JournalTOCs

Review of Accounting Studies
Journal Prestige (SJR): 2.757

Citation Impact (citeScore): 2
Number of Followers: 27

Hybrid journal (It can contain Open Access articles)
ISSN (Print) 1573-7136 - ISSN (Online) 1380-6653
Published by Springer-Verlag

[2657 journals]

Correction to: Inducement grants, hiring announcements, and adverse
selection for new CEOs
- Abstract: A Correction to this paper has been published: https://doi.org/10.1007/s11142-020-09577-2
  PubDate: 2021-06-01
Real effects of auditor conservatism
- Abstract: We examine the effect of auditor conservatism on corporate innovation. We hypothesize that, because conservative auditors constrain income-increasing accounting discretion, managers may sacrifice long-term investments in innovation to boost current earnings and meet short-term performance targets. Exploiting state-level auditor legal liability shocks as a means of identification, we find evidence consistent with this hypothesis. Cross-sectional analyses reveal that the negative effect of increased auditor conservatism on corporate innovation is more pronounced when the client firms are under greater equity- and debt-market pressures, when the client firms are exposed to greater litigation risk, and when the client firms are audited by large auditors. Our study highlights how auditors, as external monitors, can affect not only the financial reporting quality of their clients but may also induce alterations in their real operations.
  PubDate: 2021-06-01
Measuring credit risk using qualitative disclosure
- Abstract: We use machine learning methods to create a comprehensive measure of credit risk based on qualitative information disclosed in conference calls and in management’s discussion and analysis section of the 10-K. In out-of-sample tests, we find that our measure improves the ability to predict credit events (bankruptcies, interest spreads, and credit rating downgrades), relative to credit risk measures developed by prior research (e.g., z-score). We also find our measure based on conference calls explains within-firm variation in future credit events; however, we find little evidence that the measures of credit risk developed by prior research explain within-firm variation in credit risk. Our measure has utility for both academics and practitioners, as the majority of firms do not have readily available measures of credit risk, such as actively-traded CDS or credit ratings. Our study also adds to the growing body of research using machine-learning methods to gather information from conference calls and MD&A to explain key outcomes.
  PubDate: 2021-06-01
Using machine learning to detect misstatements
- Abstract: Machine learning offers empirical methods to sift through accounting datasets with a large number of variables and limited a priori knowledge about functional forms. In this study, we show that these methods help detect and interpret patterns present in ongoing accounting misstatements. We use a wide set of variables from accounting, capital markets, governance, and auditing datasets to detect material misstatements. A primary insight of our analysis is that accounting variables, while they do not detect misstatements well on their own, become important with suitable interactions with audit and market variables. We also analyze differences between misstatements and irregularities, compare algorithms, examine one-year- and two-year-ahead predictions and interpret groups at greater risk of misstatements.
  PubDate: 2021-06-01
Measuring audit quality
- Abstract: We document 45 specific allegations related to audit deficiencies based on GAAS, as detailed in 141 AAERs and 153 securities class action lawsuits over the violation years 1978–2016. Next, we use these allegations to validate popular proxies of audit quality. Of all the audit quality proxies, we find that restatements consistently predict all of the top six most cited audit deficiencies. The ratio of audit fees to total fees and the presence of a city specialist auditor predict five of the most cited deficiencies. Overall, our results suggest that the predictive power of audit quality proxies depends on (i) the settings that researchers are interested in and (ii) the specific audit deficiencies hypothesized to matter in the investigated setting. For instance, future studies related to auditor independence might consider using restatements and the ratio of audit fees to total fees as proxies of audit quality.
  PubDate: 2021-06-01
Is all disaggregation good for investors' Evidence from earnings
announcements
- Abstract: Research suggests that greater earnings disaggregation in financial statements leads to favorable market outcomes. This perspective is based on a presumption that the disaggregation separates earnings components with heterogeneous characteristics. We hypothesize that the disaggregation of homogeneous earnings components is associated with greater investor disagreement and a less efficient market response to the earnings announcement. We estimate persistence regressions at the industry level and classify earnings components with persistence that differs significantly from the persistence of sales as heterogeneous and components with persistence that does not differ from the persistence of sales as homogeneous. Consistent with our hypothesis, we find a significant positive relation between the level of homogeneous earnings disaggregation and investor disagreement around earnings announcements. We also find significantly greater post-earnings announcement drift after earnings announcements with greater homogeneous earnings disaggregation. This evidence is consistent with homogeneous earnings disaggregation hindering investors’ ability to impound earnings information into price efficiently.
