Bianchi, Carlo and Calzolari, Giorgio (1983): Confidence intervals of forecasts from nonlinear econometric models. Published in: paper presented at The Third International Symposium on Forecasting. Philadelphia: The Wharton School, June 58 (5. June 1983): pp. 120.

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Abstract
Several methods have been proposed in the last few years for evaluating uncertainty in forecasts produced by nonlinear econometric models. Some methods resort to Monte Carlo, while others resort to different simulation techniques. This work aims at comparing these methods by means of experiments on some econometric models of small, medium and large size, used in practice for forecasting purposes. In most cases of practical interest, direct simulation of confidence intervals allows to overcome the difficulties connected with the nonexistence of finite second order moments, often encountered by the authors when applying Monte Carlo methods to real world models.
Item Type:  MPRA Paper 

Original Title:  Confidence intervals of forecasts from nonlinear econometric models 
Language:  English 
Keywords:  Nonlinear econometric models; stochastic simulation; forecast; confidence intervals 
Subjects:  C  Mathematical and Quantitative Methods > C6  Mathematical Methods; Programming Models; Mathematical and Simulation Modeling > C63  Computational Techniques; Simulation Modeling C  Mathematical and Quantitative Methods > C3  Multiple or Simultaneous Equation Models; Multiple Variables 
Item ID:  29025 
Depositing User:  Giorgio Calzolari 
Date Deposited:  03. Mar 2011 20:00 
Last Modified:  17. Feb 2013 21:27 
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URI:  http://mpra.ub.unimuenchen.de/id/eprint/29025 