Path Forecast Evaluation

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dc.contributor.author JORDÀ, Òscar
dc.contributor.author MARCELLINO, Massimiliano
dc.date.accessioned 2008-11-14T11:07:30Z
dc.date.available 2008-11-14T11:07:30Z
dc.date.issued 2008
dc.identifier.issn 1725-6704
dc.identifier.uri http://hdl.handle.net/1814/9813
dc.description.abstract A path forecast refers to the sequence of forecasts 1 to H periods into the future. A summary of the range of possible paths the predicted variable may follow for a given confidence level requires construction of simultaneous confidence regions that adjust for any covariance between the elements of the path forecast. This paper shows how to construct such regions with the joint predictive density and Scheffé’s (1953) S-method. In addition, the joint predictive density can be used to construct simple statistics to evaluate the local internal consistency of a forecasting exercise of a system of variables. Monte Carlo simulations demonstrate that these simultaneous confidence regions provide approximately correct coverage in situations where traditional error bands, based on the collection of marginal predictive densities for each horizon, are vastly off mark. The paper showcases these methods with an application to the most recent monetary episode of interest rate hikes in the U.S. macroeconomy. en
dc.language.iso en en
dc.publisher European University Institute
dc.relation.ispartofseries EUI ECO en
dc.relation.ispartofseries 2008/34 en
dc.subject path forecast en
dc.subject simultaneous confidence region en
dc.subject error bands en
dc.title Path Forecast Evaluation en
dc.type Working Paper en
dc.neeo.contributor JORDÀ|Oscar|aut|
dc.neeo.contributor MARCELLINO|Massimiliano|aut|EUI70008
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