  PubDate: 2021-06-01
Heterogeneity in expertise in a credence goods setting: evidence from
audit partners
- Abstract: We examine the heterogeneity of experts in a credence goods setting. In our analytical model, clients are uncertain about how much effort experts need to provide to solve their problem, which is either simple or difficult. Experts have varying degrees of expertise. Less qualified experts are equally effective at solving simple problems but less effective at solving difficult ones. We show that clients pay a fee premium to more qualified experts, even for simple problems. This premium increases with the probability that the client has a difficult problem. We empirically test the model predictions in the context of partner industry expertise for the U.S. operations of the Big Four audit firms. We find, consistent with the model, a positive association between partner industry specialization and audit fees, even for simple audits, and a negative association between partner specialization and the client’s probability of restatements only for difficult audits. The industry specialization premium is higher in industries with higher proportions of difficult audits. Consistent with credence good agency issues, the specialization premium for simple audits is mitigated when information asymmetry between client and auditor is lower.
  PubDate: 2021-06-01
Analyst teams
- Abstract: This paper examines the impact of teamwork on sell-side analysts’ performance. Using a hand-collected sample of over 50,000 analyst research reports, we find that analyst teams issue more than 70% of annual earnings forecasts. In contrast, most research implicitly assumes that forecasts are issued by individual analysts. We document that analyst teams generate more accurate earnings forecasts than individual analysts and that the stock market reacts more strongly to forecast revisions issued by teams. Analyst teams also cover more firms, issue earnings forecasts more frequently, and issue less stale forecasts. Analysts working in teams are more likely to be voted as All-Star analysts in the future. Among analyst teams, we show that team size and team member ability are significantly associated with forecast accuracy. Moreover, using detailed analyst background information from LinkedIn, we find that forecast accuracy is positively associated with team diversity based on sell-side experience, educational background, and gender. Additional analyses suggest that analyst teams, especially more diverse ones, are more likely to issue cash-flow forecasts and use discounted cash-flow valuation models in their reports. These findings suggest that teamwork and team diversity play a crucial role in understanding sell-side analysts’ performance.
  PubDate: 2021-06-01
Voluntary versus mandatory disclosure
- Abstract: We develop a theory of asymmetries between voluntary and mandatory disclosure. Efficiently designed mandatory disclosure policies are substitutes for excessive voluntary disclosures. The efficient policy takes the form of a lower threshold below which firms must disclose bad news and an upper threshold above which firms voluntarily disclose good news. Hence mandatory disclosures are asymmetric and feature conservative reporting of bad news. The threshold to recognize bad news increases when information is more precise. We also characterize interactions between disclosures and real decisions in environments where information has social value: investment decisions, optimal liquidations, and adverse selection in a lemons market.
  PubDate: 2021-06-01
Management forecasts of volatility
- Abstract: We examine the predictive information content of the management forecasts of stock return volatility (i.e., expected volatility) that are disclosed in annual reports. We find that expected volatility predicts near-term and longer-term stock return volatility and earnings volatility incremental to implied volatility, historical volatility, firm characteristics, and alternative measures of uncertainty. We also find that expected volatility reflects managers’ private information about their firms’ future investment activities, such as mergers and acquisitions and R&D intensity. Finally, we find that the predictive power of expected volatility shrinks when managers have stronger incentives to manage earnings. Overall, we provide novel evidence that management forecasts of volatility contain private information about future uncertainty that can help forecast volatility.
