Disaggregating operating and financial activities: implications for forecasts of profitability

Researchers, practitioners, and standard setters emphasize the importance of disaggregating financial statements into operating and financial activities. However, there is a lack of research demonstrating that this disaggregation improves forecasts of profitability. In this study, we consider whether and when the operating/financial disaggregation improves forecasts of profitability. Contrary to the use of an aggregate forecasting approach by most related prior research, we first show that the operating/financial disaggregation only provides forecast improvement over a benchmark model incorporating aggregate information when the components forecasting approach is used. We also compare the operating/financial disaggregation to the unusual/infrequent disaggregation required by US GAAP. We find that the operating/financial disaggregation yields less accurate forecasts than the unusual/infrequent disaggregation. However, when using the components forecasting approach, we find that the combination of both disaggregations improves forecasts of profitability. Finally, we document that the incremental usefulness of the operating/financial disaggregation relative to a benchmark model incorporating aggregate information is a function of growth and accounting conservatism. Overall, our study provides timely evidence concerning how analysts and investors might best use the operating/financial disaggregation for forecasting profitability.     

Project selection in Post Office telecommunications R&D

In an industry in which the benefits of R & D are often difficult to quantify, numerate processes for the selection of projects and portfolios are of limited usefulness. The processes that are used provide formal means, necessary in a large organization, to enable managerial judgment at an appropriate level to be applied to both project selection and the balance of the portfolios.     

Acknowledging religious diversity: Opportunities and challenges

Because federal law protects an employee's right to religious accommodation, managers cannot ignore the issue of religious diversity. The matter is far broader than simple legal compliance, though. Certainly, managers need to better understand the laws protecting employees’ rights for accommodation and prohibiting disparate treatment, religious harassment, and retaliation. However, they also need to understand the various opportunities and challenges associated with acknowledging religious diversity. Concerning opportunities, research suggests that allowing employees to express aspects of their religion can enhance their work lives and, thus, the value they place on the organization. Furthermore, respect for religious diversity can encourage a useful mindset for communicating with other stakeholders in areas from advertising to the sports interests of salespeople. Since learning more about a range of faiths can lead to greater skills in working with diverse groups, we offer information on Prothero's God Is Not One: The Eight Rival Religions That Run the World—and Why Their Differences Matter and on different religions’ practices associated with death-related issues. In conclusion, we provide insight regarding the benefits of acknowledging religious diversity while respecting those who identify with no religion, and we do so without opening the door to proselytizing.     

通向市场的新道路

对于传统的市场营销人员来说,组织本身即意味着架构:不同的产品、销售渠道和客户群。但对于新型的营销组织而言,在瞬息万变的市场环境中,传统的架构已经不能推动价值的攀升     

Analysts’ annual earnings forecasts and changes to the I/B/E/S database

Review of Accounting Studies - I/B/E/S is a common source of analyst earnings forecast data, and the reliability of these data is important for practice and academic research. Examining a common...     

Reactions to abusive supervision: examining the roles of emotions and gender in the USA

Abusive supervision leads to many detrimental outcomes, yet the role of gender and emotions has received little attention. We applied affective events theory to study emotions in a new context. Using qualitative and quantitative methods, we tested a conditional process model of the effects of abusive supervision on subordinate work and job withdrawal as mediated by negative emotions and moderated by gender. We found support for our proposed model. Specifically, abusive supervision increased work and job withdrawal via victims’ negative emotional reactions. When negative emotions are low, women are more likely to engage in work withdrawal; when negative emotions are high, men are more likely to do so. Additionally, men experiencing high negative emotions are likely to quit their job.     

Evaluating the Risks of Modeling Assumptions Used in Risk Measurement

Over the past few years, risk measurement has become an important, high-profile responsibility for most firms in the financial services industry. With advances in academic theory and in technology, financial risk modeling has grown increasingly sophisticated. Most firms rely on a number of models to analyze their market risks (for example, sensitivity to changes in interest rates, exchange rates, commodity prices, and so on) for asset/liability management. But it is critical to recognize that even the most sophisticated models must make assumptions about key parameters that affect the results of the analysis. This so-called “model risk” reflects the fact that in the real world risk factors are unstable and the historical data upon which many modeling inputs are based can change. This paper discusses model risk, gives specific examples of how model risk can affect fixed-income portfolio valuation, and explains why risk measurement should involve stress testing of key modeling assumptions. If the results of a valuation or asset/liability analysis change dramatically given a small change in a modeling assumption, management may wish to reduce the firm’s exposure to that risk factor, as absolute certainty in financial modeling is an unobtainable goal.     

Fair value accounting for liabilities: The role of disclosures in unraveling the counterintuitive income statement effect from credit risk changes

When liabilities are accounted for at fair value, a deterioration of a company’s credit risk results in the reporting of an income statement gain; an improvement in a company’s credit risk results in a loss. Many argue that these income statement effects are counterintuitive and that financial statement-users are likely to misinterpret fair value gains as positive signals and fair value losses as negative signals. Utilizing an experiment with CPAs as participants, we find that these arguments are indeed valid. Specifically, we find that over 70% of the participants incorrectly assess a company’s credit risk as improving (deteriorating) when a fair value gain (loss) is recognized. We also find that disclosures that explicitly specify the relation between the direction of the credit risk change and the income statement effect significantly reduce participants’ misinterpretations, and are more beneficial when fair value gains versus losses are recognized. These findings provide empirical evidence in the debate over the recognition of company-specific credit risk changes and offer direction for improving disclosures in the area of fair value accounting.     

The Effect of Measurement Subjectivity Classifications on Analysts' Use of Persistence Classifications When Forecasting Earnings Items

Earnings items are typically classified in financial reports based on their persistence and measurement subjectivity. Archival research examines investors' use of persistence and measurement subjectivity classifications for forecasting and valuation. However, this research typically examines only one of these classifications at a time and ignores the potential interactive implications of an earnings item's persistence and measurement subjectivity classifications. We recruited experienced financial analysts to participate in two experiments that examined the effect of measurement subjectivity classifications on analysts' use of persistence classifications when forecasting earnings items. We find that analysts rely less on an earnings item's persistence classification when measurement subjectivity is high relative to when measurement subjectivity is low. We also find that presentation format affects analysts' use of these two classifications. Specifically, we find that the matrix format (i.e., rows display persistence classifications and columns display measurement subjectivity classifications) facilitates analysts' combined use of persistence and measurement subjectivity classifications relative to the sequential format (i.e., the classifications are displayed separately). These findings suggest that archival research could improve its examination of market participants' use of earnings classifications for forecasting and valuation by recognizing that the implications of an earnings item's persistence classification can vary according to the item's measurement subjectivity classification. By also demonstrating how presentation format affects analysts' use of earnings classifications, our study provides further insights into this fundamental issue in accounting research and standard setting.     

Information Asymmetry Around Earnings Announcements

This study examines bid-ask spreads to determine how the anticipation and release of earnings announcements affect information asymmetry in the stock market. I use regression analysis and find that bid-ask spreads are negatively related to public information availability and positively related to earnings variability and the market reaction to prior unexpected earnings. The results suggest that firms for which earnings is expected to yield a relatively larger stock market reaction have greater information asymmetry than firms for which earnings are expected to yield a smaller market reaction.I also find that bid-ask spreads gradually increase in the four days prior to earnings announcements, and increase sharply the day prior to, the day of and the day after the earnings announcements. Bid-ask spreads seven to ten days after earnings announcements are not significantly different from bid-ask spreads seven to ten days prior to earnings announcements.