heat or cold. This is fine: evidently, open-air stations are the norm both in cities with hotter summers than New York (Milan is one example, and Tokyo is another) and in cities with colder winters (for example, Stockholm). Passengers are usually dressed for the weather anyway, especially if they’re planning on walking to work from Penn or from the subway station they’re connecting to.

Architecture

Multiple commenters have said that public art and architecture matter, and building spartan train stations is unaesthetic, representing public squalor. I agree! I don’t think a hole-in-the-wall Penn Station has to be drab or brutalist. It can showcase art, on the model of the mosaics on the subway, or the sculptures on the T-Bana. It can use color to create a more welcoming environment than the monotonous gray of many postwar creations, such as the Washington Metro. The natural sunlight would help a lot.

# Height Limits: Still a Bad Idea

In a pair of recent articles on Strong Towns, Charles Marohn, best known in the urbanist community for introducing the term stroad (street+road) for a pedestrian-hostile arterial street, argues for height limits as a positive force for urbanism. He does not make the usual aesthetic argument that tall buildings are inherently unpleasant (“out of scale”), or the usual urbanist one that tall buildings lead to neighborhood decline; instead, he makes an economic argument that allowing tall buildings greatly raises land costs, and makes redevelopment of vacant lots less likely. He uses the following example:

Let’s say the local code allows [a] vacant lot to be developed as a one story strip mall, but nothing higher. If the strip mall is worth $500,000, then the vacant lot is going to be somewhere around$75,000.

Okay, but what if the development code allows that vacant lot to be developed as a sixteen story tower? If the tower is worth $20,000,000, then that vacant lot is going to fetch a much higher price, maybe as much$2.5 million.

You own that vacant lot. I come to you with an offer to buy it for $75,000. What are the odds you are going to sell it at that price when you look to the other side and see the same piece of property going for millions? Not very good. In most cities, as Charles notes, there is not enough demand to redevelop every vacant lot as a high-rise, and therefore, if high-rises are permitted, a few vacant lots will be redeveloped as high-rises, while the rest remain vacant. This is not the case in large cities, which Charles specifically exempts in his article (see also Daniel Kay Hertz’s response), but part of the problem with the argument, as we will see, is that the boundary between large cities and small ones is fuzzy. Let me now explain why this argument fails, like all the other arguments for zoning restrictions: it makes implicit assumptions on future uncertainty. The reason the vacant lot owners are not willing to sell for$75,000 is that they hope to get $2.5 million. In a stable market, with low enough population that most lots cannot fetch such a high price, the lot owners know that holding off on$75,000 offers is a gamble and that they are unlikely to ever get a higher offer. People have optimism bias and might overrate the probability that they’ll get the $2.5 million offer, but also have risk aversion; in most cases in economics, risk aversion dominates, so that safer assets cost more and have lower returns. So when do we see holdouts? Risk aversion predicts that the probability of obtaining a$2.5 million offer should be higher than the total demand for new towers divided by the number of vacant lots. If we explicitly assume that the cost figures in Charles’ example, including land costs, are unchangeable, then this means vacant lot owners expect there to be more high-rise towers in the future, which comes out of growth regions. Charles’ example is based on Sarasota, which like most of Florida has high population growth.

The other possibility is regulatory uncertainty. In a competitive market, land costs are already as low as they can be while letting lot owners cash out on past investments. Developer profits are also as low as possible, and represent the developer’s wage for managerial work. However, zoning restrictions will greatly raise both figures, and a lot owner who expects future developments to brush up against the present zoning code can hold out until prices rise.

This is the danger of a system that is based on arbitrary rules (Charles proposes up to two floors or 1.5 times the average present height, whichever is higher), and arbitrary distinctions between small cities in which height restrictions are desirable and large cities in which they are not: these introduce political discretion in the details, which introduces additional uncertainty among lot owners. True windfalls usually involve the boundary between regulatory regimes, and this creates political incentive to game the system in order to be one of the few owners whose lots can be developed as high-rises. In contrast, once a ground rule is established that there is no zoning, such as in Houston, introducing zoning is difficult, even when there are rules that are zoning in all but name, such as parking minimums.

Once we get into the realm of cities with a large proportion of their lots developed, as Charles proposes, future development can only replace old development, and this introduces a key difference between new development and redevelopment: redevelopment requires buying out the preexisting property. If a two-floor building is replaced by a three-floor building, then the developer has to not only pay construction costs for three floors, but also buy out two floors, effectively paying for five floors. But the revenue is still only that of a three-floor building, which bids up effective costs by a factor of five thirds. The formula is that if it’s possible to multiply the total built-up area by a factor of $x$ then the buy-out factor will raise the cost of each housing unit by a factor of $1 + 1/x$.

This effect is why, in major cities, we usually see buildings replaced by much larger buildings: for example, a three- or four-floor Manhattan building may be replaced by a fifteen- or twenty-story tower on a base. Charles laments that this is not small-scale or incremental, but even his example of good incremental development is similar: in Houston, single-family houses are replaced by low-rise apartment buildings, generating similarly high ratios of the floor areas of redevelopments with the buildings they replaced. Incrementalism in these cases consists of replacing small buildings by much larger ones, gradually, until a few decades later the entire neighborhood is tall.

