This study presents the results of an experiment that examines how two underlying characteristics of pro forma earnings announcements, pro forma emphasis and the presence of a quantitative reconciliation, influence nonprofessional investors' and analysts' reliance on pro forma disclosures. The results indicate that the emphasis management places on pro forma earnings, not the mere presence of pro forma earnings, influences nonprofessional investors' judgments and decisions, but that this influence is mitigated by the presence of a quantitative reconciliation. Further analysis reveals that the influence of pro forma emphasis on nonprofessional investors' judgments and decisions seems to be the result of an unintentional cognitive effect as opposed to the perceived informativeness of the earnings figure emphasized by management. Analysts' judgments and decisions were also affected by the presence of reconciliation, but in the opposite direction to those of nonprofessional investors. Specifically, the presence of a quantitative reconciliation led analysts to view pro forma earnings as more reliable, increasing their reliance on the pro forma disclosure in judging the earnings performance of the firm.

We examine how accounting transparency and investor base jointly affect financial analysts' expectations of mispricing (i.e., expectations of stock price deviations from fundamental value). Within a range of transparency, these two factors interactively amplify analysts' expectations of mispricing—analysts expect a larger positive deviation when a firm's disclosures more transparently reveal income‐increasing earnings management and the firm's most important investors are described as transient institutional investors with a shorter‐term horizon (low concentration in holdings, high portfolio turnover, and frequent momentum trading) rather than dedicated institutional investors with a longer‐term horizon (high concentration in holdings, low portfolio turnover, and little momentum trading). Results are consistent with analysts anticipating that transient institutional investors are more likely than dedicated institutional investors to adjust their trading strategies for near‐term factors affecting stock mispricings. Our theory and findings extend the accounting disclosure literature by identifying a boundary condition to the common supposition that disclosure transparency necessarily mitigates expected mispricing, and by providing evidence that analysts' pricing judgments are influenced by their anticipation of different investors' reactions to firm disclosures.

Firms’ Corporate Social Responsibility ( CSR ) reports typically frame their strategies in terms of either community or global efforts (i.e., “strategy frame”). Further, the style used to depict CSR performance in reports often highlights either pictures or words (i.e., “presentation style”). These two prominent disclosure features of CSR reports promote a natural fit or misfit in the focus (relatively low‐level or high‐level focus) investors adopt when thinking about the firm and its CSR efforts. Further, these disclosure features likely have different effects on investors depending on their numeracy or, in other words, the way that they naturally process numerical information. In this study, we predict and find that a fit between the strategy frame and the presentation style of a firm's CSR report causes less numerate investors to be more willing to invest than when a fit is not present. Specifically, we find that a fit leads less numerate investors to experience subjective feelings of processing fluency and, in turn, positive affect that serves as a cue that the positive CSR performance information can be relied upon, which positively influences willingness to invest. Our results have implications for both CSR reports as well as other types of firm disclosures that increasingly vary along similar disclosure characteristics. Our results also contribute to both the growing literature on presentation effects in accounting, as well as the broader business literature on CSR reporting.

We use experimental markets to examine how pushing investment information and the value relevance of that information interact to influence investors’ value estimate accuracy and market price efficiency. Developments in technology allow information to be pushed to investors anytime and anywhere. However, in addition to value‐relevant information, pushed information often includes information that is irrelevant for assessing firm value. Drawing on psychology theory, we find that pushing information has divergent effects depending on the value relevance of the information. Pushing only value‐relevant information increases investors’ processing of the information and leads to more accurate value estimates and market prices than when not pushed. In contrast, pushing a mix of value‐relevant and value‐irrelevant information reduces investors’ processing of value‐relevant information, leading to less accurate value estimates and market prices due to poorer acquisition and integration of information than when not pushed or when only value‐relevant information is pushed. Collectively, our results reveal a dark side to push technologies, particularly with the growing presence of value‐irrelevant information.

