Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/77218
Campo DC Valoridioma
dc.contributor.authorGonzález Martel, Cristianen_US
dc.contributor.authorHernández Guerra, Juan Maríaen_US
dc.contributor.authorManrique De Lara Peñate, Casianoen_US
dc.date.accessioned2021-01-18T08:49:12Z-
dc.date.available2021-01-18T08:49:12Z-
dc.date.issued2021en_US
dc.identifier.issn0167-9236en_US
dc.identifier.otherScopus-
dc.identifier.urihttp://hdl.handle.net/10553/77218-
dc.description.abstractEfficient detection of incorrectly filed tax returns is one of the main tasks of tax agencies. Value added tax (VAT) legislation requires buyers and sellers to communicate any exchanges that exceed a certain amount. Both statements should coincide, but sometimes the seller/buyer and its counterpart declare different amounts. This paper presents a method to detect those businesses that are more prone to misreport in their VAT declaration. Using the information of such declarations for a region in Spain during year 2002, we generated a transaction network formed by the tax declarations of buyers and sellers. Four types of error were assigned to each business in the network, defined from the mismatch between the amount declared by the firm in question and its counterpart. We applied a random forest algorithm to detect which firm-related and which network-related characteristics influence each error type. The results show the importance of relational factors among businesses in determining the probability of presenting VAT declaration errors. This information can be used to promote more efficient inspections.en_US
dc.languageengen_US
dc.relationCN45/08240/57/100en_US
dc.relation.ispartofDecision Support Systemsen_US
dc.sourceDecision Support Systems[ISSN 0167-9236],v. 141, (Febrero 2021)en_US
dc.subject5301 Política fiscal y hacienda pública nacionalesen_US
dc.subject.otherFraud Detectionen_US
dc.subject.otherNetworksen_US
dc.subject.otherRandom Foresten_US
dc.subject.otherVat Declarationen_US
dc.titleIdentifying business misreporting in VAT using network analysisen_US
dc.typeinfo:eu-repo/semantics/Articleen_US
dc.typeArticleen_US
dc.identifier.doi10.1016/j.dss.2020.113464en_US
dc.identifier.scopus85098924065-
dc.contributor.authorscopusid16230450700-
dc.contributor.authorscopusid7403026151-
dc.contributor.authorscopusid6506539491-
dc.relation.volume141en_US
dc.investigacionCiencias Sociales y Jurídicasen_US
dc.type2Artículoen_US
dc.utils.revisionen_US
dc.date.coverdateFebrero 2021en_US
dc.identifier.ulpgcen_US
dc.contributor.buulpgcBU-ECOen_US
dc.description.sjr1,973
dc.description.jcr6,969
dc.description.sjrqQ1
dc.description.jcrqQ1
dc.description.scieSCIE
dc.description.miaricds11,0
dc.description.erihplusERIH PLUS
item.grantfulltextnone-
item.fulltextSin texto completo-
crisitem.author.deptGIR Finanzas Cuantitativas y Computacionales-
crisitem.author.deptDepartamento de Métodos Cuantitativos en Economía y Gestión-
crisitem.author.deptGIR TIDES: Economía, medioambiente, sostenibilidad y turismo-
crisitem.author.deptIU de Turismo y Desarrollo Económico Sostenible-
crisitem.author.deptDepartamento de Métodos Cuantitativos en Economía y Gestión-
crisitem.author.deptGIR Economía, Comercio y Transporte Marítimo-
crisitem.author.deptDepartamento de Análisis Económico Aplicado-
crisitem.author.orcid0000-0003-1081-0843-
crisitem.author.orcid0000-0001-6897-5179-
crisitem.author.orcid0000-0003-0809-7823-
crisitem.author.parentorgDepartamento de Métodos Cuantitativos en Economía y Gestión-
crisitem.author.parentorgIU de Turismo y Desarrollo Económico Sostenible-
crisitem.author.parentorgDepartamento de Análisis Económico Aplicado-
crisitem.author.fullNameGonzález Martel, Cristian-
crisitem.author.fullNameHernández Guerra, Juan María-
crisitem.author.fullNameManrique De Lara Peñate, Casiano Alberto-
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