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dc.contributor.authorTeräsvirta, Timoen
dc.date.accessioned2012-03-28T13:05:08Z-
dc.date.available2012-03-28T13:05:08Z-
dc.date.issued2005-
dc.identifier.urihttp://hdl.handle.net/10419/56166-
dc.description.abstractThis article is concerned with forecasting from nonlinear conditional mean models. First, a number of often applied nonlinear conditional mean models are introduced and their main properties discussed. The next section is devoted to techniques of building nonlinear models. Ways of computing multi-step ahead forecasts from nonlinear models are surveyed. Tests of forecast accuracy in the case where the models generating the forecasts are nested are discussed. There is a numerical example, showing that even when a stationary nonlinear process generates the observations, future obervations may in some situations be better forecast by a linear model with a unit root. Finally, some empirical studies that compare forecasts from linear and nonlinear models are discussed.en
dc.language.isoengen
dc.publisher|aStockholm School of Economics, The Economic Research Institute (EFI) |cStockholmen
dc.relation.ispartofseries|aSSE/EFI Working Paper Series in Economics and Finance |x598en
dc.subject.jelC22en
dc.subject.jelC45en
dc.subject.jelC53en
dc.subject.ddc330en
dc.subject.keywordForecast accuracyen
dc.subject.keywordforecast comparisonen
dc.subject.keywordhidden Markov modelen
dc.subject.keywordneural networken
dc.subject.keywordnonlinear modellingen
dc.subject.keywordrecursive forecasten
dc.subject.keywordsmooth transition regressionen
dc.subject.keywordswitching regressionen
dc.subject.stwPrognoseverfahrenen
dc.subject.stwMathematische Optimierungen
dc.subject.stwNichtlineares Verfahrenen
dc.titleForecasting economic variables with nonlinear models-
dc.typeWorking Paperen
dc.identifier.ppn48832789Xen
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungenen

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