Predictions

I have a lot of readers who come from a rationalist or Effective Altruism background, and some more who come from an economics background, and both communities put a lot of stock in the idea of correct predictions about current events. The idea is that scientists have to make testable predictions about the results of their experiments, and therefore social scientists must equally make predictions about the state of the world. It’s become relevant in the corona crisis and is also relevant to my and Eric Goldwyn’s construction cost project in a specific way, so I’d like to talk about the complexities of what it exactly means to get things right.

Recession

Consider the following prediction: the economy is overheated and a recession will come soon. It’s a vague prediction. One can fill in details to make it strictly testable – “the German economy will have >6% unemployment in 2 years” – but what exactly is the point of one detail or another?

The real answer is that different classes of people have different uses for the prediction of recession, and therefore depend on different details. The investor wants to sell stocks near the peak. The Nasdaq went from 2,200 at the beginning of 1999 to a peak of 5,100. To the investor, knowing that there was a bubble at the beginning of 1999 would not have been useful – cashing out then would have meant missing on a stock market doubling over the year. It would take until about the onset of the 2001 recession for the Nasdaq to fall below January 1999 levels. To the successful investor, it is critical to know the exact timing of the peak to maximize income, and in pursuit of that goal it’s fine to miss some recessions, let alone to miss other important details like the length of the recession and the unemployment rate.

In contrast with the investor, the skilled worker has different concerns, like unemployment. In that environment, knowing that there’s going to be a recession is useful even if the timing is vague – such a worker can save more money, delay major purchases, avoid quitting a stable salaried job to start a small business, and maybe shift to a more recession-proof job even if it means taking a pay cut. Knowing how deep the recession will be is important as well, and remains important knowledge even as the recession takes place – the worker needs to know how stressed to be about savings running out if there is prolonged unemployment. All of this is equally valuable to the prospective immigrant who needs to make a decision on whether to emigrate.

The investor-worker duality is especially important for economists, and to some extent to rationalists who try to follow popular economists. They have money to invest, and often work as advisors to finance firms that pay them for investor-relevant information. But they are also researchers, who can respond to an impending recession by acquiring recession-relevant skills, like studying the history of depressions and conducting empirical research about unemployment and anti-poverty interventions. These are such big research programs that the exact timing of the recession doesn’t really matter, whereas its depth and length matter. An economist who can answer questions like “what is the impact of unemployment programs on long-term welfare?” is useful in a general period of economic weakness even if the papers appear a year into the beginning of the recession.

Predictions and construction costs

Before we started our current project, I had been writing about construction costs here, in comments, and on social media going back to 2009-10. I had some theories over the years, of which some would be confirmed by additional data and others wouldn’t:

  • The theory that common law leads to higher costs, based on high costs across the US, Singapore, the UK, Australia, Canada, India, and Bangladesh. I no longer believe this theory holds up; in the developed world, important edge cases disagree with the theory, including Quebec (expensive) and Israel (about average), and moreover Canadian and Singaporean costs only exploded in the last 15 years.
  • The theory that costs are consistent across projects in the same country, especially the same city; I’m pretty sure I brought it up even in the early 2010s, when I was saying Chinese costs seemed pretty average to me, but the starkest formulation is from 2019. This has subsequently been confirmed when thanks to Yinan Yao our knowledge of Chinese costs grew from two lines in Shanghai to more than 5,000 kilometers’ worth of lines across all major Chinese cities.
  • The theory that costs in developing countries are higher in ex-colonies than in never-colonized countries (like China and Iran) and distantly-colonized ones (like all of Latin America). As stated, there are counterexamples: I will report on our ongoing research into Arab construction costs, thanks to Anan Maalouf, but so far this is indicating that costs in never-colonized Saudi Arabia are pretty high. Call it half a correct prediction because Saudi Arabia is atypical enough I would not lump it a priori with China, Turkey, Mexico, or Iran.

With all that said, I am not too worried if my theories aren’t all confirmed by finding additional data. The reason is that this is not an experimental science but an observational one with a small, finite amount of data, so it’s much more important to have coherent mechanisms that can lead to actionable changes than to be able to predict every country’s construction costs from partial data.

In this case, the mechanisms posited in the 1.5 theories that do not stand up to additional data seem useful. The colonial theory is that high cultural cringe levels and weak state capacity lead ex-colonies to privatize planning to first-world (or Chinese) consultants, who use methods that are not appropriate for local conditions. On account of that explanation, I kept saying ex ante that I refused to make a prediction regarding Thailand, because it was never colonized but also has much more cultural cringe than China and uses first-world consultants; Thai costs are higher than Chinese ones but lower than ex-colonial ones. Saudi Arabia is similar – for all its bluster about rejecting Western governance norms, it craves first-world acceptance and the trappings of modernity, and extensively uses contractors from more developed countries. So the upshot regarding the importance of domestic state capacity and methods tailored for local urban geography and wages remains useful.

Likewise, the high costs across the Anglosphere remain a useful fact. Even more useful is the history of Singapore and Canada, which only aligned with British and American costs starting in the 2000s. The cost explosion in Singapore, Montreal, Toronto, and to some extent Calgary and Vancouver is a recent event, in accessible English-speaking cities; Stephen Wickens just wrote a long report about the Canadian cost explosion, which is of value in teasing out what happened. Even better, the persistent low costs in Scandinavia, Southern Europe, and South Korea provide ready-made sanity checks in knowing what to look for.

Timing issues

In one sense, I made a critical error that poses a serious threat to the project: I got the timing of the recession wrong. When applying for this grant throughout 2019, my assumption was that the American economy was overheated and would soon experience a demand-side recession, leading to stimulus – but that the contraction would be slow enough that the stimulus would come in 2021. With a jobs program announced in 2021, preliminary versions of our report would already be out, the full report with detailed case studies would be out later that year in time for agencies to request funding, and there would be enough time for agencies to implement our recommendations by the time of actual construction.

This may still happen, but the timeline is much less certain. People are talking about stimulus with infrastructure money now. I can promise a report with some actionable recommendations in 2021, but I can’t promise what costs I can promise, nor can I promise what investment to focus on. Our report centers on metro tunnels, but if there’s another push for high-speed rail then we’ll need to be able to adapt metro-based recommendations to a somewhat different context, in which high American costs may have different roots.

What’s more, based on what everyone knows in the United States, costs are so high there’s no point in planning for more. Maybe New York thinks it can finagle $40 billion in stimulus money; this can do a lot at Nordic costs, but unless New York thinks right now that this is possible, it won’t even try to plan more than a few lines like Second Avenue Subway Phase 2 and Gateway, each costing more than a full order of magnitude more than it would in Scandinavia or Southern Europe.

I am not that worried in the long run. There is ongoing investment in enough of the US for whatever we come up with to be relevant to at least some extent. And here too, a cost comparison with the cheaper parts of Europe would be instructive to many a German rail advocate or civil servant. I don’t expect to be in the situation of an investor who bet everything on a company that went bankrupt, just perhaps in that of one who missed a big stock market rally. Ultimately, don’t worry about me, worry about the virus this year and the unemployment rate of potentially the entire world in the next few years.

New York Ignores Best Practices for Cleaning

MTA Chair Pat Foye and Interim New York City Transit President Sarah Feinberg, have announced that the subway will close overnight in order to improve subway cleaning. For the duration of the Covid-19 crisis, the subway will close between 1 and 5 every night for disinfection. Ben Kabak has covered this to some extent; I’m going to focus on best industry practices, which do not require a shutdown. There are some good practices in Taipei, which has regular nighttime shutdowns but sterilizes trains during the daytime as well. It appears that the real rub is not cleaning but homelessness – the city and the state are both trying to get homeless people off the subway and onto the street.

How to disinfect a subway system

Alex Garcia of Taipei Urbanism shared with me what the Taipei MRT plans on doing in response to the virus, depending on how much it affects the system. As soon as there are any domestic cases within Taiwan, the plan says,

a. Sterilize equipment in each station that passengers might frequently come into contact with. (Sterilize once every 8 hours)
b. Carriages: Cleaning and sterilization before the daily operational departure and again when the carriage returns back to the terminal each day.
c. Place hand sanitizer devices at the information counter of the station for public use.

Moreover, if an emergency is declared, then the frequency of cleaning is to increase:

a. Station :
1. Sterilize equipment that passengers might frequently come into contact with at each station. (Sterilize once every 4 hours)
2. Daily disinfection of public station facilities: After operational hours the whole station, including passenger traffic flow areas and facilities, will be disinfected.
b. Carriage :
1. Sterilize equipment that passengers might frequently come in contact with. Sterilize once every 8 hours when the carriage returns to the terminal station.
2. Daily wipe down of entire carriages with disinfectant before each day’s first departure.
3. Once notified by the health authority about any confirmed or suspected case that have traveled on the MRT, intensify the cleaning and disinfection along the route taken by the passenger within 2 hours.

Moreover, the Taipei plan calls for providing all frontline workers with protective equipment, including masks, goggles, and hand sanitizer, as soon as any domestic case of the virus is detected. Moreover, all staff are subject to temperature checks at the start of the day, to prevent sick workers from infecting healthy ones. This way, infection levels among workers can be kept to a minimum, allowing service to proceed without interruption.

