This paper examines how adopting remote work affects crimes. Using mobility data as a proxy for residential occupancy and monthly crime administrative data across districts, we employ a local projections methodology to estimate the dynamic effects of remote work on different types of property crimes. Our identification strategy leverages temporal and spatial variation in remote work adoption patterns in Argentina, controlling for epidemiological, economic, and climatic conditions, district-specific characteristics, and common temporal shocks. We found that a one percentage point increase in the incidence of remote work is associated with an increase of up to 1.4 additional crimes in each district and month, with effects concentrated in residential and street robbery. The impact is greater in high-income districts. These findings contribute to our understanding of how changes in mobility patterns affect criminal behavior and have important implications for urban security policies in the context of evolving work arrangements.
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González et al. (2026) studied this question.
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