More on Declining Transit Ridership

Bern Grush wrote in about my last post (on transit decline) to say:

There is a third contributor. Marchetti, in his 1994 classic: “Anthropological invariants in Travel Behavior”, wrote: “…People spend about 13% of their disposable income on traveling. The percentage is the same in Germany or Canada, now or in 1930. Within this budget, time and money are allocated between the various modes of transport available to the traveler in such a way as to maximize mean speed. The very poor man walks and makes 5 km/day, the very rich man flies and makes 500 km/day. The rest sit in between. People owning a car use it far about one hour a day (Figure 12) and travel about 50 km/day (Figure 13). People who do not have a car spend less than 13% of their disposable income, however, presumably because public services are underrated and consequently there is no possibility of spending that share of income traveling one hour per day (Figure 14).”

What this means is that there is a heretofore unexploited opportunity gap between those just wealthy enough to {own, maintain, fuel, park}  a car and those just poor enough not to (and hence do not have a car). This car-less gap would include a lot of people who would be spending far under their nominal 13%, and could afford one or more weekly substitutions of a TNC ride for a transit ride.  As TNCs grow this market will move some of the people in the gap of that bimodal distribution from transit to TNCs.

I think this explains some of Bruce Schaller’s NYC taxi-report.

Someone else also noted TNCs (Transportation Network Companies like Uber/Lyft etc.).

While I think there is something to travel budgets (and credit Zahavi before Marchetti), they are not too rigid, clearly time spent traveling ebbs and flows (Wei and Song 2016).

I also think TNCs are too small a factor at this stage of history to explain much. As I wrote before, their market share is still pretty small, even in New York City, where presumably is its largest, and the drop in transit ridership is far more than the switch to TNC trips from transit users.

On the Predictability of the Decline of Transit Ridership in the US

Noting that transit ridership is generally down in the past few years, Jarrett Walker tweeted:

“Would somebody please do a quick but defensible study on why this is happening in so many US cities? I’m tired of having only anecdotes.”



Boom times

Income since 2009 has risen. At the trough of the recession, per capita income in nominal terms was just under $40,000, as of 2015 it is about $48,000. It is up in real terms as well. Elasticity of Transit demand with respect to income suggests that as incomes rise, transit demand falls. In other words, for most people transit is an inferior good (demand falls as income rises), with an income elasticity of about -0.98 (a 1% increase in income resulted in about a 0.98% decrease in ridership) found in Hawaii (McLeod et al 1991). In another example, the Mexico City Metro is an inferior good for middle and upper income Mexicans (Crotte et al. 2009). There are many other references, and while rail is sometimes disputed as to whether it is inferior or normal, bus is generally considered inferior.


Cheap Gas

The Price of gasoline peaked in 2008 at just above $4/gallon. It is presently $2.24. Estimates of the  Elasticity of Transit demand with respect to the price of gas vary considerably, but all suggest when the price of gasoline falls, transit demand falls with it.

The price of fuel increased sharply in the run-up to the Great Recession, as shown in Figure 3.8; this certainly discouraged car travel. Interestingly, it also reduced car crashes by more than the reduction in distance traveled, which the research team attributed to worse than average drivers (especially the young) being more likely to be priced off the road. How much less travel is there because of increases in the price of gasoline? For every 100% increase in the price of gas, there is a 5% decrease in gasoline consumption (which correlates to driving in the short run, in the long run there is also a shift in vehicle fuel economy, and the elasticity is higher). From Levinson and Krizek (2015) The End of Traffic and the Future of Transport.  Figure 3.8 Source: US Energy Information Administration
  • “the elasticities of monthly transit ridership with respect to the real gasoline price are positive and inelastic, ranging from 0.08 to 0.80. ” (Wang and Skinner 1984)
  • ” Research in 2007 established that for every 10% increase in gas prices, U.S. transit demand has increased by 1.2%, a cross-elasticity of demand to gas prices (e) of 0.12. Results also showed much higher effects on U.S. light rail systems (e = 0.27 to 0.38) for heavy rail (e = 0.17) but low sensitivity for bus (e = 0.04). In Australia, the impact of gas prices on ridership has been larger (e = 0.22) because of higher gas prices (20% to 30% higher than U.S. prices).” (Currie and Phung 2008)
  • ” the cross elasticities when gas prices were less than $3 a gallon were small, with a magnitude of less than 0.05. When prices exceeded $3 a gallon, the elasticity was larger, in the range of 0.12–0.14, for the rail modes. In the summer of 2008 when prices exceeded $4 a gallon, there was considerable responsiveness with elasticities of 0.28–0.30 for city and suburban bus, and 0.37 for commuter rail. These values are similar to, or even larger than, those found during the oil crises of the 1970s and early 1980s.” (Nowak and Savage 2013)



