Most estimates of Indian manufacturing productivity find a slowdown in the 1990s. This has puzzled analysts, given that 1990s reforms were deeper and wider than the 1980s reforms that raised the growth rate of the Indian economy by 2 per cent points. This paper tests the hypothesis of the J curve of Productivity and Growth following major liberalization and finds it to be broadly supported by the data: Technological obsolescence, gradual adoption of new technology and learning by doing result in negative effects on measured productivity.

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.

A predictable pattern of success Entrepreneurs who have read early drafts of The Start-Up J Curve responded, ''I wish I had this book years ago.'' A start-up unfolds in a predictable pattern; the more aware entrepreneurs are of this pattern, the better able they will be to capitalize on it. Author Howard Love calls this pattern the start-up J Curve: The toughest part of the endeavor is the time between the actual start of a new business and when the product and model are firmly established. The Start-Up J Curve gives entrepreneurs the tools they need to get through the early challenges so they can reach the primary value creation that lies beyond. Love brings thirty-five years of start-up experience to this comprehensive guide to starting a business. He outlines the six predictable stages of start-up growth and details the activities that should be undertaken at each stage to ensure success and to avoid common pitfalls. Instead of feeling lost and confused after a setback, start-up founders and investors can anticipate the challenges, overcome the obstacles, and ride the curve to the top.

Locate nations on the J Curve -- left for authoritarian, right for democratic. Then figure out how to force those on the left to open their societies, rather than encouraging them to shut them tighter by further isolating them. The West's isolation of Kim Jong-il's North Korea gives him the cover he needs to extend his brutal regime (the mistake the U.S. made for a long time with Saddam Hussein and Castro); in Saudi Arabia, western governments should encourage manageable change before the country breaks apart; they should help strengthen China's economy so it can further liberalize; they must encourage Israel to decide what kind of country it will be. Filled with imaginative and surprising examples of how to correct outworn political ideas, The J Curve points the way for western governments to lead the way to a realistic political balance and a healthier economic future.

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 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.

China’s growth potential has become a hotly debated topic as the economy has reached an income level susceptible to the “middle-income trap” and financial vulnerabilities are mounting after years of rapid credit expansion. However, the existing literature has largely focused on macro level aggregates, which are ill suited to understanding China’s significant structural transformation and its impact on economic growth. To fill the gap, this paper takes a deep dive into China’s convergence progress in 38 industrial sectors and 11 services sectors, examines past sectoral transitions, and predicts future shifts. We find that China’s productivity convergence remains at an early stage, with the industrial sector more advanced than services. Large variations exist among subsectors, with high-tech industrial sectors, in particular the ICT sector, lagging low-tech sectors. Going forward, ample room remains for further convergence, but the shrinking distance to the frontier, the structural shift from industry to services, and demographic changes will put sustained downward pressure on growth, which could slow to 5 percent by 2025 and 4 percent by 2030. Digitalization, SOE reform, and services sector opening up could be three major forces boosting future growth, while the risks of a financial crisis and a reversal in global integration in trade and technology could slow the pace of convergence.