Discussion/Comments by

Andy Haughwout

FRBNY Research

The views expressed here are those of the author, and do not necessarily represent those of the Federal Reserve Bank of New York or the Federal Reserve System.

SpeedBy Victor Couture, Gilles Duranton and Matt Turner

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Questions to be addressed and relevance

What does the supply curve for passenger auto travel look like?

Are cities equally productive in producing passenger auto travel?

What are the determinants of speed/productivity in producing passenger auto travel?

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Contributions of the Paper

Probably the most thorough work on disentangling (aggregate) supply and demand Literature review implies that no one else has recognized or thought

about this issue. Probably too strong a statement But few have thought about it in precisely this way

Variety of estimation methods Similar/robust results on key parameters

City-level approach allows for rankings of speed Interesting reading Allows comparative statements across cities and potential welfare

analysis

Good framework for exploring determinants of speed/transportation productivity

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Overview

An essentially empirical exercise in three parts:

1. Estimate the travel supply curve in each city using data on actual trips

2. Compare and analyze the determinants of city-level transportation productivity

3. What is cost of low transportation productivity? The welfare analysis

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Comments

Very clean set of questions addressed Well written paperSo it is easy to see what is going on

A bit harder to see the motivation Intro emphasizes the size of the transportation sector

$200 bln in road investment 18% of household budget devoted to road travel 72 minutes driving (per day?)

Is this paper in transportation economics or urban economics? I think the connections among speed, city size and form are more

interesting

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Comments (2)

How should we think about urban form?Pop & emp centralization measures added as robustness check Aren’t these fundamental, and endogenous unlike HDD and CDD?

Ie, “fast cities” get bigger and more spread out?- BTW measure [% jobs w/in 20km of centroid] somewhat

arbitrary – why not multiple nodes? “results are strongly suggestive that more compact and centralized cities are slower”. Not “slower cities are more compact and centralized”?

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Comments and Suggestions (3)

How can some cities persistently outperform others on an important dimension of welfare?How can Grand Rapids be 20-30% faster than Miami for years at a time?

1. Speed isn’t very important Authors argue against this

2. Imperfect mobility, but people depart Miami. But faster cities are declining cities – less congested?

- Or see authors’ earlier work– newer infrastructure?

3. Unobserved pricing In standard urban models, land prices would reflect

accessibility differences

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Comments and Suggestions (4)

What would happen if speed in Chicago were to rise 50%? Pure benefit to drivers?

Some micro-level reasoning/theory/modeling would help to disentangle these

Minor: are all trips in the data intra-MSA trips? Minor: are distances measured as actual driving

distance, shortest path or “as the crow flies”? Minor: Does the physical infrastructure measure

account for quality? Minor: Can we really totally ignore other modes, in

all MSAs?

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Conclusion

Interesting paper – more so than the authors let on Provocative approach and intuitive results so far Second half raises many interesting questions, New versions or future work could go in many

directions

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END