会计外文翻译

1、盈余管理和盈利质量III罗金摘要从犯罪现场调查员的视角来看盈余管理的检测，启蒙了早期对盈余管理的研究和它的 近亲：盈利质量。Ball和Shivakumar的著作（2008在会计和经济学杂志上出版的首次 公开发行时的盈利质量）和Teoh et al .的著作（1998在金融杂志53期上刊登的盈利 管理和首次公开发行后的市场表现）被用来阐释将犯罪现场调查的七个部分应用于盈利 管理的研究。关键词：市场效率 盈余管理 盈利质量 会计欺诈1、引言在诸多会计和金融的研究课题中，可能没有比盈余管理更具有刺激性的议题。为什么？ 我认为这是因为这个主题明确涉及了潜在的不法行为、恶作剧、冲突、间谍活动以及一种 神

2、秘感。正如Healy和Wahlen在1999年（Schipper在1989也下过类似的定义）定义道： “盈余管理的发生是在管理者针对财务报表和交易建立，运用判断力来改变财务报告之时。 盈余管理要么会在公司潜在的经营表现上误导一些利益相关者，要么影响合同结果，这取 决于会计报告数字。”简而言之，有人做伤害别人的事情。审计人员、监管机构、投资者 和研究者们试图找到这些违法者并解开这个谜团，而这个谜团可能会演变成涉及欺诈（或 犯罪，在此使用解决犯罪谜团的隐喻）的事件。如果我们将盈余管理看成是一个潜在的欺诈性（犯罪性）活动，那么我们可以在利用比 解决神秘谋杀案的福尔摩斯，或犯罪现场调查（CSI）更现代

3、的条件下，考虑对盈余管理的探 查。这样的调查涉及到以下七个要素：一场犯罪是否已经实施，嫌疑人的责任，使用的凶 器，犯罪活动的受害者，犯罪的动机，开展行动的机会和替代性解释。替代性解释是指除了 欺诈或犯罪活动，整个事件的起因。这个起因能够证实在目击证据的基础上得出欺诈或犯 罪的结论将是错误的。我在讨论破解盈余管理的谜团的各种要素时，所举的例子主要来自 Ball和Shivakumar（2008）和Teoh et al.（1998）。（这些要素显然是相互关联的，以下的讨 论中也有一些不可避免的重复）。盈余管理与盈利质量有很多共同之处。我想大多数人都会同意，受到高度管理的收益 盈利质量较低。然而，缺少

4、盈余管理并不足以保证高质量的收益（更普遍的说法是高质量的 会计数字）,因为其他因素也会影响收益的质量。例如，会计师挑剔地遵循一套低的会计标 准也会产生低质量的财务报告。然而，如果我们把这些给定的其他因素看成常数，我们可以 将盈余管理和盈利质量联系的更加紧密。虽然存在收益质量的其他解释，但是在接下来的 讨论中，我的观点与Ball和Shivakumar保持一致。高质量的盈利是保守的，然而低质量 的盈利呈现出不断增加的盈余管理行为。2、盈余管理产生了吗犯罪现场调查员的一个关键任务是确定犯罪是否已经发生，或者是否是一些自然原因 产生的结果。死亡是因为杀人、自杀或意外事故吗？做出这样的决定往往很困难，在

5、会计 研究中也丝毫不会更简单。正如Healy和Wahlen(1999,第370页)解释道：“尽管流行的观 点认为盈余管理是存在的，研究人员却很难提供令人信服的文字资料。这个问题产生的主 要原因在于，为了确定收益是否已经受到了管理控制，研究人员首先要估计受到管理前的 收益疽换句话说,研究人员需要区分收益中受到自然原因影响的部分和受到盈余管理活动 影响的部分。在早先对盈利管理和收益质量的研究中，研究设计普遍被总结为三个类：(1)时间序 列，(2)横断面研究，(3)越野。促使时间序列的研究方法获得世人瞩目的是 Teoh et al.(1998)，他将包含在招股说明书中的上市前财务报表作为与IPO当年

6、数值比较的一个 基准。在众多研究中使用横断面方法的是Ball和Shivakumar(2005)，他们比较了英国的 私营企业的财务报表和上市公司的财务报表。越野的方法是横断面的方法的一个变体，这 种方法探究了机构的国际性差异。在所有的研究中，基准并不完美的，而且最终得出的有 关盈利管理的衡量或盈利质量的结论十分杂乱，这种杂乱还很频繁(Dechow et al .,1995)。值得称赞的是，Ball和Shivakumar(2008)找到一个样本，这个样本克服了 Healy和 Wahlen(1999)所述的事后检测的难度。通过探查一个在英国进行首次公开发行的样本公司， 可以发现任何盈余管理都可以被精

