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International Journal of Forecasting
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International Journal of Forecasting
Article . 2007 . Peer-reviewed
License: Elsevier TDM
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SSRN Electronic Journal
Article . 2006 . Peer-reviewed
Data sources: Crossref
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Using Forecasts of Forecasters to Forecast

Authors: Nolte, Ingmar; Pohlmeier, Winfried;

Using Forecasts of Forecasters to Forecast

Abstract

Quantification techniques are popular methods in empirical research to aggregate 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 & Newbold (1997), we confront the forecasts based on survey methods with the forecasting performance of standard linear time series approaches and simple random walk forecasts.

Countries
United Kingdom, Germany
Related Organizations
Keywords

Linear time series models, info:eu-repo/classification/ddc/330, 330, Qualitative survey data, Turning points, Quantification methods, Forecasting quality

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
20
Average
Top 10%
Average
Green
hybrid