K42 | Macro Paper Warehouse

Community Engagement and Public Safety: Evidence from Crime Enforcement Targeting Immigrants

Mon, 01 Jan 0001 00:00:00 +0000

This paper studies how immigration enforcement affects public safety, asking two questions: (1) what is the effect of increased enforcement on criminal victimization, and (2) how does increased enforcement affect victims’ willingness to report crimes to police? The authors exploit the staggered rollout of the U.S. Secure Communities (SC) program — the largest expansion of interior immigration enforcement in U.S. history — across counties between 2008 and 2013. SC expanded information sharing between local police and federal immigration authorities, causing ICE honored detainer requests to increase by over 50% following program activation.

The primary data source is the restricted-access National Crime Victimization Survey (NCVS), which measures victimizations independently of whether they were reported to police and includes respondent ethnicity. This allows the authors to separately estimate effects on underlying crime incidence and on reporting behavior for Hispanic and non-Hispanic individuals. The empirical strategy uses a staggered difference-in-differences design following Sun and Abraham (2021), comparing earlier-treated counties to the last 25% of counties to activate SC, with estimates run separately by ethnicity.

The main findings run contrary to the stated policy goal of improving public safety. Among Hispanic individuals, SC caused a statistically significant 0.15 percentage point increase in monthly victimization — a 16% increase relative to the pre-period baseline of 0.9 percentage points — implying approximately 1.3 million additional crimes against Hispanics in the two years following program activation. The increase is concentrated primarily in property crimes (a statistically significant 15% increase), with a similarly sized but imprecisely estimated 15% increase in violent crime victimizations. The victimization increase is larger for Hispanic females (0.23 percentage points, or 25%) and in counties with higher shares of non-citizen Hispanic residents.

Simultaneously, SC caused a 9.5 percentage point decline in the likelihood that Hispanic victims report incidents to police — a 30% decline relative to the pre-period mean reporting rate of 33 percentage points. This reporting decline is primarily driven by a 34% decline in the reporting of property offenses. No changes in victimization or reporting are found for non-Hispanic individuals in the aggregate, though non-Hispanic individuals in neighborhoods with high Hispanic population shares do experience higher victimization rates after SC.

Critically, reported crime rates (the product of victimization and reporting) are unchanged for both Hispanic and non-Hispanic individuals, explaining why prior studies using administrative reported-crime data found null effects of SC. The null effect on reported crime masks two large, opposing causal forces.

The authors provide evidence that the decline in crime reporting is the primary driver of the increase in victimization. Cohorts with larger reporting declines experienced larger victimization increases, and a decomposition exercise shows the reporting decline is substantially more important than concurrent SC-induced changes in unemployment, wages, female-headed household shares, and the male immigrant share. Supporting data from 75 police departments confirm no change in 911 call volumes or total arrest volumes, while showing a decline in the Hispanic share of arrestees in both Hispanic and non-Hispanic neighborhoods — consistent with reduced reporting leading to reduced apprehension of offenders, with offending shifting toward non-Hispanic individuals.

Scope conditions: results are estimated for the population residing in counties exceeding 100,000 residents (representing 61% of total U.S. population and 69% of the Hispanic population), excluding southern border counties and states that actively resisted SC implementation (Illinois, Massachusetts, New York). Effects apply to all Hispanic respondents — citizens and non-citizens — consistent with prior evidence that citizen Hispanics respond to immigration enforcement out of concern for non-citizen contacts.

Q: What was the Secure Communities program and how was it implemented? A: SC was a federal program launched in 2008 that required fingerprints of individuals booked into local jails to be forwarded not only to the FBI but also to the Department of Homeland Security, enabling automatic screening for immigration violations. Local authorities could not prevent federal officials from learning of an arrestee’s immigration status. The program rolled out county-by-county between October 2008 and January 2013 due to technological constraints and resource bottlenecks, generating the staggered variation used for identification.

Q: How large was the first-stage effect on actual immigration enforcement? A: County-level honored ICE detainer requests increased by over 50% following SC activation, with a similar 40% increase in all detainer requests. The number of honored detainers nationwide doubled between 2008 and 2012. Over 90% of detainers and removals in any given month were for individuals of Hispanic ethnicity.