Obviously there are other effects, in terms of service and fares, that effect ridership, but the macro-economic condition is too large an effect to dismiss out of hand. While it is hard to attribute the particular amount of the fall of transit ridership to a particular factor (econometrics can help, but in the end at best there will be a range of results, not one specific number that people will be able to rely on), it is clear that that a 50% fall in the price of gas could easily explain more than a 5% fall in transit ridership. Similarly a 10% increase in real incomes (a 20% increase in nominal incomes) could explain perhaps a 10%  fall of ridership. Elasticities are measured at the margin, and the changes in the price of fuel are far from marginal, so one can’t be too enamored of a particular elasticity effect, but the directions are robust and clear and not surprising.


Shopping vs. Shipping

Eric Roper in the Star Tribune writes “Consumers wrestle with deluge of cardboard boxes from delivery services, online shopping“.

And what about traffic from all the deliveries?

The Minnesota Department of Transportation estimates that e-commerce will be responsible for about 5 to 10 percent more freight traffic between now and 2030, said spokesman Kevin Gutknecht.

But Twin Cities residents are also making fewer trips to the store than they did in 2001, based on travel behavior data. University of Minnesota professor David Levinson said that, coupled with the logistics efficiency of professional delivery services, likely means there are fewer trips overall.

“There will be different patterns as a result,” he said. “So there might be more traffic on some streets and less traffic on other streets.”

He said further changes will accompany new delivery technologies, such as drones or robots.

“Every science fiction movie you’ve ever seen has robots doing delivery,” Levinson said.


We have seen a drop in shopping trips from 2001 to 2011 in the Twin Cities based on data from the Travel Behavior Inventory.

Time at shopping (doing the activity out-of-home, not travel) for male workers dropped from 7 min/day in 1990 to 5 min/day in 2010, and from 15 min/day for female workers to 9 min/day.
For female non-wokers it held steady at 41 min/day from 1990 – 2010. (the sample size for male non-workers in the right age category is too small to draw conclusions). These are of course daily averages, with very wide variation. The time spent per trip is of course much higher since some days there is no shopping.
Shopping trips now (2011) comprise fewer than 9% of all trips, down from 12.5% in 2000

Unfortunately, the travel behavior inventory is not (yet?) an annual survey, though the Met Council is talking about it.

It is unlikely that the number of additional delivery vehicles can be measured in traffic in the Twin Cities (yet), they are just too few. Maybe a residential street goes from 4 to 6 delivery trucks per day, but still has hundreds of car trips. So think about UPS. If UPS is smart, it still only sends one truck down a street per day, it just has more deliveries on that street. So there are more trucks dispatched, and more total deliveries, but the number of trucks on most streets is unchanged. Of course Amazon might now have its own truck, but that is still only 1 truck per street per day, maybe 2 (I don’t think Amazon Now is a big deal yet).
So there are fewer personal shopping trips, more truck trips, but this should net out as fewer total trips, since each personal trips is less efficient than a logistics supply chain.

Rules for Researchers

Below are a selected list of rules that I have accumulated over time about academic production and output, which I impose upon students, but have never before put in one place.