One way around redevelopment’s need to buy out preexisting buildings is to mandate that future buildings be built to allow adding floors on top of them. Chicago’s Blue Cross Blue Shield Tower is an example. This is a regulation that increases the average cost of construction but reduces the marginal cost and thus the price. It’s also a regulation that only really matters in situations when it is difficult to have a high ratio of new to old floor area, such as in areas that are already high-rise, especially major city CBDs. (It is easy to quintuple floor area ratio when the preexisting buildings have three floors, but not so much when they have twelve.) The current styles of construction of most small buildings, for example sloping roofs common in American and European urban and suburban houses, tend to make adding floors impossible. Of course, the implication that such a regulation should only apply for buildings above a certain height introduces political discretion and hence uncertainty, but at least this is uncertainty that would apply equally to all buildings in an area, which is not always the case for zoning.

What Charles proposes, to develop all vacant lots first and only then start going taller, is then a recipe for high marginal costs, because of the buyout factor. In a small city uniformly developed up to one or two floors, it is difficult to spread the new development across many buildings up to three floors, precisely because there is no way to build single-family houses that are recognizable as such to Americans or Europeans from countries I’ve been to (It’s different in Canada, but this is considered a feature of the low quality of Vancouver’s housing) and that can have floors added to them. In such an environment, building tall is the only way to avoid high housing costs.

# The NITBY Problem

Usually, the barrier to new development in a neighborhood is NIMBYism: connected local community members do not want the project, saying “not in my backyard.” There’s a wealth of literature about NIMBYs’ role in restrictions on development; William Fischel’s work is a good start, and the short version is that opposition to development is local, based on fear of the risk of decline in property values. Urbanists take it for granted that decisions made with regard to regional rather than local concerns will be more pro-development: Let’s Go LA has examples from Los Angeles, and Stephen Smith explains Toronto and Tokyo’s lax rules on new development based on their high-level decisionmaking (at the provincial level in Ontario and national level in Japan). In this post, I would like to discuss the opposite problem, which I call NITBYism – “not in their backyard.”

In certain circumstances, opposition comes from people living in other areas, who are aghast that an area they don’t live in is getting so much investment. This is more likely to happen when there’s heavy public involvement in development, but, since upzoning an area is a public decision (as opposed to unthinkable across-the-board zoning abolition), opposition can sprout anytime. One common thread to NITBY opposition campaigns is that NITBYs view housing as a good thing, and want it redirected to their areas. Another is that they self-perceived as ignored by the urban elites; this is common to both right-wing populists and left-wing ones. Since the process is heavily public by assumption, the price signal telling developers to build in the center of the major city is irrelevant, and this encourages the government to build more low-value peripheral projects.

The first example of this is when the process actually is public: subsidized affordable housing. As discussed by Daniel Kay Hertz, in Chicago, affordable housing regulations require developers to pay a fee to a dedicated affordable housing fund, which then uses the money to develop or buy housing and rent it out at subsidized rates for moderate-income residents. To minimize the cost per affordable unit, the fund builds the units in the cheapest neighborhoods, i.e. the poorest ones, exacerbating housing segregation. As Payton Chung explains, the low-income housing community networks in Chicago support this arrangement, because they are based in the neighborhoods where this affordable housing is built. This is not as self-serving as the examples I will include below, since the community groups want to see the most number of housing units built at a given cost; but a common feature of NITBYism, namely that the NITBYs view housing as a good rather than as a burden imposed by outsiders, is present here.

In Israel, NITBYism does not have the cost defense that it does in Chicago. Zoning in Israel is prepared by municipalities but must get approved by the state. This means that it is geared not only toward providing services to Israelis (such as cheap and orderly housing) but also toward national goals of Judaization. The worst NITBYism is not affecting Tel Aviv, but Arab cities, where the state refuses to approve zoning plans; since independence, not a single new Arab city has been built, except to house Bedouins who the state expelled from their villages after independence, and plans to build the first new Arab city are controversial on segregation grounds. This is while the state has built many new Jewish cities from scratch, often in peripheral areas in order to ensure a Jewish majority.

However, NITBYism afflicts housing in Tel Aviv, too. Although the state could if it wanted declare a housing emergency and force upzoning in Tel Aviv, it does not. There are few permits for new apartments in the Tel Aviv District (though more new housing sales): only 5% of the national total (including settlements), as per the pie chart on page 17 of the Ministry of Construction and Housing’s report and the more complete (in English) data on page 49, compared with a national population share of 16%; the Center District, consisting of Tel Aviv suburbs (though not the richest and most expensive, such as Ramat HaSharon, which are in the Tel Aviv District), has 22% of national permits, about the same as its share of the national population. This is not just NIMBYism in Tel Aviv, although that exists in abundance. Local politicians from peripheral towns demand local construction, and view Tel Aviv construction as something useful only to outsiders, such as foreign speculators or the urban elite. During the housing protests of 2011, there was widespread debate on the left about what solutions to offer, and people representing the ethnic and geographic periphery were adamant that the state build and preserve public housing in peripheral towns and not concentrate on Tel Aviv, which they identified with the secular Ashkenazi elite. A common thread in housing and infrastructure debates to both working-class Jews from the periphery and Arabs is the demand for a policy that would create jobs and housing in their hometowns, rather than build infrastructure that would put them in the Tel Aviv orbit.

