The Adam Smith Award Address, 2004
Global Macroeconometric Forecasting Using 21st Century Information and Analysis
Lawrence R. Klein is Benjamin
Franklin Professor Emeritus at the
University of Pennsylvania. He has
served on the faculties of the
University of Chicago, University
of Michigan, University of Oxford,
and the University of
Pennsylvania, where he taught for
33 years. Dr. Klein is an econometrician
and constructed several statistical
models of the United States and various other
countries. At Penn, he founded the Wharton Econometric
Forecasting Associates (WEFA) and was a principal
investigator of Project LINK, which combined models
from countries throughout the world for studying international
trade and payments and global economic activity.
He served as president of many learned societies, edited
scholarly journals, and advised governments in matters of
economic policy. In 1976, he coordinated Jimmy Carter's
economic task force in a successful campaign for the presidency
of the United States. In 1980, he was the Nobel
Laureate in Economics. Since 1984, Dr. Klein has been
director and chairman of the Economic Policy
Committee of W.P. Carey & Co. He earned his B.A. from
the University of California, Berkeley and his doctorate
at the Massachusetts Institute of Technology.
Much of what Adam Smith said in 1776 remains fresh today—particularly on the trade-off between “guns and butter.” It is safe to say, however, that he did not anticipate macroeconometric modeling for forecasting and policy analysis. From its beginnings in the 1940s, the standards and the needs of users of forecasts are becoming ever more demanding as the information flow becomes more bountiful. We have evolved from reliance on annual data to the availability of high-frequency data and the challenges of integrating the two into reliable, timely forecasting models. In extending modeling efforts to transition and newly developing countries, I have been pleasantly surprised at the availability of important data, making possible not only models for individual countries but for linking them to understand the impacts of global phenomena such as oil shocks and financial crises. In many of these countries, however, time series are short—making efficient use of high-frequency data even more important. Another promising area of investigation is integration of input-output and flow-of-funds analysis with income and product accounts for more realistic treatment of such issues as technological change and interest rates.
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