Citing fear of legal liability as a partial explanation, prior research documents (1) managers' reluctance to voluntarily disclose management earnings forecasts, and (2) greater forecast disclosure frequencies in periods of bad news. We provide evidence on how management earnings forecast disclosure differs between the United States (U.S.) and Canada, two otherwise similar business environments with different legal regimes. Canadian securities laws and judicial interpretations create a far less litigious environment than exists in the U.S. We find a greater frequency of management earnings forecast disclosure in Canada relative to the U.S. Further, although U.S. managers are relatively more likely to issue forecasts during interim periods in which earnings decrease, Canadian managers do not exhibit that tendency. Instead, Canadian managers issue more forecasts when earnings are increasing, and their forecasts are of annual rather than interim earnings. Also consistent with a less litigious environment, Canadian managers issue more precise and longer-term forecasts. These findings hold after controlling for other determinants of management earnings forecast disclosure that might differ between the two countries—firm size, earnings volatility, information asymmetry, growth, capitalization rates, and membership in high-technology and regulated industries.
Managers often explain their earnings forecasts by linking forecasted performance to their internal actions and the actions of parties external to the firm. These attributions potentially aid investors in the interpretation of management forecasts by confirming known relationships between attributions and profitability or by identifying additional causes that investors should consider when forecasting earnings. We investigate why managers choose to provide attributions with their forecasts and whether the attributions are related to security price reactions to management earnings forecasts. Using a sample of 951 management earnings forecasts issued from 1993 to 1996, we find that attributions are more likely for larger firms, less likely for firms in regulated industries, less likely for forecasts issued over longer horizons, more likely for bad news forecasts, and more likely for forecasts that are maximum type. Furthermore, attributions are associated with greater absolute price reactions to management forecasts, more negative price reactions to management forecasts (forecast news held constant), and a greater price reaction per dollar of * University of Georgia; †Indiana University; ‡Harvard University. We thank Andrea Astill, Ben Ayers, Linda Bamber, Dave Barrett, Neil Bhattacharya, Walt Blacconiere, Christine Botosan, Claire Bush, Jenny Gaver, Ken Gaver, Eric Lie, Laureen Maines, Roger Martin, Marlene Plumlee, Jamie Pratt, Aamer Sheikh, Kimberly Smith, David Upton, Jim Wahlen, Wanda Wallace, Isabel Wang, an anonymous referee, and workshop participants at the University of Utah, Indiana University, the University of Georgia, the University of Missouri, the College of William and Mary, and Louisiana State University for comments on earlier versions of this paper. We also gratefully acknowledge the contribution of IBES International Inc. for providing earnings per share forecast data. These data have been provided as part of a broad academic program to encourage earnings expectations research. unexpected earnings. Our findings hold after control for the aforementioned determinants of attributions and after control for other firm-and forecastspecific variables that are often associated with security prices.
SUMMARYAuditing standards prescribe that the auditor should consider client management's attitude toward fraud when making fraud risk assessments. However, little guidance is provided in the auditing standards or the existing fraud literature on observable indicators of fraud attitude.We test whether observable indicators of narcissism, a personality trait linked to unethical and fraudulent behavior, is viewed by auditors as an indicator of increased fraud attitude risk. We administered an experiment to 101 practicing auditors from one international public accounting firm who assessed fraud risk based on a scenario in which client manager narcissism (attitude) and fraud motivation were each manipulated at two levels (low and high). Our results show that narcissistic client behavior and fraud motivation are significantly and positively related to auditors' overall fraud risk assessments. Implications of these findings for further research and the auditing profession are discussed.
Managers often explain their earnings forecasts by linking forecasted performance to their internal actions and the actions of parties external to the firm. These attributions potentially aid investors in the interpretation of management forecasts by confirming known relationships between attributions and profitability or by identifying additional causes that investors should consider when forecasting earnings. We investigate why managers choose to provide attributions with their forecasts and whether the attributions are related to security price reactions to management earnings forecasts. Using a sample of 951 management earnings forecasts issued from 1993 to 1996, we find that attributions are more likely for larger firms, less likely for firms in regulated industries, less likely for forecasts issued over longer horizons, more likely for bad news forecasts, and more likely for forecasts that are maximum type. Furthermore, attributions are associated with greater absolute price reactions to management forecasts, more negative price reactions to management forecasts (forecast news held constant), and a greater price reaction per dollar of * University of Georgia; †Indiana University; ‡Harvard University. We thank Andrea Astill, Ben Ayers, Linda Bamber, Dave Barrett, Neil Bhattacharya, Walt Blacconiere, Christine Botosan, Claire Bush, Jenny Gaver, Ken Gaver, Eric Lie, Laureen Maines, Roger Martin, Marlene Plumlee, Jamie Pratt, Aamer Sheikh, Kimberly Smith, David Upton, Jim Wahlen, Wanda Wallace, Isabel Wang, an anonymous referee, and workshop participants at the University of Utah, Indiana University, the University of Georgia, the University of Missouri, the College of William and Mary, and Louisiana State University for comments on earlier versions of this paper. We also gratefully acknowledge the contribution of IBES International Inc. for providing earnings per share forecast data. These data have been provided as part of a broad academic program to encourage earnings expectations research. unexpected earnings. Our findings hold after control for the aforementioned determinants of attributions and after control for other firm-and forecastspecific variables that are often associated with security prices.
In an exploratory study, we report how 140 auditors rate the relative importance of 25 risk factors (red flags) identified in SAS No. 82. The Analytic Hierarchy Process (AHP) is used to produce a decision model for each subject, and mean decision models are reported for groups of subjects. The results indicate that management characteristics and influence over the control environment red flags were approximately twice as important as operating and financial stability characteristics red flags and about four times as important as industry conditions red flags. The three single most important red flags account for almost 40 percent of the total decision weight. A particularly interesting finding is that the mean decision models of 43 Big 5 auditors, 50 regional/localfirm auditors, and 47 internal auditors were not significantly different from each other.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.