It is noteworthy that the frequent cleaning regimen operates during the daytime, and not just overnight. Sterilizing trains every 8 hours means working around their service schedules, disinfecting them during off-peak periods with lower frequency. Taipei has not cut weekday service frequency, only weekend frequency, and the weekday peak-to-base ratio is low, about 1.5 on the Green Line.

With these measures in place, and similar vigilance across Taiwanese society, the country has gone 6 days without any new case of the virus. There is no lockdown and never was one, and Taipei MRT ridership only fell 15-16% on weekdays.

What New York is doing

Foye and Feinberg announced that the subway would close overnight between 1 and 5 am so that trains could be disinfected once per day. Is daily disinfection sufficient? Almost certainly not, given the spread of the virus around the city. Does it take four hours? Of course not, cleaning can be done in minutes. And must it be done at night? Again no, New York has cut so much service that there’s a large fleet of spare trains, making rotating equipment between service and cleaning easy. It’s likely that it is possible to sterilize trains every roundtrip while they wait at the terminal.

The goal here is not about cleanliness. The subway is dirty and getting worse as cleaning staff get sick and can’t come to work, but a program designed to improve the system would look profoundly different. It would equip subway workers with protective gear, especially the cleaners; it would keep running service; it would look for ways to eliminate fomites like the push turnstiles; it would disinfect trains and stations at short intervals.

The homelessness issue

There are serious concerns with homelessness in New York, as in many other cities. This is aided by sensationalist reporting that blames homeless people for any number of problems, playing to middle-class prejudices about visible poverty. As Ben notes, NYPD swept the subway with cops but not social workers. Hotels are empty all over the city, but there is no attempt at using them for either centralized quarantine or extra shelter space. There are existing shelters, but they are unsafe and people who have been unsheltered for a while know this and avoid them for a reason.

New York is a big, expensive, high-inequality city. It has visible poverty, including homelessness. It could offer homeless people housing – empty hotels would do, employing hotel workers to do work that is already done at shelters by overtaxed volunteers. The problem is that many aggrieved people want medieval displays of police power against people who it is okay to be violent toward; they do not want to solve problems. This issue is not unique to New York: in San Francisco, sanisette installations ran into the problem that one stall had people defecating on the floor, leading the city to decide to staff every sanisette 24/7, turning what was designed as a self-cleaning system for high-cost cities for €14,400 a year per unit into a $700,000/year money sink. American cities spend millions in enforcement to avoid spending pennies on social work.

Who is being empowered?

The broader question is whether the subway is dirty because of homeless people or because of inadequate cleaning, poor training for cleaners, lack of protective equipment, etc. The vast majority of dirt one sees on trains has pretty obvious origins in ordinary if antisocial riders: spilled drinks, gum stuck to the floor, overflowing trash cans, wrappers thrown on the tracks. However, it is convenient to blame homeless people for this – they can’t politically fight back, and many law-and-order voters and political operatives relish the sight of a cop dragging someone off the train.

This leads to the question, who is being empowered by blame? Any explanation of why things don’t work empowers someone, and explanations are easier to accept if they empower local political forces that the mainstream pays attention to. For example, if I say costs are high because of union pensions, then this automatically empowers the Manhattan Institute and other anti-union forces in the city; and if I say costs are high because managers micromanage and humiliate workers too much, then this empowers the unions.

The upshot is that blaming flagging subway ridership on homeless people making riders uncomfortable empowers law-and-order voters and middle-class people who dislike seeing visible poverty, both of which are groups that even relatively liberal political operatives pay attention to. In contrast, blaming flagging ridership on technical issues with speed and frequency empowers technocrats, who are usually politically invisible, and when they’re not, this can lead to a clash of authority, as seen in Governor Andrew Cuomo’s sidelining of Byford, leading to the latter’s resignation.

This cascades to cleaning. Taipei shows how one can clean trains and stations during service. New York should learn, but that means listening to people who are familiar with Taiwanese practices, and maybe synthesize with other clean Asian systems. Shutdowns that force essential workers onto slow buses and taxis are a terrible policy, but they’re a policy the current leadership does not need to talk to people in a foreign country to implement.

Some Notes About Northeast Corridor High-Speed Rail

I want to follow up on what I wrote about speed zones a week ago. The starting point is that I have a version 0 map on Google Earth, which is far from the best CAD system out there, one that realizes the following timetable:

Boston 0:00
Providence 0:23
New Haven 1:00
New York 1:40
Newark 1:51
Philadelphia 2:24
Wilmington 2:37
Baltimore 3:03
Washington 3:19

This is inclusive of schedule contingency, set at 7% on segments with heavy track sharing with regional rail, like New York-New Haven, and 4% on segment with little to no track haring, like New Haven-Providence. The purpose of this post is to go over some delicate future-proofing that this may entail, especially given that the cost of doing so is much lower than the agency officials and thinktank planners who make glossy proposals think it should.

What does this entail?

The infrastructure required for this line to be operational is obtrusive, but for the most part not particularly complex. I talked years ago about the I-95 route between New Haven and southern Rhode Island, the longest stretch of new track, 120 km long. It has some challenging river crossings, especially that of the Quinnipiac in New Haven, but a freeway bridge along the same alignment opened in 2015 at a cost of $500 million, and that’s a 10-lane bridge 55 meters wide, not a 2-track rail bridge 10 meters wide. Without any tunnels on the route, New Haven-Kingston should cost no more than about $3-3.5 billion in 2020 terms.

Elsewhere, there are small curve easements, even on generally straight portions like in New Jersey and South County, Rhode Island, both of which have curves that if you zoom in close enough and play with the Google Earth circle tool you’ll see are much tighter than 4 km in radius. For the most part this just means building the required structure, and then connecting the tracks to the new rather than old curve in a night’s heavy work; more complex movements of track have been done in Japan on commuter railroads, in a more constrained environment.

There’s a fair amount of taking required. The most difficult segment is New Rochelle-New Haven, with the most takings in Darien and the only tunneling in Bridgeport; the only other new tunnel required is in Baltimore, where it should follow the old Great Circle Tunnel proposal’s scope, not the four-track double-stack mechanically ventilated bundle the project turned into. The Baltimore tunnel was estimated at $750 million in 2008, maybe $1 billion today, and that’s high for a tunnel without stations – it’s almost as high per kilometer as Second Avenue Subway without stations. Bridgeport requires about 4 km of tunnel with a short water crossing, so figure $1-1.5 billion today even taking the underwater penalty and the insane unit costs of the New York region as a given.

A few other smaller deviations from the mainline are worth doing at-grade or elevated: a cutoff in Maryland near the Delaware border in the middle of what could be prime 360 km/h territory, a cutoff in Port Chester and Greenwich bypassing the worst curve on the Northeast Corridor outside major cities, the aforementioned takings-heavy segment through Darien continuing along I-95 in Norwalk and Westport, a short bypass of curves around Fairfield Station. These should cost a few hundred million dollars each, though the Darien-Westport bypass, about 15 km long, could go over $1 billion.

Finally, the variable-tension catenary south of New York needs to be replaced with constant-tension catenary. A small portion of the line, between New Brunswick and Trenton, is being so replaced at elevated cost. I don’t know why the cost is so high – constant-tension catenary is standard around the world and costs $1.5-2.5 million per km in countries other than the US, Canada, and the UK. The Northeast Corridor is four-track and my other examples are two-track, but then my other examples also include transformers and not just wires; in New Zealand, the cost of wires alone was around $800,000 per km. Even taking inflation and four tracks into account, this should be maybe $700 million between New York and Washington, working overnight to avoid disturbing daytime traffic.

The overall cost should be around $15 billion, with rolling stock and overheads. Higher costs reflect unnecessary scope, such as extra regional rail capacity in New York, four-tracking the entire Providence Line instead of building strategic overtakes and scheduling trains intelligently, the aforementioned four-track version of the Baltimore tunnel, etc.

The implications of cheap high-speed rail

I wrote about high-speed rail ridership in the context of Metcalfe’s law, making the point that once one line exists, extensions are very high-value as a short construction segment generates longer and more profitable trips. The cost estimate I gave for the Northeast Corridor is $13 billion, the difference with $15 billion being rolling stock, which in that post I bundled into operating costs. With that estimate, the line profits $1.7 billion a year, a 13% financial return. This incentivizes building more lines to take advantage of network effects: New Haven-Springfield, Philadelphia-Pittsburgh, Washington-Virginia-North Carolina-Atlanta, New York-Upstate.

The problem: building extensions does require the infrastructure on the Northeast Corridor that I don’t think should be in the initial scope. Boston-Washington is good for around a 16-car train every 15 minutes all day, which is very intense by global standards but can still fit in the existing infrastructure where it is two-track. Even 10-minute service can sometimes fit on two tracks, for example having some high-speed trains stop at Trenton to cannibalize commuter rail traffic – but not always. Boston-Providence every 10 minutes requires extensive four-tracking, at least from Attleboro to beyond Sharon in addition to an overtake from Route 128 to Readville, the latter needed also for 15-minute service.