Q: What is the main finding on Hispanic victimization? A: SC caused a 0.15 percentage point increase in monthly Hispanic victimization rates, a 16% increase relative to the pre-period baseline of 0.9 percentage points. This translates to approximately 1.3 million additional crimes against Hispanics over two years following program activation, calculated by multiplying the monthly effect by 24 months and the 35.3 million Hispanics in the sample counties.

Q: What is the main finding on Hispanic crime reporting? A: SC caused a 9.5 percentage point decline in the likelihood that Hispanic victims report incidents to police, a 30% decline relative to the pre-period mean reporting rate of 33 percentage points. This decline occurred relatively quickly after activation and was concentrated in property offenses, where reporting fell by 34%.

Q: Why do reported crime rates show no change despite large shifts in victimization and reporting? A: Reported crime rates — the probability of being victimized and reporting the crime — are unchanged because the 16% increase in victimization and the 30% decline in reporting are approximately offsetting in magnitude. This explains why prior work using administrative police data (Miles and Cox 2014; Treyger et al. 2014; Hines and Peri 2019) found null effects of SC on reported crime: those data sources cannot separately identify the two underlying changes.

Q: Does SC affect non-Hispanic individuals? A: In the aggregate, SC has no statistically significant effect on non-Hispanic victimization or reporting. However, non-Hispanic individuals living in neighborhoods with high Hispanic population shares do experience victimization increases, and in those neighborhoods their reporting rates also decline slightly. Re-weighting non-Hispanic respondents to match the county composition of Hispanic respondents yields an 8% increase in non-Hispanic victimization, suggesting spillover effects in Hispanic-dense areas.

Q: What mechanism links the reporting decline to the victimization increase? A: The authors argue that reduced victim reporting lowers the probability that offenders are apprehended, thereby reducing the cost of committing crimes. They demonstrate this through two analyses: first, cohorts of counties with larger reporting declines experienced larger victimization increases; second, a decomposition shows the reporting channel is substantially more important than concurrent SC-induced changes in unemployment, wages, female-headed household shares, and the male immigrant share of the population.

Q: What do the police administrative data show about offender composition? A: Data from 75 police departments show no change in 911 call volumes or total arrest volumes following SC — consistent with the NCVS finding of unchanged reported crime rates. However, the Hispanic share of arrestees declined after SC, with a 1.5 percentage point drop in Hispanic neighborhoods (off a base of 54%), suggesting the rise in offending was more concentrated among non-Hispanic offenders as reduced reporting lowered expected punishment probabilities.

Q: How does the victimization effect vary by gender? A: The victimization point estimate for Hispanic males is 0.085 percentage points and imprecisely estimated (SE = 0.088). For Hispanic females, the effect is over 2.5 times larger at 0.23 percentage points, a 25% increase. The decline in reporting is comparable in magnitude across male and female Hispanic victims, suggesting fear of enforcement is similar by gender but that females disproportionately bear the crime burden.

Q: How does the victimization effect vary by neighborhood non-citizen Hispanic share? A: Victimization effects for Hispanics are relatively constant across neighborhood types but are higher — around 25% — in neighborhoods with the highest shares of non-citizen Hispanics. Counties with higher non-citizen Hispanic shares also exhibit higher ICE removal rates, indicating greater total enforcement, and these counties have higher victimization effects. Reporting declines among Hispanics appear relatively uniform across neighborhood types.

Q: Could survey attrition or compositional changes explain the results? A: The authors rule this out through several tests. First, SC has no statistically significant effect on household survey response rates, even in Census tracts above the 90th percentile of Hispanic share. A worst-case bias calculation implies attrition could account for at most 26% of the victimization effect. Second, re-estimating using predicted victimization (based on pre-SC demographics) yields precise null effects, indicating the increase is not driven by compositional change. Third, results are stable when restricting to respondents present at all survey waves or using individual fixed effects.

Q: Could the reporting decline be mechanical — reflecting a change in the types of crimes committed rather than behavioral change? A: The authors test this by constructing predicted reporting rates using pre-SC incident characteristics. The largest alternative estimate is -1.45 percentage points, over six times smaller than the estimated main reporting effect of 9.5 percentage points, ruling out crime composition change as the primary explanation. Results also hold when focusing on always-respondents and using individual fixed effects, ruling out entry of low-reporting individuals into the survey.

