Technology, Growth, and the Labor Market brings together research by economists from academia and the Federal Reserve System. The first section of the volume includes discussions by monetary policymakers with firsthand experience in determining how technology affects productivity, inequality, and macroeconomic growth. Papers in the second section discuss the sources of the surge in labor productivity growth during the latter half of the 1990s and present forecasts of labor productivity growth rates during the next few years. In the third section, the papers focus on the role of technological advances in changes in earnings inequality in the labor market. The authors examine whether inequality should be viewed as a causal result of skill-biased technological change or whether there is a missing link - or perhaps no link - between changes in technology and changes in wage inequality. The final section explores the relationships between computer investment, worker skills, human resource practices, and productivity at the industry and firm levels.

The National Science Foundation's National Center for Science and Engineering Statistics (NCSES), one of the nation's principal statistical agencies, is charged to collect, acquire, analyze, report, and disseminate statistical data related to the science and engineering enterprise in the United States and other nations that is relevant and useful to practitioners, researchers, policymakers, and to the public. NCSES data, based primarily on several flagship surveys, have become the major evidence base for American science and technology policy, and the agency is well respected globally for these data. This report assesses and provides guidance on NCSES's approach to measuring the science and engineering workforce population in the United States. It also proposes a framework for measuring the science and engineering workforce in the next decade and beyond, with flexibility to examine emerging issues related to this unique population while at the same time allowing for stability in the estimation of key trends