  1. Papers should be focused and to the point, and not begin with trite observations like “Congestion is a problem the world over.” Usually you can delete your opening paragraph if it begins like that, and the reader is no worse off.
  2. Strunk and White correctly say “Omit needless words.” Be merciless with the delete key. If you feel bad about that, cut and paste your precious words into a new document call “__Cuts.tex .” You can later bring them back or use them elsewhere. Always ask why each word is in the document. If you cannot give a good answer, it is deletable.
  3. Get an editor.
  4. You should use a version control system for writing, so you can access earlier drafts as needed. Some software has this built in now.
  5. The Abstract should not say the same thing as the Introduction or the Conclusion.
  6. The Introduction should not say the same thing as the Conclusion.
  7. A minimum standard for a good paper is transparency and replicability. Can the reader understand what you did, and repeat it, and get the same answer.
  8. Keep the equivalent of a lab notebook. So for instance, when doing statistics, record each regression and variable definition change.
  9. Exploratory analysis is useful, it helps you understand the data. It is important to correlate and to graph your variables.
  10. Formulate clear hypotheses based on your best understanding of how the universe works. If your data do not corroborate your hypotheses, you might consider having alternative hypotheses. Nevertheless, do not discard your original hypotheses just because they were not corroborated.
  11. Do not p-hack (or engage in other disreputable methods) intentionally or unintentionally. Getting statistically non-significant results is fine, and avoiding this is not worth losing your ethics for, and in any case adds to human knowledge. Maybe not everything gives you cancer. It may make publication more difficult, which is unfortunate. In the end, replicability is critical.
  12. If you must report a (reduced) model with only significant results to satisfy a reviewer, also report the model with the variables that you tested that were insignificant (the complete model).
  13. Every document (dissertation, thesis, report, paper) with more than a handful of variables shall have a table of nomenclature which includes each variable and its definition.
  14. Each variable shall have one, and only one, definition per document.
  15. Each defined term in the document shall be represented by one and only one variable.
  16. Lowercase and uppercase versions of the same letter should be logically related. For instance, use lowercase letters to define the PDF (probability distribution function) or individual instance, and uppercase letters the CDF (cumulative distribution function) or population, so when you sum:  i=1 to I, k=1 to K, etc.
  17. All variables shall be a single letter or symbol. Double or triple letter variables can be confused with multiplication. If you have more than 52 symbols in your paper (26 letters for both lower and upper case), consider (a) there are too many, and (b) using Greek or Hebrew characters.
  18. Use subscripts liberally to differentiate things that, for instance, are of a class but measured differently, or computed with different assumptions.
  19. All equations shall have all of their variables defined.
  20. All maps shall have legends and scales and north shall be on top (unless stated otherwise).
  21. All units shall be metric (SI) units. Imperial units may be listed as alternates.
  22. All graphs shall have their axes labeled, clearly, with units as appropriate.
  23. Legends and scales shall be as consistent as possible between graphics, so that they can be compared.
  24. Pseudo-3D graphs are morally wrong, and aim to deceive and obfuscate. Real 3D graphs with 3-axes are fine if you can make them readable on a static 2D page.
  25. The use of Microsoft Word is forbidden. Consider using LaTeX instead. Stick to the same template for your writing in as many documents as possible, this will ease compilation and mixing and matching for future research projects. Many reports to sponsors become theses and journal articles, it is convenient to be able to reuse the text with a minimum of reformatting.
  26. Use a standard reference database, like BibDesk for BibTeX. Get your references from Google Scholar or similar to maintain naming conventions for references.
  27. Use the same template for all your presentations, and use consistent fonts and styles, so you can mix and match slides with a minimum of grief. Beamer or Keynote are recommended.
  28. When you submit a paper to a journal, put an event in your calendar to email the editor after 90 days to remind them to get the reviews back to you. Journals can be black holes.
  29. The “reviewer is always right” even when they are wrong. You need to either suck it up and be obsequious and acknowledge their points, even if you don’t agree with them, or send to another journal. Sending to another journal of course restarts the review clock.
  30. Papers are almost never accepted the first round. This is a sad fact and does not reflect on you so much as on the academic process and the belief that nothing is perfect.
  31. Good papers are often rejected. Bad papers are sometimes accepted.
  32. Highly ranked journals do not necessarily have better papers than less highly ranked journals.
  33. Impact factors and H-indices have embedded scale biases favoring large journals with lots of papers (given the non-normal distribution of paper citation). They are mostly nonsense at the level of the journal.
  34. In the end, science favors truth, so flashy but wrong claims will eventually be rebutted. In the meantime those wrong claims will garner many citations. This does not justify knowingly being wrong.
  35. Articles in hot, controversial areas garner more citations immediately than in new areas. In the long run it is better to pioneer a new important field than to be the second or third or twentieth entrant in a crowded one.
  36. Review papers garner lots of citations, and deservedly so. They are not less important for scientific progress than the papers they review, they help organize the knowledge to date, identify gaps, holes, areas of consensus, and areas of dispute.
  37. If your paper is rejected, submit it somewhere else quickly, unless it genuinely was problematic. Papers under review are better than papers sitting on your computer.
  38. Make an open access version of your publication available (either publish in an open access journal or place a copy of the paper in an open archive (University conservancy, arXiv, RePEc, etc). This increases your citations, but more importantly increases the free flow of knowledge.
  39. Make your data (and code) publicly available in an open data archive, unless you cannot because of privacy or ownership considerations. This includes documenting the data properly  with metadata so that someone else (or you in a year) can properly use it.
  40. Have your own website with your own domain, that you own, that follows you across jobs. Do not rely on proprietary sites. Do not rely on your employer/university. This website should link to all your products (papers, projects, code, models, data sets, etc.), which are open access and on the web of course. I like WordPress, but there are others.
  41. Along with information management, time management is critical. In research, few deadlines are externally imposed. A fixed paper submission deadline may be the key to success of conferences like the Transportation Research Board, the whole community organizes its workflow to satisfy the hard August 1 deadline.  Unfortunately, many people require urgency before they act. Getting a paper out the door is rarely urgent in the absence of deadlines, and thus many papers become non-publications. The strategies in Getting Things Done are useful. This, more than intelligence or creativity or even hard work is the key to success.

