Significance Testing in Accounting Research: A Critical Evaluation Based on Evidence.

• Autores: Jae Kim, Kamran Ahmed, Philip Inyeob Ji
• Localización: Abacus: A journal of accounting, finance and business studies, ISSN 0001-3072, Vol. 54, Nº 4, 2018, págs. 524-546
• Idioma: inglés
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• Resumen

  • From a survey of the papers published in leading accounting journals in 2014, we find that accounting researchers conduct significance testing almost exclusively at a conventional level of significance, without considering key factors such as the sample size or power of a test. We present evidence that a vast majority of the accounting studies favour large or massive sample sizes and conduct significance tests with the power extremely close to or equal to one. As a result, statistical inference is severely biased towards Type I error, frequently rejecting the true null hypotheses. Under the 'p‐value less than 0.05' criterion for statistical significance, more than 90% of the surveyed papers report statistical significance. However, under alternative criteria, only 40% of the results are statistically significant. We propose that substantial changes be made to the current practice of significance testing for more credible empirical research in accounting. [ABSTRACT FROM AUTHOR]