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Guesstimation

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Author Info
Charemza, Wojciech W

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Abstract

Macroeconomic model builders attempting to construct forecasting models frequently face constraints of data scarcity in terms of short time series of data, and also of parameter non-constancy and underspecification. Hence, a realistic alternative is often to guess rather than to estimate parameters of such models. This paper concentrates on repetitive guessing (drawing) parameters from iteratively changing distributions, with the straightforward objective function being that of minimization of squares of ex-post prediction errors, weighted by penalty weights and subject to a learning process. The examples are those of a Monte Carlo analysis of a regression problem and of a dynamic disequilibrium model. It is also an example of an empirical econometric model of the Polish economy. Copyright © 2002 by John Wiley & Sons, Ltd.

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Publisher Info
Article provided by John Wiley & Sons, Ltd. in its journal Journal of Forecasting.

Volume (Year): 21 (2002)
Issue (Month): 6 (September)
Pages: 417-33
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Handle: RePEc:jof:jforec:v:21:y:2002:i:6:p:417-33

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Web page: http://www3.interscience.wiley.com/cgi-bin/jhome/2966

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  1. Agapie, Adriana, 2008. "Stochastic Optimization in Econometric Models – A Comparison of GA, SA and RSG," Working Papers of Institute for Economic Forecasting 080825, Institute for Economic Forecasting. [Downloadable!]
  2. Nicolae POP & Adriana AGAPIE & Nicolae TEODORESCU, 2009. "An algorithmic approach for modelling customer expectations," Management & Marketing, Economic Publishing House, vol. 4(1), Spring. [Downloadable!]
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This page was last updated on 2009-11-29.

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