This paper reports on a comprehensive study of the distributions of summary measures of error for a large collection of quarterly multiperiod predictions of six variables representing inflation, real qrowth, unemployment,and percentage changes in nominal GNP and two of its more volatile components.The data come from surveys conducted since 1968 by the National Bureau of Economic Research and the American Statistical Association and cover more than 70 individuals professionally engaged in forecasting the course of the U. S.economy (mostly economists, analysts, and executives from the world of corporate business and finance). There is considerable differentiation among these forecasts, across the individuals, variables, and predictive horizons covered. Combining corresponding predictions from different sources can result insignificant gains; thus the group mean forecasts are on the average over timemore accurate than most of the corresponding sets of individual forecasts. But there is also a moderate deqree of consistency in the relative performance of a sufficient number of the survey members, as evidenced in positive rank correlations among ratios of the individual to group root mean square errors.
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