scholarly journals The Effect of E-Verify Laws on Crime

ILR Review ◽  
2021 ◽  
pp. 001979392110444
Author(s):  
Brandyn F. Churchill ◽  
Andrew Dickinson ◽  
Taylor Mackay ◽  
Joseph J. Sabia
Keyword(s):  
External Validity ◽  
Population Survey ◽  
Reporting System ◽  
Property Crime ◽  
The United States ◽  
New Employees ◽  
Uniform Crime Reports ◽  
Using Data ◽  
The Impact ◽  
Crime Reports

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.

scholarly journals Modeling a Bridge When Survey Questions Change: Evidence from the Current Population Survey Health Insurance Redesign

2019 ◽  
Vol 35 (1) ◽  
pp. 189-202
Author(s):  
Brett O’Hara ◽  
Carla Medalia ◽  
Jerry J. Maples
Keyword(s):  
Health Insurance ◽  
Current Population Survey ◽  
Time Trend ◽  
Population Survey ◽  
The United States ◽  
Community Survey ◽  
Historical Time ◽  
Current Population ◽  
Using Data ◽  
The Impact

Abstract Most research on health insurance in the United States uses the Current Population Survey Annual Social and Economic Supplement. However, a recent redesign of the health insurance questions disrupted the historical time trend in 2013. Using data from the American Community Survey, which has a parallel trend in the uninsured rate, we model a bridge estimate of the uninsured rate using the traditional questions. Also, we estimate the effect of changing the questionnaire. We show that the impact of redesigning the survey varies substantially by subgroup. This approach can be used to produce bridge estimates when other questionnaires are redesigned.

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

2019 ◽  
Vol 51 (5) ◽  
pp. 502-529 ◽  
Author(s):  
Dennis M. Mares ◽  
Kenneth W. Moffett
Keyword(s):  
Climate Change ◽  
Positive Association ◽  
The United States ◽  
Weather Data ◽  
Historical Climatology ◽  
Global Historical Climatology Network ◽  
Uniform Crime Reports ◽  
Reported Crime ◽  
The Impact ◽  
Crime Reports

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.

Cyber Place Management and Crime Prevention: The Effectiveness of Cybersecurity Awareness Training Against Phishing Attacks

2021 ◽  
pp. 104398622110016
Author(s):  
Sinchul Back ◽  
Rob T. Guerette
Keyword(s):  
Crime Prevention ◽  
Research University ◽  
Management Strategies ◽  
Large Body ◽  
The United States ◽  
Place Management ◽  
Online Setting ◽  
Using Data ◽  
Virtual Domain ◽  
The Impact

Criminologists and crime prevention practitioners recognize the importance of geographical places to crime activities and the role that place managers might play in effectively preventing crime. Indeed, over the past several decades, a large body of work has highlighted the tendency for crime to concentrate across an assortment of geographic areas, where place management tends to be absent or weak. Nevertheless, there has been a paucity of research evaluating place management strategies and cybercrime within the virtual domain. The purpose of this study was to investigate the effectiveness of place management techniques on reducing cybercrime incidents in an online setting. Using data derived from the information technology division of a large urban research university in the United States, this study evaluated the impact of an anti-phishing training program delivered to employees that sought to increase awareness and understanding of methods to better protect their “virtual places” from cybercrimes. Findings are discussed within the context of the broader crime and place literature.

Overeducation and the Earnings of Black, Hispanic, and White Male Workers

1988 ◽  
Vol 31 (2) ◽  
pp. 190-212 ◽  
Author(s):  
Richard R. Verdugo ◽  
Naomi Turner Verdugo
Keyword(s):  
United States ◽  
Mexican Americans ◽  
Minority Groups ◽  
Puerto Ricans ◽  
White Male ◽  
The United States ◽  
Using Data ◽  
The Impact ◽  
Male Workers ◽  
White Minority

This study addresses two issues: (1) the impact of overeducation on the earnings of male workers in the United States, and (2) white-minority earnings differences among males. Given that educational attainment levels are increasing among workers, there is some suspicion that earnings returns to education are not as great as might be expected. This topic is examined by including an overeducation variable in an earnings function. Regarding the second issue addressed in this article, little is actually known about white-minority differences because the bulk of such research compares whites and blacks. By including selected Hispanic groups in this analysis (Mexican Americans, Puerto Ricans, Cubans, and Other Hispanics) we are able to assess white-minority earnings differences to a greater degree. Using data from a 5% sample of the 1980 census to estimate an earnings function, we find that overeducated workers earn less than either undereducated or adequately educated workers. Second, we find that there are substantial earnings differences between whites and minorities, and, also, between the five minority groups examined.

The Labor Market Skills of Recent Male Immigrants: Evidence from the Current Population Survey

ILR Review ◽  
1995 ◽  
Vol 48 (4) ◽  
pp. 792-811 ◽  
Author(s):  
Edward Funkhouser ◽  
Stephen J. Trejo
Keyword(s):  
United States ◽  
Labor Market ◽  
Current Population Survey ◽  
Population Survey ◽  
Census Data ◽  
The United States ◽  
Skill Levels ◽  
Recent Immigrants ◽  
Current Population ◽  
Using Data

Using data from special supplements to the Current Population Survey (CPS), the authors track the education and hourly earnings of recent male immigrants to the United States. In terms of these measures of labor market skills, the CPS data suggest that immigrants who came in the late 1980s were more skilled than those who arrived earlier in the decade. This pattern represents a break from the steady decline in immigrant skill levels observed in 1940–80 Census data. Despite the encouraging trend over the 1980s, however, the average skills of recent immigrants remain low by historical standards.

