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dc.contributor.author | Crosato, Lisa | es_ES |
dc.contributor.author | Domenech, Josep | es_ES |
dc.contributor.author | Liberati, Caterina | es_ES |
dc.date.accessioned | 2022-07-14T18:04:16Z | |
dc.date.available | 2022-07-14T18:04:16Z | |
dc.date.issued | 2021-07 | es_ES |
dc.identifier.issn | 0165-1765 | es_ES |
dc.identifier.uri | http://hdl.handle.net/10251/184214 | |
dc.description.abstract | [EN] We propose the use of online indicators, scraped from the firms¿ websites, to predict default risk for a sample of Spanish firms via nonlinear discriminant analysis and the logistic regression model. | es_ES |
dc.description.sponsorship | This work was partially supported by the Ca' Foscari University of Venice, Italy and by Agencia Estatal de Investigacion, Spain under grant PID2019107765RBI00. We also acknowledge helpful comments by an anonymous referee. | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | Elsevier | es_ES |
dc.relation.ispartof | Economics Letters | es_ES |
dc.rights | Reconocimiento (by) | es_ES |
dc.subject | Default risk | es_ES |
dc.subject | SMEs | es_ES |
dc.subject | Web scraping | es_ES |
dc.subject | Corporate websites | es_ES |
dc.subject | Nonlinear discriminant | es_ES |
dc.subject.classification | ECONOMIA APLICADA | es_ES |
dc.title | Predicting SME's default: Are their websites informative? | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.1016/j.econlet.2021.109888 | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-107765RB-I00/ES/HUELLA DIGITAL, COMPETITIVIDAD Y DEMOGRAFIA EMPRESARIAL/ | es_ES |
dc.rights.accessRights | Abierto | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Departamento de Economía y Ciencias Sociales - Departament d'Economia i Ciències Socials | es_ES |
dc.description.bibliographicCitation | Crosato, L.; Domenech, J.; Liberati, C. (2021). Predicting SME's default: Are their websites informative?. Economics Letters. 204:1-3. https://doi.org/10.1016/j.econlet.2021.109888 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | https://doi.org/10.1016/j.econlet.2021.109888 | es_ES |
dc.description.upvformatpinicio | 1 | es_ES |
dc.description.upvformatpfin | 3 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 204 | es_ES |
dc.relation.pasarela | S\437303 | es_ES |
dc.contributor.funder | AGENCIA ESTATAL DE INVESTIGACION | es_ES |
upv.costeAPC | 1740 | es_ES |