Please use this identifier to cite or link to this item: https://hdl.handle.net/10953/1161
Title: Using partial least squares in archival accounting research: an application to earnings quality measuring
Other Titles: Utilización de Mínimos Cuadrados Parciales en la investigación contable de archivo: Aplicación a la medición de la calidad del resultado
Authors: Licerán-Gutiérrez, Cano Rodríguez, Manuel Ana
Abstract: 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.
Keywords: Structural equation models (SEM)
partial least squares (PLS)
earnings dimensions
earnings quality
Issue Date: 9-May-2019
metadata.dc.description.sponsorship: PGC2018-096440-B-I00
Publisher: Taylor & Francis Online
Citation: Ana 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: 10.1080/02102412.2019.1608705
Appears in Collections:DEFC-Artículos



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