Of the above examples, in Chicago the NITBYs self-identify as leftists, and in Israel, the NITBYs who want local housing rather than Tel Aviv housing either identify as leftists or identify as economic leftists and support the right on security and ethnic identity issues. However, the populist right is not immune from this. Right-wing supporters of suburbs who oppose cities for what they represent (diversity, usually left-wing politics of the kind they associate with the liberal elite) may also oppose urban upzoning. The best example of this kind is Joel Kotkin’s opposition to upzoning in Hollywood, which sounds like a criticism of government projects until one realizes that upzoning simply means developers are permitted to build more densely if they’d like. Now, Kotkin is pro-immigration, setting him apart from the main of right-wing populism, but in all other aspects, his paranoid fear of urban liberal elites imposing behavioral controls on ordinary people would be right at home at the UK Independence Party and its mainland European equivalents. Kotkin is also just one person, but his views mirror those of Tea Party activists who equate dense urbanism with an Agenda 21 conspiracy, to the point of conflating a phrase that means building new suburbs with a plan to forcibly relocate suburbanites to central cities.

I do not know Japan’s regional patterns of politics well, but I know Ontario’s. In Ontario, there is not much us-and-them politics regarding Toronto. There is such politics regarding the inner parts of Toronto – Rob Ford was elected on the heels of an outer-urban populist backlash to David Miller’s urbanism, including the perception that Miller was fighting a war on cars. But there’s none of the hatred of the central city and all that it represents that typifies politics in both Israel and the US. Hatred of the city in the US is right-wing (though within the city, hatred of the gentrified core is often tied to left-wing anti-gentrification activism), and hatred of Tel Aviv in Israel is generically populist, but in both cases, the us-and-them aspect encourages NITBYism.

In the most expensive American cities, this is not a major problem. Anti-urban populism does not have enough votes to win in New York and California, so state control of zoning in those states would not produce these problems. The Tea Party disruption of zoning meeting I brought up above happened in San Francisco suburbs, but did not have an effect on planning; I brought this example up to show that this political force exists, even if in that specific locality it is powerlessly weak. In those areas, local NIMBYism is a much bigger problem: many New York neighborhoods were actually downzoned in the Bloomberg era by local request. The primary problems that would plague state-level decisionmaking are corruption and power brokering, in which politicians hold even straightforward rule revisions hostage to their local pet projects. The us-and-them politics of Upstate and Downstate New York contributes heavily to power brokering, but Downstate’s demographic dominance precludes ideological choking of development.

Within the US, the risks of NITBYism are different. First, in the cost tier just below that of New York and California there are city regions in more moderate states, for examples Philadelphia and the Virginia suburbs of Washington, or possibly Miami (where the county-made rules have allowed aggressive new construction, mostly urban, which Stephen Smith credits to the political power of Cuban immigrants). And second, zooming in on different neighborhoods within each expensive city, the Chicago example suggests that if New York and other expensive cities begin a major program of public housing construction, the community organizations and the populists will demand to spread construction across many neighborhoods, especially poor ones, and not in the neighborhoods where there is the most demand.

As I noted two posts ago, there is a political economy problem, coming from the fact that the politically palatable amounts of construction are not transformative enough to let the working class live in market-rate city-center apartments, not in high-income major cities. Israel could semi-plausibly double the Tel Aviv housing stock; even that requires housing forms that Israelis associate with poverty, such as buildings that touch, without side setbacks. This would allow many more people to live in Tel Aviv, but they’d be drawn from the middle class, which is being priced out to middle-class suburbs or to working-class suburbs that it gentrifies. The working class in the periphery would be able to move into these closer-in suburbs, but this cascading process is not obvious. Worse, from the point of view of community leaders, it disrupts the community: it involves a churn of people moving, which means they end up in a different municipal fief, one with leadership the current suburb’s leaders may be hostile to.

For essentially the same reasons, subsidized housing in the center produces the same problems. If Israel builds a massive number of subsidized or rent-regulated apartments in Tel Aviv, there will be immense nationwide demand for them. Few would serve the residents of a given peripheral suburb, and there is no guarantee anyone would get them. On the contrary, in such a plan, priority is likely to go to downwardly-mobile children of established residents. At the 2011 protests, the people who were most supportive of plans to lower rents in Tel Aviv specifically were people from Tel Aviv or high-income suburbs who wanted to be able to keep living in the area. The community disruption effect of offering people the ability to live where they’d want would still be there. Thus, all the incentives line up behind periphery community leader support for building public housing in the periphery, where there is little demand for it, and not in the center. Even when housing is universally seen as a benefit and there’s no NIMBYism, politics dictates that housing is built in rough proportion to current population (since that’s where political power comes from) and not future demand.

Abolishing zoning is one way to cut this Gordian knot; it is also completely unpalatable to nearly everyone who is enfranchised in a given area. Allowing more private construction is the more acceptable alternative, but leads to the same problems, only on a smaller scale. It really is easier for community leaders to twist arms to demand veto rights and local resident priority than to push for sufficient citywide upzoning to alleviate the price pressure. But in an environment with weak NIMBYs and few NITBYs, fast growth in urban housing is possible.

