IDEA Handbook Webinar Series
Join the webinar series hosted by the IDEA Initiative, which began in September 2020 and continues through February 2021. In this series the authors of the Handbook on Using Administrative Data for Research and Evidence-Based Policy will present case studies on successful administrative data partnerships and technical expertise for data access and use. To receive updates and webinar invitations, please sign up for the IDEA Handbook mailing list.
IDEA Handbook webinar schedule
The Use of Administrative Data at the International Monetary Fund
This webinar describes the use of administrative data at the International Monetary Fund (IMF, the Fund) in the context of its three main operations: macroeconomic surveillance and research, lending to member countries, and technical assistance to build capacity in policymaking in member countries. The Fund has a long-standing tradition of using administrative data in some activities, but the systematic use for monitoring economic developments in member countries and research is still in its infancy. In the future, through its bilateral engagement with its 189 member countries, participation in international data initiatives, and partnerships with universities and research networks, the IMF has the potential to gradually enhance the comparability, access, and use of (selected) administrative data produced by national authorities.
- Presenters: Era Dabla-Norris, Mission Chief to Vietnam and Division Chief in the IMF's Asia and Pacific Department, Federico J. Diez, economist at the Structural Reforms Unit in the IMF Research Department, and Romain Duval, Assistant Director in the IMF Research Department.
- Date: February 22, 2021, at 11am EST
- Join the webinar
- Read the chapter
The Private Capital Research Institute: Making Private Data Accessible in an Opaque Industry
An increasing share of economic activity today is taking place in settings that elude traditional federal data collection mechanisms or fail to capture the richest of the activity at work. Against this backdrop, economists are increasingly turning to private data. This webinar underscores the experience of the Private Capital Research Institute (PCRI), specifically the process of creating a database to facilitate access to private equity information for academics to address the myriad major concerns regarding private data. While this effort is certainly a work in progress, hopefully the experience can guide researchers who want to address similar issues in other fields.
City of Cape Town, South Africa: Aligning Internal Data Capabilities with External Research Partnerships
A new data policy at City of Cape Town government in 2016 led to a productive cooperation between the City and academic researchers to create systematic data access. This partnership between local government and university researchers prioritized strategic use of city administrative data to inform decision making for key policy challenges, including a 2018 drought crisis and the COVID-19 pandemic. Kelsey Jack presents on her chapter in the Handbook on Using Administrative Data for Research and Evidence-Based Policy, written with Hugh Cole, Brendan Maughan-Brown, and Derek Strong.
Ohio and the Longitudinal Data Archive: Developing Mutually Beneficial Partnerships Between State Government and the Research Community
A research center at Ohio State University, the Ohio Longitudinal Data Archive (OLDA) is a long-running and successful administrative data partnership that first emerged in 2007. The OLDA has a primary research focus on the outcomes of education and training, but also engages with researchers on human services, housing, and health care as need arises. This collaboration between the Ohio state government and Ohio State University makes longitudinal data from multiple state agencies available for research, and offers an example of a robust institutional partnership for researchers and data providers looking to launch their own data center.
The Stanford-SFUSD Partnership: Development of Data-Sharing Structures and Processes
The research-practice partnership between Stanford University and the San Francisco Unified School District is a long-term, mutualistic, and strategic relationship between researchers and practitioners in education, resulting in research that is both related to practical challenges and generalizable to the broader field. The Partnership exemplifies the university-based data center model, which benefits from the academic and technical resources at a large research university. SFUSD administrative data housed at Stanford University captures data on over 55,000 students, over 3,500 PreK–12 teachers, and a total of almost 10,000 staff from the academic year 2000/2001 to the present. In 2018, the Stanford data warehouse that hosts school district data received requests for data by nine projects. Moonhawk Kim presents his chapter in the Handbook on Using Administrative Data for Research and Evidence-Based Policy, written with Eric Bettinger, Norma Ming, Michelle Reininger, Jim Shen, and Laura Wentworth.
Model Data Use Agreements-- A Practical Guide
What are data use agreements? Data use agreements (DUA)—also referred to as data sharing agreements or data use licenses—are documents that describe what data are being shared, for what purpose, for how long, and any access restrictions or security protocols that must be followed by the recipient of the data. Creating, negotiating, and finalizing a DUA is one of the most common challenges facing new data partnerships, but there are few practical references available to guide data providers and researchers. Amy O'Hara presents her chapter on understanding DUAs, giving a valuable set of model agreements for new engagements with administrative data and expert insight on the legal agreements that underpin data access.