More fundamentally, once high-speed rail traffic grows beyond about 6 trains per hour, the value of a dedicated path through New York grows. This is not a cheap path – it means another Hudson tunnel, and a connection east to bypass the curves of the Hell Gate Bridge, which means 8 km of tunnel east and northeast of Penn Station and another 2 km above-ground around Randall’s Island, in addition to 5 km from Penn Station west across the river. The upshot is that this connection saves trains 3 minutes, and by freeing trains completely from regional rail traffic with four-tracking in the Bronx, it also permits using the lower 4% schedule pad, saving another 1 minute in the process.

If the United States is willing to spend close to $100 billion high-speed rail on the Northeast Corridor – it isn’t, but something like $40-50 billion may actually pass some congressional stimulus – then it should spend $15 billion and then use the other $85 billion for other stuff. This include high-speed tie-ins as detailed above, as well as low-speed regional lines in the Northeast: new Hudson tunnels for regional traffic, the North-South Rail Link, RegionalBahn-grade links around Providence and other secondary cities, completion of electrification everywhere a Northeastern passenger train runs

Incremental investment

I hate the term “incremental” when it comes to infrastructure, not because it’s inherently bad, but because do-nothing politicians (e.g. just about every American elected official) use it as an excuse to implement quarter-measures, spending money without having to show anything for it.

So for the purpose of this post, “incremental” means “start with $15 billion to get Boston-Washington down to 3:20 and only later spend the rest.” It doesn’t mean “spend $2 billion on replacing a bridge that doesn’t really need replacement.”

With that in mind, the capacity increases required to get from bare Northeast Corridor high-speed rail to a more expansive system can all be done later. The overtakes on Baltimore-Washington would get filled in to form four continuous tracks all the way, the ones on Boston-Providence would be extended as outlined above, the bypasses on New York-New Haven would get linked to new tracks in the existing right-of-way where needed, the four-track narrows between Newark and Elizabeth would be expanded to six in an already existing right-of-way. Elizabeth Station has four tracks but the only building in the way of expanding it to six is a parking garage that needs to be removed anyway to ease the S-curve to the south of the platforms.

However, one capacity increase is difficult to retrofit: new tracks through New York. The most natural way to organize Penn Station is as a three-line system, with Line 1 carrying the existing Hudson tunnel and the southern East River tunnels, including high-speed traffic; Line 2 using new tunnels and a Grand Central link; and Line 3 using a realigned Empire Connection and the northern East River tunnels. The station is already centered on 32nd Street extending a block each way; existing tunnels going east go under 33rd and 32nd, and all plans for new tunnels continuing east to Grand Central or across the East River go under 31st.

But if it’s a 3-line system and high-speed trains need dedicated tracks, then regional trains don’t get to use the Hell Gate Line. (They don’t today, but the state is spending very large sums of money on changing this.) Given the expansion in regional service from the kind of spending that would justify so much extra intercity rail, a 4-line system may be needed. This is feasible, but not if Penn Station is remodeled for 3 lines; finding new space for a fourth tunnel is problematic to say the least.

Future-proofing

The point of integrated timetable planning is to figure out what timetable one want to run in the future and then building the requisite infrastructure. Thus, in the 1990s Switzerland built the tunnels and extra tracks for the connections planned in Bahn 2000, and right now it’s doing the same for the next generation. This can work incrementally, but only if one knows all the phases in advance. If timetable plans radically change, for example because the politicians make big changes overruling the civil service to remind the public that they exist, then this system does not work.

If the United States remains uninterested in high-speed rail, then it’s fine to go ahead with a bare-bones $15 billion system. It’s good, it would generate good profits for Amtrak, it would also help somewhat with regional-intercity rail connectivity. Much of the rest of the system can be grafted on top without big changes.

But then it comes to Penn Station. It’s frustrating, because anything that brings it into focus attracts architects and architecture critics who think function should follow form. But it’s really important to make decisions soon, get to work demolishing the above-ground structures starting when the Madison Square Garden lease runs out, and move the tracks in the now-exposed stations as needed based on the design timetable.

As with everything else, it’s possible not to do it – to do one design and then change to another – but it costs extra, to the tune of multiple billions in unnecessary station reconstruction. If the point is to build high-speed rail cost-effectively, spending the same budget on more infrastructure instead of on a few gold-plated items, then this is not acceptable. Prior planning of how much service is intended is critical if costs are to stay down.

Construction Costs in China: Preliminary Notes

Eric and I are in the process of building up our database of construction costs and starting to select case studies for in-depth study. Most of the world was already in my original database from late 2019, but there are big gaps, most notably China, which has built more subways in the last 20 years than in my entire database combined. For this, we work with students; I mentioned Min-Jae Park in a previous post, but we have others. A Chinese master’s student of public administration at NYU named Yinan Yao is working with us on this, and has used Chinese sources, mainly official (what I call “plan” in my dataset), to construct a dataset that so far has 5,700 km, of which around two-thirds is underground.

I’m not putting the database out yet – this is still preliminary and subject to some edits, and we’ll publish a merged database of everything when it’s done (probably in the summer of this year, but don’t yell at me if it takes longer). However, I want to point out some observations that come from the data:

Chinese costs are fairly consistent: most recent subways cluster somewhat below 1 billion yuan per kilometer, or around $250 million per kilometer in PPP terms. This is consistent across the entire PRC. Costs are slightly higher in Beijing and Shenzhen than in the rest of China, and are even higher in Shanghai, where they approach 1.5 billion yuan per km. This is in accordance with what I’ve found in the rest of the world: costs are remarkably consistent within countries, especially within cities, to the point that variations, like New York’s higher-than-US-average costs or the difference between Milan and Rome, require separate explanation.

More difficult lines cost more: this is again not surprising, but it’s useful to check this on the largest national database of costs. Yinan points out that certain lines that cost more are more central, in that sense of passing under older lines with many transfer stations. See for example the Shanghai plan for 2018-23, with a map, a list of lines, and their costs (in hundreds of millions of yuan, not billions) on the last page: the highest cost per kilometer is actually a short elevated extension of Line 1, which has to be done while keeping the line’s current Xinzhuang terminal open for service as it is a critical transfer point to Line 5. The same map also shows the cost difference between the more central Lines 19 and 20 and the more suburban Airport Line, which goes around city center as the center is already connected to Pudong Airport via Line 2.

Why is Shanghai more expensive? Shanghai has a more built-out metro system than any other city in China save Beijing. That could explain its cost premium, but then again, relatively suburban lines like the Airport Line have similar costs to rest-of-China lines, including city center tunneling. Yinan suggests that the reason is geological: Shanghai is in the alluvial plain at the mouth of the Yangtze. This theory would suggest that tunneling in other parts of the world at the mouths of big rivers is expensive as well – and this is in fact true in Europe, as construction costs in the Netherlands are high. It is worth investigating, not just because of the implications for China but also for the implications for Europe: if Dutch costs are high for geological reasons, then there is nothing to explain regarding the quality of Dutch institutions, and thus if certain institutions (such as consensus democracy) occur in low-cost countries like Switzerland and the Nordic countries but also in the Netherlands, then the retort “but the Netherlands has this too and is expensive” loses impact.

There is very little regional rail in China. The definition of regional rail in a Chinese context is dicey – China did not inherit big legacy commuter rail networks, unlike India or most developed countries. Suburban rail lines are greenfield metros, rather like the Tsukuba Express or some of the more speculative parts of Grand Paris Express. In our dataset, regional rail is broken out from other urban rail because the concept of regional rail means only tunneling the hardest parts, and doing the rest on the surface using legacy railroads, which cuts overall costs but raises the costs per km of tunneling. China doesn’t do this, so all lines have the tunnel composition of a metro.

Having a lot of quantitative data makes things easier. Chinese costs are in the context of a consistent set of national institutions, and involve a lot of different subway lines. Even income differences are not so huge as to render analysis impossible – there is a lot of geographic inequality in China, but less than between (say) China and the developed world, and for the most part the bigger cities are on the richer side. This makes it easier to formulate hypotheses, for example regarding what exactly it means for a line to be more or less central. Eric, Yinan, and I are trying to come up with a coherent definition, which we can then try to test on other countries that build a lot of subways, like France, Russia, India, South Korea, and Spain.

All data is valuable. I started looking at costs in 2009-10 in order to figure out how to affordably build more subways in New York, and thus focused on the largest and richest world cities, like London and Paris. But really, all data is valuable. Comparing various developing countries is important because of issues like cultural cringe, and likewise figuring out if Shanghai is more expensive due to geology is important because of the implications regarding Dutch institutions. It is ignorant and harmful when New Yorkers reject knowledge that comes from outside their comfort zone of the city and perhaps the few rich global cities it deigns to compare itself with. On the contrary, Chinese data should be of immense value to both richer countries like the US and poorer ones like India, and likewise data from the rest of the world (for example, some Japanese and Korean best practices) should be of immense value in China.

There is a lot of knowledge out there. The point of comparative research is to access knowledge that people in one reference group (in our case, New York) do not have. Eric and I don’t speak Chinese; our language coverage, plus some non-English Google searches, is pretty useful, but far from panglossian. Yinan is so far tremendously helpful to this project. (The other students are helpful too in what they cover – they’ll get posts too, just this one focuses on China.)

