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Forecasting European Union politics : Real-time forecasts in political time series analysis

Forecasting European Union politics : Real-time forecasts in political time series analysis

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BECHTEL, Michael M., Dirk LEUFFEN, 2010. Forecasting European Union politics : Real-time forecasts in political time series analysis. In: European Union Politics. 11(2), pp. 309-327. ISSN 1465-1165

@article{Bechtel2010Forec-12831, title={Forecasting European Union politics : Real-time forecasts in political time series analysis}, year={2010}, doi={10.1177/1465116509360846}, number={2}, volume={11}, issn={1465-1165}, journal={European Union Politics}, pages={309--327}, author={Bechtel, Michael M. and Leuffen, Dirk} }

<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:bibo="http://purl.org/ontology/bibo/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcterms="http://purl.org/dc/terms/" xmlns:xsd="http://www.w3.org/2001/XMLSchema#" > <rdf:Description rdf:about="https://kops.uni-konstanz.de/rdf/resource/123456789/12831"> <dc:contributor>Bechtel, Michael M.</dc:contributor> <dc:creator>Bechtel, Michael M.</dc:creator> <dc:contributor>Leuffen, Dirk</dc:contributor> <bibo:uri rdf:resource="http://kops.uni-konstanz.de/handle/123456789/12831"/> <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2011-07-12T09:56:35Z</dcterms:available> <dc:language>eng</dc:language> <dcterms:bibliographicCitation>First publ. in: European Union Politics 11 (2010), 2, pp. 309-327</dcterms:bibliographicCitation> <dcterms:rights rdf:resource="http://nbn-resolving.org/urn:nbn:de:bsz:352-20140905103605204-4002607-1"/> <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2011-07-12T09:56:35Z</dc:date> <dcterms:issued>2010</dcterms:issued> <dcterms:title>Forecasting European Union politics : Real-time forecasts in political time series analysis</dcterms:title> <dcterms:abstract xml:lang="eng">Forecasting plays an increasingly important role in the scientific study of European Union politics and in political science in general. This is because forecasts are not only indispensable for (political) actors who need to form expectations about future events, but can also be used to judge the validity of (competing) theoretical models. While the debate about whether political science should engage in forecasting is largely over, many questions about how this should be done in everyday research are still open. One of these is how forecasts of political time series can be derived from theoretical models. Using a practical example from European Union research, we start to address this question. We first show how forecasts of political time series can be derived from both theoretical and atheoretical models. Subsequently, we use an atheoretical time series (ARMA) imputation approach to demonstrate how they can be fruitfully integrated in order to overcome some of the limitations to making forecasts of political time series which are based on theoretical models.</dcterms:abstract> <dc:rights>deposit-license</dc:rights> <dc:creator>Leuffen, Dirk</dc:creator> </rdf:Description> </rdf:RDF>

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