In October 1999, the U.S. government dramatically revised its data series on real gross domestic product, the best measure of the economy’s total output. The new data showed that the economy had been growing somewhat faster over the previous decade than had been reported earlier. When data are revised, economists face unique problems when forecasting, studying the economy, and analyzing economic policy.
For example, economists are constantly trying new methods of forecasting the economy. An economist develops a new forecasting method by taking data about the economy, such as real output, unemployment, interest rates, and inflation rates, then relating those variables to each other through a set of equations that make up an economic model. The economist then looks at how well the model explains movements of the data in the past and how well it forecasts future movements of the data. But substantial data revisions, like those in October 1999, throw a monkey wrench into the development of economic models. A key problem is that the data now being used to develop forecasting models can differ from the data used prior to October 1999.
This article appeared in the September/October 2000 edition of Business Review.
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