Spontaneous Access: Reflexions on Designing Cities and Transport on sale for $0.99 at Amazon Kindle TODAY only

Spontaneous Access: Reflexions on Designing Cities and Transport on sale for $0.99 at Amazon Kindle TODAY (March 9, 2017) only.

Spontaneous Access: Reflexions on Designing Cities and Transport. By David M. Levinson

Table of Contents

  1. The City Spontaneous
  2. The 60-Year Line
  3. Community without dendricity
  4. The pint-of-milk test
  5. The timeless way of building networks
  6. Axioms about roads
  7. Garden streets
  8. Vitality
  9. An archipelago of walkability
  10. Filling in
  11. Leapin’ frogs
  12. The reorganization of road function
  13. Beyond the plan view
  14. Interfaces of freedom
  15. Instruments of control
  16. Shared space
  17. Winter is coming
  18. Diversity as insurance
  19. Differentiate city and country
  20. Don’t confuse the place for the time
  21. Great Britain doesn’t have an Americans with Disabilities Act
  22. Designs serve varied and sometimes conflicting interests
  23. A vision of visions
  24. A faster horse
  25. The Ant and the Grasshopper
  26. Deconstructing Busytown
  27. Spontaneity in a can, spontaneity in a plan
  28. Building the city spontaneous
  29. Framing regional development
  30. First do no harm

There are several themes in the book: 

Cities and their networks operate on multiple timescales simultaneously. Traffic lights change by the second, rights-of-way last millennia. Cities see massive daily flows of people in and out. The core, timeless, enduring elements contrast with the faddish ephemera that too much effort is focused on. The future is emerging, but determining what we are looking forward to will be enduring or ephemeral should be the critical focus of anyone involved with transport and city design.

This book does not shy away from the normative and prescriptive. In this it differs from much academic work, including my own, which tends to the positive and descriptive. Principles are laid out, which I believe to be true and correct, many of which are not scientific in the way they are framed. They of course may lead to testable hypotheses, but they are also value-based.

The idea of the ‘spontaneous city,’ one that serves needs and wants in real-time, is a theme running through both the title and the text. What conditions encourage people to take advantage of their city (and therefore make it stronger)? What conditions worsen life for the users of the city?

The emergence of new transport technologies gives us a chance to restore and correct, to right what is wrong with the places we live. From the railroad and electric streetcar creating separation between places where people lived and where they worked, to the elevator enabling high rise construction, to the motorcar which put suburbanization into over-drive, all significant transport innovations reshape cities. The new autonomous vehicle, the new electric vehicle, the new shared vehicle, the vehicle form, shape, and size are a transformation of similar scale and scope. These changes will create opportunities over the coming decades, which we can seize or reject.

This book is about how cities do work, how cities can work, and how cities should work. In part it is about traditional fields of planning and engineering, but takes a much broader concept of design principles than those fields usually do. This is because it is also about evolution and it is about opportunism. The world is changing fast. We can make it a more humane place than it has ever been, or we can allow it to devolve into a more brutish environment, where we remain a victim of our collectively built environments, rather than their master.

