Effects of parameter estimation on prediction densities a bootstrap approach

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dc.contributor.author Pascual, Lorenzo
dc.contributor.author Romo, Juan
dc.contributor.author Ruiz Ortega, Esther
dc.contributor.editor Universidad Carlos III de Madrid. Departamento de Estadística
dc.date.accessioned 2010-01-08T10:32:54Z
dc.date.available 2010-01-08T10:32:54Z
dc.date.issued 1999-04
dc.identifier.uri http://hdl.handle.net/10016/6304
dc.description.abstract In this paper, we study the impact of parameter estimation on prediction densities using a bootstrap strategy to estimate these densities. We focus on seasonal ARlMA processes with possibly non normal innovations. We compare prediction densities obtained using the Box and Jenkins approach with bootstrap densities which may be constructed taking into account parameter estimation variability (PRR) or using parameter estimates as if they were the true parameters (CB). By means of Monte Carlo experiments, we show that the average coverage of the intervals is closer to the nominal value when intervals are constructed incorporating parameter uncertainty. The effects of parameter estimation are particularly important for small sample sizes and when the error distribution is not Gaussian. We also analyze the effect of the estimation method on the shape of prediction densities comparing prediction densities constructed when the parameters are estimated by OLS and by LAD. We show how, when the error distribution is not Gaussian, the average coverage and length of intervals based on LAD estimates are closer to nominal values than those based on OLS estimates. Finally, the performance of the PRR procedure is illustrated with two empirical examples.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.relation.ispartofseries UC3M Working Papers. Statistics and Econometrics
dc.relation.ispartofseries 99-31-09
dc.rights Atribución-NoComercial-SinDerivadas 3.0 España
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject.other Forescating
dc.subject.other Least absolute deviations
dc.subject.other non normal distributions
dc.subject.other Ordinaty least squares
dc.title Effects of parameter estimation on prediction densities a bootstrap approach
dc.type workingPaper
dc.subject.eciencia Estadística
dc.rights.accessRights openAccess
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