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dc.contributor.authorLicerán-Gutiérrez, Cano Rodríguez, Manuel Ana-
dc.identifier.citationAna Licerán-Gutiérrez & Manuel Cano-Rodríguez (2020) Using partial least squares in archival accounting research: an application to earnings quality measuring, Spanish Journal of Finance and Accounting / Revista Española de Financiación y Contabilidad, 49:2, 143-170, DOI: 10.1080/02102412.2019.1608705es_ES
dc.identifier.issn02102412, 23320753es_ES
dc.description.abstractDespite the advantages of Structural Equation Modelling (SEM) over regression models that have contributed to its popularisation in several fields of research in social sciences, it has not been broadly applied in archival accounting research. In this paper, we present a guidance for the application of SEM – and, particularly, the Partial Least Squares (PLS) method – to the (arguably) most recurrent topic on empirical archival accounting research: earnings quality. We highlight several problems that arise in earnings quality measuring, indicating how PLS can help to overcome them. We also run a simulation process whose results show that PLS method outperforms the other approaches even in situations of limited information.es_ES
dc.publisherTaylor & Francis Onlinees_ES
dc.relation.ispartofSpanish Journal of Finance and Accountinges_ES
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 España*
dc.subjectStructural equation models (SEM)es_ES
dc.subjectpartial least squares (PLS)es_ES
dc.subjectearnings dimensionses_ES
dc.subjectearnings qualityes_ES
dc.titleUsing partial least squares in archival accounting research: an application to earnings quality measuringes_ES
dc.title.alternativeUtilización de Mínimos Cuadrados Parciales en la investigación contable de archivo: Aplicación a la medición de la calidad del resultadoes_ES
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