Balancing Privacy and Data Usability: An Overview of Disclosure Avoidance Methods
The purpose of the Handbook is to provide guidance on how to enable broader but ethical and legal access to data. The Five Safes framework is one way of thinking about security of different aspects of a project, and is used throughout the Handbook and in research with administrative data. Within the Five Safes framework, data providers need to create safe data that can be provided to trusted safe people for use within safe settings, as part of safe projects. Finally, any findings that are shared publicly must be safe outputs.
The processes used to create safe data and safe outputs (manipulations that render data less sensitive and therefore more appropriate for public release) are generally referred to as statistical disclosure limitation (SDL). In this webinar, Ian Schmutte will present his chapter in the Handbook, coauthored with Lars Vilhuber, describing techniques traditionally used within the field of SDL, pointing at methods as well as metrics to assess the resultant statistical quality and sensitivity of the data. This presentation offers technical guidance applicable to any data provider or researcher looking for practical tools to apply to their own data to reduce the risk to privacy.
- Presenter: Ian M. Schmutte, Associate Professor in the Department of Economics in the Terry College of Business at the University of Georgia, research economist with the Center for Enterprise Dissemination - Disclosure Avoidance at the U.S. Census Bureau, and fellow of the Global Labor Organization and the Labor Dynamics Institute.
- Date: November 2, 2020, at 11am EST
- Watch recorded webinar
- Read the chapter
Collaborating with the Institutional Review Board (IRB)
The IRB is an administrative body that reviews human research (defined by 45 CFR 46.102 (e)(1)) to ensure the ethical protection of participants from the reasonably foreseeable risks of harm caused by research. For example, an inadvertent disclosure of sensitive or identifiable information is a common risk in social and behavioral research because the disclosure can result in social, psychological, or legal harm. The goal of Kathleen Murphy's chapter in the Handbook is to provide researchers, data providers, data stewards, and other stakeholders with the tools they need to understand the IRB process. This presentation focuses on what the IRB does and does not do and what researchers, data providers, and related stakeholders can expect from IRB review. IRB review is a key step in launching projects, and learning about the IRB perspective will help researchers and policymakers understand how to successfully navigate this process.
Aurora Health Care: Using Electronic Medical Records for a Randomized Evaluation of Clinical Decision Support
This case study describes a randomized evaluation using administrative data, focusing on the process for sharing and using individual-level data from electronic medical records (EMR) for project with Aurora Health Care (a large, private, not-for-profit, integrated health care provider in Wisconsin and Illinois, comprising fifteen hospitals and more than 150 clinics in thirty communities).
In this case, the delivery of the intervention and the measurement of outcomes were conducted through the EMR system, making access to administrative data a critical feature of the research project. This presentation describes the process by which the research team sought approval to conduct the study and access data, worked to understand data not originally designed for research, and addressed the challenges of working with de-identified data. Laura Feeney presents this chapter, coauthored with Amy Finkelstein, on a successful partnership with a large, private, healthcare organization, leveraging the rich administrative data captured through electronic medical records for research on mutually interesting questions.
New Brunswick Institute for Research, Data and Training: A Ten-Year Partnership Between Government and Academia
This presentation describes the establishment and development of the New Brunswick Institute for Research, Data and Training (NB-IRDT) in Fredericton, NB, Canada. Launched in 2015 with the delivery of the first data set, NB-IRDT now holds and provides research access to more than 45 linkable person-level data sets from across the spectrum of service provision in NB. This includes access to data on health, social assistance, education and training, aged care, and workers compensation. Donna Curtis-Maillet and Ted McDonald will present their chapter in the Handbook on Using Administrative Data for Research and Evidence-based Policy, highlighting notable and unique aspects of the NB-IRDT partnership, including the legal context for receiving data from across NB public bodies, data access that is not restricted to academic users alone but also includes users from government, the non-profit sector, and the private sector, and active engagement with the NB government in collaborative research on government priority areas.
- Presenters: Donna Curtis Maillet, Privacy Officer for the NB Institute for Research, Data and Training, and Ted McDonald, professor of economics at the University of New Brunswick in Fredericton and founding director of NB-IRDT.