Q: How robust are the results to alternative empirical strategies? A: Results are robust to including states that resisted SC (with somewhat smaller magnitudes as expected), alternative population cutoffs, TWFE specifications, the Borusyak et al. (2021) and Callaway and Sant’Anna (2021) estimators (which yield larger point estimates), a triple-differences specification using non-Hispanics as an additional control group, and the inclusion of time-varying unemployment rates. The dynamic event-study plots show parallel pre-trends across all specifications.

Q: What are the policy implications of the null effect on aggregate victimization? A: The authors estimate that the policy ruled out declines in aggregate victimization larger than 3.3%, indicating SC did not generate meaningful improvements in aggregate public safety. This contradicts the stated mission of immigration enforcement agencies. The findings imply that policies targeting immigrant communities can generate public safety costs through trust erosion that outweigh any deterrence or incapacitation benefits.

Secure Communities (SC): A federal program launched in 2008 requiring automatic sharing of fingerprints from local jail bookings with the Department of Homeland Security, enabling identification of unauthorized immigrants among local arrestees and triggering ICE detainer requests; the largest expansion of interior immigration enforcement in U.S. history.

Chilling effect: The mechanism by which immigration enforcement raises the perceived cost of contacting law enforcement for immigrant victims and witnesses — through fear that they, a family member, or neighbor will be detained or deported — thereby reducing willingness to report crimes independently of any change in underlying criminality.

Victimization rate: The likelihood that an individual is the victim of a crime in a given period, measured via the NCVS independently of whether the crime was reported to police; the paper’s primary measure of public safety.

Reporting rate: The likelihood that a criminal victimization is reported by the victim to the police, measured as a share of all crime incidents; distinct from victimization rate and central to the paper’s decomposition of reported crime into its two components.

Reported crime rate: The joint probability of being victimized and reporting the crime, analogous to measures available in administrative police data such as the FBI UCR; this outcome masks the opposing effects of SC on victimization and reporting.

Honored detainer: An ICE detainer request that results in a transfer of the arrested individual to ICE custody; the paper’s preferred measure of immigration enforcement intensity because it is available both before and after SC activation and is more directly linked to deportation actions than all detainer requests.

Decomposition of victimization increase: The paper’s procedure for quantifying the relative importance of the reporting-channel (reduced probability of apprehension) versus other SC-induced social and economic changes (unemployment, wages, female-headed households, male immigrant share) in explaining the rise in Hispanic victimization.

Professional Motivations in the Public Sector: Evidence from Police Officers

Mon, 01 Jan 0001 00:00:00 +0000

This paper studies how public sector workers balance professional motivations against private economic concerns, using arrest decisions by Dallas Police Department (DPD) officers as the empirical laboratory. The central institutional feature exploited is that arrests made near the end of an officer’s shift typically require the officer to stay and work overtime, generating private costs that must be weighed against the professional benefits of making an arrest (e.g., crime reduction or duty fulfillment). The paper further leverages variation from DPD’s “secondary employment” program: approximately 30% of officers held a registered second job at some point during 2019–2021, and on days when a second job is scheduled after the police shift, the opportunity cost of late-shift policing is higher.

The data cover all DPD arrests from January 2015 to December 2021, linked to officer shift assignments, charge types, prosecutorial outcomes (whether the Dallas County Attorney chose to prosecute), and second-job schedules. The sample excludes traffic violations and arrests without shift information. The authors observe wide variation in prosecution rates by charge type: drug and gang offenses exceed 70%, property and violent crimes run 30–50%, and minor charges fall below 20%.

Four main findings emerge. First, arrest rates fall sharply in the last 30–40 minutes of a shift, with the decline most pronounced for drug and gang charges (approximately 50% drop in arrest rate) and smallest for violent charges, consistent with officers having more discretion over the former. Second, arrests that do occur late in the shift are of higher quality: conditional on being made, they are approximately 1.5–2.5 percentage points more likely to result in prosecution than arrests made earlier, with the quality premium larger in more discretionary charge categories (drugs/gang > property > violent). Third, on days when an officer has a second job scheduled, arrest rates are lower by roughly 5–10% relative to baseline across the full shift, with effects concentrated in the second half; and the conditional probability of prosecution on those days is 1–2 percentage points higher than on non-second-job days. The second-job effect appears even earlier in the shift than the overtime effect alone, consistent with the second job magnifying the opportunity cost mechanism.

