The productivity slowdown of the 1970s and 1980s and the resumption of productivity growth in the 1990s have provoked controversy among policymakers and researchers. Economists have been forced to reexamine fundamental questions of measurement technique. Some researchers argue that econometric approaches to productivity measurement usefully address shortcomings of the dominant index number techniques while others maintain that current productivity statistics underreport damage to the environment. In this book, the contributors propose innovative approaches to these issues. The result is a state-of-the-art exposition of contemporary productivity analysis. Charles R. Hulten is professor of economics at the University of Maryland. He has been a senior research associate at the Urban Institute and is chair of the Conference on Research in Income and Wealth of the National Bureau of Economic Research. Michael Harper is chief of the Division of Productivity Research at the Bureau of Labor Statistics. Edwin R. Dean, formerly associate commissioner for Productivity and Technology at the Bureau of Labor Statistics, is adjunct professor of economics at The George Washington University.

Presents the proceedings of two workshops on productivity measurement and analysis, which brought together representatives of statistical offices, central banks and other officials involved with the analysis and measurement of productivity at aggregate and industry levels.

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

The 32nd issue of the International Productivity Monitor is a special issue produced in collaboration with the OECD. All articles published in this issue were selected from papers presented at the First Annual Conference of the OECD Global Forum on Productivity held in Lisbon, Portugal, July ...

A timely investigation of the potential economic effects, both realized and unrealized, of artificial intelligence within the United States healthcare system. In sweeping conversations about the impact of artificial intelligence on many sectors of the economy, healthcare has received relatively little attention. Yet it seems unlikely that an industry that represents nearly one-fifth of the economy could escape the efficiency and cost-driven disruptions of AI. The Economics of Artificial Intelligence: Health Care Challenges brings together contributions from health economists, physicians, philosophers, and scholars in law, public health, and machine learning to identify the primary barriers to entry of AI in the healthcare sector. Across original papers and in wide-ranging responses, the contributors analyze barriers of four types: incentives, management, data availability, and regulation. They also suggest that AI has the potential to improve outcomes and lower costs. Understanding both the benefits of and barriers to AI adoption is essential for designing policies that will affect the evolution of the healthcare system.

Skilled technical occupationsâ€"defined as occupations that require a high level of knowledge in a technical domain but do not require a bachelor's degree for entryâ€"are a key component of the U.S. economy. In response to globalization and advances in science and technology, American firms are demanding workers with greater proficiency in literacy and numeracy, as well as strong interpersonal, technical, and problem-solving skills. However, employer surveys and industry and government reports have raised concerns that the nation may not have an adequate supply of skilled technical workers to achieve its competitiveness and economic growth objectives. In response to the broader need for policy information and advice, Building America's Skilled Technical Workforce examines the coverage, effectiveness, flexibility, and coordination of the policies and various programs that prepare Americans for skilled technical jobs. This report provides action-oriented recommendations for improving the American system of technical education, training, and certification.

This book provides a careful historical analysis of the co-evolution of educational attainment and the wage structure in the United States through the twentieth century. The authors propose that the twentieth century was not only the American Century but also the Human Capital Century. That is, the American educational system is what made America the richest nation in the world. Its educational system had always been less elite than that of most European nations. By 1900 the U.S. had begun to educate its masses at the secondary level, not just in the primary schools that had remarkable success in the nineteenth century. The book argues that technological change, education, and inequality have been involved in a kind of race. During the first eight decades of the twentieth century, the increase of educated workers was higher than the demand for them. This had the effect of boosting income for most people and lowering inequality. However, the reverse has been true since about 1980. This educational slowdown was accompanied by rising inequality. The authors discuss the complex reasons for this, and what might be done to ameliorate it.