  PubDate: 2021-06-01
Correction to: The unintended benefit of the risk factor mandate of 2005
- Abstract: An Erratum to this paper has been published: https://doi.org/10.1007/s11142-021-09590-z
  PubDate: 2021-05-13
Are corruption and corporate tax avoidance in the United States
related'
- Abstract: We examine whether state-level corruption and corporate tax avoidance in the United States (U.S) are related. Using a sample of 36,078 U.S. firm-year observations from 1998 to 2014, we find that corruption is significantly positively related to tax avoidance. Our main finding is consistent across a series of robustness tests. In additional analysis at the state level, we observe that corruption is significantly positively related to corporate tax avoidance in states that have low levels of litigation risk, irrespective of whether the states rank high or low in terms of corporate governance, social capital, or money laundering. We also correlate state- and firm-level corruption with firm-level corporate tax avoidance and find that the interaction terms are generally significantly positively related to corporate tax avoidance. Finally, we show that state-level corruption and corporate tax avoidance are complementary across industry sectors. Overall, our results indicate that the broader state-level corruption (cultural) effects of where a firm is headquartered have significant consequences for corporate tax avoidance.
  PubDate: 2021-05-12
Does litigation change managers’ beliefs about the value of voluntarily
disclosing bad news'
- Abstract: Research suggests that earnings-disclosure-related litigation causes managers to reduce subsequent disclosure, perhaps stemming from a belief that even their good faith disclosures will cause them trouble. This paper considers unexplored dimensions of disclosure and alternative channels of disclosure to provide additional evidence that speaks to how litigation shapes managers’ disclosure strategies. Consistent with Skinner (1994)’s classic legal liability hypothesis, we find that, while managers reduce and delay forecasts of positive earnings news following litigation, they increase the frequency and timeliness of their bad news forecasts. Moreover, many managers who were nonguiders prior to facing legal scrutiny begin guiding following litigation. Managers also maintain (if not increase) the information they provide via press releases and during conference calls following litigation. Supporting the notion that managers use disclosure to walk down expectations, additional analyses document an increase in the likelihood that lawsuit firms report earnings that beat consensus forecasts in the post-lawsuit period. Collectively, our evidence suggests that following litigation managers continue to view disclosure as a valuable tool that shapes their firms’ information environments and reduces expected legal costs. In so doing, it supports an important alternative viewpoint of how firms respond to litigation as well as the effectiveness of litigation as a disciplining mechanism.
  PubDate: 2021-05-07
IAS 7 and value relevance: the direct method versus the indirect method
- Abstract: We identify and predict circumstances where the direct method statement of cash flows is expected to provide more value relevant information to financial statement users. We predict the direct method is more informative when earnings are of lower quality (earnings are less permanent or companies report losses), companies are in a more stable state (proxied by small absolute changes in accruals/operating cash flow), and when cash flows/accruals are measured with more error using the indirect method. Direct method disclosure is also predicted to be more useful for small companies, where investors have fewer alternative sources of information beyond financial statements. We analyze Australian companies because they are required to report the direct and indirect method, and we further decompose the sample into industrial, mining, and company size to account for unique features of the Australian market. Our results are consistent with our predictions. This suggests the indirect method is as informative as the direct method on average but the direct method incrementally informs stock returns in specific circumstances. We also identify operational factors that significantly increase estimation error when estimating direct method line items for cash receipts and cash payments.
  PubDate: 2021-05-05
Earnings announcement return extrapolation
- Abstract: We propose that extrapolative beliefs about earnings announcement (EA) returns may contribute to the understanding of EA return patterns. We construct a theoretically motivated measure of extrapolative investors’ expectations based on a stock’s recent history of EA returns. We then show that this measure explains cross-sectional variation in stock returns and investor behavior around EAs. Stocks expected to have high EA returns, according to our measure, experience predictable increases in prices before EAs and predictable decreases afterward. These patterns are economically significant: investors that buy (sell) a portfolio that is long firms with high recent EA returns and short firms with low recent EA returns in the pre-EA (post-EA) period earn daily five-factor abnormal returns of 16.1 bps (18.3 bps). Using individual investor trades data and a measure of institutional trading, we find that individual and institutional investors are more likely to purchase stocks with high recent EA returns, consistent with at least a subset of investors forming extrapolative beliefs about EA returns.