Impact of Health Plan Deductibles and Health Insurance Marketplace Enrollment on Health Care Experiences

2018 ◽  
Vol 77 (5) ◽  
pp. 483-497
Author(s):  
Weiwei Chen ◽  
Timothy F. Page
Keyword(s):  
Health Care ◽  
Health Insurance ◽  
The United States ◽  
Health Plans ◽  
Medical Needs ◽  
Care Access ◽  
Health Care Experiences ◽  
Monitoring Survey ◽  
Using Data ◽  
The Impact

High-deductible health plans (HDHPs) have become increasingly prevalent among employer-sponsored health plans and plans offered through the Health Insurance Marketplace in the United States. This study examined the impact of deductible levels on health care experiences in terms of care access, affordability, routine checkup, out-of-pocket cost, and satisfaction using data from the Health Reform Monitoring Survey. The study also tested whether the experiences of Marketplace enrollees differed from off-Marketplace individuals, controlling for deductible levels. Results from multivariable and propensity score weighted regression models showed that many of the outcomes were adversely affected by deductible levels and Marketplace enrollment. These results highlight the importance of efforts to help individuals choose the plan that fits both their medical needs and their budgets. The study also calls for more attention to improving provider acceptance of HDHPs and Marketplace plans as these plans become increasingly common over time.

Quantifying changes in bicycle volumes using crowdsourced data

2022 ◽  
pp. 239980832110661
Author(s):  
Ali Al-Ramini ◽  
Mohammad A Takallou ◽  
Daniel P Piatkowski ◽  
Fadi Alsaleem
Keyword(s):  
Machine Learning ◽  
The United States ◽  
Crowdsourced Data ◽  
Machine Learning Approach ◽  
Bicycle Infrastructure ◽  
The Difference ◽  
Infrastructure Investments ◽  
Using Data ◽  
The Impact ◽  
The City

Most cities in the United States lack comprehensive or connected bicycle infrastructure; therefore, inexpensive and easy-to-implement solutions for connecting existing bicycle infrastructure are increasingly being employed. Signage is one of the promising solutions. However, the necessary data for evaluating its effect on cycling ridership is lacking. To overcome this challenge, this study tests the potential of using readily-available crowdsourced data in concert with machine-learning methods to provide insight into signage intervention effectiveness. We do this by assessing a natural experiment to identify the potential effects of adding or replacing signage within existing bicycle infrastructure in 2019 in the city of Omaha, Nebraska. Specifically, we first visually compare cycling traffic changes in 2019 to those from the previous two years (2017–2018) using data extracted from the Strava fitness app. Then, we use a new three-step machine-learning approach to quantify the impact of signage while controlling for weather, demographics, and street characteristics. The steps are as follows: Step 1 (modeling and validation) build and train a model from the available 2017 crowdsourced data (i.e., Strava, Census, and weather) that accurately predicts the cycling traffic data for any street within the study area in 2018; Step 2 (prediction) use the model from Step 1 to predict bicycle traffic in 2019 while assuming new signage was not added; Step 3 (impact evaluation) use the difference in prediction from actual traffic in 2019 as evidence of the likely impact of signage. While our work does not demonstrate causality, it does demonstrate an inexpensive method, using readily-available data, to identify changing trends in bicycling over the same time that new infrastructure investments are being added.

The Differential Impact of New Product Development “Make/Buy” Choices on Immediate and Future Product Quality: Insights from the Automobile Industry

2017 ◽  
Vol 81 (6) ◽  
pp. 1-23 ◽  
Author(s):  
Kartik Kalaignanam ◽  
Tarun Kushwaha ◽  
Tracey A. Swartz
Keyword(s):  
Product Development ◽  
Product Quality ◽  
New Product Development ◽  
Automobile Industry ◽  
Positive Impact ◽  
New Product ◽  
The United States ◽  
Trade Offs ◽  
Using Data ◽  
The Impact

This article examines the impact of new product development (NPD) “make/buy” choices on product quality using data from the automobile industry. Although the business press has lamented that NPD outsourcing compromises product quality, there is no systematic evidence to support or refute this assertion. Against this backdrop, this study tests a contingency model of the impact of NPD make/buy decisions on immediate and future product quality. The hypotheses are tested using data on NPD make/buy choices of 173 models of 12 automobile firms in the United States between 2007 and 2014. The authors find that whereas NPD buy has a more positive impact on immediate product quality, NPD make has a more positive impact on future product quality. Furthermore, the immediate product quality impact of NPD buy is stronger when (1) technologies are more complex and (2) firm NPD capability is higher. In contrast, the future product quality impact of NPD make is stronger when (1) there is postlaunch adverse feedback and (2) firm NPD capability is higher. The study highlights the complex trade-offs associated with NPD make/buy decisions and offers valuable insights on how firms could manage these decisions.

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