Volume 23 Issue 1 (January-March 2007)

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Using forecasts of forecasters to forecast

Nolte, I. , Pohlmeier, W.
Pages 15-28

Quantification techniques are popular methods in empirical research for aggregating the qualitative predictions at the micro-level into a single figure. In this paper, we analyze the forecasting performance of various methods that are based on the qualitative predictions of financial experts for major financial variables and macroeconomic aggregates. Based on the Centre of European Economic Research's Financial Markets Survey, a monthly qualitative survey of around 330 financial experts, we analyze the out-of-sample predictive quality of probability methods and regression methods. Using the modified Diebold-Mariano test of Harvey, Leybourne and Newbold (Harvey, D., Leybourne, S., & Newbold, P. (1997). Testing the equality of prediction mean squared errors. International Journal of Forecasting, 13, 281-291.), we compare the forecasts based on survey methods with the forecasting performance of standard linear time series approaches and simple random walk forecasts.

Keywords: [jel] G10 , [jel] E30 , [jel] E31 , [jel] E37 , [jel] C10 , [jel] C42 , Forecasting quality , Qualitative survey data , Quantification methods , Linear time series models , Turning points
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