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Transportation and the Spatial Distribution of Economic Activity

Paper Session

Tuesday, Jan. 5, 2021 3:45 PM - 5:45 PM (EST)

Hosted By: American Economic Association
  • Chair: James Poterba, Massachusetts Institute of Technology and NBER

Does America Invest Too Little in Road Maintenance?

Edward Glaeser
,
Harvard University and NBER
Gabriel Kreindler
,
Harvard University
Lindsey Currier
,
Harvard University

Abstract

Does America invest too little in maintaining its infrastructure? Vertical acceleration data from millions of Uber drives allows us to measure the roughness of roads across American cities and neighborhoods. This high frequency data correlates well with low frequency International Roughness Index data provided by the Department of Transportation, and it can be used to measure weekly road depreciation and to see the impact of discrete events like road repaving. We use this data to establish stylized facts, such as the correlation between road smoothness, income and race across neighborhoods. We also measure the impact of road roughness on free flow speeds and gasoline usage. Comparing before and after road paving provides us with plausible causal estimates of these parameters that we then use to calibrate an optimal repaving model. We then apply this model to the city of Chicago and compare our implications for optimal repaving to the actual repaving schedule.

The Welfare Effects of Transportation Infrastructure Improvements

Treb Allen
,
Dartmouth College and NBER
Costas Arkolakis
,
Yale University and NBER

Abstract

Each year in the U.S., hundreds of billions of dollars are spent on transportation infrastructure and billions of hours are lost in traffic. We incorporate traffic congestion into a quantitative general equilibrium spatial framework and apply it to evaluate the welfare impact of transportation infrastructure improvements. Our approach yields analytical expressions for transportation costs between any two locations, the traffic along each link of the transportation network, and the equilibrium distribution of economic activity across the economy, each as a function of the underlying quality of infrastructure and the strength of traffic congestion. We characterize the properties of such an equilibrium and show how the framework can be combined with traffic data to evaluate the impact of improving any segment of the infrastructure network. Applying our framework to both the U.S. highway network and the Seattle road network, we find highly variable returns to investment across different links in the respective transportation networks, highlighting the importance of well-targeted infrastructure investment.

Quantifying Consumption Access Within Cities Using Smartphone Data

Stephen James Redding
,
Princeton University and NBER
Kentaro Nakajima
,
Hitotsubashi University
Yuhei Miyauchi
,
Boston University

Abstract

“What determines the spatial distribution of economic activity?” is one of the classic questions in economics. Existing approaches emphasize agents’ production and residence decisions. Canonical theoretical models of agglomeration focus on production externalities (e.g. knowledge spillovers). Recent quantitative urban models concentrate on the separation of workplace and residence and bilateral patterns of commuting flows. However, location decisions involve more than simply access to employment opportunities. A growing popular
literature emphasizes the ``consumer city'' and access to consumption opportunities, including social networks, coffee shops, bars, restaurants, theaters, music venues etc. We provide new theory and evidence on the role of access to consumption opportunities in understanding the agglomeration of economic activity within cities. From a theoretical perspective, we develop a quantitative urban model that incorporates both commuting trips and consumption trips, and use the structure of the model to decompose variation in land rents into the contributions of both workplace and consumption access. From an empirical point view, we make use of a novel dataset for Tokyo that combines smartphone location data every five minutes of the day, building land use data, and census data on economic activity with individual establishments. We use these data to measure commuting trips and different types of consumption trips and to structurally estimate the parameters of the model. We show that changing consumption access plays an important role in shaping the impact of the opening of a new subway line on the spatial distribution of economic activity.
Discussant(s)
Clifford Winston
,
Brookings Institution
Caitlin Gorback
,
National Bureau of Economic Research
Rebecca Diamond
,
Stanford University
JEL Classifications
  • R4 - Transportation Economics
  • O1 - Economic Development