Hostname: page-component-cd9895bd7-dzt6s Total loading time: 0 Render date: 2024-12-28T01:11:32.273Z Has data issue: false hasContentIssue false

Some New Economy Lessons for Macroeconomists

Published online by Cambridge University Press:  17 August 2016

Karl Whelan*
Affiliation:
Division of Research and Statistics, Federal Reserve Board
Get access

Summary

The evidence on U.S. investment in high-tech equipment and labor productivity in the 1990s is briefly reviewed and some implications discussed. First, capturing the role of information technologies has raised a number of important measurement issues, which have led to a change in the construction of aggregate real series in the U.S. national accounts, such as real GDP. Second, the recent period provided an important confirmation for traditional neoclassical theories of business investment and productivity. Third, there is a discussion of what type of theoretical and empirical models of economic growth are likely to prove helpful in the future.

Résumé

Résumé

Après avoir passé brièvement en revue les statistiques des années 1990 sur l’investissement en haute technologie et sur la productivité du travail, nous abordons certaines de leurs conséquences. Tout d’abord, mesurer le rôle des technologies d’informations soulève quelques difficultés techniques ce qui a conduit à modifier la construction des séries réelles agrégées, comme le PIB réel, dans les comptes nationaux aux Etats-Unis. Par ailleurs, la période récente a apporté des éléments importants validant les théories néoclassiques traditionnelles de l’investissement et de la productivité. Enfin, nous terminons par la discussion de quels modèles de croissance, théoriques et économétriques, peuvent se révéler utiles à l’avenir.

Type
I. Macroeconomics and National Accounting
Copyright
Copyright © Université catholique de Louvain, Institut de recherches économiques et sociales 2002 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

*

Mail Stop 80,20th and C Streets NW, Washington DC 20551. Email: kwhelan ©frb.gov. The views expressed are my own and do not necessarily reflect the views of the Board of Governors or the staff of the Federal Reserve System.

References

Barro, Robert and Sala-i-Martin, Xavier (1995), Economic Growth, New York: McGraw-Hill.Google Scholar
Campbell, John and Shiller, Robert (2001), “Valuation Ratios and the Long-Run Stock Market Outlook”, NBER Working Paper, No. 8221.Google Scholar
Chirinko, Robert (1993), “Business Fixed Investment Spending: A Critical Survey of Modelling Strategies, Empirical Results, and Policy Implications”, Journal of Economic Literature, 18751911.Google Scholar
Chow, Gregory (1967), “Technological Change and the Demand for Computers”, American Economic Review, 57(5), 1117–30.Google Scholar
Cole, Roseanne, Y. C. Chen, Joan, Barquin-Stolleman, Ellen, Dulberger, Nurthan, Helvacian, and James, Hodge (1986), “Quality-Adjusted Price Indexes for Computer Processors and Selected Peripheral Equipment”, Survey of Current Business, 66, January, 4150.Google Scholar
Cummins, Jason, Kevin, Hassett, and Glenn Hubbard, R. (1994), “A Reconsideration of Investment Behavior Using Tax Reforms as Natural Experiments”, Brookings Papers on Economic Activity, 2, 159.Google Scholar
David, Paul (1990), “The Dynamo and the Computer: An Historical Perspective on the Modern Productivity Paradox”, American Economic Review, 80, May, 355361.Google Scholar
Fisher, Irving (1922), The Making of Index Numbers, Boston: Houghton-Mifflin.Google Scholar
Glassman, James K. and Hassett, Kevin (1999), Dow 36,000: The New Strategy for Profiting from the Coming Rise in the Stock Market, New York: Times Business.Google Scholar
Griliches, Zvi (1961), “Hedonic Price Indexes for Automobiles: An Econometric Analysis of Quality Change”, reprinted in Zvi, Grilliches (ed.) Price Indexes and Quality Change, 1971, Cambridge: Harvard University Press.Google Scholar
Jones, Charles I. and Williams, Kevin (1998). “Measuring the Social Return to R&D”, Quarterly Journal of Economics, 113, 11191135.Google Scholar
Jorgenson, Dale (1963), “Capital Theory and Investment Behavior”, American Economic Review, 53, 247259.Google Scholar
Jorgenson, Dale and Grilliches, Zvi (1967), “The Explanation of Productivity Change”, Review of Economic Studies, 34, 249280.Google Scholar
Jorgenson, Dale and Stiroh, Kevin (2000). “U.S. Economic Growth in the New Millennium”, Brookings Papers on Economic Activity, 1, 125211.Google Scholar
King, Robert, Charles, Plosser, James, Stock, and Mark, Watson (1991), “Stochastic Trends and Economic Fluctuations”, American Economic Review, 81, No. 4, 819840.Google Scholar
Oliner, Stephen and Sichel, Daniel (1994), “Computers and Output Growth Revisited: How Big is the Puzzle?”, Brookings Papers on Economic Activity, 2, 273317.Google Scholar
Oliner, Stephen and Sichel, Daniel (2000), “The Resurgence of Growth in the Late 1990s: Is Information Technology the Story?”, Journal of Economic Perspectives, 14, Fall, 322.Google Scholar
Romer, Paul (1990), “Endogenous Technological Change”, Journal of Political Economy, 98(5), S71102.Google Scholar
Tevlin, Stacey and Whelan, Karl (2001), “Explaining the Investment Boom of the 1990s”, forthcoming, Journal of Money, Credit, and Banking.Google Scholar
Whelan, Karl (2000a), “A Guide to the Use of Chain Aggregated NIPA Data”, Federal Reserve Board, Finance and Economics Discussion Series Paper No. 2000–35.Google Scholar
Whelan, Karl (2000b). “Computers, Obsolescence, and Productivity”, forthcoming, Review of Economics and Statistics.Google Scholar
Whelan, Karl (2001), “A Two-Sector Approach to Modeling U.S. NIPA Data”, forthcoming in Journal of Money, Credit, and Banking.Google Scholar