Knowledge that Transforms

The range of non-EPS forecast types provided by individual analysts to I/B/E/S has increased dramatically over time but varies considerably across firms. We propose that in providing a broader range of forecast types, analysts can signal superior research ability and research effort. Consistent with this hypothesis, we document positive associations between the number of forecast types (NFT) an analyst provides and common proxies for research quality, including earnings forecast accuracy, price target accuracy, stock recommendation profitability, market reactions to stock recommendation revisions, and analyst career outcomes. The effects of NFT are incremental to other quality proxies used in the literature and are distinct from the issuance of specific non-EPS forecast types studied previously (e.g., cash flow forecasts). We demonstrate the information value of NFT to investors by examining the out-of-sample performance of portfolios formed conditional on NFT and exploiting revisions in consensus earnings forecasts and individual analysts’ stock recommendations. We conclude that the number of forecast types an analyst provides for a firm is a readily available proxy for the quality of her research.

We examine the choice of organizational structure for VC-backed startup firms. These firms overwhelmingly organize as C-corporations rather than as tax advantaged limited liability companies (LLCs). This results in foregone tax savings of $43.9 billion, or 4.9% of the total equity invested in the sample firms. The decision is puzzling, given plausible estimates of the direct costs involved, but appears related to “hassle” and other transition costs generated by participants implementing a new form. Firms with more employees and investors are likely to choose the C-corporation. VCs appear to prefer the C-corporation form, as receiving VC money is associated with most LLC firms switching to a C-corporation within 30 days. Greater VC preferences for C-corporations are linked to a preference for familiarity, and less attention to taxes.

The Gong, Young, and Zhou (GYZ) (Gong et al. 2023) paper examines potential earnings management by movie studio companies. Using a large sample of 3094 US-produced English-language movies released between 1997 and 2019, they find that movie studio companies, when faced with a below expected US box office revenue yield from their movies in a specific quarter, move up the release dates of movies with high expected revenues. This “move-up” release is an example of what the accounting research literature calls real earnings management. This commentary on GYZ (Gong et al. 2023) adds more structure to the decision-making context in which movie release dates are set, placing greater emphasis on the role of movie screening companies, which have the final say on the release dates for the movies they show on their screens. It also highlights the rich information setting that exists in the motion picture industry, which can be further exploited to probe the reliability of the earnings management findings reported by GYZ (Gong et al. 2023). This rich information includes security analyst reports and screen days available to quarter-end for each movie released. The commentary has relevance for other research in specific industries where the institutional domain has the potential to provide insight into real earnings management.

We provide an applied introduction to Bayesian estimation methods for empirical accounting research. To showcase the methods, we compare and contrast the estimation of accruals models via a Bayesian approach with the literature’s standard approach. The standard approach takes a given model of normal accruals for granted and neglects any uncertainty about the model and its parameters. By contrast, our Bayesian approach allows incorporating parameter and model uncertainty into the estimation of normal accruals. This approach can increase power and reduce false positives in tests for opportunistic earnings management as a result of better estimates of normal accruals and more robust inferences. We advocate the greater use of Bayesian methods in accounting research, especially since they can now be easily implemented in popular statistical software packages.

This study examines how a strategic tax auditor affects a multinational firm’s transfer pricing in a tax compliance game. Our model uses a divisionalized firm, in both a low-tax and a high-tax country, that decides to implement a transfer-pricing regime with either one or two sets of books. After observing its unit costs, the firm reports a compliant or noncompliant tax transfer price. In a regime with one set of books, the single transfer price coordinates the quantity decision and determines the tax payments. In a regime with two sets, different transfer prices serve those tasks. In contrast to previous studies, our analysis incorporates a strategic tax auditor, who observes the tax transfer price and decides whether to audit the firm. Real-world regulations suggest larger penalties for detected noncompliance under a two-sets-of-books transfer-pricing regime. Our analysis identifies the mixed strategy equilibria and examines how variations in the tax regulation—the tax rate difference and the penalty difference—affect the firm’s tax aggressiveness. We show that a firm acts less tax aggressively with a higher tax rate difference. Additionally, the model predicts that the firm either increases or decreases the probability of keeping one set of books for a smaller penalty difference.

