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Estimating fundamental cross-section dispersion from fixed event forecasts

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Author Info
Jonas Dovern () (The Kiel Institute for the World Economy (IfW))
Ulrich Fritsche () (Department for Economics and Politics, University of Hamburg, and DIW Berlin)

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Abstract

A couple of recent papers have shifted the focus towards disagreement of professional forecasters. When dealing with survey data that is sampled at a frequency higher than annual and that includes only fixed event forecasts, e.g. expectation of average annual growth rates measures of disagreement across forecasters naturally are distorted by a component that mainly reflects the time varying forecast horizon. We use data from the Survey of Professional Forecasters, which reports both fixed event and fixed horizon forecasts, to evaluate different methods for extracting the ``fundamental'' component of disagreement. Based on the paper's results we suggest two methods to estimate dispersion measures from panels of fixed event forecasts: a moving average transformation of the underlying forecasts and estimation with constant forecast-horizon-effects. Both models are easy to handle and deliver equally well performing results, which show a surprisingly high correlation (up to 0.94) with the true dispersion.

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File URL: http://www.wiso.uni-hamburg.de/hepdoc/macppr_1_2008.pdf
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File Function: First version, 2008
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Publisher Info
Paper provided by Hamburg University, Department Wirtschaft und Politik in its series Macroeconomics and Finance Series with number 200801.

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Length: 14 pages
Date of creation: May 2008
Date of revision:
Handle: RePEc:hep:macppr:200801

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Web page: http://www.wiso.uni-hamburg.de/dwp
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Related research
Keywords: survey data; dispersion; disagreement; fixed event forecasts;

Other versions of this item:

Find related papers by JEL classification:
C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions
C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions
E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation

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Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Jonas Dovern & Ulrich Fritsche & Jiri Slacalek, 2009. "Disagreement among Forecasters in G7 Countries," Macroeconomics and Finance Series 200906, Hamburg University, Department Wirtschaft und Politik. [Downloadable!]
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