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

Ana Licerán-Gutiérrez, Manuel Cano-Rodríguez
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引用次数: 8

Abstract

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.
偏最小二乘在档案会计研究中的应用:盈余质量测量
尽管结构方程模型(SEM)比回归模型有优势,这有助于其在社会科学研究的几个领域的普及,但它尚未广泛应用于档案会计研究。在本文中,我们提出了一个应用SEM的指导-特别是偏最小二乘(PLS)方法-在实证档案会计研究中(可以说)最经常出现的主题:盈余质量。我们强调了盈余质量测量中出现的几个问题,表明PLS如何帮助克服这些问题。我们还运行了一个仿真过程,结果表明PLS方法即使在有限信息的情况下也优于其他方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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