No CrossRef data available.
Article contents
Some New Economy Lessons for Macroeconomists
Published online by Cambridge University Press: 17 August 2016
Summary
The evidence on U.S. investment in high-tech equipment and laborproductivity in the 1990s is briefly reviewed and some implicationsdiscussed. First, capturing the role of information technologies has raiseda number of important measurement issues, which have led to a change in theconstruction of aggregate real series in the U.S. national accounts, such asreal GDP. Second, the recent period provided an important confirmation fortraditional neoclassical theories of business investment and productivity.Third, there is a discussion of what type of theoretical and empiricalmodels of economic growth are likely to prove helpful in the future.
Résumé
Après avoir passé brièvement en revue les statistiques des années 1990 surl’investissement en haute technologie et sur la productivité du travail,nous abordons certaines de leurs conséquences. Tout d’abord, mesurer le rôledes technologies d’informations soulève quelques difficultés techniques cequi a conduit à modifier la construction des séries réelles agrégées, commele PIB réel, dans les comptes nationaux aux Etats-Unis. Par ailleurs, lapériode récente a apporté des éléments importants validant les théoriesnéoclassiques 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.
Keywords
Information
- Type
- I. Macroeconomics and National Accounting
- Information
- Copyright
- Copyright © Université catholique de Louvain, Institut de recherches économiques et sociales 2002
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,
1875–1911.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, 41–50.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, 1–59.Google Scholar
David, Paul
(1990), “The Dynamo and the Computer: An
Historical Perspective on the Modern Productivity
Paradox”, American Economic Review,
80, May,
355–361.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,
1119–1135.Google Scholar
Jorgenson, Dale
(1963), “Capital Theory and Investment
Behavior”, American Economic Review,
53,
247–259.Google Scholar
Jorgenson, Dale
and Grilliches, Zvi
(1967), “The Explanation of Productivity
Change”, Review of Economic Studies,
34,
249–280.Google Scholar
Jorgenson, Dale
and Stiroh, Kevin
(2000). “U.S. Economic Growth in the New
Millennium”, Brookings Papers on Economic
Activity, 1,
125–211.Google Scholar
King, Robert,
Charles, Plosser,
James, Stock, and
Mark, Watson
(1991), “Stochastic Trends and Economic
Fluctuations”, American Economic Review,
81, No. 4,
819–840.Google Scholar
Oliner, Stephen
and Sichel, Daniel
(1994), “Computers and Output Growth
Revisited: How Big is the Puzzle?”, Brookings
Papers on Economic Activity, 2,
273–317.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, 3–22.Google Scholar
Romer, Paul
(1990), “Endogenous Technological
Change”, Journal of Political Economy,
98(5),
S71–102.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