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.Business Economics (2005) 40, 6–10; doi:10.2145/20050101
