Using PanelMatch to Estimate the Causal Effects of Police Interventions with Irregular Treatment Patterns: An Assessment of the NYPD’s Summer All Out, 2014–2019

Abstract Objectives The New York City Police Department’s Summer All Out (SAO) was a recurring, presence-based foot-patrol initiative non-randomly deployed to precincts between 2014 and 2019. Using both two-way fixed effects (TWFE) and a novel matching and weighting estimator ( PanelMatch ),we assess whether the SAO deployment influenced a variety of crime outcomes. Methods Since the treatment pattern varies over time intermittently, we analyze a 10-year precinct-month-year panel using TWFE, a difference-in-differences (DiD) methodology. We then expand with Imai et al.’s (2023) PanelMatch , a causal inference estimator never before used in this field, which selects and reweights control units based on similarity in pretreatment crime trajectories and precinct level covariates, thereby addressing endogenous targeting of precincts and evolving group composition over time. Results TWFE estimates suggest SAO was associated with increases in violent crime, while property crime shows no detectable change. When applying PanelMatch , which employs propensity-score matching and weighting, and used lagged outcomes and precinct covariates in the refinement process, these effects attenuate toward zero. We find no statistically significant impact of SAO foot deployments on violent or property crime. These results persist with robustness checks using different crime types, including alternative functional forms. The divergence between TWFE and PanelMatch results is consistent with a scenario where SAO officers were assigned to precincts experiencing short-term crime surges. Conclusions The divergence between the results of a more traditional TWFE and the novel PanelMatch analysis suggest that evaluations of episodic, repeatedly targeted interventions should account for endogenous assignment using designs that leverage pretreatment outcome histories. Substantively, SAO’s presence-based foot patrols did not measurably reduce violent or property crime on average—reallocating officers for fixed deployments within large jurisdictions may not yield general deterrent effects.

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Publication Details

Journal
Journal of Quantitative Criminology
Published
2026-08-03
DOI
https://doi.org/10.1007/s10940-026-09678-2
Primary Topic
Crime Patterns and Interventions
Type
article
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article

Using PanelMatch to Estimate the Causal Effects of Police Interventions with Irregular Treatment Patterns: An Assessment of the NYPD’s Summer All Out, 2014–2019

Sean Patrick Roche, Thomas J. Bilach
Journal of Quantitative Criminology
Crime Patterns and Interventions
article

Using PanelMatch to Estimate the Causal Effects of Police Interventions with Irregular Treatment Patterns: An Assessment of the NYPD’s Summer All Out, 2014–2019

Sean Patrick Roche, Thomas J. Bilach
article en

Abstract

Abstract Objectives The New York City Police Department’s Summer All Out (SAO) was a recurring, presence-based foot-patrol initiative non-randomly deployed to precincts between 2014 and 2019. Using both two-way fixed effects (TWFE) and a novel matching and weighting estimator ( PanelMatch ),we assess whether the SAO deployment influenced a variety of crime outcomes. Methods Since the treatment pattern varies over time intermittently, we analyze a 10-year precinct-month-year panel using TWFE, a difference-in-differences (DiD) methodology. We then expand with Imai et al.’s (2023) PanelMatch , a causal inference estimator never before used in this field, which selects and reweights control units based on similarity in pretreatment crime trajectories and precinct level covariates, thereby addressing endogenous targeting of precincts and evolving group composition over time. Results TWFE estimates suggest SAO was associated with increases in violent crime, while property crime shows no detectable change. When applying PanelMatch , which employs propensity-score matching and weighting, and used lagged outcomes and precinct covariates in the refinement process, these effects attenuate toward zero. We find no statistically significant impact of SAO foot deployments on violent or property crime. These results persist with robustness checks using different crime types, including alternative functional forms. The divergence between TWFE and PanelMatch results is consistent with a scenario where SAO officers were assigned to precincts experiencing short-term crime surges. Conclusions The divergence between the results of a more traditional TWFE and the novel PanelMatch analysis suggest that evaluations of episodic, repeatedly targeted interventions should account for endogenous assignment using designs that leverage pretreatment outcome histories. Substantively, SAO’s presence-based foot patrols did not measurably reduce violent or property crime on average—reallocating officers for fixed deployments within large jurisdictions may not yield general deterrent effects.

Journal of Quantitative Criminology
Texas State University (US), National Institute of Justice (US)
Peace, Justice and strong institutions
Openalex Percentile: Top 4%
Crime Patterns and Interventions
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