# Dispersing Expensive Centers: Edge City Version

This is somewhat of an addendum to my post before about dispersal of urban networks toward cheaper cities. I addressed the question of dispersal from rich, expensive metro areas, especially San Francisco, to cheaper ones, as a way of dealing with high housing prices. But more common is dispersal within metro areas: gentrification spilling from a rebounding neighborhood to adjacent neighborhoods that remain cheaper, and office space spilling from the primary CBD to the edge cities. I am going to address the latter issue in this post.

CBDs are expensive. They have intense demand for office space, as well as high-end retail and hotels. In many cities, there’s demand for office space even at the construction costs of supertall skyscrapers, going up to about $5,000-6,000 per square meter in privately-built New York towers. Zoning regimes resist the height required to accommodate everyone, and this is worse in Europe than in North America and high-income East Asia. Paris proper has many towers just above the 100 meter mark, but only three above 120. On a list of the tallest buildings in Sweden, not a single one above 100 meters is in central Stockholm, and the tallest within the zone are not in the CBD but in Södermalm; compare this with Vancouver, a metro area of similar size. But in the US, too, expanding CBDs is difficult in the face of neighborhood opposition, even in Manhattan. The solution many cities have adopted is to put the skyscrapers in edge cities. Paris famously built La Defense, which has far more skyscrapers than the city proper does; Stockholm is building skyscrapers in Kista; London built Canary Wharf; Washington, the major US city with the tightest CBD height limits, sprouted skyscraper clusters in several suburbs in Maryland and Virginia. Ryan Avent proposed this as one solution to NIMBYism: in new-build areas, there are few residents who could oppose the new development. In contrast, near zoning-constrained CBDs, not only are there many residents, but also the land is so desirable that they are typically high-income, which means they have the most political power to oppose new development. The problem with this solution is that those secondary CBDs are not public transit hubs. In Paris, this has created an east-west disparity, in which people from (typically wealthy) western suburbs can easily reach La Defense, whereas people from poorer ones need to take long RER trips and often make multiple transfers. In every transit city, the CBD is unique in that it can be reached from anywhere. To give similar accessibility to a secondary center, massive investment is required; Paris is spending tens of billions of euros on circumferential regional rail lines to improve suburb-to-suburb connectivity, expand access in the eastern suburbs, and ameliorate the east-west imbalance (see for example isochrones on PDF-pp. 20-21 of the links here). Those lines are going to be well-patronized: the estimate is 2 million daily passengers. And yet, the east-west imbalance, if nothing else, would be a lesser problem if instead of building La Defense, Paris had built up Les Halles. The situation in other cities is similar. Kista is on one branch of one subway line, two stops away from its outer terminus. Living in Central Stockholm, my coworkers and I can get to KTH on foot or by bike, but a coworker who teaches at KTH’s satellite campus in Kista has a long commute involving circumferential buses (taking the subway and changing at T-Central would be even longer because of the detour). While many individual sub-neighborhoods of Central Stockholm are quite dense, the overall density in the center is not particularly high, certainly not by the standards of Paris or New York. A similar problem happens in Washington, where the biggest edge city cluster, Tysons Corner, is traditionally auto-oriented and was only just connected to Metro, on a branch. This always affects poorer people the worst, as they can’t afford to live in the CBD, where there is easy access to all secondary destination, and often are pushed to suburbs with long commutes. There is a political economy problem here, as is usually the case with zoning. (Although in the largest cities skyscraper heights are pushing beyond the point of constant marginal costs, purchase prices at least in New York are much higher than construction costs.) The people living near CBDs, as noted before, are usually rich. The displacement of office space to the suburbs affects them the least, for three reasons. First, if they desire work within walking distance or short subway distance, they can have it, since their firms typically make enough money to afford CBD office rents. Second, since they live in the transit hub, they can access suburban jobs in any direction. And third, if the transit options are lacking, they can afford cars, although of course traffic and parking remain problematic. Against their lack of incentive to support CBD office space, they have reasons to support the status quo: the high rents keep it exclusive and push poor people away, and often the traditional mid-rise buildings are genuinely more aesthetic than skyscrapers, especially ones built in modernist style. These concerns are somewhat muted in the US, where rich people decamped for the suburbs throughout the 20th century, and have supported zoning that mandates single-family housing in the suburbs, instead of staying in the city and supporting zoning that keeps the city mid-rise. This may have a lot to do with the formation of high-rise downtowns in American cities of such size that in Europe they’d be essentially skyscraper-free. However, what’s worse in the US is the possibility of short car-free commutes to the edge cities. Where La Defense is flanked by suburbs with high residential density, and Kista’s office blocks are adjacent to medium-density housing projects for working- and middle-class people, American edge cities are usually surrounded by low-density sprawl, where they are easily accessible by car but not by any other mode of transportation. This is because the American edge cities were usually not planned to be this way, but instead arose from intersections of freeways, and developed only after the residential suburbs did. As those edge cities are usually in rich areas, the residents again successfully resist new development; this is the point made in Edgeless Cities, which notes that, in major US metro areas, growth has been less in recognizable edge cities and more in lower-density edgeless cities. As with the possibility of dispersing innovation clusters from rich, expensive metro areas to poorer and cheaper ones, the already-occurring