When the book speaks of ‘cities’ it really means the entire metropolitan ‘urban system,’ not just the historic core city (or the central business district). Downtown is but a part of the city, and the central city in many metropolises is not even a plurality of residents.

Much of this book includes complaint, and it may feel like shouting into the wind. But every complaint is about a design failure, either with intention or by accident, that degrades experience for everyone, or degrades the experience of some for the benefit of others. Life is comprised of tradeoffs, but not all tradeoffs are made at the appropriate rate of exchange. Both cities and their transport networks are the product of thoughtful human actions and unconscious emergent processes, where systematic behavior drives the underlying logic of designs.

The optimal design of transport networks to serve the goal of spontaneous access cannot be determined in the absence of knowledge about the actual development pattern. The optimal development pattern cannot be known without regards to the plan of the network. Discovering the right combinations of networks, land use, and other urban features is what makes cities successful. The measure of their success is their population, their wealth, their happiness.

But even more importantly, the optimal transport network for the technology of one era is not necessarily the optimal network of the future, and the same is true for development.

Much of Spontaneous Access is drawn from my blog, or, although it has been significantly edited and reorganized from posts that may have appeared there. In that sense, it is a younger sibling to the recent (2015) book The End of Traffic and the Future of Transport with Kevin Krizek. It is a collection of reflexions (a somewhat archaic British way of spelling “reflections”), short essays that collectively give insight into today’s design problems and some possible solutions.

With Hyperloop, India eyes an unrealistic future | Quartz


Ananya Bhattacharya at Quartz India writes: “With Hyperloop, India eyes an unrealistic future.” I remain puzzled by the popularity of Hyperloop. I am quoted.

“I don’t think it’s (Hyperloop) practical any time soon,” David Levinson, a professor of civil engineering at the […] University of Minnesota, said. “Tunneling remains expensive. We have no idea how ordinary humans will respond to be being in windowless containers with that level of acceleration and deceleration. Or what happens if there is a malfunction or an attack on the tubes. It might be more appropriate for freight, but again, it is yet to be tested.”

More than 54% of India’s land is vulnerable to earthquakes currently, and swathes of India, including in states such as Delhi, Maharashtra, Jammu & Kashmir, and Uttarakhand are among the “very severe intensity” or “severe intensity” zones.

“2021 is probably a bit short for India but realistic for places like Saudi Arabia or places with wide open places,” Hugh Hunt, a senior lecturer in mechanics in the department of engineering at Cambridge University, and a Fellow of Trinity College, said. Unlike India, the proportion of uninhabited or uncultivable land in the Arabian Gulf countries is often much higher.

Meanwhile, there could be another concern. For decades, the process of land acquisition has stumbled in India, with a large number of projects stuck due to this. India’s bullet train plan is an example. Since taking power, the Modi government has tried, unsuccessfully, to amend the laws to ease this process.

“Focusing on fantasy technologies instead of real technologies is a distraction if you want to solve actual problems,” Levinson said.

Real network technologies include the auto/truck/highway system (which will be more productive with automation), rail (in close, high density corridors), including High Speed Rail in places, airlines and airports (for longer distance markets), and seaports (primarily for international shipping). I can’t say what should be used where since I have never been to India, but I think India should be smart enough to figure this out.

By all means if some private group is wealthy enough to  build and test Hyperloop somewhere they should do so, and IF it works technically, figure out whether it can be made to work financially. But until that actually happens, talking about and building Hyperloop networks is a chimera.


MPR March 7, 2017 at 9 am … Talking about Infrastructure

I will be on Minnesota Public Radio’s MPR News with Kerri Miller program Tuesday March 7, 2017 at 9 am CT regarding President Trump’s plans to beef up spending on infrastructure – what that might look like, how it might work, what the spending might focus on, etc.


Update:  You can find the podcast of the show here.

Transcript of “The Economics for and Against Trump’s Infrastructure Plan”

In late November, I appeared on NPR Here and Now  discussing “The Economics for and Against Trump’s Infrastructure Plan

I thought it went well, so I got a transcript made for another project, so here it is for the record. Speaker 1 is the host Robin Young. It’s rough, because it is spoken rather than written language.




