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

Author

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  • Hoffman, Ian
  • Mast, Evan

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.

Suggested Citation

  • Hoffman, Ian & Mast, Evan, 2019. "Heterogeneity in the effect of federal spending on local crime: Evidence from causal forests," Regional Science and Urban Economics, Elsevier, vol. 78(C).
    • Handle: RePEc:eee:regeco:v:78:y:2019:i:c:s0166046219300122
    DOI: 10.1016/j.regsciurbeco.2019.103463
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    Citations

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    Cited by:

    1. Resce, Giuliano & Vaquero-Piñeiro, Cristina, 2022. "Predicting agri-food quality across space: A Machine Learning model for the acknowledgment of Geographical Indications," Food Policy, Elsevier, vol. 112(C).
    2. Ying Deng & Qianqian Yue & Xin Zhao, 2024. "What Does Air Quality Information Disclosure Deliver and to Whom? Evidence from the Ambient Air Quality Standard (2012) Program in China," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 87(11), pages 2859-2887, November.
    3. Johnson, Josiah & Smith, Rhet A., 2023. "Main street business initiatives and crime in small towns," Journal of Economic Behavior & Organization, Elsevier, vol. 209(C), pages 91-112.
    4. Mark Kattenberg & Bas Scheer & Jurre Thiel, 2023. "Causal forests with fixed effects for treatment effect heterogeneity in difference-in-differences," CPB Discussion Paper 452, CPB Netherlands Bureau for Economic Policy Analysis.
    5. Hiroyuki Egami & Md. Shafiur Rahman & Tsuyoshi Yamamoto & Chihiro Egami & Takahisa Wakabayashi, 2024. "Causal effect of video gaming on mental well-being in Japan 2020–2022," Nature Human Behaviour, Nature, vol. 8(10), pages 1943-1956, October.

    More about this item

    Keywords

    Place-based policies; Amenities; Machine learning; Crime;
    All these keywords.

    JEL classification:

    • R1 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics
    • H2 - Public Economics - - Taxation, Subsidies, and Revenue
    • R23 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Regional Migration; Regional Labor Markets; Population

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