Holidays by Train

What does leisure travel look like in a world where driving and flying are prohibitively expensive, and rail travel is more abundant and convenient?

It does not look exactly like today’s travel patterns except by train. Where people choose to travel is influenced by cultural expectations that are themselves influenced by available technology, prices, and marketing. Companies and outfits providing transportation also market the destinations for it, whether it’s a private railway selling real estate in the suburbs on its commuter lines, an airline advertising the resort cities it flies to, or a highway authority promoting leisure drives and auto-oriented development. The transition may annoy people who have gotten used to a set of destinations that are not reachable by sustainable transportation, but as the tourism economy reorients itself to be greener, new forms of leisure travel can replace old ones.

Historic and current examples

Railroads were the first mode of mechanized transportation, and heavily marketed the destinations one could reach by riding them. The involvement of some railroads in suburban development, such as Japanese private railroads or the original Metropolitan Railway, is fairly well-known to the rail advocacy community. Lesser-known but equally important is rail-based tourism. Banff and Jasper owe their existence to transcontinental railways, Lake Louise was founded as a montane resort on top of the Canadian Pacific Railway, Glacier National Park opened thanks to its location next to the (American) Great Northern. Even Niagara Falls, for all its unique natural beauty, benefited from heavy marketing by the New York Central, which offered the fastest route there from New York.

Other than Niagara Falls, the North American examples of rail-based tourism are all in remote areas, where people no longer travel by train. Some may drive, but most fly over them. The American system of national parks, supplemented by some state parks like the Adirondacks and Catskills, has thus reoriented itself around long-distance leisure travel by car. This includes popular spots like Yellowstone, Bryce, Grand Canyon, and Yosemite in the United States, Schwarzwald in Germany, or the tradition of summer homes in outlying areas in Sweden or the American East Coast.

The airline industry has changed travel patterns in its own way. Planes are fast, and require no linear infrastructure, so they are especially suited for getting to places that are not easy to reach by ground transportation. Mass air travel has created a tourism boom in Hawaii, the Maldives, southern Spain, the Caribbean, any number of Alpine ski resorts, Bali, all of Thailand. Much of this involves direct marketing by the airlines telling people in cold countries that they could enjoy the Mediterranean or Indian Ocean sun. Even the peak season of travel shifted – English vacation travel to the Riviera goes back to the early Industrial Revolution, but when it was by rail and ferry the peak season was winter, whereas it has more recently shifted to the summer.

The politics of vacation travel

In some cases, states and other political actors may promote particular vacation sites with an agenda in mind. Nationalists enjoy promoting national unity through getting people to visit all corners of the country, and if this helps create a homogeneous commercial national culture, then all the better. This was part of the intention of the Nazi program for Autobahn construction and Volkswagen sales, but it’s also very common in democratic states that aim to use highways for nation-building, like midcentury America.

If there’s disputed land, then nationalists may promote vacation travel there in order to instill patriotic feelings toward it among the population. Israel has turned some demolished Arab villages into national forests, and promoted tourism to marginal parts of the country; settler forces are likewise promoting vacation travel to the settlements, cognizant of the fact that the median Israeli doesn’t have strong feelings toward the land in the Territories and wouldn’t mind handing them over in exchange for a peace agreement.

Politics may also dictate promoting certain historic sites, if they are prominent in the national narrative. In the Jewish community, two such trips are prominent, in opposite directions: the first is the organized Israeli high school trips to Poland to see the extermination camps and the ghettos, perpetuating the memory of the Holocaust in the public; the second is Birthright trips for Jews from elsewhere to visit Israel and perhaps find it charming enough to develop Zionist feelings toward it.

So what does this mean?

I bring up the politics and economic history of leisure travel, because a conscious reorientation of vacation travel around a green political agenda is not so different from what’s happened in the last few generations. The big change is that the green agenda starts from how people should travel and works out potential destinations and travel patterns from there, whereas nationalist agendas start from where people should travel and are not as commonly integrated with economic changes in how people can travel.

The point, then, is to figure out what kinds of vacation travel are available by train. Let’s say the map that I put forth in this post is actually built, and in contrast, taxes on jet fuel as well as petrol rise by multiple euros per liter in order to effect a rapid green transition. Where can people go on vacation and where can’t they?

Intercity leisure travel

By far the easiest category of leisure travel to maintain in a decarbonized world is between cities within reasonable high-speed rail range. Tens of millions of people already visit Paris and London every year, for business as well as for tourism. This can continue and intensify, especially if the green transition also includes building more housing in big high-income cities, creating more room for hotels.

High-speed rail lives on thick markets, the opposite of air travel. Once the basic infrastructure is there, scaling it up to very high passenger volumes on a corridor is not difficult; the Shinkansen’s capacity is not much less than 20,000 passengers per hour in each direction. Many people wish to travel to Paris for various reasons, so the TGV makes such travel easier, and thus even more people travel to and from the capital. A bigger and more efficient high-speed rail network permits more such trips, even on corridors that are currently underfull, like the LGV Est network going toward much of Germany or the LGV Sud-Europe Atlantique network eventually connecting to much of Spain.

Germany does not have a Paris, but it does have several sizable cities with tourist attractions. A tightly integrated German high-speed rail network permits many people in Germany and surrounding countries to visit the museums of Berlin, go to Carnival in Cologne, attend Oktoberfest in Munich, see the architecture of Hamburg, or do whatever it is people do in Frankfurt. The international connections likewise stand to facilitate German travel to neighboring countries and their urban attractions: Paris, Amsterdam, Basel, Vienna, Prague.

Intercity travel and smaller cities

Big cities are the most obvious centers of modern rail-based tourism. What else is there? For one, small cities and towns that one encounters on the way on corridors designed to connect the biggest cities. Would Erfurt justify a high-speed line on its own? No. But it has an ICE line, built at great expense, so now it is a plausible place for travel within Germany. The same can be said about cities that are not on any plausible line but could easily connect to one via a regional rail transfer. When I fished for suggestions on Twitter I got a combination of cities on top of a fast rail link to Berlin, like Leipzig and Nuremberg, and ones that would require transferring, like Münster and Heidelberg.

Even auto-oriented vacation sites can have specific portions that are rail-accessible, if they happen to lie near or between large cities. In North America the best example is Niagara Falls, conveniently located on the most plausible high-speed rail route between New York and Toronto. In Germany, South Baden is normally auto-oriented, but Freiburg is big enough to have intercity rail, and as investment in the railroad increases, it will be easier for people from Frankfurt, Munich, and the Rhine-Ruhr to visit.

Farther south, some Swiss ski resorts have decent enough rail connections that people could get there without too much inconvenience. If the German high-speed rail network expands with fast connections to Basel (as is planned) and Zurich (which is nowhere on the horizon), and Switzerland keeps building more tunnels to feed the Gotthard Base Tunnel (which is in the Rail 2035 plan but with low average speed), then people from much of central and southern Germany could visit select Swiss ski resorts in a handful of hours.

Non-urban travel

The green transition as I think most people understand it in the 21st century is an intensely urban affair. Berlin offers a comfortable living without a car, and as the German electric grid replaces coal with renewables (slower than it should, but still) it slowly offers lower-carbon electricity, even if it is far from Scandinavia or France. Small towns in contrast have close to 100% car ownership, the exceptions being people too poor to own a car. But the world isn’t 100% urban, and even very developed countries aren’t. So what about travel outside cities large and small?

The answer to that question is that it depends on what cities and what railroads happen to be nearby. This is to a large extent also true of ordinary economic development even today – a farming town 20 km from a big city soon turns into a booming commuter town, by rail or by highway. Popular forests, trails, mountains, and rivers are often accessible by railroad, depending on local conditions. For example, some of the Schwarzwald valleys are equipped with regional railways connecting to Freiburg.

Here, it may be easier to give New York examples than Berlin ones. Metro-North runs along the banks of the Hudson, allowing riders to see the Palisades on the other side. The vast majority of travelers on the Hudson Line do not care about the views, but rather ride the train to commute from their suburbs to Manhattan. But the line is still useful for leisure trips, and some people do take it up on weekends, for example to Poughkeepsie. The Appalachian Trail intersects Metro-North as well, though not many people take the train there. Mountains are obstacles for rail construction, but rivers are the opposite, many attracting railroads near their banks, such as the Hudson and the Rhine.

Conversely, while New York supplies the example of the Hudson Line, Germany supplies an urban geography that facilitates leisure travel by rail out of the city, in that it has a clear delineation between city and country, with undeveloped gaps between cities and their suburbs. While this isn’t great for urban rail usage, this can work well for leisure rail usage, because these gaps can be developed as parkland.

Where’s the catch?

Trains are great, but they travel at 300-360 km/h at most. An aggressive program of investment could get European trains to average around 200-240 km/h including stops and slow zones. This allows fast travel at the scale of a big European country or even that of two big European countries, but does not allow as much diversity of climate zones and biomes as planes do.

