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.

On May 8, 2009, the symposium, The Federal Statistical System: Recognizing Its Contributions, Moving It Forward was held in Washington, DC. One of the topics considered at that symposium was the health of innovation in the federal statistical system. A consequence of the symposium was an agreement by the Committee on National Statistics to hold a workshop on the future of innovation in the federal statistical system. This workshop was held on June 29, 2010. The original statement of task for the workshop focused on three challenges to the statistical system: (1) the obstacles to innovative, focused research and development initiatives that could make statistical programs more cost effective; (2) a gap between emerging data visualization and communications technologies and the ability of statistical agencies to understand and capitalize on these developments for their data dissemination programs; and (3) the maturation of the information technology (IT) discipline and the difficulties confronting individual agencies in keeping current with best practice in IT regarding data confidentiality. This report, Facilitating Innovation in the Federal Statistical System, is a descriptive summary of what transpired at the workshop. It is therefore limited to the views and opinions of the workshop participants. However, it does not strictly follow the agenda of the workshop, which had four sessions. Instead, it is organized around the themes of the discussions, which migrated across the four sessions.

This is the second Consensus Study Report of the Panel on Improving Federal Statistics for Policy and Social Science Research Using Multiple Data Sources and State-of-the-Art Estimation Methods. Our first report, Innovations in Federal Statistics: Combining Data Sources While Protecting Privacy, was released in January 2017. In that report, the panel noted that there has been increasing attention in recent years to using data already collected by government entities for statistical purposes, such as evaluation of government programs. These data include such records as employment and earnings information on state unemployment insurance, income reported on federal tax forms, Social Security earnings and benefits, medical conditions and payments made for services from Medicare and Medicaid records, and food assistance program benefits.

The National Center for Science and Engineering Statistics (NCSES), at the U.S. National Foundation, is 1 of 14 major statistical agencies in the federal government, of which at least 5 collect relevant information on science, technology, and innovation activities in the United States and abroad. The America COMPETES Reauthorization Act of 2010 expanded and codified NCSES's role as a U.S. federal statistical agency. Important aspects of the agency's mandate include collection, acquisition, analysis, and reporting and dissemination of data on research and development trends, on U.S. competitiveness in science, technology, and research and development, and on the condition and progress of U.S. science, technology, engineering, and mathematics (STEM) education. Improving Measures of Science, Technology and Innovation: Interim Report examines the status of the NCSES's science, technology, and innovation (STI) indicators. This report assesses and provides recommendations regarding the need for revised, refocused, and newly developed indicators designed to better reflect fundamental and rapid changes that are reshaping global science, technology and innovation systems. The book also determines the international scope of STI indicators and the need for developing new indicators that measure developments in innovative activities in the United States and abroad, and Offers foresight on the types of data, metrics and indicators that will be particularly influential in evidentiary policy decision-making for years to come. In carrying out its charge, the authoring panel undertook a broad and comprehensive review of STI indicators from different countries, including Japan, China, India and several countries in Europe, Latin America and Africa. Improving Measures of Science, Technology, and Innovation makes recommendations for near-term action by NCSES along two dimensions: (1) development of new policy-relevant indicators that are based on NCSES survey data or on data collections at other statistical agencies; and (2) exploration of new data extraction and management tools for generating statistics, using automated methods of harvesting unstructured or scientometric data and data derived from administrative records.

The environment for obtaining information and providing statistical data for policy makers and the public has changed significantly in the past decade, raising questions about the fundamental survey paradigm that underlies federal statistics. New data sources provide opportunities to develop a new paradigm that can improve timeliness, geographic or subpopulation detail, and statistical efficiency. It also has the potential to reduce the costs of producing federal statistics. The panel's first report described federal statistical agencies' current paradigm, which relies heavily on sample surveys for producing national statistics, and challenges agencies are facing; the legal frameworks and mechanisms for protecting the privacy and confidentiality of statistical data and for providing researchers access to data, and challenges to those frameworks and mechanisms; and statistical agencies access to alternative sources of data. The panel recommended a new approach for federal statistical programs that would combine diverse data sources from government and private sector sources and the creation of a new entity that would provide the foundational elements needed for this new approach, including legal authority to access data and protect privacy. This second of the panel's two reports builds on the analysis, conclusions, and recommendations in the first one. This report assesses alternative methods for implementing a new approach that would combine diverse data sources from government and private sector sources, including describing statistical models for combining data from multiple sources; examining statistical and computer science approaches that foster privacy protections; evaluating frameworks for assessing the quality and utility of alternative data sources; and various models for implementing the recommended new entity. Together, the two reports offer ideas and recommendations to help federal statistical agencies examine and evaluate data from alternative sources and then combine them as appropriate to provide the country with more timely, actionable, and useful information for policy makers, businesses, and individuals.

What is innovation and how should it be measured? Understanding the scale of innovation activities, the characteristics of innovative firms and the internal and systemic factors that can influence innovation is a prerequisite for the pursuit and analysis of policies aimed at fostering innovation.

Workshop participants offered a variety of suggestions to the National Science Foundation (NSF) and other federal agencies to improve the usefulness and relevance of data on industrial research and innovation, as well as to increase efficiency in collecting and processing the data. The suggestions dealt with the need to (1) clarify policy information needs; (2) improve the quality, coverage, and collection of existing data items; and (3) identify and collect new types of data.