  PubDate: 2021-05-01
The value of board commitment
- Abstract: Boards can learn about the environment of their firms through information gathering and communicating with the CEO. In the post-Sarbanes-Oxley environment, some boards have taken steps to shape the communication more proactively by committing to decision rules, such as spending limits, before eliciting a report from the CEO. All else equal, such commitment power on the part of the board improves its communication with the CEO. However, taking into consideration the endogeneity of board composition/bias, we show that the board’s commitment power may in fact impede such communication, in equilibrium, by prompting the shareholders to appoint a more antagonistic board. We identify other cases where, in equilibrium, the board’s commitment power does foster communication, but ultimately reduces shareholder value, because the improved information flow dampens the board’s effort incentives. We discuss applications of our model to board staggering.
  PubDate: 2021-05-01
Status motives and agent-to-agent information sharing
- Abstract: Although decision-making within firms improves when agents share information with one another, agents often have limited motivation to share because doing so takes effort and time. In four experiments, we examine how agents’ responses to information sharing controls depend on an important source of motivation: active status motives, that is, the desire to gain respect from others. In a rewards-based system that compensates agents for sharing, agents with active status motives demand relatively larger rewards. In a sacrifice-based system that does not compensate agents for sharing, agents with active status motives make larger sacrifices but only when sharing is visible to others. In brief, agents with active status motives show off in the manner the control system frames as easiest, that is, conspicuous value-signaling or conspicuous generosity-signaling. Broadly speaking, active status motives inhibit sharing when sharing involves rewards but decrease barriers when sharing involves sacrifice. Understanding the motivation for status is critical to motivating agent-to-agent sharing within firms.
  PubDate: 2021-04-26
Accounting-based thresholds and growth decisions in the banking industry
- Abstract: This paper examines the effects of accounting-based thresholds in regulation on growth decisions in the banking industry. To investigate this relation we study changes in growth around the $10 billion asset threshold specified in the Dodd-Frank Act. We first document that, in the years after the new threshold-based regulations are announced, banks slow their asset growth as they approach the threshold and then accelerate their asset growth as they cross the threshold. Next, we document the primary mechanism banks use to achieve each of these changes in growth: reduced deposit growth rates to slow growth and increased acquisition activity to accelerate growth. Finally, we document that, while banks attempt to remain below the threshold, they reduce the growth of their investment portfolio and report a lower return on assets. Also, when banks accelerate growth through acquisition activity, those acquisitions involve larger and riskier target banks. These findings suggest that regulations with accounting-based thresholds can affect growth decisions and profitability in the banking industry.
  PubDate: 2021-04-24
Correction to: Management forecasts of volatility
- Abstract: A Correction to this paper has been published: https://doi.org/10.1007/s11142-021-09592-x
  PubDate: 2021-03-25
Non-random sampling and association tests on realized returns and risk
proxies
- Abstract: This paper investigates how data requirements often encountered in archival accounting research can produce a data-restricted sample that is a non-random selection of observations from the reference sample to which the researcher wishes to generalize results. We illustrate the effects of non-random sampling on results of association tests in a setting with data on one variable of interest for all observations and frequently-missing data on another variable of interest. We develop and validate a resampling approach that uses only observations from the data-restricted sample to construct distribution-matched samples that approximate randomly-drawn samples from the reference sample. Our simulation tests provide evidence that distribution-matched samples yield generalizable results. We demonstrate the effects of non-random sampling in tests of the association between realized returns and five implied cost of equity metrics. In this setting, the reference sample has full information on realized returns, while on average only 16% of reference sample observations have data on cost of equity metrics. Consistent with prior research (e.g., Easton and Monahan The Accounting Review 80, 501–538, 2005), analysis using the unadjusted (non-random) cost of equity sample reveals weak or negative associations between realized returns and cost of equity metrics. In contrast, using distribution-matched samples, we find reliable evidence of the theoretically-predicted positive association. We also conceptually and empirically compare distribution-matching with multiple imputation and selection models, two other approaches to dealing with non-random samples.
  PubDate: 2021-03-09
  DOI: 10.1007/s11142-021-09581-0