Review of Accounting Studies最新文献

Research concludes that managers’ political orientation influences their decision-making and offers the political connections and risk tolerance hypotheses as explanations. We investigate partisan bias as an additional way political orientation may influence managers’ decisions. Partisan bias results in individuals whose partisan orientation aligns with that of the US president expressing more optimistic economic expectations. We examine whether partisan bias is present in managers’ annual earnings forecasts. We find that firms with CEOs whose partisanship aligns with that of the US president issue more optimistically biased annual earnings forecasts than firms with other CEOs. Higher-ability CEOs, however, are less susceptible to partisan bias. Additionally, we find that overestimating customer demand contributes to the forecast over-optimism of partisan-aligned CEOs and results in greater firm overinvestment. Furthermore, investors fail to discount the news in forecasts of partisan-aligned CEOs, and their firms’ post-forecast abnormal returns are lower.

We examine how locked-in CEO equity attributable to large unrealized capital gains tax liabilities influences the cost and restrictiveness of debt contracts. We find that firms enjoy lower loan spreads and are more (less) likely to receive ratings upgrades (downgrades) when their CEO has a large tax burden. Using the capital gains tax rate decrease in the Tax Reform Act of 1997 as an exogenous shock to CEO tax burdens, we find that CEOs with large tax burdens before the tax cut experience a sharp increase in loan spreads afterward. This increase in spreads is larger when the firm has low profitability, high bankruptcy risk, and when loans are unsecured. Further, CEO tax burdens decrease the restrictiveness of nonprice loan terms, increase syndicate size, and decrease issue costs.

This study investigates the influence of central bank private-sector quantitative easing (QE) policies on firms’ voluntary disclosures. While the effects of QE on borrowing costs and asset prices are well documented, spillovers in the disclosure realm remain understudied. This study specifically analyzes the effects of the Corporate Sector Purchase Program (CSPP), a private-sector QE policy implemented by the European Central Bank (ECB) in 2016 targeting corporate bonds in the euro area. Applying a difference-in-differences methodology to pre- and post-CSPP periods, I find that firms whose bonds the central bank purchased under the CSPP decreased their voluntary disclosures, particularly those related to cash flows and liabilities. My analysis attributes this decrease to reduced demand for firm-specific information from the central bank. My findings highlight the indirect consequences of QE monetary policy tools on corporate disclosure and contribute to the understanding of the transmission of monetary policy and investor-clientele dynamics.

Current corporate disclosures regarding carbon emissions lack generally accepted accounting rules. The transactional carbon accounting system described here takes the rules of historical cost accounting for operating assets as a template for generating carbon emissions (CE) statements comprising a balance sheet and a flow statement. The asset side of the CE balance sheet reports the carbon emissions embodied in operating assets. The liability side conveys the firm’s cumulative direct emissions into the atmosphere as well as the cumulative emissions embodied in goods acquired from suppliers less those sold to customers. Flow statements report the company’s annual corporate carbon footprint calculated as the cradle-to-gate carbon footprint of goods sold during the current period. Taken together, balance sheets and flow statements generate key performance indicators of a company’s past, current, and future performance in the domain of carbon emissions.

This study examines the investment value of information provided by crypto-influencers, that is, social media influencers covering crypto assets on Twitter. We examine the returns associated with approximately 36,000 tweets issued by 180 of the most prominent crypto social media influencers covering over 1,600 crypto assets for the two years spanning through December 2022. Our primary results indicate that crypto-influencers’ tweets are initially associated with positive returns. However, these tweets are followed by significant negative longer-horizon returns, suggesting they generate minimal long-term investment value. These effects are most pronounced for tweets issued by crypto-influencers proclaiming to be crypto experts, for smaller cap crypto asset securities and for self-described experts with many Twitter followers. In an additional analysis, we use machine-learning methods to classify tweets and find that this pattern of results strengthens when the tweets have a more positive sentiment or relate to buy recommendations.

While the production of credit ratings has long been limited mainly to rating agencies (CRAs), recent years have seen the growing popularity of consensus credit ratings crowdsourced from banks (i.e., bank ratings). We provide the first comprehensive examination of the properties and informativeness of bank ratings relative to CRA ratings. We find that bank ratings often deviate from CRA ratings, with over 60% of firm-months having different bank and CRA ratings. These deviations contain useful information. Bank ratings improve out-of-sample prediction of defaults and CRA rating revisions and explain the cross-section of credit spreads. However, bank ratings do not improve out-of-sample prediction of credit excess returns, indicating that current prices incorporate bank rating information. Overall our findings suggest that bank ratings are a useful supplement to traditional credit ratings.

Decentralized finance (DeFi) has emerged to offer traditional financial services such as lending, borrowing, and trading without intermediaries (e.g., banks). DeFi transactions are typically executed using a special digital class of contracts called smart contracts. These contracts are self-executing and hard-coded directly on a blockchain. We observe the emergence of a new class of voluntary audits that evaluate the integrity of these contracts. Using a hand-coded sample of about 8,500 smart contract audit reports, we provide some of the first evidence showing that (1) these audits are pervasive, (2) the audit firm market is composed of new technical audit firms, (3) the scope of these audits can span a variety of contract features, (4) the audit inputs and outputs differ substantively from those of conventional financial audits, and (5) the market reacts positively to the release of these audit reports, suggesting that these reports are value-relevant. These findings highlight the demand for novel assurance services driven by blockchain technology.

We study how the launch of an electronically traded fund (ETF) that holds firms in a specific industry changes the behavior of analysts who follow that firms in that industry. An industry ETF allows investors to trade the firm-specific payoff separately from the industry payoff. This causes significant changes in the value of different types of information. In particular, following an increase in a firm’s industry ETF coverage, the firm’s analyst coverage increases in the following year, and this holds after controlling for changes in institutional investment and other characteristics. We also find that, following an increase in ETF coverage, analyst recommendations are more likely to include an industry recommendation separate from the firm-specific recommendation, and the latter is more likely to be stated in relative terms. Our results strengthen when the new ETF is a better hedge against the industry payoff factor and when we introduce a plausible control for endogeneity.

From 2008 to 2020, 180 of S&P 1500 have disclosed employee diversity targets. We conduct the first analysis of firms’ employee diversity targets and ask three research questions: (i) who announces diversity targets? (ii) do firms deliver on their diversity targets? (iii) what are the implications of disclosure of such targets for employee hiring and investors? We find that firms with a greater willingness (proxied by past ESG penalties, higher CEO-to-median employee pay ratio, more media coverage, and after #MeToo and Black Lives Matter movements) and ability (proxied by financial strength, a blue-collar heavy labor force, and gender and ethnic minorities on boards) to improve employee diversity are more likely to disclose diversity targets. Exploiting the Revelio dataset of 15,639 firm-years for 1,203 distinct firms from 2008 to 2020, we observe that firms that disclosed a diversity target have indeed hired more diverse employees, but such diversity levels had already increased substantially prior to the target disclosure. Firms with numerical, forward-looking, and rank-and-file employee-targeted goals are associated with greater employee diversity relative to firms that announce other types of diversity goals. Moreover, improved diversity performance does not appear to occur at the cost of employee quality, as measured by Revelio. Overall our results have practical implications for how investors and stakeholders might want to interpret corporate diversity targets.