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A Short History of Socialist Economic Thought by Gerd Hardack, Dieter Karras, Ben Fine

By Gerd Hardack, Dieter Karras, Ben Fine

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The lesson to be learned is that forecast evaluations should try, at least when aiming at inter-temporal comparisons, to account for this period-dependence of forecasts. The above studies use at least one of the two equivalent methods from the introduction — in short: division by standard deviation or comparison with naive benchmark — in order to measure the relative performance of forecasts. In sum, they come to the result that macroeconomic forecasts do mostly outperform the naive benchmark. Yet, they do so with marginal lead, and it is not always clear whether their lead is significant or not.

3 ... and different forecasting methods In this section, we will have a closer look at different forecasting methods and their specific performance. Practitioners indeed use a large variety of different methods to generate macroeconomic forecasts which range from personal judgment and simple extrapolation to forecasting with sophisticated models incorporating hundreds of equations. As far as I can tell, there is no canonical taxonomy of forecasting methods; quite the opposite, we find fairly different categorizations in the literature.

2001) find strong similarities between forecast errors of academic, official and private forecasters, too. They interpret this finding as indicating a herd-behavior of forecasters who tend to make the same forecasts as well as the same revisions. This conclusion is also shared by Coyle (2001), former organizer of The Independent'^ "Golden Guru" forecasting competition. Given the rather similar performance of forecasters, does pooling yield better forecasts? According to Zamowitz & Braun (1992), it is widely accepted that joining individual forecasts together into one consensus forecast (calculating the average forecast) increases the forecast performance.

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