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dc.contributor.authorBaltagi, Badi H.en_US
dc.contributor.authorBresson, Georgesen_US
dc.contributor.authorPirotte, Alainen_US
dc.date.accessioned2009-08-05en_US
dc.date.accessioned2010-07-07T11:51:01Z-
dc.date.available2010-07-07T11:51:01Z-
dc.date.issued2009en_US
dc.identifier.piurn:nbn:de:101:1-2009070340en_US
dc.identifier.urihttp://hdl.handle.net/10419/35367-
dc.description.abstractThis paper compares various forecasts using panel data with spatial error correlation. The true data generating process is assumed to be a simple error component regression model with spatial remainder disturbances of the autoregressive or moving average type. The best linear unbiased predictor is compared with other forecasts ignoring spatial correlation, or ignoring heterogeneity due to the individual effects, using Monte Carlo experiments. In addition, we check the performance of these forecasts under misspecification of the spatial error process, various spatial weight matrices, and heterogeneous rather than homogeneous panel data models.en_US
dc.language.isoengen_US
dc.publisherForschungsinst. zur Zukunft der Arbeit Bonnen_US
dc.relation.ispartofseriesIZA Discussion Papers 4242en_US
dc.subject.jelC33en_US
dc.subject.ddc330en_US
dc.subject.keywordForecastingen_US
dc.subject.keywordBLUPen_US
dc.subject.keywordpanel dataen_US
dc.subject.keywordspatial dependenceen_US
dc.subject.keywordheterogeneityen_US
dc.subject.stwPrognoseverfahrenen_US
dc.subject.stwPanelen_US
dc.subject.stwRäumliche Interaktionen_US
dc.subject.stwTheorieen_US
dc.titleForecasting with spatial panel dataen_US
dc.typeWorking Paperen_US
dc.identifier.ppn605236445en_US
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungen-
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