Fourth, the authors estimate a dynamic structural model of the arrest decision. At each moment of the shift the officer chooses whether to arrest, trading off a professional benefit b_p against a private cost c(t, secondjob) that rises when overtime begins and rises further on second-job days. Structural estimates indicate the overtime cost is large enough to reduce the expected professional value of an arrest in the final 30 minutes of the shift by roughly 20–30%. The additional second-job cost reduces expected professional value by a further 10–20%. Counterfactual simulation implies that eliminating the overtime cost would increase overall arrests by approximately 5–8%, a magnitude the authors describe as economically significant. Welfare analysis shows that the desirability of high overtime costs depends on whether citizens weight quantity of arrests or quality: under quality-weighted preferences the current overtime-cost regime may be socially optimal because officers self-select toward arrests they perceive as likely to result in prosecution; under quantity preferences, reducing overtime costs would increase police activity.

The identification strategy relies on within-officer variation in second-job scheduling, absorbing officer fixed effects (and officer-by-month fixed effects in robustness checks) and time fixed effects. The key identifying assumption is that second-job days are not systematically assigned to low-crime or low-patrol days. Supporting evidence includes balance tests showing second-job status is uncorrelated with local crime call patterns conditional on fixed effects, and the observation that officers who take second jobs do not exhibit a systematically different enforcement style (measured by arrest patterns across the shift) relative to officers who do not.

Scope conditions: results are from a single medium-sized urban police department (approximately 3,000 officers) in Dallas, Texas, a city described as diverse by race, income, and political affiliation. The department is 29% Black, 43% Hispanic, 27% White, and 15% female. Generalizability to other jurisdictions or institutional structures is not established by this study.

Q: What is the main research question? A: The paper asks how public sector workers balance professional motivations (e.g., crime reduction, duty fulfillment) against private economic concerns (e.g., overtime costs, opportunity costs from second jobs). It uses police arrest decisions as the empirical setting because the shift-end timing of arrests generates a clear, observable private cost that varies within officer across days.

Q: What is the key institutional feature that generates identification? A: Arrests made near the end of a shift typically require the arresting officer to stay past the shift and work overtime. This creates a personal cost — more time, delayed transition to off-duty activities — that makes late-shift arrests more costly without changing their professional value. The DPD secondary employment program adds a second source of variation: on days when an officer has a registered second job scheduled after the police shift, the opportunity cost of any arrest (and especially a late-shift arrest) is higher.

Q: How large is the drop in arrest rates near shift end? A: The baseline arrest rate declines by approximately 0.12 percentage points per six-minute time bucket in the last 30 minutes of the shift, or about 5% relative to the mean arrest rate of 2.3 percentage points. The drop is most dramatic for drug and gang charges, where the arrest rate falls by approximately 50%, and smallest for violent charges, where officers appear to arrest regardless of shift timing.

Q: How does arrest quality change near shift end? A: Arrests made in the last 30 minutes of a shift are approximately 1.5–2.5 percentage points more likely to result in prosecution than arrests made earlier in the shift, after controlling for charge type composition and officer fixed effects. The quality premium is larger in more discretionary charge categories (drugs/gang, then property, then violent), consistent with officers becoming more selective to avoid overtime costs on arrests unlikely to result in prosecution.

Q: Does the shift-end drop reflect officer fatigue or overtime cost? A: The paper argues both pieces of evidence point to overtime cost rather than fatigue alone. First, arrest rates increase sharply after the official shift end when the officer is already earning overtime pay — if fatigue were the mechanism, arrests would also decline post-shift. Second, on second-job days arrest rates fall earlier in the shift and by more, consistent with higher opportunity costs rather than accumulated fatigue.

Q: What is the effect of having a second job scheduled on arrest rates? A: Having a second job scheduled reduces arrest rates by roughly 5–10% relative to the baseline across the full shift, with effects concentrated in the second half. The reduction is even larger in the final 30 minutes, consistent with the second job amplifying the overtime cost mechanism.

