利用收入分类转移进行盈利管理:来自中国上市公司的证据

IF 3.2 Q1 BUSINESS, FINANCE
Ajid ur Rehman, Asad Yaqub, Tanveer Ahsan, Zia-ur-Rehman Rao
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引用次数: 0

摘要

本研究旨在调查中国上市公司收入分类转移的收益管理实践。本研究采用了中国上海和深圳证券交易所 2003-2019 年期间 2920 家 A 股上市公司的数据集。研究结果表明,企业利用适用财务报告准则提供的灵活性对收入进行了错误分类。通过回归分析获得的实证证据表明,管理者将非营业收入重新归类为营业收入,以改变经济现实,同时利用财务报告用户对损益表项目上半部分的估值高于下半部分的弱点。研究结果进一步表明,国际财务报告准则的采用抑制了利用收入分类转移进行收益管理的做法。本研究的独特之处在于,它从收入分类的角度研究了新兴市场的收益管理,而该市场的特点是存在各种市场缺陷,如投资者保护程度较低和信息不对称程度较高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Earnings management using classification shifting of revenues: evidence from Chinese-listed firms
PurposeThis study aims to investigate earnings management practice of classification shifting of revenues in Chinese-listed firms.Design/methodology/approachThe study employs a dataset of 2,920 A-listed firms from Chinese stock exchanges of Shanghai and Shenzhen for the period of 2003–2019. We apply both univariate and panel regression analysis by using fixed effect estimation with robust standard errors.FindingsOur findings reveal that firms misclassify revenues by taking advantage of the flexibility provided by applicable financial reporting standards. The empirical evidence obtained through regression analysis suggest that managers reclassify non-operating revenues as operating revenue to alter the economic reality while seeking the advantage of financial reports users’ vulnerability for valuing the upper half of income statement items more as compared to lower part. The results further indicate that international financial reporting standards adoption inhibits the earnings management practices using classification shifting of revenues. It is also concluded that firms, which are suffering losses or having low growth, are more persistently involved in misclassification of revenues.Originality/valueThe study is unique from the point of view that it investigates earnings management from the prospective of revenue’s classification in an emerging market characterized by various market imperfections such as lower investor protection and higher information asymmetry.
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来源期刊
CiteScore
5.80
自引率
13.00%
发文量
38
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