Measuring Economic Growth and Productivity: Foundations, KLEMS Production Models, and Extensions presents new insights into the causes, mechanisms and results of growth in national and regional accounts. It demonstrates the versatility and usefulness of the KLEMS databases, which generate internationally comparable industry-level data on outputs, inputs and productivity. By rethinking economic development beyond existing measurements, the book's contributors align the measurement of growth and productivity to contemporary global challenges, addressing the need for measurements as well as the Gross Domestic Product. All contributors in this foundational volume are recognized experts in their fields, all inspired by the path-breaking research of Dale W. Jorgenson. Demonstrates how an approach based on sources of economic growth (KLEMS – capital, labor, energy, materials and services) can be used to analyze economic growth and productivity Includes examples covering the G7, E7, EU, Latin America, Norway, China, Taiwan, Japan, Korea, India and other South Asian countries Examines the effects of digital, information, communication and integrated technologies on national and regional economies

Since the Great Depression, researchers and statisticians have recognized the need for more extensive methods for measuring economic growth and sustainability. The recent recession renewed commitments to closing long-standing gaps in economic measurement, including those related to sustainability and well-being. The latest in the NBER’s influential Studies in Income and Wealth series, which has played a key role in the development of national account statistics in the United States and other nations, this volume explores collaborative solutions between academics, policy researchers, and official statisticians to some of today’s most important economic measurement challenges. Contributors to this volume extend past research on the integration and extension of national accounts to establish an even more comprehensive understanding of the distribution of economic growth and its impact on well-being, including health, human capital, and the environment. The research contributions assess, among other topics, specific conceptual and empirical proposals for extending national accounts.

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.

This text is designed to provide a comprehensive guide to students, researchers, or consultants who wish to carry out and to interpret analyses of economic performance, with an emphasis on productivity growth. The text includes an overview of standard productivity growth measurement techniques and adaptations, and data construc tion procedures. It goes further, however, by expanding the tradition al growth accounting (index number) framework to allow consider ation of how different aspects of firm behavior underlying productivity growth are interrelated, how they can be measured con sistently in a parametric model, and how they permit a well-defined decomposition of standard productivity growth measures. These ideas are developed by considering in detail a number of underlying theoretical results and econometric issues. The impacts of various production characteristics on productivity growth trends are also evaluated by overviewing selected methodological extensions and em pirical evidence. More specifically, in the methodological extensions, emphasis is placed on incorporation of cost and demand characteristics, such as fixity and adjustment costs, returns to scale, and the existence of market power, into analyses of productivity growth. These character istics, generally disregarded in such analyses, can have very important impacts on production structure and firm behavior, and thus on economic performance. They also provide the conceptual basis for vii viii PREFACE measures that are often used independently as indicators of economic performance, such as investment, capacity utilization, and profit measures.

Theory and Measurement of Economic Externalities provides information on some analytical and empirical developments in the field of externalities. This book presents the function of turning out producer's goods in the form of better knowledge, analytical formulation, and approaches for application to current problems. Organized into five parts encompassing 12 chapters, this book begins with an overview of the notion of externalities in connection with analyses of economic welfare. This text then discusses the relationship between publicness and external diseconomies when either consumption or production or decision sets are nonconvex due to a high degree of externalities. Other chapters consider disproving the pessimistic conclusions concerning tax–subsidy schemes. This book discusses as well the solutions for the allocation of resources in an economy with public goods and interdependent preferences. The final chapter deals with a general framework for estimating externality production functions. This book is a valuable resource for economists.

Editor is well known. She is presidnet of the History of Economics Society and has completed a 12 year term as editor of the Eastern Economics Journal Work is controversial - challenges the relevance of mathematics in economics

Can money buy happiness? Is income a reliable measure for life satisfaction? In this book, three economists explore the happiness-prosperity connection, investigating how economists measure life satisfaction and well-being. --