Spatial Economics for Granular Settings
Abstract/Contents
- Abstract
- 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 where people choose from a large set of potential residence-workplace pairs, idiosyncratic choices affect equilibrium outcomes. Using both Monte Carlo simulations and event studies of 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.
Description
| Type of resource | text |
|---|---|
| Date created | September 9, 2021 |
Creators/Contributors
| Author | Dingel, Jonathan I. |
|---|---|
| Author | Tintelnot, Felix |
| Organizer of meeting | Diamond, Rebecca |
| Organizer of meeting | van Dijk, Winnie |
| Organizer of meeting | Schneider, Martin |
| Organizer of meeting | Tsivanidis, Nick |
Subjects
| Subject | commuting |
|---|---|
| Subject | granularity |
| Subject | gravity equation |
| Subject | quantitative spatial economics |
| Genre | Text |
| Genre | Working paper |
| Genre | Grey literature |
Bibliographic information
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- License
- This work is licensed under a Creative Commons Attribution 4.0 International license (CC BY).
Preferred citation
- Preferred citation
- Dingel, J. and Tintelnot, F. (2022). Spatial Economics for Granular Settings. Stanford Digital Repository. Available at https://purl.stanford.edu/vc393vm1986
Collection
SITE Conference 2021
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