计量经济分析 = Econometric analysis

1. Introduction and Overview. 2. Detecting Influential Observations and Outliers. 3. Detecting and Assessing Collinearity. 4. Applications and Remedies. 5. Research Issues and Directions for Extensions. Bibliography. Author Index. Subject Index.

Regression Diagnostics: Identifying Influential Data and Sources of Collinearity

Researchers have used various measures as indications of "earnings quality" including persistence, accruals, smoothness, timeliness, loss avoidance, investor responsiveness, and external indicators such as restatements and SEC enforcement releases. For each measure, we discuss causes of variation in the measure as well as consequences. We reach no single conclusion on what earnings quality is because "quality" is contingent on the decision context. We also point out that the "quality" of earnings is a function of the firm's fundamental performance. The contribution of a firm's fundamental performance to its earnings quality is suggested as one area for future work.

/pdf/understanding-earnings-quality-a-review-of-the-proxies-their-1r9rjtuq8l.pdf

Understanding Earnings Quality: A Review of the Proxies, Their Determinants and Their Consequences

Earnings Management and Investor Protection: An International Comparison

羟氨苄青霉素引起大疱性类天疱疮样疹

This study explains the challenges associated with the Heckman (1979) procedure to control for selection bias, assesses the quality of its application in accounting research, and offers guidance for better implementation of selection models. A survey of 75 recent accounting articles in leading journals reveals that many researchers implement the technique in a mechanical way with relatively little appreciation of important econometric issues and problems surrounding its use. Using empirical examples motivated by prior research, we illustrate that selection models are fragile and can yield quite literally any possible outcome in response to fairly minor changes in model specification. We conclude with guidance on how researchers can better implement selection models that will provide more convincing evidence on potential selection bias, including the need to justify model specifications and careful sensitivity analyses with respect to robustness and multicollinearity. Data Availability: Data used...

Selection models in accounting research

https://msbfile03.usc.edu/digitalmeasures/clennox/intellcont/JAE08-1.pdf

Audit effort and earnings management

https://msbfile03.usc.edu/digitalmeasures/clennox/intellcont/JEB99-1.pdf

Identifying failing companies: a re-evaluation of the logit, probit and DA approaches

https://msbfile03.usc.edu/digitalmeasures/clennox/intellcont/JAE00-1.pdf

Do companies successfully engage in opinion-shopping? Evidence from the UK

We examine the association between Big Five audits and the incidence of accounting frauds allegedly committed by U.S. public companies between 1981 and 2001. Many commentators argue that the prominent financial reporting failures that led to major corporate governance reforms cast serious doubt on whether the large public accounting firms continue to supply relatively high-quality audits, especially in recent years. However, in unmatched and matched samples, we provide strong, robust evidence that fraudulent financial reporting becomes less likely with the presence of a Big Five auditor. Importantly, time-series tests suggest that the Big Five are consistently associated with a lower incidence of fraudulent accounting, including in the last five years of our sample period when the number of frauds soared. Moreover, we find evidence implying that these relations are causal rather than an artifact of endogeneity in auditor choice.

/pdf/big-five-audits-and-accounting-fraud-32a260lxdd.pdf

Clive S. Lennox

Papers

Selection models in accounting research

Audit effort and earnings management

Identifying failing companies: a re-evaluation of the logit, probit and DA approaches

Do companies successfully engage in opinion-shopping? Evidence from the UK

Big Five Audits and Accounting Fraud