Coherent Forecast with Nonlinear Econometric Models

Giorgio Calzolari and Lorenzo Panattoni

MPRA Paper from University Library of Munich, Germany

Abstract: The drawbacks of forecasts obtained with the usual deterministic solution methods in nonlinear systems of stochastic equations have been widely investigated in the literature. Most of the proposed therapies are based on some estimation of the conditional mean of the endogenous variables in the forecast period. This however provides a solution to the problem which does not respect the internal coherency of the model, and in particular does not satisfy nonlinear identities. This paper proposes to estimate the mode of the joint distribution of the endogenous variables as an alternative optimal predictor.

Keywords: Nonlinear econometric models; stochastic simulation; mean and mode; coherent solution (search for similar items in EconPapers)
JEL-codes: C3 C63 (search for similar items in EconPapers)
Date: 1988-06-12
References: View references in EconPapers View complete reference list from CitEc
Citations:

Published in paper presented at The Eighth International Symposium on Forecasting. Universiteit van Amsterdam and Vrije Universiteit Amsterdam, June 12-15. (1988): pp. 1-6

Downloads: (external link)
https://mpra.ub.uni-muenchen.de/28802/1/MPRA_paper_28802.pdf original version (application/pdf)

Related works:
Journal Article: Mode predictors in nonlinear systems with identities (1990)
Working Paper: Il problema della coerenza delle previsioni nei modelli econometrici non lineari (1988)
Working Paper: Mode predictors in nonlinear systems with identities (1988)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:28802

Access Statistics for this paper

More papers in MPRA Paper from University Library of Munich, Germany Ludwigstraße 33, D-80539 Munich, Germany. Contact information at EDIRC.
Bibliographic data for series maintained by Joachim Winter ().