Innovations in Federal Statistics


Book Description

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.




Open Data Now: The Secret to Hot Startups, Smart Investing, Savvy Marketing, and Fast Innovation


Book Description

Get unprecedented access to thousands of databases. It's called Open Data, and it's revolutionizing business. The business leader’s guide to using Open Data to analyze patterns and trends, manage risk, solve problems—and seize the competitive edge Two major trends—the exponential growth of digital data and an emerging culture of disclosure and transparency—have converged to create a world where voluminous information about businesses, government, and the population is becoming visible, accessible, and usable. It’s called Open Data, and this book helps leaders harness its power to market and grow their companies. Open Data Now gives you the knowledge and tools to take advantage of this phenomenon in its early stages—and beat the competition to leveraging its many benefits. Joel Gurin is an expert on making complex data sets useful in solving consumer problems, analyzing corporate information, and addressing social issues. He has collaborated with leaders in data, technology, and policy in the U.S. and UK governments, including officials in the White House and 10 Downing Street and at more than 20 U.S. federal agencies.




Data-Driven Innovation Big Data for Growth and Well-Being


Book Description

This report improves the evidence base on the role of Data Driven Innovation for promoting growth and well-being, and provide policy guidance on how to maximise the benefits of DDI and mitigate the associated economic and societal risks.




Facilitating Innovation in the Federal Statistical System


Book Description

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.




The Measurement of Scientific, Technological and Innovation Activities Oslo Manual 2018 Guidelines for Collecting, Reporting and Using Data on Innovation, 4th Edition


Book Description

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.




A Guide to Teaching Statistics


Book Description

A Guide to Teaching Statistics: Innovations and Best Practices addresses the critical aspects of teaching statistics to undergraduate students, acting as an invaluable tool for both novice and seasoned teachers of statistics. Guidance on textbook selection, syllabus construction, and course outline Classroom exercises, computer applications, and Internet resources designed to promote active learning Tips for incorporating real data into course content Recommendations on integrating ethics and diversity topics into statistics education Strategies to assess student's statistical literacy, thinking, and reasoning skills Additional material online at www.teachstats.org




Big Data for Twenty-First-Century Economic Statistics


Book Description

Introduction.Big data for twenty-first-century economic statistics: the future is now /Katharine G. Abraham, Ron S. Jarmin, Brian C. Moyer, and Matthew D. Shapiro --Toward comprehensive use of big data in economic statistics.Reengineering key national economic indicators /Gabriel Ehrlich, John Haltiwanger, Ron S. Jarmin, David Johnson, and Matthew D. Shapiro ;Big data in the US consumer price index: experiences and plans /Crystal G. Konny, Brendan K. Williams, and David M. Friedman ;Improving retail trade data products using alternative data sources /Rebecca J. Hutchinson ;From transaction data to economic statistics: constructing real-time, high-frequency, geographic measures of consumer spending /Aditya Aladangady, Shifrah Aron-Dine, Wendy Dunn, Laura Feiveson, Paul Lengermann, and Claudia Sahm ;Improving the accuracy of economic measurement with multiple data sources: the case of payroll employment data /Tomaz Cajner, Leland D. Crane, Ryan A. Decker, Adrian Hamins-Puertolas, and Christopher Kurz --Uses of big data for classification.Transforming naturally occurring text data into economic statistics: the case of online job vacancy postings /Arthur Turrell, Bradley Speigner, Jyldyz Djumalieva, David Copple, and James Thurgood ;Automating response evaluation for franchising questions on the 2017 economic census /Joseph Staudt, Yifang Wei, Lisa Singh, Shawn Klimek, J. Bradford Jensen, and Andrew Baer ;Using public data to generate industrial classification codes /John Cuffe, Sudip Bhattacharjee, Ugochukwu Etudo, Justin C. Smith, Nevada Basdeo, Nathaniel Burbank, and Shawn R. Roberts --Uses of big data for sectoral measurement.Nowcasting the local economy: using Yelp data to measure economic activity /Edward L. Glaeser, Hyunjin Kim, and Michael Luca ;Unit values for import and export price indexes: a proof of concept /Don A. Fast and Susan E. Fleck ;Quantifying productivity growth in the delivery of important episodes of care within the Medicare program using insurance claims and administrative data /John A. Romley, Abe Dunn, Dana Goldman, and Neeraj Sood ;Valuing housing services in the era of big data: a user cost approach leveraging Zillow microdata /Marina Gindelsky, Jeremy G. Moulton, and Scott A. Wentland --Methodological challenges and advances.Off to the races: a comparison of machine learning and alternative data for predicting economic indicators /Jeffrey C. Chen, Abe Dunn, Kyle Hood, Alexander Driessen, and Andrea Batch ;A machine learning analysis of seasonal and cyclical sales in weekly scanner data /Rishab Guha and Serena Ng ;Estimating the benefits of new products /W. Erwin Diewert and Robert C. Feenstra.




Big Data Meets Survey Science


Book Description

Offers a clear view of the utility and place for survey data within the broader Big Data ecosystem This book presents a collection of snapshots from two sides of the Big Data perspective. It assembles an array of tangible tools, methods, and approaches that illustrate how Big Data sources and methods are being used in the survey and social sciences to improve official statistics and estimates for human populations. It also provides examples of how survey data are being used to evaluate and improve the quality of insights derived from Big Data. Big Data Meets Survey Science: A Collection of Innovative Methods shows how survey data and Big Data are used together for the benefit of one or more sources of data, with numerous chapters providing consistent illustrations and examples of survey data enriching the evaluation of Big Data sources. Examples of how machine learning, data mining, and other data science techniques are inserted into virtually every stage of the survey lifecycle are presented. Topics covered include: Total Error Frameworks for Found Data; Performance and Sensitivities of Home Detection on Mobile Phone Data; Assessing Community Wellbeing Using Google Street View and Satellite Imagery; Using Surveys to Build and Assess RBS Religious Flag; and more. Presents groundbreaking survey methods being utilized today in the field of Big Data Explores how machine learning methods can be applied to the design, collection, and analysis of social science data Filled with examples and illustrations that show how survey data benefits Big Data evaluation Covers methods and applications used in combining Big Data with survey statistics Examines regulations as well as ethical and privacy issues Big Data Meets Survey Science: A Collection of Innovative Methods is an excellent book for both the survey and social science communities as they learn to capitalize on this new revolution. It will also appeal to the broader data and computer science communities looking for new areas of application for emerging methods and data sources.




Federal Statistics, Multiple Data Sources, and Privacy Protection


Book Description

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.




Summary of a Workshop on Information Technology Research for Federal Statistics


Book Description

Part of an in-depth study of how information technology research and development could more effectively support advances in the use of information technology (IT) in government, Summary of a Workshop on Information Technology Research for Federal Statistics explores IT research opportunities of relevance to the collection, analysis, and dissemination of federal statistics. On February 9 and 10, 1999, participants from a number of communitiesâ€"IT research, IT research management, federal statistics, and academic statisticsâ€"met to identify ways to foster interaction among computing and communications researchers, federal managers, and professionals in specific domains that could lead to collaborative research efforts. By establishing research links between these communities and creating collaborative mechanisms aimed at meeting relevant requirements, this workshop promoted thinking in the computing and communications research community and throughout government about possibilities for advances in technology that will support a variety of digital initiatives by the government.