Options, restricted stock, bonuses tied to total shareholder return, and similar equity-based compensation contracts stipulate payments that depend on stock price. Any such contract is a function of shareholder value net of the compensation payment, because stock price (1) is proportional to this net value or “net outcome” and (2) anticipates compensation-related payments and dilution. The net outcome, in turn, is reduced by the payment and so depends on the contract. Standard moral hazard analyses, wherein contractual payments are based on the gross outcome before any payment to the agent, overlook this dependency. We characterize the optimal net-outcome contract, describe its shape and pay-for-performance sensitivity, contrast it with the optimal gross-outcome contract, and discuss implications for equity-based compensation arrangements.

The many management guidance withdrawals during the COVID-19 pandemic have attracted considerable attention from the media, investors, and regulators. This study analyzes the determinants and consequences of these withdrawals. We find that guidance withdrawals are due to economic uncertainty, resulting from firms’ exposure to the COVID-19 pandemic rather than poor financial performance. Also, the effect of COVID-19 exposure on guidance withdrawals is stronger when firms face higher litigation risk. Further, guidance withdrawals result in abnormally large trading volumes and high analyst forecast dispersion but do not harm stock prices or the level of analyst earnings forecasts. Overall we believe the findings have implications for understanding corporate disclosure practices during periods with heightened economic uncertainty.

This paper studies the effect of timing and commitment of verification in a principal-agent relationship with moral hazard. To acquire additional information about the agent’s behavior, the principal possesses a costly technology that produces a noisy signal about the agent’s effort choice. The precision of this signal is affected by the principal’s verification effort. Two verification procedures are discussed: monitoring where the principal verifies the agent’s behavior simultaneously with his effort choice and auditing where the principal can condition her verification effort on the realized outcome. As it is well known, the principal prefers to audit the agent’s behavior if she can commit to her verification effort at the time of contracting. The main contribution of this paper is to highlight the importance of commitment by the principal to her verification effort. In particular, I show that, when the principal cannot commit to her verification effort ex-ante, the principal strictly prefers monitoring to auditing if the gains from choosing high effort are sufficiently high.

We examine whether dividends serve as substitutes or complements to accounting information in firm valuation. Consistent with dividends substituting for earnings information, we find that dividend paying firms have 11%–15% lower earnings response coefficients (ERCs) than non-payers. We find more substitution when the dividend provides a stronger signal of permanent earnings: when the firm is less likely to cut the dividend, when the firm is likely to fund the dividend out of earnings rather than cash reserves, or when the dividend is larger. We then show that dividend payers have lower absolute returns, less trading volume, and fewer analyst forecasts at the earnings announcement (EA), suggesting that dividend payers attract less attention to their less informative EAs. Finally, we show that the lower EA attention translates into less earnings management and fewer earnings-related disclosures for dividend payers relative to non-payers. Collectively, this evidence suggests that dividends supply information about permanent earnings and, although costly, could be an efficient way for some firms to satisfy investors’ demand for earnings information.

We analyze the extent to which individual audit partners influence the audited narrative disclosures in their clients’ financial reports. Using a sample of 3,281,423 private and public client firm-pairs, we find that the similarity among audited narrative disclosures is higher when two client firms share the same audit partner. Specifically, we find that the wording similarity of management reports (notes) increases by 30 (48) percent, the content similarity by 29 (49) percent, and the structure similarity by 48 (121) percent. Moreover, we find that audit partners in particular are relevant for their clients’ narrative disclosures because the increase in narrative disclosure similarity when sharing the same audit partner is nine (four) times greater than when sharing the same audit firm (audit office). We show that this influence of audit partners goes beyond adding boilerplate statements and, using novel field evidence, we shed light on the underlying mechanisms. Our findings are economically relevant because a stronger involvement of audit partners with their clients’ narratives is associated with a higher quality of narrative disclosures, which helps users better predict the future profitability of client firms.