dispersal from city centers to edge and subsequently edgeless cities has negative effects. It lengthens transit commutes. Although in Tokyo, long commutes first arose as a problem of a monocentric CBD, and the city developed secondary CBDs as a solution, the situation in European cities an order of magnitude smaller is very different. It worsens housing segregation: the development of an edge city tends to be in the direction of the favored quarter, since that’s where the senior managers live, and conversely, higher-income workers can choose to move nearby for the short commute. Although nearly all metro areas have favored quarters, decentralization of jobs thus tends to lengthen the commutes of poor people more than those of rich people. This is not quite the same as what happens when entire metro areas are forced to disperse due to housing cost. The agglomerations generally stay intact, since an entire industry can move in the same direction: smaller cities have just one major favored quarter with edge cities, and larger ones still only have a few, so that industries can specialize, for example in New York, biotech and health care cluster in the Edison-Woodbridge-New Brunswick edge city. Moreover, the specialized workers are usually high-income enough that they can stay in the central city or migrate to the favored quarter. San Francisco’s programmers are not forced to move individually to faraway poor neighborhoods; they move in larger numbers to ones near already gentrifying ones, spurring a new wave of gentrification in the process; were they to move alone, they’d lose the access to the tech shuttles. The negative effects are predominantly not on richer people, but on poorer people. The problem is that even among the poor, there is little short-term benefit from supporting upzoning. If Paris, London, and Stockholm liberalize housing and office construction, the first towers built of both kinds will be luxury, because of the large backlogs of people who would like to move in and are willing to pay far in excess of construction costs. I am going to develop this point further in two posts, on what is best called NITBYism – Not In Their Backyard – but this means that the incentive for poor and peripheral populations is not to care too much about development in rich centers. The marginal additional building in a rich city center is going to go to the upper middle class; sufficient construction would trickle to the middle class; only extensive construction would serve the working class, and then not all of it. In the US, the marginal additional building may actually displace poor people, if no new construction is allowed, simply by removing low-income apartments. It may even create local demand for high-income housing, for example by signaling that the neighborhood has improved. In San Francisco, this is compounded by the tech shuttles, as a critical mass of Silicon Valley-bound residents can justify running shuttles, creating demand for more high-income housing. The amount of construction required to benefit the bottom half of the national income distribution is likely to be massive. This is especially true in France and the UK, which have sharp income differences between the capital and the rest of the country; their backlogs of people who would like to move to the capital are likely in the millions, possibly the high millions. Such massive construction is beyond the pale of political reality: the current high-income resident population is simply not going to allow it – when forced to share a building with the working class, it pushes for poor doors, so why would it want zoning that would reduce the market-rate rent to what the working class would afford? The only political possibility in the short run is partial plans, but these are not going to be of partial use to the working class, but of no use to it, benefiting the middle class instead. As a result, there is no push by the working class and its social democratic political organs to liberalize construction, nor by the small-is-beautiful green movement. Ultimately, the attempt to bypass restrictions on urban CBD formation by building edge cities, like every other kludge, is doomed to failure. The fundamental problem of rich people making it illegal to build housing nearby is not solved, and is often made even worse. The commutes get worse, and the inequality in commutes between the rich and the poor grows. Office space gets built, where otherwise it would spread along a larger share of the medium-rise CBD, but for most workers, this is not an improvement, and the environmental effects of more driving have negative consequences globally. And once city center is abandoned to the rich, there is no significant political force that can rectify the situation. What seems like a workaround and an acceptable compromise only makes the situation worse. # Zoning and Market Pricing of Housing The question of the effects of the supply restrictions in zoning on housing prices has erupted among leftist urbanist bloggers again. On the side saying that US urban housing prices are rising because of zoning, see anything by Daniel Kay Hertz, but most recently his article in the Washington Post on the subject. On the side saying that zoning doesn’t matter and the problem is demand (and by implication demand needs to be curbed), see the article Daniel is responding to in Gawker, and anything recent by Jim Russell of Burgh Diaspora, e.g. this link set and his Pacific Standard article on the subject. This is not a post about why rising prices really are a matter of supply. I will briefly explain why they are, but the bulk of this post is about why, given that this is the case, cities need to apportion the bulk of their housing via market pricing and not rent controls, as a matter of good political economy. Few do, which is also explainable in terms of political economy. But first, let us look at the anti-supply articles. Gawker claims that San Francisco prices are rising despite a building boom. We’ll come back to this point later, but let me note that in reality, growth in housing supply has been sluggish: Gawker links to a SPUR article about San Francisco’s housing growth, which shows there was high growth in 2012, but anemic growth in previous years. The Census put the city’s annual housing unit growth last decade at 0.8%. In New York, annual growth was 0.5%, as per a London study comparing London, Paris, New York, and Tokyo. In contrast, Tokyo, where zoning is relatively lax, growth was 2%, and rents have sharply fallen. The myth that there is a building boom in cities with very low housing unit growth is an important aspect of the non-market-priced system. Jim’s arguments are more