ChatGPT, a language-learning model chatbot, has garnered considerable attention for its ability to respond to users’ questions. Using data from 14 countries and 186 institutions, we compare ChatGPT and student performance for 28,085 questions from accounting assessments and textbook test banks. As of January 2023, ChatGPT provides correct answers for 56.5 percent of questions and partially correct answers for an additional 9.4 percent of questions. When considering point values for questions, students significantly outperform ChatGPT with a 76.7 percent average on assessments compared to 47.5 percent for ChatGPT if no partial credit is awarded and 56.5 percent if partial credit is awarded. Still, ChatGPT performs better than the student average for 15.8 percent of assessments when we include partial credit. We provide evidence of how ChatGPT performs on different question types, accounting topics, class levels, open/closed assessments, and test bank questions. We also discuss implications for accounting education and research.

Purpose The purpose of this paper is to examine restrictions placed by the Troubled Asset Relief Program (TARP) on executive compensation during the financial crisis. Since it remains unclear if TARP restored public confidence in financial institutions, the authors also analyze what effect such regulations had on investors’ confidence in the information provided by earning with respect to executive compensation during this critical period. Design/methodology/approach To test the assertions, the authors employ an Earnings Response Coefficient model, which captures the association between firms’ earnings surprise (ES) and perceived earnings informativeness. The authors implement both a long- and short-window test to obtain a better understanding of the effects of TARP on financial institutions’ earnings informativeness. The authors use the long-window approach to gather evidence about whether and how financial institutions’ ES are absorbed into security prices conditional on both their participation in TARP and their compliance with TARP’s compensation restrictions. The authors attempt to establish a stronger causal link by also using a short-window approach. Findings The authors find that firms paying their CEOs above the TARP threshold show higher earnings informativeness. Financial institutions that paid their CEOs above the TARP threshold achieved better performance during their participation in TARP. The authors also find that a decrease in total compensation while participating in TARP is associated with improved earnings informativeness. Lastly, separating total compensation into its cash and stock-based components, the authors find that firms improve earnings informativeness when they increase (decrease) cash (performance) compensation during TARP. However, overall earnings informativeness decreases during and after TARP relative to the pre-TARP period. Practical implications The research suggests that executive compensation incentives affect earnings informativeness and that tradeoffs are made between direct and indirect costs in retaining executives. The results have implications for policy makers, investors and researchers because the results allow policy makers and regulators to improve on how they design and implement accounting, market and finance regulations and reforms. Investors may potentially use the results when evaluating firm experiencing financial and, in some case, political distress. It also helps firms and offering optimal compensation contracts to create proper incentives for executives and ensure that managerial actions result in successful firm performance. Social implications The study shows how firms react to changing regulations that affect executive compensation and earning informativeness. The results of the study allow regulators to potentially design more effective regulations by targeting certain aspects of firms’ operation such excessive risk-taking behavior and rent extraction opportunities. Originality/value There are very few studies that deal with how firms react to regulation that affect executive compensation. The authors provide evidence regarding what effect TARP and its compensation restrictions had on financial institutions’ earnings informativeness. The evidence in the study will further regulators’ understanding of whether TARP improved investors’ confidence in financial institutions. The paper also contributes to the understanding in how changes in executive compensation in times of high political scrutiny affect investors’ perceptions of firm performance.

The oil and gas industry is subject to different types of risks, many of which have the potential to generate extreme results. Classifying extreme events as global, industry specific and firm specific, we use a Bayesian probability model and the Exponential Generalized Autoregressive Conditional Heteroskedasticity (EGARCH) model to evaluate the impact of disclosure of extreme events on returns and return volatilities. The results suggest political events have more of a pronounced effect compared to those classified as economic events. The overall effects are more pronounced at the global and firm‐level classifications. At the firm level, extreme economic events have a more significant impact than political extreme events.

Purpose This paper aims to examine the applicability of real options methodology with respect to developing internal transfer pricing mechanisms. A pervasive theme in existing models is their inability to handle the dynamic and volatile nature of today’s business environment, as well as their lack of objective managerial flexibility. The authors address these and other issues and develop a transfer pricing mechanism based on Black–Scholes and the binomial options pricing methodology, which is better suited in today’s dynamic business environment. Design/methodology/approach The authors use a conceptual approach in developing theoretical justifications and show, practically, how a transfer price can be developed using two different real options pricing models. Findings The authors find that real options transfer price mechanism (real options framework [ROF]) can effectively deal with many of the issues that permeate a modern organization with complex multi-dimensional operations. The authors argue that uncertainty and behavioral issues commonly associated with setting transfer prices are better handled using a transfer pricing mechanism that preserves flexibility at the business unit level, the managerial level and the firm level. The approach allows for different managerial styles in both centralized and decentralized sub-units within the same organization. The authors argue that an open multi-dimensional framework using real options is suitable under conditions of uncertainty and managerial opportunism. Practical implications ROF-based transfer pricing may be significant in that firms can use it as a tool to manage an organization by setting the prices centrally and at the same time allowing managers to select the transfer price that best suits their specific situation and operating conditions. This may result in a more efficient and more profitable organization. Originality/value The contribution of the paper is the melding of the ROF from the finance literature with the accounting problem of setting a transfer price for items lacking a competitive market price. The authors also contribute to existing research by explicitly developing a framework that values managerial flexibility, takes into account uncertainty and considers the behavioral aspects of the transfer pricing process. The authors establish the conditions under which a generic real options model is a feasible alternative in determining a transfer price.

Purpose The purpose of this study is to examine the association between revenue-based earnings management in the periods immediately before and after firms’ initial public offerings (IPOs) and regulatory scrutiny by the United States Securities and Exchange Commission (SEC) during review of IPO firms’ registration statements. Design/methodology/approach This paper uses conditional discretionary revenues (Stubben, 2010) as its measure of earnings management, and revenue recognition comments delivered by the SEC as its measure of regulatory scrutiny. The authors use ordinary least squares regression (OLS) models, as well as a supplemental count model, to assess the association between conditional discretionary revenues and revenue recognition comments delivered by the SEC. Findings This study finds evidence of a positive association between earnings management measures in the pre-IPO period and the number of revenue recognition comments received by those firms during the SEC’s review. Furthermore, this study provides evidence that greater numbers of comments are associated with declining earnings management measures in the post-IPO period. However, the evidence suggests that these associations apply only to income-decreasing earnings management. Originality/value This paper extends the IPO earnings management literature by using conditional discretionary revenues as the measure of earnings management, and contributes to a nascent research stream in the accounting literature by investigating the SEC’s comment letter process and its association with, and impact upon, earnings management in the IPO process.