- Date: November 23rd, 2020, at 11am EST
- Watch recorded webinar
- Read the chapter
Administrative Data in Research at the World Bank: The Case of Development Impact Evaluation (DIME)
As a global research program, DIME provides tailored impact evaluation services to governments. With about 200 long-term collaborations with government agencies across sixty countries, DIME works with governments to develop the data infrastructure and know-how to improve the evidence-base for public policy over time. In partnership with about thirty multilateral and bilateral organizations, DIME also invests in transforming the way development finance is used. This presentation on the Handbook chapter by Arianna Legovini and Maria Ruth Jones will describe how DIME generates demand from government agencies and supplies them with research services that augment their data, program management, and policy functions. DIME's work ranges from developing a pilot administrative data system, to digitizing paper-based administrative data, to leveraging existing cross-sector administrative data to develop a country data set, and to developing sector-specific data sets across multiple countries.
Institute for Employment Research, Germany: Access to Administrative Labor Market Data for International Researchers
The Research Data Center at the Institute for Employment Research (RDC-IAB) in Nuremberg, Germany, founded in 2004, is a research department of the Institute for Employment Research (IAB), which belongs to the Federal Employment Agency (BA) of Germany. The RDC-IAB has three core functions: creating standardized research data for the scientific community, providing access to these data, and conducting research with and about IAB data. Various kinds of standardized labor market data are provided by the RDC-IAB. Administrative research data are based on the notification procedure of the German Social Security System and process-generated data are based on the BA. Additionally, surveys conducted by the IAB or partner institutes become part of the data portfolio. Furthermore, linked data between surveys and administrative data are produced. All data products are specifically created for the purpose of allowing external researchers access to the data. In this webinar, Handbook authors Dana Müller and Philipp vom Berge discuss how data is made available to researchers at multiple universities around the world, and how the data held by the RDC-IAB is securely accessed through legal, institutional, and practical processes.
- Presenters: Dana Müller, the Head of the Research Data Center (RDC-IAB) of the Federal Employment Agency at the Institute for Employment Research (IAB) in Nuremberg, Germany, and Philipp vom Berge, Deputy Head of the RDC-IAB of the Federal Employment Agency at the IAB.
- Date: Monday, December 7, 2020, at 11am EST
- Watch the recorded webinar
- Read the chapter
Using Administrative Data to Improve Social Protection in Indonesia
This webinar will depart from our typical Monday morning talks and be hosted by J-PAL Southeast Asia (J-PAL SEA) Scientific Directors Rema Hanna and Ben Olken, in collaboration with their partners in the Government of Indonesia. Join us on Monday, January 25, 2021 at 9PM EST (Tuesday January 26 at 9AM WIB) to hear the authors of the Handbook chapter Using Administrative Data to Improve Social Protection in Indonesia share the story of their unique government partnership and discuss current work future plans.
- Presenters: Rema Hanna and Ben Olken, the scientific directors of J-PAL SEA, Vivi Alatas, lead economist at the World Bank during the work discussed here, and Sudarno Sumarto, senior research fellow at the SMERU Research Institute and a policy adviser at TNP2K.
- Date and time: Monday January 25 2021, at 9PM EST (note the different time)
- Read the chapter
- Webinar recording coming soon
Designing Access with Differential Privacy
Differential privacy technology has passed a preliminary transition from being the subject of academic work to initial implementations by large organizations and high-tech companies that have the expertise to develop and implement customized differentially private methods. With a growing collection of software packages for generating differentially private releases from summary statistics to machine learning models, differential privacy is now transitioning to being usable more widely and by smaller organizations. This webinar explains how administrative data containing personal information can be collected, analyzed, and published in a way that ensures the individuals in the data will be afforded the strong protections of differential privacy.
- Presenter: Alexandra Wood, Berkman Center fellow contributing to the Privacy Tools for Sharing Research Data project at the Berkman Klein Center for Internet & Society at Harvard University
- Date: February 1, 2021, at 11am EST
- Read the chapter (coming soon)
- Webinar recording coming soon
Physically Protecting Sensitive Data
Keeping sensitive data safe relies heavily on the physical environments in which data are stored, processed, transmitted, and accessed, and from which researchers can access computers that store and process the data. However, it is also the setting that is most dependent on rapidly evolving technology. This webinar will give a snapshot of the technologies available and in use as of 2020, as well as characterize the technologies along a multi-dimensional scale, allowing for some comparability across methods.
- Presenters: Jim Shen, Senior Manager of the IDEA Initiative at J-PAL, and Lars Vilhuber, Executive Director of the Labor Dynamics Institute at Cornell University, research faculty in Cornell University’s Economics Department, and American Economic Association’s Data Editor.
- Date: February 8, 2021, at 11am EST
- Read the chapter
- Join the webinar