7、确地检测到。这是因为存在两套财务报表，第一套(我 称之为“影子财务报表”)属于在英国公司注册处备案的有限责任公司，这些公司仍然属 于私营企业。第二套是在IPO招股说明书中的财务报表。我们可以提出合理的假设，即影 子财务报表相对于受到IPO诱导的，IPO招股说明书中的财务报表拥有更大的收益管理的 自由。因此，影子财务报表为没有受到管控的盈利提供了一个良好的基准。同时，我们可 以推断出在高精度的比较下，任何盈余管理活动可以利用两套财务报表之间的差异。Healy和Wahlen专注于检测的技术难度，这仅仅是站在事后的角度讨论。我认为考虑 事前检测技术的难度也很重要。从根本上说，希望那些管理收益不应该被

8、很容易地探测到。 经理越是老练，他或她便更不太可能进行容易被检测到的盈利管理，甚至为了逃避检测， 他们的隐藏计划会更复杂。推论是，如果什么东西，比如盈余管理，看起来太明显了，那 么很有可能不是。在财务报告中，涉及到的人通常是有经验的、聪明的、受过良好教育的、 接受过明确的专业行为准则或隐式的伦理准则的指导的。我不认为他们可能从事浮夸的、 头脑简单的盈余管理，如果他们这样做，我希望他们的盈余管理不至于因过于明显而被检 测到。然而事后检测的问题是解决了，Ball和Shivakumar的研究背景是发觉盈余管理的 可能性几乎是零的情况。期望投资者、他们的律师以及监管机构不去注意财务报告的主要 差异是不

9、合理的，同样不合理的是，如果企业管理者采用了可能被允许进行特别检测的盈 利管理方法，却无法系统地预测随之而来的负面影响。换句话说，如果为了获得好处而参 与其中，盈余管理必须做到难以发现。在此讨论的基础上,我认为Ball和Shivakumar没有发现任何明显的盈利管理行为完 全不足为奇。事实上，他们发现的唯一的显著差异在于财务报表中与无形资产有关的项目， 这些数据表现记录在了 IPO账户中。很明显,这种记录很容易识别，被读者接受的可能性 也很高。当我声称，在英国的IPO中，肯定会实际发生盈余管理被检测到的事时，我也许夸大 了事实。参照Ball和Shivakumar样本研究，这种说法应该被合理化。

10、这个研究只包括了 那些IPO财务报表与在公司署有备案的公司财报具有可比性的企业。换句话说，样本中只 包含了那些可以在财务报表项目之间作出一个简单和直接的比较的公司。这就剔除了所有 会增加或减少数量细节，或改变各种物品分类的公司。这样的公司占据了总量的绝大部分: 在t1,t2、t3三个年度中，越393家IPO公司中，这类公司的数量分别为140、198 和245。如果采用更加复杂的比较方法，这不是给管理被检测到的可能性更低的账户提供 机会吗？也许为了伪装他们的盈利管理行为，他们故意使IPO财务报表相比于影子财务报 表变得不具可比性，在我看来，那些没有可比财报的公司存在隐瞒盈余管理的可能性，也 更值

11、得检验。通过解决事后发现这个问题，Ball和Shivakumar “扔婴儿连同洗澡水一起 倒掉”。出于同样的原因,我认为从英国IPO研究情况推断到其他情形是不合理的，比如Teoh et al.(1998)研究的美国的IPO销量。由于没有可供比较的公开上市前的财务报表，在美 国，盈余管理更难被发现。谁应当对盈余管理负责神秘的谋杀事件有时被称为一个“侦探小说”。在这样的一个故事中，“是谁”的疑问 无疑最重要。然而，“是谁”在会计研究中是一个有待进一步研究的问题。尽管犯罪现场调查员自然想试图找出罪魁祸首，学术研究却对最终确定是否一个特定 的公司，更不用说任何个人，实施了盈余管理不太关心。他们对寻找盈

