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dc.date.accessioned2024-08-13T18:02:03Z
dc.date.available2024-08-13T18:02:03Z
dc.date.issued2024-06-28es_MX
dc.identifier.issn2673-4591
dc.identifier.urihttps://cathi.uacj.mx/20.500.11961/28685
dc.description.abstractThe Real Decreto-ley 13/2022 has amended the framework governing the calculation of Social Security contributions for Spanish self-employed workers. This framework obligates taxpayers to the annual revenue projection, under the possibility of lending money for free or paying unexpected taxes at the end of the year in the case of deviations. To address this issue, the Declarando firm has developed an algorithm to recommend the optimal contributions that combines a Simple Moving Average forecasting method with an offset-adjustment technique. This paper examines how this strategy can be improved by cleaning the input data and combining different forecasts using an Ensemble-based approach. After testing experimentally various alternatives, a promising strategy involves employing a median-based Ensemble on preprocessed data. Although this Ensemble-based approach significantly reduces forecasting errors, the improvements are diluted when the predictions are combined with the offset-adjustment process.es_MX
dc.description.urihttps://www.mdpi.com/2673-4591/68/1/5es_MX
dc.language.isoenes_MX
dc.publisherMDPIes_MX
dc.relation.ispartofProducto de investigación IITes_MX
dc.relation.ispartofInstituto de Ingeniería y Tecnologíaes_MX
dc.subjecttime series forecastinges_MX
dc.subjectrevenue forecastinges_MX
dc.subjectpredictive tax modellinges_MX
dc.subjectsuggestion systemses_MX
dc.subjectSpanish self-employed workerses_MX
dc.subject.otherinfo:eu-repo/classification/cti/7es_MX
dc.titleOptimizing Social Security Contributions for Spanish Self-Employed Workers: Combining Data Preprocessing and Ensemble Models for Accurate Revenue Estimationes_MX
dc.typeMemoria in extensoes_MX
dcterms.thumbnailhttp://ri.uacj.mx/vufind/thumbnails/rupiiit.pnges_MX
dcrupi.institutoInstituto de Ingeniería y Tecnologíaes_MX
dcrupi.cosechableSies_MX
dcrupi.subtipoInvestigaciónes_MX
dcrupi.alcanceInternacionales_MX
dcrupi.paisEspañaes_MX
dc.contributor.coauthorGarcía, Vicente
dcrupi.tipoeventoCongresoes_MX
dcrupi.evento10th International Conference on Time Series and Forecastinges_MX
dcrupi.estadoGran Canariaes_MX
dc.contributor.authorexternoPalomero, Luis
dc.contributor.coauthorexternoSánchez, J. Salvador
dcrupi.colaboracionextEspañaes_MX
dcrupi.pronacesNingunoes_MX


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