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.

"Policy-makers often call for expanding public spending on infrastructure, which includes a broad range of investments from roads and bridges to digital networks that will expand access to high-speed broadband. Some point to near-term macro-economic benefits and job creation, others focus on long-term effects on productivity and economic growth. This volume explores the links between infrastructure spending and economic outcomes, as well as key economic issues in the funding and management of infrastructure projects. It draws together research studies that describe the short-run stimulus effects of infrastructure spending, develop new estimates of the stock of U.S. infrastructure capital, and explore the incentive aspects of public-private partnerships (PPPs). A salient issue is the treatment of risk in evaluating publicly-funded infrastructure projects and in connection with PPPs. The goal of the volume is to provide a reference for researchers seeking to expand research on infrastructure issues, and for policy-makers tasked with determining the appropriate level of infrastructure spending"--

The conditions for sustainable growth and development are among the most debated topics in economics, and the consensus is that institutions matter greatly in explaining why some economies are more successful than others over time. This book explores the relationship between economic conditions, growth, and inequality.

We take for granted today that the assessments, measurements, and forecasts of economists are crucial to the decision-making of governments and businesses alike. But less than a century ago that wasn’t the case—economists simply didn’t have the necessary information or statistical tools to understand the ever more complicated modern economy. With Political Arithmetic, Nobel Prize–winning economist Robert Fogel and his collaborators tell the story of economist Simon Kuznets, the founding of the National Bureau of Economic Research, and the creation of the concept of GNP, which for the first time enabled us to measure the performance of entire economies. The book weaves together the many strands of political and economic thought and historical pressures that together created the demand for more detailed economic thinking—Progressive-era hopes for activist government, the production demands of World War I, Herbert Hoover’s interest in business cycles as President Harding’s commerce secretary, and the catastrophic economic failures of the Great Depression—and shows how, through trial and error, measurement and analysis, economists such as Kuznets rose to the occasion and in the process built a discipline whose knowledge could be put to practical use in everyday decision-making. The product of a lifetime of studying the workings of economies and skillfully employing the tools of economics, Political Arithmetic is simultaneously a history of a key period of economic thought and a testament to the power of applied ideas.

The recent recession has brought fiscal policy back to the forefront, with economists and policy makers struggling to reach a consensus on highly political issues like tax rates and government spending. At the heart of the debate are fiscal multipliers, whose size and sensitivity determine the power of such policies to influence economic growth. Fiscal Policy after the Financial Crisis focuses on the effects of fiscal stimuli and increased government spending, with contributions that consider the measurement of the multiplier effect and its size. In the face of uncertainty over the sustainability of recent economic policies, further contributions to this volume discuss the merits of alternate means of debt reduction through decreased government spending or increased taxes. A final section examines how the short-term political forces driving fiscal policy might be balanced with aspects of the long-term planning governing monetary policy. A direct intervention in timely debates, Fiscal Policy after the Financial Crisis offers invaluable insights about various responses to the recent financial crisis.

"Innovation and entrepreneurship are ubiquitous today, both as fields of study and as starting points for conversations among experts in government and economic development. But while these areas on continue to attract public and private investments, many measurements of their resulting economic growth-including productivity growth and business dynamism-have remained modest. Why this difference? Because not all business sectors are the same, and the transformative gains of some industries have been offset by stagnation or contraction in others. Accordingly, a nuanced understanding of the economy requires a nuanced understanding of where innovation and entrepreneurship occur and where they matter. Answering these questions allows for strategic public investment and the infrastructure for economic growth.The Role of Innovation and Entrepreneurship in Economic Growth, the latest entry in the NBER conference series, seeks to codify these answers. The editors leverage industry studies to identify specific examples of productivity improvements enabled by innovation and entrepreneurship, including those from new production technologies, increased competition, new organizational forms, and other means. Taken together, the volume illuminates whether the contribution of innovation and entrepreneurship to economic growth is likely to be concentrated, be it selected sectors or more broadly"--

A calculation of the social returns to innovation /Benjamin F. Jones and Lawrence H. Summers --Innovation and human capital policy /John Van Reenen --Immigration policy levers for US innovation and start-ups /Sari Pekkala Kerr and William R. Kerr --Scientific grant funding /Pierre Azoulay and Danielle Li --Tax policy for innovation /Bronwyn H. Hall --Taxation and innovation: what do we know? /Ufuk Akcigit and Stefanie Stantcheva --Government incentives for entrepreneurship /Josh Lerner.

This volume presents six new papers on environmental and energy economics and policy in the United States. Rebecca Davis, J. Scott Holladay, and Charles Sims analyze recent trends in and forecasts of coal-fired power plant retirements with and without new climate policy. Severin Borenstein and James Bushnell examine the efficiency of pricing for electricity, natural gas, and gasoline. James Archsmith, Erich Muehlegger, and David Rapson provide a prospective analysis of future pathways for electric vehicle adoption. Kenneth Gillingham considers the consequences of such pathways for the design of fuel vehicle economy standards. Frank Wolak investigates the long-term resource adequacy in wholesale electricity markets with significant intermittent renewables. Finally, Barbara Annicchiarico, Stefano Carattini, Carolyn Fischer, and Garth Heutel review the state of research on the interactions between business cycles and environmental policy.

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.