interesting. He quotes a Fed study showing that housing vacancies in the most expensive US cities have not fallen, as we’d expect if price hikes came from lack of supply. (In San Francisco, vacancies went up last decade, at least if you believe that the Census did not miss anyone.) This is too not completely right, because in Los Angeles County, as noted on PDF-page 18 here, vacancies did recently fall. But broadly, it’s correct that e.g. New York’s vacancy rate has been 3% since the late 1990s, as per its housing surveys. But I do not think it’s devastating to the supply position at all. The best way to think about it is in analogy with natural rates of unemployment. Briefly: it’s understood in both Keynesian and neo-classical macroeconomics that an economy with zero employment will have high and rising inflation, because to get new workers, employers have to hire them away from existing jobs by offering higher wages. There is a minimum rate of unemployment consistent with stable inflation, below which even stable unemployment will trigger accelerating inflation. In the US, this is to my understanding about 4%; whether the recession caused structural changes that raised it is of course a critical question for macroeconomic policy. A similar concept can be borrowed into the more microeconomic concept of the housing market. There’s also the issue of friction, again borrowed from unemployment. There’s a minimum frictional vacancy, in which all vacant apartments are briefly between tenants, and if people move between apartments more, it rises. For what it’s worth, the breakdown of 2011 New York vacancies on pages 3-4 by borough and type of apartment suggests friction is at play. First, the lowest vacancy by borough is 2.61%, in Brooklyn, not far below city average. Second, the only type of apartment with much lower vacancy than the city average is the public housing sector, with 1.4% vacancy, where presumably people stay for decades so that friction is very low; rent-stabilized units have lower vacancy than market-rate units, 2.6% vs. 4.4%, which accords with what I would guess about how often people move. So if high rents are the result of supply restrictions, and it appears that they are, the way to reduce them should be to relax zoning restrictions. If this is done, then this allows living even in currently expensive areas without spending much on rent. Urban construction costs are lower than people think: New York’s condo average is$2,300 per square meter, and London’s is not much higher, entirely eaten by PPP conversions; Payton Chung notes the much higher cost of high-rises than that of low-rises, but the cost of high-rise apartment buildings is still only about $2,650/m^2 in Washington, and (using the same tool) about$3,100 in New York, and at least based on the same tool, mid-rises are barely any cheaper. For US-wide single-family houses, construction costs are 61.7% of sale prices, but the $3,100 figure already includes overheads and profit. Excluding land costs, which are someone else’s profit, construction, profit, and overheads are 92.5%; so let’s take our$3,100/m^2 New York high-rise and add the rest to get about $3,300, which is already more than most non-supertall office skyscrapers I have found data for in other major cities. The metro area appears to have a price-to-rent ratio of about 25, and with the caveat that this may go down slightly if the city gets more affordable, this corresponds to a monthly rent of$11 per square meter, at which point, a 100-m^2 apartment, sized for a middle-class family of four, becomes affordable, without subsidies, to families making about $44,000 a year and up, about twice the poverty line and well below the median for a family of that size. If we allow some compromises on construction costs – perhaps slightly smaller apartments, perhaps somewhat lower-end construction – we could cover most of the gap between this and the poverty line. But given that demand for housing at prices that match construction costs, there has to be a way of allocating apartments. Under market pricing, they’re allocated to the highest bidder. If there is a perfectly rigid supply of 2 million housing units and a demand for 4 million at construction costs, the top 2 million bidders get housing, at the rent that the 2 millionth bidder is willing to pay. I do not know of any expensive city with low home ownership that uses market pricing: too many existing residents would lose their homes. High home ownership has the opposite effect, of course – Tel Aviv may have rising rents, and high price-to-income ratios, but since home ownership is high, the local middle class is profiting rather than being squeezed, or at least its older and slightly richer members are. Instead, cities give preference to people who have lived in them for the longest time. Rent control, which limits the increase in annual rent, is one way to do this. City-states, i.e. Singapore and Monaco, have citizenship preference for public housing to keep rents down for their citizens. Other cities use regulations, including rent control but also assorted protections for tenants from eviction, to establish this preference. Instead of market pricing allocation, there is allocation based on a social hierarchy, depending on political connections and how long one has lived in the city. People who moved to San Francisco eight years ago, at age 23, organize to make it harder for other people to move to the city at this age today. Going to market pricing, which means weakening rent controls over the next few years until they’re dead letter, is the only way to also ensure there is upzoning. Although rent control and upzoning both seem to be different policies aimed at affordability, they’re diametrically opposed to each other: one makes it easy for people to move in, one makes it hard. As I mentioned years ago, rent-controlled cities tend to have parallel markets: one is protected for long-timers, and for the rest there is a market that’s unregulated and, because so much of the city’s housing supply is taken off it, very expensive. In exchange-rate dollars, I pay$1,000 for a studio of 30 square meters, of which maybe 20 are usable, the rest having low sloped ceilings. In PPP dollars it’s \$730, still very high for the size of the unit. If I put my name on a waiting list, I could get a similar apartment for a fraction of the price; to nearly all residents, rents are far lower than what I pay, because of tight rent controls. Stockholm at least has a relatively short waiting list for rent-controlled apartments, 1.5 years, for international visitors at my university; American cities (or perhaps American universities) never do foreigners such favors.

