The California Policy Lab pairs
trusted experts from UCLA and UC Berkeley with policymakers to solve our most
urgent social problems, including homelessness, poverty, crime, and education
The federal Earned Income Tax Credit (EITC), and its state counterpart, the California Earned Income Tax Credit (CalEITC), provided low-income Californians with a nearly $7 billion boost in 2018. This report provides an in-depth analysis of the approximately 2.8 million households who claimed the credits, including household size, which households are claiming both credits, the financial impacts, and a county-by-county breakdown, including the average amount of each credit claimed in each county. The California legislature and Governor Newsom approved a significant expansion to the CalEITC in 2019. The expansion is expected to double the amount of CalEITC credits claimed, and coupled with a new Young Child Tax Credit, the total value of the state credits is expected to reach $1 billion. This report provides an important roadmap for policymakers interested in understanding who this important anti-poverty program reaches in California
The California Policy Lab analyzed responses from more than 64,000 adults in the United States experiencing both sheltered and unsheltered homelessness. Unsheltered adults are far more likely to report suffering from chronic health conditions, mental health issues, and experiences with trauma and substance abuse problems as compared to homeless people who are living in shelters. As policymakers design interventions for unsheltered individuals and balance investments in emergency housing and permanent housing, they will need to consider whether emergency housing is adequate or appropriate for a highly vulnerable population, half of whom are trimorbid.
Assembly Bill 1076 proposes to extend automatic record clearance in California to certain eligible arrests and convictions. If passed, the California Department of Justice (CA DOJ) would, beginning in 2021, identify persons eligible for relief and grant relief without requiring the person to file a petition. The California Policy Lab (CPL) created a computer program to identify eligible arrests and convictions using CA DOJ’s Automated Criminal History System (ACHS). We found that 1 in 8 Californians with a criminal record are potentially eligible to have their full record cleared. Further, approximately 81% of persons with a criminal record are potentially eligible for relief of at least one arrest or conviction (approximately 1.8 million persons in the study cohort).
California needs a centralized authority for linking the state’s administrative data. Legislators are focusing on new datasets and data systems, which is a step in the right direction. But what the state truly needs is a new office with a clear mandate to link the state’s core data assets, a clear set of tools for doing so, and governance that ensures data are used to inform program improvement. Think of it as the state’s Census Bureau – or “Statistics California.”
We propose here a roadmap toward that goal: (1) create a new, independent office with the mandate and expertise to link data across siloes, (2) sequence the linkage process by starting with education and expanding outward, and (3) establish streamlined governance that makes data available to improve state policies and programs.
The following brief is a summary of a September 2018 report co-authored by California Policy Lab faculty affiliates Meredith Phillips, Sarah Reber, and Jesse Rothstein titled “Making California Data More Useful for Educational Improvement.” The full report was released by the “Getting Down to Facts II” project, which aims to bring evidence to bear on the conditions of California education and to guide future policy. We would like to thank the California Department of Education for their thoughtful feedback.
We review the linking of datasets that contain identifying information (e.g., names, birthdates) but not unique common identifiers for each individual. We discuss strategies for identifying matches in three families: rules-based matching, supervised machine learning, and unsupervised machine learning. These vary in the ways that they combine human knowledge with computing power. We define different measures of accuracy and explore the performance of common algorithms in test data.
Our goal is to de-mystify data linking for non-technical readers. We attempt to explain the criteria that should inform the choice of linking methods, and the decisions that need to be made to implement them.
Additional resources, including code and public data referenced on pp. 26-34 is available at: https://github.com/californiapolicylab/data-linking.
We evaluate the effect on reported daily criminal incidents of a sizable reallocation of police officers from plain clothes special-task force assignments to uniformed foot patrol. On September 1st, 2017, the San Francisco Police Department (SFPD) re-assigned 69 officers (roughly 3.5 percent of sworn officers in the department) to various foot patrol assignments across the city’s ten police districts. We use microlevel data on criminal incidents to generate daily counts of crime by broad category for the ten most frequently reported offenses (accounting for over 90 percent of incidents reported to the police) for the 120-day period surrounding the September 1st policy change. We conduct an event study analysis to test for a discrete change in the daily level of criminal incidents coinciding in time with the reallocation of police officers. We document discrete and statistically significant declines in the daily number of larceny thefts and assaults reported to the police coinciding with the increase in the number of officers assigned to foot-beats. We show that the observed declines are not evident for comparable time periods in earlier years. The decline in larceny theft is geographically broad-based across police districts within the city while the decline in assaults is concentrated in a few districts. We do not observe larger crime declines (either in absolute terms or proportional to pre-change crime levels) in districts that experienced greater increases in foot-beat assignments.
Over 150,000 low- and moderate-income California high school graduates each year are eligible for CalGrant entitlement awards, which can cover full tuition and most fees at any of the three public higher education segments in the state, or can make substantial contributions toward tuition at private colleges. Unfortunately, many eligible students don’t take up the awards. Many may not be aware of their eligibility, know how to navigate the system, or feel like these funds are truly meant for them. In 2017-8, the California Policy Lab worked with the California Student Aid Commission to design and test more effective notifications to eligible high school seniors. The redesigned letters were clearer, shorter, and encouraged students to think of themselves as college-bound. The results were promising. Students who received the redesigned letters were much more likely to take the first step toward claiming the award than a randomly selected comparison group. Future analyses will measure impacts on college enrollment, CalGrant payouts, and eventual college completion.
US courts provide constitutionally mandated legal services to low-income criminal defendants via private court-appointed attorneys and public defenders. This study finds that defendants in multiple-defendant cases experience better case outcomes when they are represented by a public defender compared with those appointed a private attorney. In San Francisco, they are 3.8 percentage points (6%) less likely to be convicted and 1.8 percentage points (22%) less likely to receive a prison sentence. These differences are more pronounced in more serious cases and for individuals with longer criminal histories. This study compared the outcomes of codefendants who are assigned separate counsel to avoid conflicts of interest. It suggests that public defenders may provide better representation than court-appointed attorneys, especially when the stakes are higher.
In October 2017, the San Francisco Public Defender’s Office piloted the Pre-Trial Release Unit (PRU) to enhance access to pre-arraignment legal representation for indigent arrestees. Using data provided by the Office, this study finds the pilot program doubled the likelihood of release at arraignment – from 14% to 28% for arrestees who received arrest-responsive interventions from the PRU. The intervention is projected to save approximately 11,200 jail bed-days per year at an annual cost of approximately $335,000. Furthermore, the PRU’s efforts to advocate for the dismissal of parole holds reduced pre-trial incarceration by 44%, or an average of 9.5 days, among eligible parolees who were held in custody for violation of their parole orders.