We use a machine learning technique to assess whether the thematic content of financial statement disclosures (labeled topic ) is incrementally informative in predicting intentional misreporting. Using a Bayesian topic modeling algorithm, we determine and empirically quantify the topic content of a large collection of 10‐K narratives spanning 1994 to 2012. We find that the algorithm produces a valid set of semantically meaningful topics that predict financial misreporting, based on samples of Securities and Exchange Commission (SEC) enforcement actions (Accounting and Auditing Enforcement Releases [AAERs]) and irregularities identified from financial restatements and 10‐K filing amendments. Our out‐of‐sample tests indicate that topic significantly improves the detection of financial misreporting by as much as 59% when added to models based on commonly used financial and textual style variables. Furthermore, models that incorporate topic significantly outperform traditional models when detecting serious revenue recognition and core expense errors. Taken together, our results suggest that the topics discussed in annual report filings and the attention devoted to each topic are useful signals in detecting financial misreporting.

An enduring issue in financial reporting is whether and how salient summary measures of firm performance (“earnings metrics”) affect market price efficiency. In laboratory markets, we test the effects of salient earnings metrics, which vary in how they combine persistent and transitory elements, on investor information search, beliefs about value, offers to trade, and market price efficiency. We find that including transitory elements in salient earnings metrics causes traders to search unnecessarily for further information about these elements and to overestimate their effect on fundamental value relative to a rational benchmark. In contrast, separately displaying persistent elements in earnings increases the accuracy of traders’ value estimates. Prices generally reflect traders’ beliefs about value, and prices are most efficient when transitory elements are excluded from earnings metrics entirely. Our study contributes to research on salience effects in financial reporting by showing that including transitory elements in salient earnings metrics causes inefficient information search and biased beliefs about value that can aggregate to affect market prices. We also contribute to research in experimental markets by showing that redundant disclosure is not always beneficial; redundant disclosure of transitory earnings elements, in particular, appears to have negative consequences for investor behavior and market efficiency.

Technological advances are creating a shift in the information disclosure environment allowing more investors to interact with management. We examine three key levels of trader‐management interaction to assess the accuracy of traders' market‐tested value estimates and resulting market price. These data require an engaging experiment and a complex, contextually rich asset, which we create by playing a popular gaming app before the experiment. Participants view financial information, ask management questions, estimate value, and trade. We find that receiving non‐personalized question responses improves trader estimates of value and market price efficiency relative to when traders ask questions but do not expect a response. This occurs because traders exert more effort estimating value and trading. However, receiving personalized versus non‐personalized responses harms value estimates and market efficiency. This occurs because traders receiving personalized responses fixate on the interaction with management, dividing their attention and diverting it away from valuing and trading the asset.

We investigate a key assumption underlying much of the experimental research in financial accounting that graduate business students are a good proxy for nonprofessional investors. To conduct our investigation, we categorize recent experimental studies in financial accounting, based on the relative level of integrative complexity inherent in each study's task. We then conduct experiments using two tasks, one that is relatively low in integrative complexity and one that is relatively high in integrative complexity, and compare the responses of two groups of M.B.A. students and nonprofessional investors. Our results suggest that using M.B.A. students as a proxy for nonprofessional investors is a valid methodological choice, provided researchers give careful consideration to aligning a task's integrative complexity with the appropriate level of M.B.A. student. M.B.A. students who have completed their core M.B.A. courses and are enrolled in or have completed a financial statement analysis course are a good proxy for nonprofessional investors in tasks that are relatively low in integrative complexity. Though less definitive, the majority of our tests also suggest that these students are a good proxy for nonprofessional investors in tasks that are relatively high in integrative complexity. However, care must be taken when using students in the first-year core financial accounting course. In tasks that are relatively low in integrative complexity, these students perform similarly to nonprofessional investors except when they are asked to make an investment decision. In tasks that are relatively high in integrative complexity, these students acquire information similarly to nonprofessional investors, but they do not appear to integrate the information in a similar manner.