12、余管理的倾向更感 兴趣。当然，关注点的差异和研究人员获得的信息量较少以及需要通过增加样本大小来提 高统计的说服力密切相关。然而，即使需要大样本，仍然存在可以被检验的有趣的“是谁” 问题。例如，培训和资历对盈余管理倾向的影响是什么？如果拥有专业职称，管理者管理 盈余的可能性是否会降低，甚至因此遵守职业道德准则？不同的会计制度需要管理者作出 不同程度的判断是否会导致不同程度的盈余管理？管理者之间的经济和文化差异会起到 一定的作用吗？参考文献Ball, R., Shivakumar, L., Earnings quality in UK private firms: comparative loss

13、 recognition timeliness. Journal of Accounting and Economics,2005(39):83-128.Ball, R., Shivakumar, L.,Earnings quality at initial public offerings. Journal of Accounting and Economics, submitted for publication.Dechow, P.M., Sloan, R.G., Sweeney, A.P., Detecting earnings management.TheAccounting Rev

14、iew,1995(70):193 - 225Earnings management and earnings qualityKin LoViewing the detection of earnings management from the perspective of a crime scene investigator sheds new light on prior research on earnings management and its close relative, earnings quality. The works of Ball and Shivakumar 2008

15、. Earnings quality at initial public offerings. Journal of Accounting and Economics, in press. and Teoh et al. 1998. Earnings management and the subsequent market performance of initial public offerings. Journal of Finance 53, 1935 -1974. are used to illustrate the application of seven components of

16、 a crime scene investigation to earnings management research.Keywords: Market efficiency Earnings management Earnings quality Accounting fraudIntroductionAmong research topics in accounting and finance, none is perhaps more provocative than earnings management. Why? I think it is because the topic e

17、xplicitly involves potential wrongdoing, mischief, conflict, cloak and dagger, and a sense of mystery. As Healy and Wahlen (1999) (and similarly Schipper, 1989) define:Earnings management occurs when managers use judgment in financial reporting and in structuring transactions to alter financial repo

18、rts to either mislead some stakeholders about the underlying economic performance of the company or to influence contractual outcomes that depend on reported accounting numbers. Emphasis added. Simply put, someone is doing something that harms someone else.1 Auditors, regulators, investors, and rese

19、archers seek to find these wrongdoers and solve the mystery, which might turn out to involve fraud (or a crime, to use the metaphor of solving a criminal mystery).2If we view earnings management as a potentially fraudulent (criminal) activity, then we can think about its detection in terms of a murd

20、er mystery a la Sherlock Holmes, or a crime scene investigation (CSI) in more contemporary terms. Such investigations involve considering the following seven elements: whether a crime has been committed, suspects responsible, weapons used, victims of the crime, motives for the crime, opportunity to

21、carry out the act, and alternative explanations.3 Alternative explanations refer to causes of the event other than fraudulent or criminal activity, and thus, a conclusion of fraud or crime on the basis of observed evidence would be erroneous. I discuss the various elements of solving an earnings-man

22、agement mystery, with examples primarily drawn from Ball and Shivakumar (2008) and Teoh et al. (1998). (These elements are clearly interrelated and some overlap in the discussion below is unavoidable.)Earnings management has a lot in common with earnings quality. I think most would agree that highly

23、 managed earnings have low quality. However, the lack of earnings management is not sufficient to guarantee high-quality earnings (or high-quality accounting numbers more generally), because other factors contribute to the quality of earnings. For example, accountants fastidiously following a poor s

24、et of standards will generate low-quality financial reports. Nevertheless, if we take these other contributing factors as given constant, then we can draw a much closer connection between earnings management and earnings quality. While there are other interpretations of earnings quality, in the foll

25、owing discussion, to be consistent with Ball and Shivakumar (2008),high-quality earnings are conservative, while low-quality earnings are upwardly managed earnings.4.Did earnings management occur?One key task of a crime scene investigator is to determine whether a crime has occurred at all, or alter

26、natively, whether some natural cause has produced the outcome under investigation. Was a death due to a homicide, a suicide, or accident? Making such determinations is often difficult, and no less so in accounting research. As Healy and Wahlen (1999, p. 370) explain, “Despite the popular wisdom that

27、 earnings management exists, it has been remarkably difficult for researchers to convincingly document it. This problem arises primarily because, to identify whether earnings have been managed, researchers first have to estimate earnings before the effects of earnings management. In other words, res

28、earchers need to distinguish the part of earnings from natural causes from the part due to earnings management activities.Research designs in prior studies on earnings management and earnings quality more generally can be summarized into three categories: (i) time series, (ii) cross-sectional, and (