Q: What is the effect of second-job days on arrest quality? A: Arrests made on second-job days are 1–2 percentage points more likely to result in prosecution compared to arrests on non-second-job days, after controlling for time of day, charge type composition, and officer fixed effects. This parallels the shift-end quality effect and is consistent with officers applying higher selectivity thresholds when opportunity costs are elevated.

Q: How is the second-job variation used for identification? A: The main specification compares the same officer’s behavior on shifts where a second job is scheduled versus shifts where it is not, absorbing officer fixed effects and time fixed effects. The identifying assumption is that second-job scheduling is uncorrelated with unobservable determinants of enforcement intensity conditional on fixed effects. The authors support this with balance tests showing second-job status is not predicted by lagged activity measures or contemporaneous crime call patterns.

Q: What does the dynamic structural model add? A: The structural model formalizes the arrest decision as a dynamic problem where the officer compares the professional benefit b_p of an arrest to the private cost c(t, secondjob), which rises discontinuously when overtime begins and rises further on second-job days. Estimating the model by matching moments (baseline arrest rates, shift-timing patterns, quality changes, second-job effects) yields preference parameters. The model enables counterfactual and welfare analysis that the reduced-form estimates alone cannot provide.

Q: What are the structural estimates of overtime and second-job costs? A: The overtime cost c_ot is estimated to be large enough that arresting someone in the final 30 minutes of the shift reduces the expected professional value of that arrest by roughly 20–30%. The additional second-job cost c_sj reduces expected professional value by a further 10–20%. Both estimates are described as statistically precise.

Q: What does the counterfactual removal of overtime costs imply for arrests? A: Eliminating the overtime cost is estimated to increase overall arrests by approximately 5–8%, which the authors characterize as economically significant. This implies that officers’ private costs have a first-order impact on the quantity of law enforcement activity.

Q: What does the welfare analysis conclude about overtime costs? A: The welfare effect of eliminating overtime costs depends on citizen preferences. Under quality-weighted preferences — where citizens value the probability that an arrest results in prosecution — the current overtime-cost regime may be socially optimal because it induces officers to self-select toward arrests they perceive as likely to stick. Under quantity preferences — where citizens value the total number of arrests per period — reducing overtime costs would increase police activity and benefit citizens.

Q: What are the scope conditions of the study? A: The study is conducted entirely within the Dallas Police Department, a single medium-sized urban department with approximately 3,000 officers. Dallas is described as a diverse city by race, income, and political affiliation, and the department itself is relatively diverse (29% Black, 43% Hispanic, 27% White, 15% female). The findings may not generalize to departments with different overtime rules, labor contracts, or institutional cultures.

professional motivations: The non-pecuniary benefits officers derive from making arrests, such as crime reduction, duty fulfillment, or the legitimacy of their work; modeled as a professional benefit b_p that motivates arrest independent of financial compensation.

private costs of arrest: The personal costs borne by officers when making an arrest, chiefly the overtime cost when an arrest extends the shift past its scheduled end, and the opportunity cost on days when a second job is scheduled. These costs are distinct from professional motivations and respond to economic incentives.

arrest quality: The conditional probability that an arrest results in prosecution by the Dallas County Attorney’s office; used as a revealed-preference measure of the officer’s assessment of arrest strength. Higher arrest quality near shift end reflects greater selectivity under elevated private costs.

secondary employment (second job): A formal DPD program allowing officers to register as certified police officers for private security work after their primary shift. Approximately 30% of DPD officers held a second job at some point during 2019–2021. The scheduled second job raises the opportunity cost of late-shift primary-shift arrests and provides a second source of variation in private costs.

overtime cost: The cost incurred when an arrest requires an officer to remain past the end of the scheduled shift to complete paperwork and processing. Modeled as c_ot per period spent in overtime, this cost is the primary mechanism reducing late-shift arrest rates and increasing arrest selectivity.

dynamic model of arrest decisions: A structural model in which officers decide each moment whether to arrest, balancing professional benefit against private cost as a function of shift timing and second-job status. Estimated by minimum distance on moments from the data; used to recover preference parameters and conduct counterfactual welfare analysis.