Ed Glaeser, what have you started?

First, you post a series of articles over with the New York Times on how the math for High Speed Rail doesn’t add up.   The poor assumptions force guys like Ryan Avent to rip these articles to shreds.  Any back of the envelope calculation will involve a lot of assumptions, but the kinds of assumptions Glaeser makes defy credulity.

Now, you’ve inspired copycats.   Avent again:

Today, the Washington Post’s lame excuse for an economics columnist, Robert Samuelson, used numbers from Glaeser’s analysis in writing an extremely regrettable piece arguing that investments in high-speed rail are misguided. But this is no honest entry into the discussion of how best to invest in transportation infrastructure. It’s a hack job, plain and simple.

From an urbanism perspective, the most egregious error Samuelson makes (as Avent points out) is his treatment of American space and density.

Samuleson:

What works in Europe and Asia won’t in the United States. Even abroad, passenger trains are subsidized. But the subsidies are more justifiable because geography and energy policies differ.

Densities are much higher, and high densities favor rail with direct connections between heavily populated city centers and business districts. In Japan, density is 880 people per square mile; it’s 653 in Britain, 611 in Germany and 259 in France. By contrast, plentiful land in the United States has led to suburbanized homes, offices and factories. Density is 86 people per square mile. Trains can’t pick up most people where they live and work and take them to where they want to go. Cars can.

Of course, stating that passenger rail is ‘subsidized’ without putting that into the context of all transportation subsidies is somewhat useless.  But that error can be forgiven in a persuasive piece.  The density argument cannot.

The US is a big place, but we’ve got a whole bunch of nothing out in the western portions of the country.  In fact, most of our population has clustered in several key mega-regions that all contain the proper distances and densities for high speed rail travel.   No one’s arguing for high speed trains between San Diego and Portland, Maine – but that’s exactly what Samuelson’s average density figure would imply.

(I can’t recall where I saw this, but blog comments in reaction to this piece somewhere likened Samuelson to the tale of the statistician who drowned trying to wade across the river.  Shouldn’t have been a problem, as the average depth was only 3 feet…)

Thankfully, Ryan Avent’s done a masterful job at debunking the faulty assumptions in these articles (as have several others).  Now, Yonah Freemark has put together a competing back of the envelope plan to rival Glaeser’s.  Yonah’s plan is available on Infrastructurist, and unsurprisingly reaches a different conclusion:

That may even to have been Glaeser’s intent in writing the series. The problem is that–through a sorry mix of omission, oversimplification, distortion, and deficiency–his calculations bear no relation the effects he is claiming to consider. So it’s important to show that “the numbers” do not at all undermine the viability of HSR in the US, even outside the northeast and California. In fact, the tend to support it.

By populating his model with a better set of assumptions, we hope to show how badly the economist missed the mark even on his handpicked example of an HSR link between Houston and Dallas. In reality, a well-designed high speed intercity rail project between the two largest cities in Lone Star State would likely produce a net economic benefit–nothing at all like the white elephant Glaeser conjures up. In this more comprehensive model that takes into account trivialities like regional population growth and a reality-based route, the total annual benefits $840 million compared with construction and maintenance costs of $810 million. Which is to say, our numbers show that HSR pays for itself rather handily.

Yonah’s analysis is worth a read.  It’s still a simplistic back of the envelope calculation, but based on a far more realistic set of assumptions.  Thank you for interjecting some sanity into the discussion.