This does not mean trains offer monotonous urban travel. Far from it – there’s real difference in culture, climate, topography, and architecture within the German-speaking world alone, Basel and Cologne looking completely different from each other even as both are very pretty. But it does limit people to a smaller tranche of the world, or even Europe, than planes do. A Berliner who travels by train alone can reach Italy, but even with a Europe-scale high-speed rail program, it’s somewhat less than 4:45 to Venice, 5:00 to Milan, 5:30 to Florence, 6:45 to Rome, 7:45 to Naples. It’s viable for a long vacation but not as conveniently as today by plane with airfare set at a level designed to redraw coastlines. Even in Italy, there’s great access to interesting historic cities, but less so to coastal resorts designed around universal car use, located in topographies where rail is too difficult.

The situation of Spanish resorts is especially dicey. There isn’t enough traffic from within Spain to sustain them, there are so many. Germany is too far and so is Britain if planes are not available at today’s scale. What’s more, people who are willing to travel 7 or 8 hours to a Spanish resort can equally travel 5 hours to a French or Italian one. The French Riviera has gotten expensive, so tourism there from Northern Europe feels higher-income to me than tourism to Alicante, but if people must travel by train, then Nice is 4:30 from Paris and Alicante is 7:30, and the same trip time difference persists for travelers from Britain and Germany.

Is it feasible?

Yes.

High carbon taxes are not just economically feasible and desirable, but also politically feasible in the context of Europe. The jet fuel tax the EU is discussing as part of the Green Deal program is noticeable but not enough to kill airlines – but what environmental policy is not doing, the corona virus crisis might. If low-cost air travel collapses, then much of the market for leisure travel specifically will have to reorient itself around other modes. If Europe decides to get more serious about fighting car pollution, perhaps noticing how much more breathable the air in Paris or Northern Italy is now than when people drive, then taxes and regulations reducing mass motorization become plausible too.

The transition may look weird – people whose dream vacation involved a long drive all over Italy or France or Germany may find that said vacation is out of their reach. That is fine. Other vacations become more plausible with better rail service, especially if they’re in big cities, but also if they involve any of a large number of natural or small-town destinations that happen to be on or near a big city-focused intercity rail network.

Some Data on New York City Subway Ridership in the Covid-19 Crisis

The MTA has weekly data on ridership by train station, which it divides into fare data, i.e. data by what kind of fare it is (single-use, monthly, etc.), and turnstile data, i.e. data by what bank of turnstiles was used to enter the station. MTA chief communications officer Abbey Collins talked to me briefly when I was writing this New York Daily News op-ed, and told me that the turnstile data is less accurate, so I am using the fare data.

Here is the table I’m using, comparing ridership in mid-January and the fourth week of March. It’s not fully sanitized, so some stations appear twice, which reflects multiple major entrances, e.g. the Times Square and the Port Authority sides of a single complex with in-system transfers. The relevant column is column E, labeled ratio. The highest-ratio station is Alabama Avenue on the J/Z, which has kept 53.5% of its January ridership; the next proper subway station, Bay Parkway on the F, is just at 38.6%, and it goes down from there. Overall, the ratio is 14.1%.

The general pattern is that the Manhattan CBD stations got pummeled. Grand Central has kept 7.5% of its pre-crisis ridership, and the Times Square side of the Times Square-Port Authority complex has kept 7.2%. A couple of Midtown and Lower Manhattan stations, like Rockefeller Center, are at the 5% mark. Practically no non-CBD station is this low, but one notable exception is Bedford Avenue on the L, in the center of Williamsburg. A few additional notable areas are in the 8-10% area, including more stations in Williamsburg, stations in Downtown Brooklyn and South Brooklyn, most stations on Central Park West, and Columbia. It’s notable that Columbia is low even though it has a major hospital, but it’s even more of a university.

Despite the stereotype, much of the Upper West and East Sides are not in the single digits. The key express stations, like 86th on the 4/5/6 and 72nd and 96th on the 1/2/3, are around 13-14%. Harlem is much higher, especially the busiest Harlem stations, 125th Street on the A/B/C/D and on the 4/5/6, both express stops, which have maintained 19.5% and 27.2% of ridership, respectively. 168th Street on the 1/A/C in Washington Heights is at 23.8%.

In general, working-class and lower middle-class stations seem to have maintained the most ridership. Jamaica Center, a key bus connection point to much of Eastern Queens, is by far the busiest among the >30% stations, at 35.3%. Utica Avenue on the 3/4 in Crown Heights is at 28.7%, and 149th Street on the 4/5/6 in the South Bronx is at 29.2%. Bedford-Stuyvesant is all over the map – Nostrand Avenue on the A/C is at 17.5%, Utica Avenue on the A/C is at 21.7%, the two Flushing Avenue stations are at about 27%, the Broadway stations on the J/Z past Flushing are in the teens.

I give those descriptive statistics because it relates to the question of subway ridership and the Covid-19 crisis. The crisis has hit outer neighborhoods harder than inner ones and working-class neighborhoods harder than middle-class ones, but beyond that pattern there is not much correlation at the level of detail. Bed-Stuy and Central Harlem have low infection rates and have maintained much more of their subway ridership than the city average.

The patterns probably concern essential workers. There are essential workers in all social classes, but more in the working class – cleaners, transit workers, sanitation workers, nursing assistants. The middle class supplies doctors and registered nurses, but there are fewer of these on the list of essential workers than lower-income, lower-education workers. Thus, middle-class neighborhoods, like the Upper East and West Sides, Astoria, Williamsburg, Sunnyside, Forest Hills, and Bay Ridge have below-average ratios, that is they’ve kept less of their ridership than the rest of the city.

One final pattern, or rather non-pattern, is that I can’t really see the hospitals on the table. The stations on the 2/5 closest to the Kings County Hospital, Winthrop Street and Church Avenue, are at 22.4% and 22.8% respectively, not too different from the rest of the Nostrand Avenue Line. The two Flushing Avenue stations have similar ratios, even though one is on top of Woodnull Medical Center and the other isn’t. 96th and 103rd Streets on the 6, the closest to Mount Sinai, have similar ratios to 110th and 116th farther up in East Harlem.

Speed Zones on Railroads

I refined my train performance calculator to automatically compute trip times from speed zones. Open it in Python 3 IDLE and play with the functions for speed zones – so far it can’t input stations, only speed zones on running track, with stations assumed at the beginning and end of the line.

I’ve applied this to a Northeast Corridor alignment between New York and Boston. The technical trip times based on the code and the alignment I drew are 0:36:21 New York-New Haven, 0:34:17 New Haven-Providence, 0:20:40 Providence-Boston; with 1-minute dwell times, this is 1:33 New York-Boston, rising to maybe 1:40 with schedule contingency. This is noticeably longer than I got in previous attempts to draw alignments, where I had around 1:28 without pad or 1:35 with; the difference is mainly in New York State, where I am less aggressive about rebuilding entire curves than I was before.

I’m not uploading this alignment yet because I want to fiddle with some 10 meter-scale questions. The most difficult part of this is between New Rochelle and New Haven. Demolitions of high-price residential properties are unavoidable, especially in Darien, where there is no alternative to carving a new right-of-way through Noroton Heights.

The importance of speeding up the slowest segments

The above trip times are computed based on the assumption that trains depart Penn Station at 60 km/h as they go through the interlocking, and then speed up to 160 km/h across the East River, using the aerodynamic noses designed for 360 km/h to achieve medium speed through tunnels with very little free air. This require redoing the switches at the interlocking; this is fine, switches in the United States are literally 19th-century technology, and upgrading them to Germany’s 1925 technology would create extra speed on the slowest segment.

Another important place to speed up is Shell Interlocking. The current version of the alignment shaves it completely, demolishing some low-rise commercial property in the process, to allow for 220 km/h speeds through the city. Grade separation is obligatory – the interlocking today is at-grade, which imposes unreasonable dependency between northbound and southbound schedules on a busy commuter railroad (about 20 Metro-North trains per hour in the peak direction).

In general, bypasses west of New Haven prioritize the slowest segments of the Northeast Corridor: the curves around the New York/Connecticut state line, Darien, Bridgeport. East of New Haven the entire line should be bypassed until Kingston, even the somewhat less curvy segment between East Haven and Old Saybrook, just because it’s a relatively easy segment where the railroad can mostly twin with I-95 and not have any complex viaducts.

The maximum speed is set at 360 km/h, but even though trains can cruise at such speed on two segments totaling 130 km, the difference in trip time with 300 km/h is only about 3 minutes. Similarly, in southwestern Connecticut, the maximum speed on parts of the line, mostly bypasses, is 250 km/h, and if trains could run at 280 km/h on those segments, which isn’t even always possible given curvature, it would save just 1 minute. The big savings come from turning a 10 miles per hour interlocking into a modern 60 km/h (or, ideally, 90+ km/h) one, eliminating the blanket 120 km/h speed limit between the NY/CT state line and New Haven, and speeding up throats around intermediate stations.

Curve easements

Bypasses are easier to draw than curve modifications. Curves on the Northeast Corridor don’t always have consistent radii – for example, the curves flanking Pawtucket look like they have radius 600 meters, but no, they have a few radii of which the tightest are about 400 meters, constraining speed further. Modifying such curves mostly within right-of-way should be a priority.

Going outside the right-of-way is also plausible, at a few locations. The area just west of Green’s Farms is a good candidate; so is Boston Switch, a tight curve somewhat northeast of Pawtucket whose inside is mostly water. A few more speculative places could get some noticeable trip time improvements, especially in the Bronx, but the benefit-cost ratio is unlikely to be good.

