Econometric GNP forecasts: Incremental information relative to naive extrapolation

Econometric GNP forecasts: Incremental information relative to naive extrapolation

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Article ID: iaor19921351
Country: Netherlands
Volume: 5
Start Page Number: 417
End Page Number: 426
Publication Date: Dec 1989
Journal: International Journal of Forecasting
Authors: ,
Keywords: textbooks: general
Abstract:

Recent studies of macroeconomic forecasts have focused primarily on the relative performance of individual forecasts and combinations thereof. The authors suggest that these forecasts be evaluated in terms of the incremental information that they provide relative to a simple extrapolation forecast. Using a Bayesian approach, the authors measure the incremental information contained in econometric forecasts of U.S. GNP relative to a random-walk-with-drift time series forecast. The results indicate that (1)substantial incremental gains can be obtained from econometric GNP forecasts for the current quarter, but that these gains decrease rapidly as the forecast horizon increases, and (2)after one econometric forecast has been consulted, subsequent such forecasts add little information.

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