Standard errors of forecasts in dynamic simulation of nonlinear econometric models: some empirical results
Carlo Bianchi () and
MPRA Paper from University Library of Munich, Germany
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
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Published in Time Series Analysis: Theory and Practice, ed. by O.D.Anderson Amsterdam: North Holland (1983): pp. 177-198
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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:22657
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