Information Sources in Economics, Second Edition aims to bring together all sources of information in the field of economics into one convenient form, as well as present a picture of the international scene in the disciplines covered in the book. The text discusses the different sources of information such as the different kinds of libraries; bibliographic tools such as encyclopedias, dictionaries, directories, and almanacs; periodicals; unpublished material; and statistics sources. The book also related branches of economics such as macroeconomics, industrial, and agricultural economics, as well as their related literature. The monograph is recommended for students and practitioners in the field of economics who are in need of sources of information on economics, especially those who are engaged in studies.

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.

A comprehensive textbook on data analysis for business, applied economics and public policy that uses case studies with real-world data.

This open access book covers the use of data science, including advanced machine learning, big data analytics, Semantic Web technologies, natural language processing, social media analysis, time series analysis, among others, for applications in economics and finance. In addition, it shows some successful applications of advanced data science solutions used to extract new knowledge from data in order to improve economic forecasting models. The book starts with an introduction on the use of data science technologies in economics and finance and is followed by thirteen chapters showing success stories of the application of specific data science methodologies, touching on particular topics related to novel big data sources and technologies for economic analysis (e.g. social media and news); big data models leveraging on supervised/unsupervised (deep) machine learning; natural language processing to build economic and financial indicators; and forecasting and nowcasting of economic variables through time series analysis. This book is relevant to all stakeholders involved in digital and data-intensive research in economics and finance, helping them to understand the main opportunities and challenges, become familiar with the latest methodological findings, and learn how to use and evaluate the performances of novel tools and frameworks. It primarily targets data scientists and business analysts exploiting data science technologies, and it will also be a useful resource to research students in disciplines and courses related to these topics. Overall, readers will learn modern and effective data science solutions to create tangible innovations for economic and financial applications.

Environmental Economics and Policy is a best-selling text for environmental economics courses. Offering a policy-oriented approach, it introduces economic theory, empirical fieldwork, and case studies that show how underlying economic principles provided the foundation for environmental policies. Key features include: Introductions to the theory and method of environmental economics, including externalities, benefit-cost analysis, valuation methods, and ecosystem goods and services. Extensive coverage of the major issues including climate change mitigation and adaptation, air and water pollution, and environmental justice. Boxed "Examples" and "Debates" throughout the text, which highlight global examples and major talking points. This text will be of use to undergraduate students of economics. Students will leave the course with a global perspective of how environmental economics has played and can continue to play a role in promoting fair and efficient environmental management. The text is fully supported with end-of-chapter summaries, discussion questions, and self-test exercises in the book. Additional online resources include references, as well as PowerPoint slides for each chapter.

This SPR Departmental Paper will provide policymakers with a framework for studying changes to national data policy frameworks.

"The most consistent and courageous—and unapologetic—liberal partisan in American journalism." —Michael Tomasky, New York Review of Books In this "clear, provocative" (Boston Globe) New York Times bestseller, Paul Krugman, today's most widely read economist, examines the past eighty years of American history, from the reforms that tamed the harsh inequality of the Gilded Age and the 1920s to the unraveling of that achievement and the reemergence of immense economic and political inequality since the 1970s. Seeking to understand both what happened to middle-class America and what it will take to achieve a "new New Deal," Krugman has created his finest book to date, a "stimulating manifesto" offering "a compelling historical defense of liberalism and a clarion call for Americans to retake control of their economic destiny" (Publishers Weekly). "As Democrats seek a rationale not merely for returning to power, but for fundamentally changing—or changing back—the relationship between America's government and its citizens, Mr. Krugman's arguments will prove vital in the months and years ahead." —Peter Beinart, New York Times