The problem here is entirely political. Cities have the power to zone. Thus, supply depends entirely on whether local community leaders accept more housing. This housing, almost invariably, goes to outsiders, who would dilute the community’s politics, forming alternative social networks and possibly caring about different political issues. It’s somewhat telling that ultra-Orthodox Jews in the New York areas support aggressive upzoning, since the new residents are their children and not outsiders; Stephen Smith has written before about the Brooklyn Satmars’ support for upzoning, and the resulting relatively low prices. In the vast majority of the first world, with its at- or below-replacement birth rates, this is not the case, and communities tend to oppose making it easier to build more housing.

There is a certain privilege to being organized here. We see the pattern when we compare how US minorities vote on zoning to what minority community leaders say. In San Francisco specifically, activists who oppose additional development have made appeals to white gentrification in nonwhite neighborhoods, primarily the Mission District. Actual votes on the subject reveal the exact opposite: see the discussion on PDF-pp. 13-15 of this history of Houston land use controls, which notes that low-income blacks voted against zoning by an overwhelming margin because of scare tactics employed by the zoning opponents. (Middle-income blacks voted for zoning, by a fairly large margin.) Polling can provide us with additional data, less dependent on voter turnout and mobilization, and in Santa Monica, Hispanics again favor new hotel development more than whites. In areas where being low-income or nonwhite means one is not organized, low-income minorities are not going to support restrictions that benefit community leaders.

The result is that organized communities are going to instead favor zoning, because it gives them more power, as long as they are insulated from the effect of rising prices. In suburbs with high home ownership, they actually want higher prices: my rents are their property values. In cities with low home ownership, rent controls provide the crucial insulation, ensuring that established factions do not have to pay higher rents. Zoning also ensures that, since the developers who do get variances can make great profits, community groups can extort them into providing amenities. This is of course the worst in high-income areas: every abuse of power is worse when committed by people who are already powerful. But the poor can learn to do it just the same, and this is what happens in San Francisco; TechCrunch has a comprehensive article about various abuses, by San Franciscans of all social classes, culminating in the violent protests against the Google shuttles, and in many cases, the key to the abuse was the community’s ability to veto private developments.

The risk, of course, is displacement. As the gap between the regulated and market rent grows, landlords have a greater incentive to harass regulated tenants into leaving. This is routine in New York and San Francisco. Community groups respond by attacking such harassment individually, which amounts to supporting additional tenant protections. In California, this is the debate over the Ellis Act. The present housing shortages are such that supporting measures that would lower the market rent has no visible short-term benefits, and may even backfire, if a small rent-controlled building is replaced by a large unregulated building.

So with rent controls, community groups have every incentive to support restrictive zoning, and none to support additional development. With market pricing, the opposite is the case. What of low-income city residents’ access to housing, then? Daniel mentions housing subsidies as a necessity for the poor. To be honest, I don’t see the purpose, outside land-constrained cities like Hong Kong and Singapore. If it is possible through supply saturation to cut rents to levels that are affordable to families making not much more than the poverty line, say 133% of the US poverty line, the Medicaid threshold, then direct cash benefits are better. In the ongoing debate over a guaranteed minimum income, the minimum should be slightly higher than the US poverty line, which is lower as a proportion of GDP per capita than most other developed countries’ poverty lines, as seen in the government programs with slightly higher limits, led by Medicaid.

Leftists have spent decades arguing for state involvement in health care and education – not just cash benefits, but either state provision, or state subsidies combined with some measure of cost control. There are many arguments, but the way I understand them, none applies to housing:

1. Positive externalities: Ed Glaeser has noted that if some people in a metro area get more education then there is higher income growth even for other people in the area. In health care, there are issues like herd immunity.

2. Very long-term benefits: if college is as expensive as it is in the US today, it takes many years for graduates’ extra incomes to be worth the debt. With health care, the equivalent is preventive care. When benefits take so much time to accrue, first some people face poverty traps and don’t have the disposable income today to invest in their own health and education, and second, the assumptions of rational behavior in classical economics are less true.

3. Natural monopolies outside large cities: hospitals, schools, and universities have high fixed capital costs, so there can only be sufficient competition in very large cities. The same is of course true of rail transit.

4. Asymmetric information: students and parents can’t know easily whether a school is effective, and patients face the same problem with doctors; short-term satisfaction surveys, such as student evaluations, may miss long-term benefits, and are as a result very unpopular in academia.

With housing, we instead have competitive builder markets everywhere, no appreciable benefits to having your neighbor get a bigger or better apartment, and properties that can be evaluated by viewing them.

The only question is what to do in the transition from the present situation to market pricing. This is where a limited amount of protection can be useful. For example, rent controls could be relaxed into a steady annual gain in the maximum allowed real rent. While market-rate housing remains expensive, public housing is a stopgap solution, and although it should be awarded primarily based on need rather than how long one has lived in the city, a small proportion should be set aside to people in rent-controlled small buildings that were replaced by new towers. None of this should be a long-term solution, but in the short run, this may guarantee the most vulnerable tenants a soft landing.

