Economics at your fingertips  

Standard errors of forecasts in dynamic simulation of nonlinear econometric models: some empirical results

Carlo Bianchi () and Giorgio Calzolari

MPRA Paper from University Library of Munich, Germany

Abstract: In nonlinear econometric models, the evaluation of forecast errors is usually performed, completely or partially, by resorting to stochastic simulation. However, for evaluating the specific contribution of errors in estimated structural coefficients, several alternative methods have been proposed in the literature. Three of these methods will be compared empirically in this paper through experiments performed on a set of "real world" econometric models of small, medium and large size. This work extends to dynamic simulation of nonlinear econometric models, for which the authors have recently analysed the one-period (static) forecast errors empirically.

Keywords: Nonlinear econometric models; forecast; Monte Carlo; standard errors (search for similar items in EconPapers)
JEL-codes: C53 C30 (search for similar items in EconPapers)
Date: 1983, Revised 1983
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4) Track citations by RSS feed

Published in Time Series Analysis: Theory and Practice, ed. by O.D.Anderson Amsterdam: North Holland (1983): pp. 177-198

Downloads: (external link) original version (application/pdf)

Related works:
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:

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 ().

Page updated 2020-07-01
Handle: RePEc:pra:mprapa:22657