Using computers, expertise, and hunches to forecast US economy
''We came within a couple of billion dollars. Let's declare victory,'' Frank Cooper quips to his colleagues at Wharton Econometric Forecasting Associates. Mr. Cooper, a business activity expert, is referring to Wharton's February estimate of fourth-quarter 1983 corporate profits. Government data released in late March indicate the Wharton prediction was too high.Skip to next paragraph
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Every month Cooper and three other economists meet around a table in an office building here, gather their courage, and predict how the $1.6 trillion United States economy will perform during the next three years.
Using a combination of computer modeling, experience, intuition, and self-depreciating humor, they predict a staggering 1,400 different statistics for every three-month period. The items forecast range from the nation's total economic output to the demand for clothing and shoes. A computer model is a set of equations representing the economy.
The predictions cranked out at Wharton and other major forecasters like Data Resources Inc. (DRI) and Chase Econometrics have a serious impact on the lives of average citizens. For instance, administration and congressional tax plans are based in part on what the forecasting firms' models say the economy will be doing and thus how much tax revenue will be flowing into government coffers.
And many major corporations make sales projections, and thus hiring or firing plans, based to some degree on economic data the forecasting firms provide or help companies calculate in-house.
''We are trying to determine sales for the appliance industry'' using Wharton model data, says Frank Maly, supervisor of market analysis for Whirlpool Corporation, the big appliance manufacturer. ''You don't want to overshoot'' consumer demand or goods will back up in warehouses, he notes. But firms also want to avoid underestimating potential sales and thus not having enough products to meet demand.
The forecasting firms are far from infallible in predicting the economy. For instance, forecasts made in 1981 and early 1982 generally underestimated the recession and the slowdown in inflation that accompanied it. Year-end 1982 predictions for 1983 were better but tended to underestimate economic growth and overestimate inflation.
''There is almost no chance we will be correct'' in predicting the gross national product (the value of the nation's goods and services, or GNP) for 1986 , admits Robert Westcott, assistant director of Wharton's quarterly modeling service.
The reason is that there are many influences on the economy that can't be reduced to a mathematical equation. ''No model can predict how Tip O'Neill and Ronald Reagan are going to resolve the deficit problem,'' says James F. Smith, chief economist at Union Carbide Corporation.
Other unpredictable factors include changing oil prices and shifts in the Federal Reserve Board's monetary policy.
Critics say the forecasting firms' record is no better than that of than individual forecasters who operate without huge computer data banks and large forecasting staffs.