What this is not, however, is a workable compromise. Community organizations are not going to accept any zoning reform that lets in people who are members of out-groups. They have no real reason to negotiate in good faith; they can negotiate in bad faith as a delaying tactic, which has much the same effect as present zoning regimes. What they want is not just specific amenities, but also the power to demand more in the future; it’s precisely this power that ensures the neighborhoods that are desirable to outsiders are unaffordable to them. What they want is a system in which their political connections and social networks are real resources. A city that welcomes newcomers is the exact opposite. Expensive housing is ultimately not a market failure; it’s a political failure.

# Suburban Geography and Transit Modes

A post on Let’s Go LA from last year, about different suburban development patterns in different regions of the US, praises Los Angeles’s suburbs for having an arterial grid that allows some density and permits frequent bus service. The Northeast, in contrast, has a hierarchical system, of town centers surrounded by fractured streets and cul-de-sacs, at much lower density. This is how Los Angeles’s urban area has the highest standard density in the US, and one of the highest weighted densities, nearly tying San Francisco for second place after New York. It sounds like a point in favor of Los Angeles, but missing from the post is an analysis of how Rust Belt suburban development patterns reinforce prewar transit. Briefly, Western US grids are ideal for arterial buses, Northeastern town centers are ideal for commuter rail, which used to serve every town.

For a Northeastern example, the post brings up Attleboro as a historic town center. Look at the image and notice the walkable grid and development near the train station, although one quadrant of the station radius is taken up by parking. Attleboro is in fact the town with the oldest development on the Northeast Corridor between Boston and the Providence conurbation, and the only one that, when taking the train between Boston and Providence, I’d be able to see development in from the train. Sharon and Mansfield, both developed decades later, do not have as strong town centers. But conversely, many town centers similar to Attleboro’s exist in the Northeast: Framingham, Norwalk, Tarrytown/Sleepy Hollow, Huntington, Morristown, Paoli.

Now, a careful look at the specific examples of Norwalk and Huntington will show that the most walkable development is not necessarily at the train station. In both suburbs, the old town center is where the original road goes – Northern Boulevard and its eastern extensions in Long Island, the Boston Post Road in Connecticut. Huntington has a second center around the LIRR station; Norwalk has a much smaller second center around the South Norwalk Metro-North station. For the most part, the railroads went close enough to the older roads that the town center is the same, as is the case especially in Attleboro, Tarrytown, and Paoli, and in those cases, commuter rail can at least in principle serve jobs at the suburban town center.

This boils down to the difference between optimal bus and rail networks. Buses love grids: they typically serve the scale of a single city and its inner suburbs, and there it’s feasible to provide everywhere-to-everywhere service, which grids are optimal for. For the suburbs, this breaks down. Buses on uncongested arterial roads are still surface transit; an average speed of 30 km/h is aspirational, and that is for suburbs, not dense urban neighborhoods. On a road where the bus can average 30, cars can average 50, and cars can also use expressways without splitting frequency between different suburban destinations, speeding their journeys up greatly. Meanwhile, commuter rail can, depending on stop spacing, average 50-60 km/h easily, and an aggressive timetable can cross 80 if the stop spacing is relatively express.

There is no such thing as a rapid transit grid. Subway networks almost invariably look like a central mesh, often containing a circumferential line, with spokes radiating out of it in all directions. Mexico City has a larger mesh, approximating a subway grid, but its outer ends again look hub-and-spoke. Counting commuter rail, the hub-and-spoke system is as far as I can tell universal, with the exception of highly polycentric metro areas like the Ruhr. The spokes are rarely clean: they often cross each other (see for example the London Underground to scale). But looking at a city’s rail transit map, you’ll almost always be able to tell where the CBD is, where the inner-urban neighborhoods are, and where the outer-urban and suburban areas are.

At this distance, then, having a bus-friendly grid doesn’t matter much. What matters is having a good network of historical rights-of-way that can be used for regional rail, and a preexisting pattern of development following these lines and their junctions. In the US, the older cities have this, whereas the newer ones do not. In a suburb like Attleboro, good transit means good regional rail, with high all-day frequency, and a network of feeder buses timed to meet the trains. Grids aren’t especially useful for that.

And this is why, despite being so dense, Los Angeles has so little transit usage. Its street network is set up for bare-bones public transit, usable by people who can commute two hours in each direction and will never get cars. Because it was a medium-size city when its car ownership exploded, it doesn’t have as many town centers; its density is uniform. It has a higher weighted density than the Rust Belt outside New York, but its weighted-to-standard density ratio is much lower than those of Philadelphia, Boston, and Chicago. (It barely trails Washington, which has fewer town-center suburbs than the Rust Belt, but made an effort to actually build them around Metro; its Tarrytowns have Metro service rather than infrequent commuter rail.)

The optimal urban geography for urban transit is not the same as that for suburban transit, and the optimal street network for surface transit is not the same as that for rapid transit. Los Angeles could potentially excel at surface urban transit, but there’s only so much surface transit can provide the backbone of public transportation in a city. It has a handful of strong lines for rapid transit, and that’s a serious problem, which a grid won’t really solve.