Working Paper: CEPR ID: DP14819
Authors: Jonathan Dingel; Felix Tintelnot
Abstract: We introduce a general-equilibrium model of a "granular" spatial economy populated by a finite number of people. Our quantitative model is designed for application to the growing body of fine spatial data used to study economic outcomes for regions, cities, and neighborhoods. Conventional approaches invoking the law of large numbers are ill-suited for such empirical settings. We evaluate quantitative spatial models' out-of-sample predictions using event studies of large office openings in New York City. Our granular framework improves upon the conventional continuum-of-individuals model, which perfectly fits the pre-event data but produces predictions uncorrelated with the observed changes in commuting flows.
Keywords: commuting; granularity; gravity equation; quantitative spatial economics
JEL Codes: C25; F16; R1; R13; R23
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| granular model (E10) | changes in commuting flows (R41) |
| granular model (E10) | economic outcomes (F61) |
| commuting elasticities (R41) | workplace productivities (J29) |
| granular features modeling (C52) | estimates of commuting elasticities (R41) |
| granular features modeling (C52) | parameter values (D46) |
| granular model predictions (C52) | observed changes in commuting patterns (R41) |
| granular model predictions (C52) | land prices (R31) |
| commuting costs (R48) | individual location choices (R30) |
| individual location choices (R30) | wages (J31) |
| individual location choices (R30) | rents (R21) |