Bush consulting on takings

In some situations, there’s a choice of which route to take – for example, which side of I-95 to go on east of New Haven (my alignment mostly stays on the north side). Some right-of-way deviations from I-95 offer additional choice about what to demolish in the way.

In that case, it’s useful to look for less valuable commercial properties, and try to avoid extensive residential takings if it’s possible (and often it isn’t). This leads to some bush consulting estimates of how valuable a strip mall or hotel or bank branch is. It’s especially valuable when there are many options, because then it’s harder for one holdout to demand unreasonable compensation or make political threats – the railroad can go around them and pay slightly more for an easier takings process.

How fast should trains run?

Swiss planners run trains as fast as necessary, not as fast as possible. This plan does the opposite, first in order to establish a baseline for what can be done on a significant but not insane budget, and second because the expected frequency is high enough that hourly knots are not really feasible.

At most, some local high-speed trains could be designated as knot trains, reaching major stations on the hour or half-hour for regional train connections to inland cities. For example, such a local train could do New York-Boston in 2 hours rather than 1:40, with such additional stops as New Rochelle, Stamford, New London (at I-95, slightly north of the current stop), and Route 128 or Back Bay.

But for the most part, the regional rail connections are minor. New York and Boston are both huge cities, so a train that connects them in 1:40 is mostly an end-to-end train, beefed up by onward connections to Philadelphia, Baltimore, and Washington. Intermediate stops at New Haven and Providence supply some ridership too, much more so than any outlying regional connections like Danbury and Westerly, first because those outlying regional connections are much smaller towns and second much of the trip to those towns is at low speed so the trip time is not as convenient as on an all-high-speed route.

This does not mean Swiss planning maxims can be abandoned. Internal traffic in New England, or in Pennsylvania and South Jersey, or other such regions outside the immediate suburbs of big cities, must hew to these principles. Even big-city regional trains often have tails where half-hourly frequency is all that is justified. However, the high-speed line between Boston and New York (and Washington) specifically should run fast and rely on trips between the big cities to fill trains.

How much does it cost?

My estimate remains unchanged – maybe $7 billion in infrastructure costs, closer to $9-10 billion with rolling stock. Only one tunnel is included, under Bridgeport; everywhere else I’ve made an effort to use viaducts and commercial takings to avoid tunneling to limit costs. The 120 km of greenfield track between New Haven and Kingston include three major viaducts, crossing the Quinnipiac, Connecticut, and Thames; otherwise there are barely any environmentally or topographically sensitive areas and not many areas with delicate balance of eminent domain versus civil infrastructure.

I repeat, in case it is somehow unclear: for $7 billion in infrastructure investment, maybe $8 billion in year-of-expenditure dollars deflated to the early 2020s rather than early 2010s, trains could connect New York and Boston in 1:40. A similar project producing similar trip times between New York and Washington should cost less, my guess is around $3 billion, consisting mostly of resurrecting the old two-track B&P replacement in lieu of the current scope creep hell, building a few at-grade bypasses in Delaware and Maryland, and replacing the variable-tension catenary with constant-tension catenary.

None of this has to be expensive. Other parts of the world profitably build high-speed rail between cities of which the largest is about the size of Boston or Philadelphia rather than the smallest; Sweden is seriously thinking about high-speed trains between cities all of which combined still have fewer people than metropolitan Boston. Better things are possible, on a budget, and not just in theory – it’s demonstrated every few years when a new high-speed rail line opens in a medium-size European or Asian country.

The Subway is Probably not Why New York is a Disaster Zone

New York is the capital of the coronavirus pandemic, with around 110,000 confirmed cases and 10,000 confirmed deaths citywide, and perhaps the same number across its suburbs. There must be many reasons why this is so; one possibility that people have raised is infection from crowded subways, so far without much evidence. Two days ago, MIT economist Jeffrey Harris wrote a paper claiming that the subways did in fact seed the Covid-19 epidemic in New York, but the paper cites no evidence. Sadly, some people have been citing the paper as a serious argument, which it isn’t; the purpose of this post is to explain what is wrong with the paper.

New York and other subways

In multiple other countries, one cannot see the transit cities in the virus infection rates. In Germany the rates in the largest cities are collectively the same as in the rest of the country. In South Korea, the infection is centered on Daegu; Seoul’s density and high transit usage are compatible with an infection rate of about 700 in a city of 9.5 million, about 1.5 orders of magnitude less per capita than in most Western countries and 2.5 orders of magnitude less than in New York. In Taipei, the MRT remains crowded, with weekday ridership in February and March down by 15-16%. In Italy, car usage is high outside a handful of very large cities like Milan, and Milan’s infection rate isn’t high by the standards of the rest of Lombardy.

However, rest-of-world evidence does not mean that the New York City Subway is safe. The Taipei MRT has mandatory mask usage and very frequent cleaning. German U- and S-Bahn networks are a lot dirtier than anything I’ve seen in Asia, but much cleaner than anything I’ve seen in New York, and also have much less peak crowding than New York. New York uniquely has turnstiles requiring pushing with one’s hands or bodies, and the only other city I know of with such fare barriers is Paris, whose infection rates are far below New York’s but still high by French standards.

So the question is not whether rapid transit systems are inherently unsafe for riders, which they are not. It’s whether New York, with all of its repeated failings killing tens of workers from exposure to the virus, has an unsafe rapid transit system. Nonetheless, the answer appears to be negative: no evidence exists that the subway is leading to higher infection rates, and the paper does not introduce any.

What’s in the paper?

A lot of rhetoric and a lot of lampshade hanging about the lack of natural experiments.

But when it comes to hard evidence, the paper makes two quantitative claims. The first is in figure 3: Manhattan had both the least increase in infections in the 3/13-4/7 period, equivalent to a doubling period of 20 days whereas the other boroughs ranged between 9.5 and 14, and also the largest decrease in subway entries in the 3/2-16 period, 65% whereas the other boroughs ranged between 33% and 56%.

The second is a series of maps showing per capita infection levels by zip code, similar to the one here. The paper also overlays a partial subway map and asserts that the map shows that there is correlation of infection rates along specific subway routes, for example the 7, as people spread the disease along the line.

I will address the second claim first, regarding line-level analysis, and then the first, regarding the borough-level difference-in-differences analysis; neither is even remotely correct.

Can you see the subway on an infection map?

Here is a static version of the infection map by zip code:

This is cases for 1,000 people – note that my post about Germany looks at rates per 10,000 people, so the range in New York is consistently about an order of magnitude worse than in Germany. The map shows high rates in Eastern Queens, the North Bronx, and Staten Island, hardly places with high public transportation ridership. The rates in Manhattan and the inner parts of Brooklyn are on the low side.

There are no ribbons of red matching any subway line – there are clumps and clusters, as in Southern Brooklyn in Orthodox Jewish neighborhoods, and in Central Queens around Corona and East Elmhurst. There is imperfect but noticeable correlation with income – working-class areas have higher infection rates, perhaps because they have higher rates at which people are required to still show up to work, where they can be infected. East Asian neighborhoods have lower rates, like Flushing and environs, or to some extent Sunset Park; Asians are infected at noticeably lower rates than others in New York and perhaps in the rest of the Western world, perhaps because they took news in China more seriously, began practicing social distancing earlier, and wear masks at higher rates. There are many correlates, none of which looks like it has anything to do with using the public transportation network.

What’s more, the paper is not making any quantitative argument why the graph shows correlation with subway usage. It shows the graph with some lines depicted, often misnamed, for example the Queens Boulevard Line is called Sixth Avenue Local, leading to a discussion about higher infection rates on local trains than on express trains where in fact the F runs express in Queens. But it does not engage in any analysis of rates of subway usage or changes therein, or in infection rates. The reader is supposed to eyeball the graph and immediately agree with the author’s conclusion, where there is no reason to do so.

Manhattan confounders

The claim about Manhattan is the only real quantitative claim in the paper. Unlike the zip code analysis, the borough analysis does make some statistical argument: Manhattan had larger reduction in subway usage than the rest of the city and also a slower infection rate. However, this argument relies on an N of 2. Among the other boroughs, there is no such correlation. The argument is then purely about Manhattan vs. the rest of the city. This is incorrect for so many reasons:

  1. Manhattan is the highest-income borough, with many people who can work from home. If they’re not getting infected, it could be from not commuting as much, but just as well from not getting the virus at work as much.
  2. The Manhattan subway stops are often job centers, so the decline in ridership there reflects a citywide decline. A Manhattanite who stops taking the subway is seen as two fewer turnstile entries in Manhattan, whereas a New Yorker from the rest of the city who does the same is likely to be seen as one fewer Outer Borough entry and one fewer Manhattan entry.
  3. Many Manhattanites left the city to shelter elsewhere, as seen in trash collection data.
  4. Manhattan’s per capita subway usage is probably higher than that of the rest of the city counting discretionary trips, so 65% off the usual ridership in Manhattan may still be higher per capita than 56% off in Brooklyn or 47% in Queens. (But this is false on the level of commuting, where Manhattan, the Bronx, and Brooklyn all have 60% mode share.)

Does the paper have any value?

No.