00:00 Speaker 1: One of President Elect Donald Trump’s plans for job creation is a massive infrastructure project. The country’s roads and bridges are in disrepair. The Obama administration also pushed infrastructure but ran into spending road blocks. Trump’s plan will look beyond government dollars to public private partnerships, tax breaks to encourage companies to get involved, and borrowing an idea long favored by Democrats and candidate Hillary Clinton, he would work to create an infrastructure bank. Congress would put in seed money, companies would match it. Now Trump advisors say his proposals could inject around $1 trillion dollars over 10 years into building. Democrats say they want to work with Trump to improve the country’s infrastructure. Some Republicans worry about the price tag. David Levinson is faculty at the University of Minnesota, Department of Civil, Environmental and Geoengineering. He’s also the author of the book, “The End of Traffic and the Future of Transport,” and writes the blog Transport Us. He joins us now. Welcome.

00:53 David Levinson: Thank you.

00:55 S1: Let’s start with what’s got a lot of people thinking, Donald Trump’s use of a public private partnership. What might that mean?

01:02 DL: It’s used today to mean a number of different ways of providing infrastructure ranging from something as simple as what’s called design-build so that a single firm is responsible for both designing the bridge and building it, which speeds up the process and ensures that there’s a single point of responsibility, so you don’t have one company or one agency doing the design and the second agency doing the construction and then people complain because there’s some miscommunication. It can also be design, build, operate and maintain. And then the firm that builds the bridge is responsible for operating and maintaining it over a long period of time, and so they don’t build it cheap and then let it fail early because they’re gonna pay for that cost if they’re responsible for maintaining it. And presumably that leads to higher quality of infrastructure and lower lifetime costs.

01:50 S1: Does that mean, for instance, that a company might build a highway but also own the tolls?

01:55 DL: There could be a toll funded project, but it doesn’t have to be. Tolls don’t always cover the costs of any given infrastructure project. They do in some cases, but as you can see looking at the United States most roads are not tolled, most bridges are not tolled. And putting a single toll bridge out there might not work from an economic perspective if there’s nearby alternatives, but it still may be worthwhile to have the infrastructure. So the state might step in and instead of paying for the road itself and maintaining itself, it pays the firm to do this and it pays it some amount of money each year, and the firm is responsible for maintaining it to a certain performance standard.

02:31 S1: And so what are the arguments for and against this private involvement in America’s infrastructure?

02:38 DL: Well, the argument in favor of it would be that if the firm is responsible for financing and gets paid back over time, that might help a cash-strapped local government or state government provide infrastructure that it otherwise couldn’t provide without borrowing the money. And borrowing is often difficult for local and state governments because there’s rules and regulations that different states have. On the downside there’s a question of who bears the risk? The negotiation of this is not just negotiation over how much money does somebody get to be paid, but what happens if the tolls that are expected don’t come in? What happens if the demand that’s expected on the road doesn’t materialize? How do you deal with that? And that’s one of the major issues in public private partnerships.

03:16 S1: We’re reading that in some of the current projects or past projects, one might have gone bankrupt, others just weren’t finished, so that feeling of accountability gets a little bit lost if it’s a private company.

03:27 DL: Right. It depends very much on how it’s organized. It doesn’t have to be a new project. You can have a sale of an existing asset as well. A few years back, Indiana sold the Indiana Tollway and got a large upfront set of money which then it used to build other infrastructure. And in exchange, the firm that purchased the toll road collected the tolls over a long period of time. It turned out they did this just before the Great Recession. Demand turned down and it especially turned down on that road because they raised the tolls more on that road because they’re a private firm and were trying to collect more money. And as a result they had to go through bankruptcy, essentially. The road didn’t disappear. It continued to provide service and that’s one of the great things about infrastructure. Even if the firm goes bankrupt, the asset is still there. It’s not like they can pick up the road and move it to Australia or something. A lot of ’em haven’t worked out financially in the last decade and a half in the US. Doesn’t mean they can’t, but it means that it’s a difficult proposition.

04:23 S1: But what about the fact that Trump’s plan calls for a huge tax credit for private investors? The hope there is that it’ll bring more investors, but economists who looked at this said you need something like $137 billion in federal tax breaks to attract a trillion in infrastructure finance.

