We examine how removing user anonymity affects social media’s ability to generate value-relevant information for the stock market. Using a difference-in-differences design that exploits the differential timing of adopting real-name verification policies by the two most popular investment-related social media websites in China, we find that content on the treated site becomes significantly more informative about future stock returns and earnings after the policy takes effect. This effect is primarily driven by continuing users who post more actively in the pre-period. Although these users post less after the policy, the informational content of their posts increases, suggesting greater prudence in expressing opinions. Our results strengthen for firms that attract regulatory scrutiny. Overall, our study suggests that real-name verification policies can discipline internet users and potentially improve the informativeness of investment-related social media, particularly in emerging markets where retail investors predominate.

We examine whether information processing constraints limit managers’ ability to effectively integrate tax planning and core business strategies (i.e., effective tax planning). We propose that artificial intelligence (AI) tools, such as machine learning, can mitigate these constraints by providing enhanced predictive information for key business decisions (e.g., customer demand, supply chain), thereby reducing processing costs. Using a recently developed firm-year measure of investment in AI-related human capital for a broad sample of U.S. nontechnology firms between 2010 and 2018, we find that AI investment is positively associated with tax effectiveness. This effect is concentrated among more complex firms and those where the tax function holds a higher status. Consistent with AI reducing information processing costs, we find that it improves tax effectiveness by enhancing internal information quality and internal capital management. We provide novel evidence that processing constraints hinder effective tax planning and show that AI can mitigate these constraints.

We extract and describe corporate-issued guidance contained in over 23,000 LSEG Guidance Reports of S&P 1,500 firms from 2005 to 2021. Our sample contains 1.735 million Guidance Reports guidance instances that span over 180 guided items and fall into three broad categories: (1) qualitative topics, (2) consolidated financial statements, and (3) other key performance indicators. We identify research opportunities arising from Guidance Reports’ rich features, including quantitative or qualitative form, underpinning text, disclosure channels, and source speakers. We also compare Guidance Reports to the commonly used I/B/E/S Guidance database, which covers only quantitative guidance for 13 items. Approximately 1.494 million Guidance Reports instances fall outside I/B/E/S Guidance’s coverage, and even among overlapping items, only a subset is translated to I/B/E/S Guidance based on LSEG cost–benefit considerations. Our findings suggest researchers should be aware of the extent and nature of I/B/E/S Guidance omissions when studying guidance.

We examine the impact of auditors’ reputation impairments on their private-client market share to explore how conducting low-quality audits affects auditors’ broader client portfolios. Prior evidence implies that an audit office loses public-client market share after a client announces a restatement. However, auditors’ private clients may be less concerned about auditor reputation and quality, given that they have lower agency costs and their financial statement users are often creditors that can rely on direct monitoring to narrow information asymmetry. Also, differences between public and private company audits cast doubt on whether public-client restatements are relevant to private clients. We find that the private-client market share of a Big Four audit office falls by, on average, 5 percent the year after a public client announces a restatement. This evidence suggests that Big Four offices cannot simply replace lost public-client revenue with private-client revenue after suffering reputation damage.

We examine the relation between mandatory environmental disclosure and corporate green innovation. Adopting a difference-in-differences research design, we find that the adoption of state-level greenhouse gas emissions disclosure mandates is associated with an increase in the quantity of patents related to climate change mitigation/adaptation technologies (i.e., “green innovations”). This increase is stronger among firms with more environmental investors, suggesting investor preferences influence this relation. We also document a positive association between these mandates and firms’ future environmental performance ratings, suggesting a positive externality. However, we find that these mandates are associated with a reduction in future financial performance for some firms, suggesting a potential negative effect on shareholder welfare. Collectively, our results provide new evidence on the real effects of mandatory environmental disclosure and the determinants of green innovation and contribute to the literature on the motivations for green innovation and the literature on corporate disclosure and investment decisions.

Research suggests that board members value financial reporting quality because executive dismissal often follows low reporting quality events. However, inferences about the board’s demand for reporting quality in these studies are confounded by board members’ reputation incentives because the events examined are public (e.g., restatements). We investigate boards’ demand for reporting quality by exploiting a private signal of misreporting: audit adjustments communicated to the Board by the external auditor. We first survey 29 audit committee chairs to understand whether boards use audit adjustments in their oversight of management and then conduct an empirical investigation to answer our research question. We find an increased likelihood of CFO dismissal following audit adjustments. This association is driven by adjustments that reduce income and by firms with better board oversight. These findings suggest that boards proactively use nonpublic signals of reporting quality and incorporate information from auditors into their monitoring function.