US GAAP requires most intangible investments to be expensed as incurred, potentially distorting performance measurement. We examine whether voluntary non-GAAP disclosures mitigate these distortions for intangible-intensive firms. We find that intangible-intensive firms are more likely to report non-GAAP performance metrics when GAAP earnings lack relevance and that the resulting exclusions are of higher quality. Challenging the prevailing view that high-quality exclusions are limited to transitory items, we demonstrate that non-GAAP disclosures can also enhance performance measurement by excluding investment expenditures. Consistent with this mechanism, we find that intangible-intensive firms are more likely to exclude investment-related expenditures, that their non-GAAP disclosures are associated with higher returns to intangible investments, and that removing R&D enhances the predictive relevance of the performance metric. These effects are unique to firms that expense, rather than capitalize, intangible assets, highlighting the role of non-GAAP reporting in mitigating distortions arising from the mandatory expensing of intangible investments.

We investigate whether consistent non-GAAP reporting is associated with investment efficiency. Prior research finds a positive association between non-GAAP reporting and investment levels, concluding that it represents overinvestment. We corroborate this positive association, but additional tests are not consistent with the conclusion of inefficient overinvestment. Specifically, we explore the relation between investment and future cash flows as a proxy for the realization of investments in positive net present value projects. We find that the investments of firms that consistently report non-GAAP metrics are associated with similar or higher future cash flows than the investments of firms reporting only GAAP earnings, which is consistent with efficient investment. We observe similar associations in multiple specifications, performance horizons, and outcome variables, including future returns and earnings. Given the prevalence of non-GAAP reporting and the SEC's ongoing concern with the consequences of non-GAAP disclosure, our analyses offer timely evidence relevant to this important discussion.

We investigate whether income smoothing affects the usefulness of earnings for contracting through the monitoring role of earnings‐based debt covenants. First, we examine initial contract design and predict that income smoothing will increase (decrease) the use of earnings‐based covenants if income smoothing improves (reduces) the usefulness of earnings to monitor borrowers. We find that private debt contracts to borrowers with greater income smoothing are more likely to include earnings‐based covenants. A structural model that explores the cause of this relationship provides evidence that smoothing improves the ability of earnings to reflect credit risk. Second, we examine technical default following contract inception. We find that income smoothing is associated with a lower likelihood of spurious technical default (when the borrower's economic performance has not declined but the loan nevertheless enters technical default). In contrast, we find no association between income smoothing and performance technical default (when the borrower's economic performance has declined). Collectively, this evidence is consistent with income smoothing improving the effectiveness of earnings‐based information in monitoring borrowers.

Firm life‐cycle stage reflects a firm's current strategic direction toward exploration independent of age or size. We provide evidence that young life‐cycle firms are particularly vulnerable to negative innovation consequences from financial regulation but do not appear to experience any compensating financial reporting quality (FRQ) benefits. Using a generalized difference‐in‐differences design around Sarbanes Oxley Act of 2002 (SOX), we document a significant reduction in both research and development (R&D) spending and innovation outputs for young life‐cycle stage firms after regulation. Declines in innovation manifest both from the diversion of scarce resources and from the imposition of an organizational culture mismatched to the pursuit of explorative innovation, resulting in a less generalizable and less diversified patent portfolio. However, we find no evidence that improvements to FRQ materialize to offset these costs. Event study analyses suggest that this negative impact was expected by market participants, and postregulation returns confirm this expectation.

Researchers typically infer real earnings management when a firm's operating and investing activities differ from industry norms. A significant problem with classifying deviations from industry averages as myopic earnings management is that companies can change their operating and investing decisions for strategic business reasons rather than to mislead stakeholders. Using principal components analysis, we systematically evaluate existing measures and develop a comprehensive real activities measure to better capture earnings manipulation. Our measure reflects (i) deviations from industry averages across multiple activities and (ii) other signals of manipulation. This approach is promising because, although there are many sources of abnormal activities, manipulation is more likely the cause when managers engage in multiple income‐increasing abnormal activities that coincide with other signals that indicate an elevated risk of manipulation. This simple approach results in a metric that associates negatively with future operating performance and earnings persistence, yields high‐power tests, and captures manipulation reasonably well across most life‐cycle stages. Importantly, this approach performs better than the standard real earnings management metrics across all dimensions. Specifically, it generates the expected reduction in future earnings and reduced earnings persistence in 82% of the tests compared to 36% and 46% in common alternatives. Also, because this innovation does not require a long time‐series or rely on future period realizations for classification, it can be useful in more research settings than other recent innovations in the literature.