04:40 DL: Yeah, the proposal that was put out by Trump’s team before the election is a bit of a shell game because the assumption is that the federal government will provide these tax credits to these private companies who will then raise money and build infrastructure, and that the tax credits will presumably… The claim is they’ll be offset by greater revenue that comes into the federal treasury because of income tax, because there’s workers now who are working on it who would otherwise wouldn’t have been. And that’s a little bit disingenuous in a full employment economy because these resources would otherwise be used. The workers would be working on something. If they weren’t working on this road, they’d be working on a different road. There would be profits and there would be income taxes that would be coming into the federal treasury anyway that aren’t going to be if they’re reallocated to this. Now, if they were otherwise unemployed, so if we were in the depths of a recession and then you’re employing them and otherwise they’d be idle, then something like this would make a little bit more sense because you then would be getting revenue that otherwise wouldn’t happen. But doing a stimulus when the unemployment rate is 4.9% is very different than doing a stimulus when the unemployment rate is 11%.

05:45 S1: Well, explain that to us because there’s a huge disconnect there. We know that this recent election was propelled by people who were crying out that their industry had left the Rust Belt and their coal mines were closing. And the promise of a Donald Trump was that he would people put these people to work. But then we’ve also recently reported on the fact that there really aren’t enough workers right now to do huge infrastructure projects. Is that because… We were reminded back in the 1930s with the Works Progress Administration when thousands of largely men were hired to go out and build dams and things. They were hands-on digging ditches, and that’s really not the work that’s available in construction today.

06:30 DL: Right. So when we see the grainy black and white films from the 1930s, we see thousands and thousands of people with hand shovels digging ditches and leveling roads, and doing things like that. And today road construction and all construction is much more capital-intensive. It uses big equipment to do things, and so where previously it might’ve taken a hundred men with a shovel, now it takes one construction worker with a large piece of construction equipment, a bulldozer or a backhoe or something like that to move as much dirt. Our mental model of building infrastructure which is formed from the 1930s in the Great Depression doesn’t apply in a world where we have a lot of automation, and we still have a lot fewer people required to build the same length of road as we used to.

07:16 DL: Another important difference is where does the unemployment occur? The areas of need of new infrastructure are in larger cities and in areas that are doing economically very well, and the areas of excess labor are in other parts of the country, do those people wanna relocate? It might not be cost-effective personally for them to do that because living in the big city is a lot more expensive than living in a rural area. There’s also skills required. Construction is not an unskilled work. It might not require a college degree, but there’s a lot of skill that’s required in building a road properly and that needs to be understood by the workers who have gained experience over time building roads. And the people who build roads are different than the people who build railroads, are different than the people who build storm sewers and water pipelines.

07:58 S1: As someone who’s looked at this, what would be the best infrastructure plan to create the jobs for the people in this country who desperately need them right now?

08:08 DL: I think you need to separate out two things. One is what is the best plan to create new jobs for people in the country, and the second is what is the best infrastructure plan because those don’t necessarily align. And if we think of infrastructure as a jobs program, we’re gonna build things that are expensive but we’re not gonna think about the long-term effects of it. Because infrastructure, sure, there’s a large upfront cost of building it, but 10 years from now you have to resurface it and 20 years from now you need to rebuild the road, and 50 years from now you need to rebuild the bridges, who’s gonna pay for those costs? That needs to be considered when you’re making a decision as to whether something’s worth doing. As a private investor, if you are looking at remodeling your house and the construction firm said to you, “We’ll use 20 workers,” and another came to you and said, “We’ll use 10 workers,” you’d probably go with the firm that used 10 workers ’cause their cost would be lower. And if we are thinking about this is a jobs program, we’re gonna maximize the inefficiency of the construction rather than trying to make it as efficient as possible.

09:03 DL: So we might wanna think about jobs programs in other fields, things that require a lot of person-to-person interaction. I can think of various types of service jobs which don’t have this long-term maintenance cost and these long-term reconstruction obligations that are gonna be put on us by building infrastructure which is, from a transportation perspective, for which we wanna be as efficient as possible so that we can move as many people as quickly and as safely as possible.

09:28 S1: It’s David Levinson, faculty at the University of Minnesota, Department of Civil and Environmental and Geoengineering and author of the book, “The End of Traffic and the Future of Transport.” David, thank you.

09:38 DL: Thank you.

The Transportist: February 2017

Welcome to the fifth issue of The Transportist. As always you can follow along at the blog or on Twitter.

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