29、iii) cross-country. Notable in the time-series approach is Teoh et al. (1998), who use the pre-IPO financial statements included in the prospectus as a benchmark to compare with the IPO year numbers.5 Among the many studies that use the cross-sectional approach is Ball and Shivakumar (2005), who com

30、pare the financial statements of private and public companies in the UK. The cross-country approach is a variation of the cross-sectional approach that exploits international differences in institutions (see footnote 2 of Ball and Shivakumar (2008) as examples of studies in this category). In all of

31、 these studies, the benchmark is imperfect and the measure of earning management or earning quality is consequently noisy, often tremendously so (Dechow et al., 1995).To their credit, Ball and Shivakumar (2008) find a sample that overcomes the ex post difficulty of detection as described by Healy an

32、d Wahlen (1999). By examining a sample of firms undergoing initial public offerings (IPOs) in the United Kingdom, any earnings management can be detected precisely because there are two sets of financial statements. The first set (which I will call the “shadow financial statements) is the one filed

33、with the Companies House as required of all limited liability companies, but while the companies are still private. The second set is the one in the IPO prospectus. It is reasonable to assume that the shadow financial statements are relatively free of earnings management compared to the one in the p

34、rospectus, which is subject to incentives induced by the IPO. Thus, the shadow financial statements provide a good benchmark for nonmanaged earnings, and it is possible to infer with high precision any earnings management activity using the differences of the two sets of financial statements.Healy a

35、nd Wahlen s focus on the technical difficulty of detection just discussed is an ex post perspective. I think it is also important to think about this difficulty of detection ex ante. Fundamentally, the hope of those managing earnings is that it should not be easy to detect. The more sophisticated th

36、e manager, the less likely it is that he or she will engage in easy-to-detect earnings management, and the more elaborate will be the plans for concealment to evade detection.6 The corollary is that if something looks too obviously like earnings management, there is a good chance that it is not. In

37、financial reporting, the people involved are generally experienced, intelligent, well educated, and guided by explicit professional codes of conduct or implicit codes of ethics. I do not think that they are likely to engage in blatant, simple-minded earnings management, and if they were to do so, I

38、would expect them to make it not so obvious to detect. While the ex post detection problem is solved, Ball and Shivakumar s research context is one in which the exante likelihood of detectible earnings management is virtually nil. It is unreasonable to expect that investors, their lawyers, and regul

39、ators to not notice major differences in the financial reports, and equally unreasonable for corporate managers to systematically fail to anticipate the negative consequences that would ensue if they were to manage earnings in ways that would allow certain detection.7 In other words, earnings manage

40、ment must be somewhat difficult to detect if it has any hope of garnering benefits for those engaged in the activity.Based on this discussion, I find it completely unsurprising that Ball and Shivakumar find no significant earnings management. In fact, they find that the only significant differences

41、in the financial statements relate to intangibles, which their data show are written down in the IPO accounts. Such write-downs are clearly identifiable, and in all likelihood acceptable to readers and not litigable.I am perhaps overstating the case when I claim that earnings management can be detec

42、ted with virtual certainty for IPOs in the UK. This claim should be qualified to refer to the sample studied by Ball and Shivakumar, which includes only firms for which the IPO financial statements are comparable to those filed with the Companies House. In other words, the sample includes only firms

43、 where a simple and direct comparison can be made between the line items of the financial statements. This leaves out all the firms that increase or decrease the amount of detail, or change the categorization of various items. Such firms comprise a substantial portion of the total: 140, 198, and 245

44、 out of a possible 393 IPO firms in year t_1, t_2, and t_3, respectively. If comparisons are made more difficult, would this not provide the opportunity to manage the accounts with a lower likelihood of detection? Perhaps management deliberately made the IPO financial statements non-comparable to th

45、e shadow financial statements in order to camouflage their earnings management. It seems to me that the firms with non-comparable reports are the ones that could have some chance of hiding earnings management and a sample more worthy of examination. By solving the problem of ex post detection, Ball

46、and Shivakumar have “thrown the baby out with the bathwater.”By the same token, I believe it is unreasonable to extrapolate from the UK IPO context to other circumstances, such as IPOs in the US studied by Teoh et al. (1998).Earnings management in the US is more difficult to detect there given that there are no publicly available financial statements prior to the IPO with which to compare.Who is responsible for earnings management?A murder mystery is sometimes referred to as a “whodunit,” and the question of “who” is ultimately the most im