This Handbook intends to inform Data Providers and researchers on how to provide privacy-protected access to, handle, and analyze administrative data, and to link them with existing resources, such as a database of data use agreements (DUA) and templates. Available publicly, the Handbook will provide guidance on data access requirements and procedures, data privacy, data security, property rights, regulations for public data use, data architecture, data use and storage, cost structure and recovery, ethics and privacy-protection, making data accessible for research, and dissemination for restricted access use. The knowledge base will serve as a resource for all researchers looking to work with administrative data and for Data Providers looking to make such data available.

Every day, social service agencies collect millions of pieces of data about the children and families they serve. Agencies depend on this data to inform decision-making by personnel throughout the organization and to provide meaningful research and evaluation on program effectiveness and outcomes. As capacity for collecting and utilizing data has increased so has the recognition that this data can and should be used more broadly. Further, it should include not just single-system data, but data across different human service agencies. Administrative/big data systems can be powerful tools in increasing the efficiency and effectiveness of public child welfare services. Understanding, harnessing, and using big data holds tremendous promise in creating transformative change in the social services. Data analytics and data mining can lead to a better understanding of what services work for specific populations (targeting and predictive modelling), provide a more nuanced understanding of service outcomes for the workforce and major stakeholders (transparency), and facilitate collaboration across existing service delivery silos to reduce duplication of services and enhance consumer access to services (efficiency). This book was originally published as a special issue of the Journal of Public Child Welfare.

In the light of better and more detailed administrative databases, this open access book provides statistical tools for evaluating the effects of public policies advocated by governments and public institutions. Experts from academia, national statistics offices and various research centers present modern econometric methods for an efficient data-driven policy evaluation and monitoring, assess the causal effects of policy measures and report on best practices of successful data management and usage. Topics include data confidentiality, data linkage, and national practices in policy areas such as public health, education and employment. It offers scholars as well as practitioners from public administrations, consultancy firms and nongovernmental organizations insights into counterfactual impact evaluation methods and the potential of data-based policy and program evaluation.

Bureaucracy, confusing paperwork, and complex regulations—or what public policy scholars Pamela Herd and Donald Moynihan call administrative burdens—often introduce delay and frustration into our experiences with government agencies. Administrative burdens diminish the effectiveness of public programs and can even block individuals from fundamental rights like voting. In AdministrativeBurden, Herd and Moynihan document that the administrative burdens citizens regularly encounter in their interactions with the state are not simply unintended byproducts of governance, but the result of deliberate policy choices. Because burdens affect people’s perceptions of government and often perpetuate long-standing inequalities, understanding why administrative burdens exist and how they can be reduced is essential for maintaining a healthy public sector. Through in-depth case studies of federal programs and controversial legislation, the authors show that administrative burdens are the nuts-and-bolts of policy design. Regarding controversial issues such as voter enfranchisement or abortion rights, lawmakers often use administrative burdens to limit access to rights or services they oppose. For instance, legislators have implemented administrative burdens such as complicated registration requirements and strict voter-identification laws to suppress turnout of African American voters. Similarly, the right to an abortion is legally protected, but many states require women seeking abortions to comply with burdens such as mandatory waiting periods, ultrasounds, and scripted counseling. As Herd and Moynihan demonstrate, administrative burdens often disproportionately affect the disadvantaged who lack the resources to deal with the financial and psychological costs of navigating these obstacles. However, policymakers have sometimes reduced administrative burdens or shifted them away from citizens and onto the government. One example is Social Security, which early administrators of the program implemented in the 1930s with the goal of minimizing burdens for beneficiaries. As a result, the take-up rate is about 100 percent because the Social Security Administration keeps track of peoples’ earnings for them, automatically calculates benefits and eligibility, and simply requires an easy online enrollment or visiting one of 1,200 field offices. Making more programs and public services operate this efficiently, the authors argue, requires adoption of a nonpartisan, evidence-based metric for determining when and how to institute administrative burdens, with a bias toward reducing them. By ensuring that the public’s interaction with government is no more onerous than it need be, policymakers and administrators can reduce inequality, boost civic engagement, and build an efficient state that works for all citizens.

Federal government statistics provide critical information to the country and serve a key role in a democracy. For decades, sample surveys with instruments carefully designed for particular data needs have been one of the primary methods for collecting data for federal statistics. However, the costs of conducting such surveys have been increasing while response rates have been declining, and many surveys are not able to fulfill growing demands for more timely information and for more detailed information at state and local levels. Innovations in Federal Statistics examines the opportunities and risks of using government administrative and private sector data sources to foster a paradigm shift in federal statistical programs that would combine diverse data sources in a secure manner to enhance federal statistics. This first publication of a two-part series discusses the challenges faced by the federal statistical system and the foundational elements needed for a new paradigm.

The Oxford Handbook of Evidence-based Management shows how leaders and managers can make effective use of best available evidence in the decisions they make — and what educators and researchers need to do to help them come to the right solution.

This book gathers an expert group of social scientists to showcase emerging forms of analysis and evaluation for public policy analysis. Each chapter highlights a different method or approach, putting it in context and highlighting its key features before illustrating its application and potential value to policy makers. Aimed at upper-level undergraduates in public policy and social work, it also has much to offer policy makers and practitioners themselves.