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dc.contributor.authorLUETKEPOHL, Helmut
dc.date.accessioned2010-03-30T15:37:13Z
dc.date.available2010-03-30T15:37:13Z
dc.date.issued2010
dc.identifier.issn1725-6704
dc.identifier.urihttps://hdl.handle.net/1814/13662
dc.description.abstractDespite the fact that many aggregates are nonlinear functions and the aggregation weights of many macroeconomic aggregates are timevarying, much of the literature on forecasting aggregates considers the case of linear aggregates with fixed, time-invariant aggregation weights. In this study a framework for nonlinear contemporaneous aggregation with possibly stochastic or time-varying weights is developed and different predictors for an aggregate are compared theoretically as well as with simulations. Two examples based on European unemployment and inflation series are used to illustrate the virtue of the theoretical setup and the forecasting results.en
dc.format.mimetypeapplication/pdf
dc.relation.ispartofseriesEUI ECOen
dc.relation.ispartofseries2010/11en
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectForecastingen
dc.subjectStochastic aggregationen
dc.subjectAutoregressionen
dc.subjectMoving averageen
dc.subjectVector autoregressive processen
dc.subjectC32en
dc.titleForecasting Nonlinear Aggregates and Aggregates with Time-varying Weightsen
dc.typeWorking Paperen
dc.neeo.contributorLUETKEPOHL|Helmut|aut|EUI70007
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