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Using partial least squares in archival accounting research: an application to earnings quality measuring

Fecha

2019-05-09

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Editor

Taylor & Francis Online

Resumen

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.

Descripción

Palabras clave

Structural equation models (SEM), partial least squares (PLS), earnings dimensions, earnings quality

Citación

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

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