{"dcterms:modified":"2025-04-01","dcterms:creator":"Harvard Dataverse","@type":"ore:ResourceMap","schema:additionalType":"Dataverse OREMap Format v1.0.1","dvcore:generatedBy":{"@type":"schema:SoftwareApplication","schema:name":"Dataverse","schema:version":"6.6 build 1829-192cdc4","schema:url":"https://github.com/iqss/dataverse"},"@id":"https://dataverse.harvard.edu/api/datasets/export?exporter=OAI_ORE&persistentId=https://doi.org/10.7910/DVN/EBMA","ore:describes":{"author":{"citation:authorName":"Graefe, Andreas","citation:authorAffiliation":"LMU Munich"},"citation:keyword":{"citation:keywordValue":"Bayesian Model Averaging, election forecasting"},"publication":{"publicationCitation":"Limitations of Ensemble Bayesian Model Averaging for forecasting social science problems"},"citation:datasetContact":{"citation:datasetContactEmail":"N/A"},"citation:dsDescription":{"citation:dsDescriptionValue":"We compare the accuracy of simple unweighted averages and Ensemble Bayesian Model Averaging (EBMA) to combining forecasts in the social sciences. A review of prior studies from the domain of economic forecasting finds that the simple average was more accurate than EBMA in four out of five studies. On average, the error of EBMA was 5% higher than the error of the simple average. A reanalysis and extension of a published study provides further evidence for US presidential election forecasting. The error of EBMA was 33% higher than the corresponding error of the simple average. Simple averages are easy to describe, easy to understand and thus easy to use. In addition, simple averages provide accurate forecasts in many settings. Researchers who develop new approaches to combining forecasts need to compare the accuracy of their method to this widely established benchmark. Forecasting practitioners should favor simple averages over more complex methods unless there is strong evidence in support of differential weights."},"citation:distributor":{"citation:distributorName":"Harvard Dataverse Network","citation:distributorURL":"http://thedata.harvard.edu/dvn/","citation:distributorLogoURL":"http://thedata.harvard.edu/dvn/resources/images/dvnPoweredByLogo.gif"},"citation:productionDate":"2014","dateOfDeposit":"2014-07-21","title":"Replication data for: Limitations of Ensemble Bayesian Model Averaging for forecasting social science problems","citation:distributionDate":"2014","@id":"https://doi.org/10.7910/DVN/EBMA","@type":["ore:Aggregation","schema:Dataset"],"schema:version":"1.0","schema:name":"Replication data for: Limitations of Ensemble Bayesian Model Averaging for forecasting social science problems","schema:dateModified":"Mon Jul 21 05:20:57 UTC 2014","schema:datePublished":"2014-07-21","schema:creativeWorkStatus":"RELEASED","schema:license":"http://creativecommons.org/publicdomain/zero/1.0","dvcore:fileTermsOfAccess":{"dvcore:fileRequestAccess":false},"schema:includedInDataCatalog":"Harvard Dataverse","schema:isPartOf":{"schema:name":"Andreas Graefe Dataverse","@id":"https://dataverse.harvard.edu/dataverse/agraefe","schema:description":"Data for studies authored by Andreas Graefe, LMU Munich","schema:isPartOf":{"schema:name":"Harvard Dataverse","@id":"https://dataverse.harvard.edu/dataverse/harvard","schema:description":"<span><span><span><h3>Share, archive, and get credit for your data. Find and cite data across all research fields.</h3></span></span></span>"}},"ore:aggregates":[{"schema:description":"","schema:name":"EBMA.xlsx","dvcore:restricted":false,"schema:version":1,"dvcore:datasetVersionId":67263,"@id":"doi:10.7910/DVN/EBMA/IHY9RK","schema:sameAs":"https://dataverse.harvard.edu/api/access/datafile/:persistentId?persistentId=doi:10.7910/DVN/EBMA/IHY9RK","@type":"ore:AggregatedResource","schema:fileFormat":"application/vnd.openxmlformats-officedocument.spreadsheetml.sheet","dvcore:filesize":19158,"dvcore:storageIdentifier":"s3://dvn-cloud:213706","dvcore:rootDataFileId":-1,"dvcore:checksum":{"@type":"MD5","@value":"4ef405d397d0f113b3560f1fc7b45f20"}}],"schema:hasPart":["doi:10.7910/DVN/EBMA/IHY9RK"]},"@context":{"author":"http://purl.org/dc/terms/creator","citation":"https://dataverse.org/schema/citation/","dateOfDeposit":"http://purl.org/dc/terms/dateSubmitted","dcterms":"http://purl.org/dc/terms/","dvcore":"https://dataverse.org/schema/core#","ore":"http://www.openarchives.org/ore/terms/","publication":"http://purl.org/dc/terms/isReferencedBy","publicationCitation":"http://purl.org/dc/terms/bibliographicCitation","schema":"http://schema.org/","title":"http://purl.org/dc/terms/title"}}