The Effect of E-Verify Laws on Crime

E-Verify laws, which have been adopted by 23 states, require employers to verify whether new employees are eligible to legally work prior to employment. This study explores the impact of state E-Verify laws on crime. Using data from the 2004–2015 National Incident Based Reporting System, the authors find that the enactment of E-Verify is associated with a 7% reduction in property crime incidents involving Hispanic arrestees. This finding was strongest for universal E-Verify mandates that extend to private employers and its external validity bolstered by evidence from the Uniform Crime Reports. Supplemental analyses from the Current Population Survey suggest two mechanisms to explain this result: E-Verify-induced increases in the employment of low-skilled natives of Hispanic descent and out-migration of younger Hispanics. Findings show no evidence that arrests were displaced to nearby jurisdictions without E-Verify or that violent crime or arrests of African Americans were affected by E-Verify laws. The magnitudes of the estimates suggest that E-Verify laws averted $491 million in property crime costs to the United States.

Did Connecticut’s “Raise the Age” Increase Motor Vehicle Thefts?

In 2010, Connecticut followed the pattern of most other U.S. states by raising the age of juvenile jurisdiction from 15 to 16. This was further raised from 16 to 17 years, 2 years later in July 2012. This sweeping change meant youth were no longer automatically prosecuted as adults in the criminal justice system. Following the change, crimes in Connecticut steadily decreased in line with nationwide trends—However, a subsequent increase in motor vehicle thefts prompted concern among critics of the “raise the age” (RTA) legislation. This study examines the change in Uniform Crime Reports (UCR) county-level index crimes before and after Connecticut changed the maximum age of juvenile jurisdiction from 16 to 17 in 2012, focusing specifically on motor vehicle thefts. Using a weighted difference-in-differences design, we estimate that RTA played a minimal role on the increase in Connecticut auto thefts between 2012 and 2017.

Climate Change and Crime Revisited: An Exploration of Monthly Temperature Anomalies and UCR Crime Data

A growing body of research suggests a positive connection between climate change and crime, but few studies have explored the seasonal nature of that link. Here, we examine how the impact of climate change on crime may partly depend on specific times of the year as recent climatological research suggests that climate change may have a diverging impact during different times of the year. To do so, we utilize the largest, most current dataset of all main categories of reported crime by month and year in the United States—the Federal Bureau of Investigation’s (FBI) Uniform Crime Reports. We employ historical weather data collected by the Global Historical Climatology Network to measure climate change, and develop a procedure that weighs and connects these data to individual crime reporting agencies. We discover not only a positive association between climate change and crime but also substantial monthly variation in this association.

Hate Crime Victimization Data in Pennsylvania: A Useful Complement to the Uniform Crime Reports

Data on the incidence and prevalence of hate crimes in the United States come primarily from the Uniform Crime Reports (UCR). Although UCR data undercount most crimes, hate crimes are particularly underreported, especially for some groups. We compare 2000–2011 UCR data in Pennsylvania to data from a state agency that came from police, media, and citizen reports. First, we find that the state-agency database is generally consistent with the UCR data, in terms of absolute counts, correlations, and predictors. Second, we find that UCR data underestimate hate crime rates by a factor of about 1.6 overall and by a factor of 2.5 for rural areas. Moreover, although UCR data on hate crimes show a decrease in the most recent 5-year period, the state agency data show that hate crime incident counts have not dropped. We suggest that using a broader index that includes both the UCR and a database like that in Pennsylvania will give a more complete picture of hate crime.

Assessing the Coverage and Representativeness of the National Incident-Based Reporting System

This article examines the coverage of the National Incident-Based Reporting System (NIBRS) as of 2013. We use NIBRS, Uniform Crime Reports (UCR), and Supplementary Homicide Reports to assess the population coverage and index crime coverage of NIBRS. We also examine the correspondence of crime rates between the UCR and agencies that do and do not participate in NIBRS. We found that NIBRS covers 29.3% of the U.S. population and 28% of UCR index crimes. We also found that the crime rates in NIBRS jurisdictions are appreciably lower than jurisdictions that do not participate in NIBRS. As of 2013, therefore, NIBRS data are not representative of the U.S. population, crime counts, or crime rates.