Abstract not found

For many years, there has been considerable debate about whether the IT revolution was paying off in higher productivity. Studies in the 1980s found no connection between IT investment and productivity in the U.S. economy, a situation referred to as the productivity paradox. Since then, a decade of studies at the firm and country level has consistently shown that the impact of IT investment on labor productivity and economic growth is significant and positive. This article critically reviews the published research, more than 50 articles, on computers and productivity. It develops a general framework for classifying the research, which facilitates identifying what we know, how well we know it, and what we do not know. The framework enables us to systematically organize, synthesize, and evaluate the empirical evidence and to identify both limitations in existing research and data and substantive areas for future research. The review concludes that the productivity paradox as first formulated has been effectively refuted. At both the firm and the country level, greater investment in IT is associated with greater productivity growth. At the firm level, the review further concludes that the wide range of performance of IT investments among different

Stockton, and conference participants for very useful comments and discussions. For extremely valuable help with data, they are grateful to Charlie Gilbert from the Federal Reserve Board, Bruce Grimm and David Wasshausen from the Bureau of Economic Analysis, and Michael Harper, Larry Rosenblum, and Steve Rosenthal from the Bureau of Labor Statistics. This paper draws heavily from the authors ’ earlier work, including text taken directly from Oliner and Sichel (2000a, b) and Sichel (1997). After a quarter-century of lackluster gains, the U.S. economy experienced a remarkable resurgence in productivity growth during the second half of the 1990s. From 1995 to 2000, output per hour in nonfarm business grew at an average annual rate of about 21 /2 percent compared with increases of only about 11 /2 percent per year from 1973 to 1995. 1 Our earlier work, along with other research, linked this improved performance to the

Notes: Center Discussion Papers are preliminary materials circulated to stimulate discussions and critical comments. We thank seminar participants at Yale University and Joe Altonji, Eileen Brooks, and Valery Lazarev for helpful comments and suggestions. Fairlie was partially funded by the William T. Grant Foundation. The views contained herein are solely those of the authors, and do not necessarily represent those of the institutions with which the authors are associated. Menzie D.

portion of this paper may be reproduced without permission of the authors. Discussion papers are research materials circulated by their authors for purposes of information and discussion. They have not necessarily undergone formal peer review or editorial treatment.

Some observers have raised the possibility that production spillovers and network effects associated with information and communications technology (ICT) are an important part of the “New Economy.” Across U.S. manufacturing industries, however, ICT capital appears correlated with the acceleration of average labor productivity (ALP) growth as predicted by a standard production model, but not with total factor productivity (TFP) growth as these New Economy forces imply. Once one allows for productivity differences across industries, measured TFP growth is uncorrelated with all capital inputs, including ICT capital. This provides little evidence for a New Economy story of ICT-related spillovers or network effects driving TFP growth throughout U.S. manufacturing.

In this paper, we develop a model of technology adoption and economic growth in which households optimally obtain either a concept-based, “general ” education or a skill-specific, “vocational ” education. General education is costly to obtain, but enables workers to operate new production technologies. Firms weigh the cost of adopting and operating new technologies against increased profits and optimally choose the level of adoption. We show that an economy whose policies favor vocational education will grow slower in equilibrium than one that favors general education. More importantly, the gap between their growth rates will increase with the growth rate of available technology. By characterizing the optimal Ramsey education policy we demonstrate that the optimal subsidy for general education increases with the growth rate of available technology as well. Our theory suggests that European education policies that favored specialized, vocational education might have worked well, both in terms of growth rates and welfare, during the 60s and 70s when available technologies changed slowly. However, in the information age of the 80s and 90s when new technologies emerged at a more rapid pace, they might have contributed to suboptimally slow growth and increased the growth gap relative to the US.

Abstract not found

Abstract not found

for comments on earlier versions of this paper. We also thank Kirk Moore for excellent research assistance and Judith Goff for editorial assistance. The views expressed herein are those of the authors and do not necessarily reflect those of the Board of Governors of the Federal Reserve System or their staff, the Shifts in the long-run rate of productivity growth—such as those experienced by the U.S. economy in the 1970s and 1990s—are difficult, in real time, to distinguish from transitory fluctuations. In this paper, we analyze the evolution of forecasts of longrun productivity growth during the 1970s and 1990s and examine in the context of a dynamic general equilibrium model the consequences of gradual real-time learning on the responses to shifts in the long-run productivity growth rate. We find that a simple updating rule based on an estimated Kalman filter model using real-time data describes economists ’ long-run productivity growth forecasts during these periods extremely well. We then show that incorporating this process of learning has profound implications for the effects of shifts in trend productivity growth and can dramatically improve the model’s ability to generate responses that resemble historical experience.