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Titre: Using partial least squares in archival accounting research: an application to earnings quality measuring
Auteur(s): Licerán-Gutiérrez, Ana
Cano-Rodríguez, Manuel
Résumé: Despite 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.
Mots-clés: Structural Equation Model (SEM)
Partial Least Squares (PLS)
Earnings dimensions
Earnings quality concept
Earnings quality construct
Earnings quality measurement
Date de publication: 2020
metadata.dc.description.sponsorship: FPI Acción 16 UJA y Proyecto de Investigación de la Universidad de Jaén UJA/2015/06/04
Editeur: Taylor & Francis
Référence bibliographique: Licerán-Gutiérrez, A., & Cano-Rodríguez, M. (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.
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