I have heard people on Twitter claim that correlation is not causation. This argument is too generous to the paper, which has not shown any correlation at all, since the only quantitative point it makes has an N of 2 and plenty of confounders.

For comparison, my analysis of metro construction costs has an effective N of about 40, since different subway  projects in the same country tend to have similar costs with few exceptions (such as New York’s extreme-even-for-America costs), and I consider 40 to be low enough that Eric Goldwyn and I must use qualitative methods and delve deep into several case studies before we can confidently draw conclusions. The paper instead draws strong conclusions, even including detailed ones like the point the paper tries to make about local trains being more dangerous than express trains, from an N of 2; it’s irresponsible.

But what about the workers?

A large and growing number of New York City Transit workers have succumbed to the virus. The current count is close to the citywide death toll, but transportation workers are by definition all healthy enough to be working, whereas citywide (and worldwide) the dead are disproportionately old or have comorbidities like heart disease. Echoing the union’s demands for better protection, Andy Byford had unkind words to say about Governor Andrew Cuomo’s appointees in charge of the system, MTA chair Pat Foye and acting NYCT chair Sarah Feinberg.

However, this is not the same as infection among passengers. The dead include workers who are in close proximity to passengers on crowded vehicles, such as bus drivers, but also ones who are not, such as train operators, maintenance workers, and cleaners. Train cleaners have to remove contaminated trash from the platforms and vehicles without any protective equipment; NYCT not only didn’t supply workers with protective equipment, but also prohibited them from wearing masks on the job even if they’d procured them privately. Contamination at work is not the same as contamination during travel.

So, should people avoid public transportation in New York?

Absolutely not.

If the best attempt to provide evidence that riding the subway is a health hazard in a pandemic is this paper, then that by itself is evidence that there is no health hazard. This is true even given New York City Transit’s current level of dirt, though perhaps not given its pre-crisis peak crowding level. Social distancing is reducing overall travel and this is good, not necessarily because travel is hazardous, but mostly because the destination is often a crowded place with plenty of opportunity for person-to-person infection.

In preparation for going back to normal, the current level of cleanliness is not acceptable. The state should make sure people have access to masks, even if they’re ordinary ones rather than N95 ones, and mandate their usage in crowded places including the subway once they are available. It should invest far more in cleaning public spaces, including the subway, to the highest standards seen in the rich countries of Asia. It should certainly do much more to protect the workers, who face more serious hazards than the riders. But it should not discourage people who are traveling from doing so by train.

Coronavirus and Cities

There’s a meme going around the American discourse saying that the Covid-19 outbreak is proving that dense cities are bad. Most of this is bullshit from politicians, like Andrew Cuomo. But now there’s serious research on the subject, by a team at Marron led by the excellent Solly Angel. Solly’s paper looks at confirmed infection rates in American metropolitan areas as of late March and finds a significant correlation with density, but no significant correlation between deaths and density. In this post, I’m going to look at Germany. Here, big or dense cities are not disproportionately affected by the virus.

Why Germany?

Germany has pretty reliable data on infections because testing is fairly widespread, so far covering 1.6% of the population. Moreover, testing is this high throughout the country, whereas in the US, there are vast differences in testing as well as in other aspects of response by state, e.g. New York has tested 2% of state population, Louisiana 1.9%, Florida 0.8%, California and Texas 0.4%.

I also have granular data on infection rates in Germany, thanks to Zeit. The data I’m using is synchronic rather than diachronic, i.e. I’m looking at current infection rates rather than growth. Growth rates aren’t the same everywhere – in particular, they’re lower in North Rhine-Westphalia, which was the epicenter of the German outbreak weeks ago, than in southern Germany – but they’re low enough that I don’t think the situation will change in short order.

Size and density

Within Germany, there aren’t huge gradients in density between cities. More central neighborhoods have taller buildings than less central ones and higher ratios of building to courtyard, but there are no huge differences in residential built form the way there are between American cities.

For example, look at densities by neighborhood in Berlin, Hamburg, Munich, Frankfurt, Cologne, Stuttgart. There aren’t big differences in the pattern: the densest inner neighborhoods have about 15,000 people per square kilometer, and density falls to 3,000-5,000 in outer neighborhoods. Hamburg has a few areas with no residents, since they include the city’s immense port. Stuttgart’s densest districts are in the 5,000-6,000/km^2 range, but that’s because the districts are not very granular and the dense ring of inner-city neighborhoods just outside the commercial center is not congruent to district boundaries.

The upshot is that the big question about density and the risk of epidemics cannot be answered by comparing German cities to one another, but only to the surrounding rural areas. So the real question should be, are the major German cities more afflicted by the virus than the rest of the country?

Infection rates by city

As of the end of 2020-04-09, Zeit reports 118,215 confirmed coronavirus cases, which is 14.2 per 10,000 people. The six states of former East Germany, counting the entirety of Berlin and not just East Berlin, total only 12,873 cases, or 7.9 per 10,000. The Robert Koch Institute’s definitive numbers are slightly lower, but are also slightly outdated, as states sometimes take 1-2 days to report new cases. Going by Zeit data, we have the following infection rates by major city:

City Population Cases Cases/10,000
Berlin 3,644,826 4,357 12
Hamburg 1,841,179 3,518 19.1
Munich 1,471,508 4,123 28
Hanover* 1,157,624 1,389 12
Cologne 1,085,664 1,947 17.9
Frankfurt 753,056 730 9.7
Stuttgart 634,830 1,056 16.6
Dusseldorf 619,294 737 11.9
Leipzig 587,857 451 7.7
Dortmund 587,010 507 8.6
Essen 583,109 578 9.9
Bremen 569,352 425 7.5
Dresden 554,649 476 8.6
Nuremberg 518,365 733 14.1
Duisburg 498,590 525 10.5

*Zeit reports Hanover data for the entire region; the city itself only has 538,000 people

The sum total of the fifteen largest cities in Germany, with 15.1 million people, is 21,552 cases, which is 14.3 cases per 10,000 people. This is the same as in the rest of the country to within measurement error of total population, let alone to within measurement error of Covid-19 cases.

State patterns

Bavaria and Baden-Württemberg both have high confirmed case counts, averaging 23.6 and 21.7 per 10,000 people respectively. Munich’s rate is somewhat higher than the Bavarian average, but its suburbs are on a par with the city, as are some entirely rural areas all over the state. Oddly, the second and third largest cities in the state, Nuremberg and Augsburg, have lower rates – though both Fürth and the rural areas around Nuremberg and Fürth have very high rates as well.

The pattern around Stuttgart is perhaps similar to that around Nuremberg. The city’s infection rate is not much higher than the national average, but the infection rates in counties and cities around it are: Esslingen (24.8/10,000), Reutlingen (29.3), Tübingen (47.9), Böblingen (28.4), Ludwigsburg (22.9).

NRW’s rate is 13.9/10,000, i.e. essentially the same as the national average. The worst is in areas right on the Belgian border, like Heinsberg. Cologne has a noticeably higher rate, but Dusseldorf has a lower rate, and the cities of the Ruhr area a yet lower one. Don’t let the fact that these cities only have around 600,000 people each fool you – they’re major city centers, with the density and transportation network to boot. Dortmund alone has three independent subway-surface trunks, meeting in a Soviet triangle; total public transportation ridership in Dortmund across all modes is 130 million per year. Essen has two subway-surface trunks, one technically light rail and one technically a streetcar tunnel; total ridership there and in Mülheim, population 170,000, is 140 million per year.

What’s going on in Frankfurt?

There is some correlation between wealth and a high infection rate, since Bavaria and Baden-Württemberg have high rates of confirmed cases and the East German states have low ones. However, Frankfurt’s rate is fairly low as well, as are the rates of surrounding suburbs like Offenbach and Darmstadt. Frankfurt is not as rich as Munich, but like Hamburg and Stuttgart, it is fairly close, all three metro regions surpassing Ile-de-France and roughly matching London per Eurostat’s per capita market income net of rent and interest table.

In particular, it is unlikely that the greater international connections of rich cities like Munich explain why they have higher rates. Frankfurt Airport is the primary international hub in Germany, with many passengers standing in line at the terminal and coughing on other people. It would have been the easiest for imported infections to arise there rather than in the Rhineland, and yet it doesn’t have a major cluster.

Frankfurt also has extensive O&D business travel; Wikipedia puts it third after Berlin and Munich, but Frankfurt’s visitors are most likely disproportionately business travelers rather than tourists. This is important, since February and March are low season for tourism, whereas business travelers are if anything more likely to be going to Frankfurt during low season because during the summer high season they go on vacation in more interesting places.

So, is urban density more vulnerable to infectious diseases?

Probably not. Rural Germany has some areas with Korean levels of confirmed cases per capita, and some where 1% of the population and counting has tested positive. Overall, there isn’t much of an urban-rural difference – the 15 largest cities in Germany collectively have the same rate as the rest of the country, and moreover, where there are notable state-level patterns, they also hold for the states’ big cities. If Munich’s high infection rate is caused by its high rate of U- and S-Bahn usage, then the suburbs should have lower infection rates (they’re more auto-oriented) and the rest of Bavaria should be much lower; in reality, nearly the entirety of Bavaria has high rates.

