Title

Heterogeneity in the effect of federal spending on local crime: Evidence from causal forests

Publication Date

6-9-2020

Source

Regional Science and Urban Economics 78(September 2019)

Abstract

Federal place-based policy could improve efficiency if it targets areas with large amenity or agglomeration externalities. We begin by showing that positive shocks to federal spending in a county and their associated economic stimulus substantially decrease crime, an important amenity. We then employ two machine learning algorithms—causal trees and causal forests—to conduct a data-driven search for heterogeneity in this effect. The effect is larger in below-median income counties, and the difference is economically and statistically significant. This heterogeneity likely improves the efficiency of the many place-based policies that target such areas.

DOI

10.1016/j.regsciurbeco.2019.103463

Publisher

Elsevier

Subject Areas

ECONOMIC DEVELOPMENT

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Citation

Hoffman, Ian and Evan Mast. 2019. "Heterogeneity in the effect of federal spending on local crime: Evidence from causal forests." Regional Science and Urban Economics 79(September). https://doi.org/10.1016/j.regsciurbeco.2019.103463