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Toward a Theory of Evaluating Predictive Accuracy

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Author Info
Kunst, Robert M. (Department of Economics and Finance, Institute for Advanced Studies and Department of Economics, University of Vienna)
Jumah, Adusei (Department of Economics and Finance, Institute for Advanced Studies and Department of Economics, University of Vienna)

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Abstract

We suggest a theoretical basis for the comparative evaluation of forecasts. Instead of the general assumption that the data is generated from a stochastic model, we classify three stages of prediction experiments: pure non-stochastic prediction of given data, stochastic prediction of given data, and double stochastic simulation. The concept is demonstrated using an empirical example of UK investment data.

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File URL: http://www.ihs.ac.at/publications/eco/es-162.pdf
File Format: application/pdf
File Function: First version, 2004
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Publisher Info
Paper provided by Institute for Advanced Studies in its series Economics Series with number 162.

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Length: 43 pages
Date of creation: Nov 2004
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Handle: RePEc:ihs:ihsesp:162

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Related research
Keywords: Forecasting; Time series; Investment;

Find related papers by JEL classification:
C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions
C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Other Model Applications
E27 - Macroeconomics and Monetary Economics - - Macroeconomics: Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation

References listed on IDEAS
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  1. Alvaro Escribano & Santiago Mira, 2001. "Nonlinear error correction models," Documentos de trabajo conjunto ULL-ULPGC 2001-03, Facultad de Ciencias Económicas de la ULPGC. [Downloadable!]
  2. Diebold, Francis X & Mariano, Roberto S, 1995. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 253-63, July.
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This page was last updated on 2009-12-10.

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