The highest density in the developed world does not exist in Germany. German neighborhoods top at 15,000/km^2, with individual sections scratching 20,000; Paris tops at 40,000 in the 11th Arrondissement, New York scratches 50,000 on the Upper East Side, and Hong Kong has entire districts in the 50s. So the “density doesn’t matter” null hypothesis, while amply supported on German data, requires some extrapolation for the handful of world cities with the highest density.

Nonetheless, these are not huge caveats. German data is pretty reliable in the density range for which it exists; if cities today had the infection rates they did before modern plumbing, when a noticeable fraction of a city’s population might die in a single epidemic, it would be noticeable today. But there is no mass death, nor are urban hospitals here collapsing under the strain. On both the level of a basic sanity check and that of looking at the data, cities do not appear to be vulnerable to disease.

What does this mean?

There is no need to redesign the world to be less urban or dense in the wake of the coronavirus. Nor is there any need to let go of collective public transportation. The Rhine-Ruhr and Frankfurt are not Tokyo or Hong Kong in their public transportation usage, or even Paris or Berlin, but they have extensive urban and regional connections by train. And yet, the Heinsberg disaster zone and the high infection rate of Cologne have not been exported to the Ruhr, nor is southern Hesse particularly affected by German standards.

The virus has exposed serious issues with cleanliness. But even given Germany’s current levels of urban cleanliness, those issues are not enough to turn Berlin, Frankfurt, Hanover, or the Ruhr cities into hotspots. There is no danger to public health coming from urbanization, density, development, or public transportation. Cities should keep investing in all four in order to reduce the costs of transportation and environmental damage, even if the occasional failed politician blames the virus on density to deflect attention from his own incompetence.

Train and Bus Cleaning

Well before the coronavirus struck, I noticed how trains in Asia were cleaner than in Europe, which are for the most part cleaner than in the United States. There are overlaps: the elevated BTS in Bangkok is similar to the cleaner cities in Europe, like London (but the underground MRT is similar to Singapore and Taipei), while the Berlin U-Bahn is similar to the cleaner American cities, like maybe Washington. But for the most part, this holds. The issue of cleanliness is suddenly looking more important now in a pandemic.

How much cleaning is necessary overall?

It is unclear. Singapore has 56,000 registered cleaners and Taipei has 5,000; even assuming Taipei just refers to the city proper, Singapore has five times as many per capita. When I visited Taipei in December it was visibly messier, and Taipei City Mall felt more lived-in than comparable underpasses in Singapore, but the City Mall was not dirty, and the Taipei MRT did not feel any dirtier than the Singapore MRT. The infection rates in both countries are very low – Taiwan’s are much lower per capita nowadays, though this has other explanations, such as higher mask usage and less international travel.

How much cleaning is necessary for specific tasks?

In Singapore, SBS Transit announced increased cleaning levels on January 30th. Cleaners disinfect vehicles and stations at the following rates:

  • Trains: every day
  • Buses: every week
  • Train stations: three times a day
  • Bus stations: every two hours

In Japan, JR East’s Shinkansen trains are cleaned at Tokyo Station in 7 minutes. There are many pieces on the subject, describing how a crew of 22, comprising one cleaner per second-class car and two to three per first-class car (“green car”), sweeps an entire train so fast. Many of the tasks are not required for metro service, but passenger density is higher in metro service than in intercity service.

One advantage of regular cleaning, say once per roundtrip, is that there hasn’t been so much time for the train (or bus) to become grimy. Two hours’ dirt is easier to pick up, sweep, or water and dry than a day’s dirt.

How much does all of this cost?

Cleaner wages track local working-class wages, and differ greatly; a city with the per capita income of New York, Paris, or London will have to pay more than one with that of Berlin or Tokyo. On top of what the English-speaking middle class thinks is an appropriate wage for an unskilled worker the agency will need to pay a premium to account for the fact that fast cleaning is a difficult job even if the required education level for it isn’t high.

What is more controllable and comparable is staffing needs. The sources for JR East’s cleaning crew productivity differ, but the reasonable ones say it’s 20 trains per day. This already accounts for downtime, so if trains aren’t quite frequent enough for there to always be some train to occupy a cleaning crew, an agency is probably still capable of squeezing 20 trains per daily crew shift. If a roundtrip with turnaround time is two hours, then this means about one cleaning crew is needed per 2.5 trainsets operated in regular service, rising to about one cleaning crew per 1.8 trainsets taking weekend days into account; this can be adjusted if a train runs peak-only, since part-time shifts are common in this sector.

How can equipment be made easier to clean?

Some materials are easier to clean than others. Transit agencies should use these in future procurement, and look into emergency orders to retrofit existing trains and buses. Metal poles are easier to clean than leather straps, and hard plastic and metal seats are easier to clean than padded ones. I suspect that bench seating is easier to clean than bucket seating, since it is possible to run a mop down the entire bench.

As with schedule planning, cleaning planning should integrate operating and capital expense optimization. That is, public transportation agencies should budget for cleaning whenever they buy a bus or train or build a train station, and make decisions on layout and materials that reduce the spread of disease and increase the efficiency of cleaning as well as maintenance and other operating costs.

What else can be done?

Hand sanitizer! Taipei and Singapore both distribute it at stations, and if I remember correctly, so does Bangkok. It made me feel less grimy, especially after long walks in Taipei or any exposure to the outdoor air pollution of Bangkok.

In addition, fomite removal is a good idea, which means any of the following:

  • Barrier-free train stations, or if not then automatic fare barriers like those of Taipei or Singapore or London rather than ones requiring pushing by hand as in New York and Paris.
  • Automatic train doors, since implemented on newer trains in Berlin and I think in the rest of Europe as an emergency measure, without requiring button pushing.
  • Disposable chopsticks for pressing buttons on elevators, as in South Korea.

Do passengers care?

Yes. I’ve taken the Berlin U-Bahn a few times in the last few weeks, to view apartments and most recently (earlier today) to buy matzos from a kosher grocery store far from my neighborhood. I don’t sit anymore, not trusting even the hard metal seats at the stations, let alone the padded cloth ones on the trains. Neither do many other riders, so there’s about the usual number of standees on the trains, trying to distribute ourselves as evenly as possible inside the train and avoid loud or space-taking passengers, even as many seats stay empty.

Would I sit if this were Singapore? Probably. As of the small hours of 2020-04-08 Europe time, Singapore has 1,500 infections and Berlin has 4,000 on two thirds the population, but a big share of Singapore’s cases are imports, and the MRT is vastly cleaner than the U- and S-Bahn here. And then there’s Taiwan, with 400 cases on a population of 24 million.

Why is this not done already?

Managers love metrics, and the costs of cleaning are much easier to quantify than the benefits. Therefore, they cut cleaning whenever there is a budget crunch. Within the English-speaking world, Singapore is a standout in cleanliness, because Lee Kuan Yew decided it was important and launched a campaign to sweep public spaces. In Japan, one of the articles about the seven-minute cleaning process talks about the history of how JR East hired a new manager who has previously been at the safety division – within the company of course, this is Japanese and not American business culture – and said manager, Teruo Yabe, improved morale by taking worker suggestions and promoting line workers to supervisory roles.

I don’t want to dunk on Anglo business culture here too much – London has cleaner trains than Berlin, and is about comparable to Paris. Nor is this quite a cultural cleave between the West and Asia, since Singaporean business culture pilfers the most authoritarian aspects of Japan (long hours, face-time culture) and the Anglosphere (at-will employment, no unions to speak of) and melds them together.

My suspicion is that low standards in the US in particular come from a sense of resignation among managers who don’t really use their own systems, and view the passengers in contempt. New York has an added sense of grit, in which people romanticize the 1970s and 80s and think enduring trash on the street, high crime rates (no longer high), delayed trains, cockroaches, rats, and drivers who play Carmageddon is part of what makes one a Real New Yorker. Consider how the New York- (and London-)suffused urban discourse treats “antiseptic” as a pejorative, viewing Singapore as a less real city because it isn’t killing thousands of its people, soon to be tens of thousands, from coronavirus.

Can Western cities get better?

Absolutely! Especially New York, which has nowhere to go but up.

Most of the positive aspects of Continental Western Europe that awe Americans, like convenient urban public transportation and six weeks of paid vacation per year, are recent, rarely going farther back than the 1970s and 80s. The Swiss planning maxims I repeat to Americans as mantras were invented in the 1980s and implemented in the 1990s and 2000s.

This is even truer of East Asia – in the 1960s Japan was middle-income and the rest of East Asia was very poor; the Shinkansen opened in 1964, but the speed and efficiency standards as we know them only go back to the 300 Series, put into service in 1992. Moreover, the state of Shinkansen cleaning was not so good 15 years ago, before JR East put Yabe in charge. The high cleanliness levels are a recent success, not some ingrained feature that goes back to the 7th century and can’t possibly be replicated elsewhere.

New York needs to look at itself in the mirror now, when it is the global center of a pandemic with death toll that will most likely surpass even the highest-end estimates of those of Wuhan. Is “antiseptic” really a bad trait for a city? If cleaning is a priority, see above for what it takes to do it right. And if it isn’t, I’m sure New York will be more than happy to have another pandemic in the future.