Spatial Economics for Granular Settings
We examine the application of quantitative spatial models to the growing body of fine spatial data used to study economic outcomes for regions, cities, and neighborhoods. In "granular" settings, the number of location pairs rivals the number of people. Using both Monte Carlo simulations and neighborhood employment booms, we demonstrate that calibration procedures that equate observed shares and modeled probabilities perform very poorly in such settings. We introduce a general-equilibrium model of a granular spatial economy. Applying this model to Amazon's proposed HQ2 in New York City reveals that the project's predicted consequences for most neighborhoods are small relative to the idiosyncratic component of individual decisions in this setting. We propose a convenient approximation for researchers to quantify the "granular uncertainty" accompanying their counterfactual predictions.
Professor Jonathan Dingel is an Associate Professor of Economics at the University of Chicago Booth School of Business, a Faculty Research Fellow at the National Bureau of Economic Research, and a Research Fellow at the Centre for Economic Policy Research. His research focuses on spatial variation in the amount and nature of economic activity across neighborhoods, cities, and countries. In recent work, he has studied the scope for telecommuting, using satellite images to define cities, and how the global climate affects agricultural trade. At Booth, Professor Dingel teaches Managing the Firm in the Global Economy. He received the “2014 World Trade Organization Essay Award” for Young Economists. He earned his Ph.D. in economics from Columbia University in 2014.