We investigate the optimal savings decisions for investors with access to pre-tax (traditional) and post-tax (Roth) versions of tax-advantaged retirement accounts. The model features a progressive tax schedule and uncertainty over future tax rates. Traditional accounts are valuable for hedging retirement account performance and managing current income near tax-bracket cutoffs, whereas Roth accounts allow investors to mitigate uncertainty over future tax schedules. The optimal asset location policy for most households involves diversifying between traditional and Roth vehicles. Contrary to conventional advice, the substantial economic benefits from Roth investments are not limited to investors with low current income.

We examine the influence of mobile communication on local information flow and local investor activity using the enforcement of statewide distracted driving restrictions, which are exogenous events that constrain mobile communication while driving. By restricting mobile communication across a potentially sizable set of local individuals, these restrictions could inhibit local information flow and, in turn, the market activity of stocks headquartered in enforcement states. We first document a decline in Google search activity for local stocks when restrictions take effect, suggesting that constraints on mobile communication significantly affect individuals’ information search activity. We further find significant declines in local trading volume when restrictions are enforced. This drop in liquidity is (1) attenuated when laws provide substitutive means of mobile communication and (2) magnified when locals have long car commutes and when their daily commutes overlap with regular exchange hours. Moreover, trading volume suffers the most for local stocks with lower institutional ownership, less analyst coverage, and more intangible information. Additional analyses show lower intraday volume during local commute times when mobile connectivity is constrained. Together, our results suggest that local information and local investors matter in stock markets and that mobile communication is an important mechanism through which these elements operate to affect liquidity and price discovery.

Recent regulatory amendments aimed at modernizing disclosures and enhancing their usefulness focus on repetition and interactivity within firms’ disclosure filings. We use two experiments to provide evidence on the effects of disclosure repetition (repeating of information in the filing) and disclosure interactivity (user involvement in directing the form or content of the information displayed) on investors’ information processing and investment judgments. Results show that repetition increases investors’ processing of repeated information, consistent with the informational role of repetition documented in prior research. In contrast, repetition reduces investors’ processing of other, nonrepeated information when the filing is less interactive. This evidence corroborates concerns that repetition can obscure value‐relevant information from investors. However, we find that more interactive disclosures mitigate this harmful effect of repetition on investors’ processing of nonrepeated information. Further, more interactive disclosures lead to deeper overall processing of both repeated and nonrepeated information, rather than more interactive disclosures redirecting investors’ attention and processing away from repeated information. Thus, our evidence suggests that disclosure interactivity is an important disclosure attribute that counteracts the potentially harmful effects of repetition on investors' processing of nonrepeated information, while preserving repetition's informational role.

We use a machine learning technique to assess whether the thematic content of financial statement disclosures (labeled topic ) is incrementally informative in predicting intentional misreporting. Using a Bayesian topic modeling algorithm, we determine and empirically quantify the topic content of a large collection of 10‐K narratives spanning 1994 to 2012. We find that the algorithm produces a valid set of semantically meaningful topics that predict financial misreporting, based on samples of Securities and Exchange Commission (SEC) enforcement actions (Accounting and Auditing Enforcement Releases [AAERs]) and irregularities identified from financial restatements and 10‐K filing amendments. Our out‐of‐sample tests indicate that topic significantly improves the detection of financial misreporting by as much as 59% when added to models based on commonly used financial and textual style variables. Furthermore, models that incorporate topic significantly outperform traditional models when detecting serious revenue recognition and core expense errors. Taken together, our results suggest that the topics discussed in annual report filings and the attention devoted to each topic are useful signals in detecting financial misreporting.

We examine the influence of investor sentiment on managers’ discretionary disclosure of “pro forma” (adjusted) earnings metrics in earnings press releases. We find that managers’ propensity to disclose an adjusted earnings metric (especially one that exceeds the GAAP earnings number) increases with the level of investor sentiment. Furthermore, our analyses suggest that, as investor sentiment increases, managers: (1) exclude higher levels of both recurring and nonrecurring expenses in calculating the pro forma earnings number and (2) emphasize the pro forma figure by placing it more prominently within the earnings press release. Additional analyses indicate that the association between investor sentiment and managers’ pro forma disclosure decisions at least partly reflects opportunistic motives. Finally, we find that managers’ own sentiment‐driven expectations also play a role in their pro forma disclosure decisions.

We examine whether the complexity of mandatory accounting disclosures prompts managers to voluntarily disclose adjusted measures of actual earnings performance, and whether this practice reflects attempts to obfuscate or mitigate the informational opacity accounting complexity creates for investors. Using the metadata in XBRL filings, we construct measures of accounting complexity that map directly to the mandated standards applied in financial statement filings. We find a positive and economically significant association between accounting complexity and managers’ propensity to disclose non-GAAP earnings information. This relation is robust and incremental to common measures of business and linguistic complexity, and the transitory nature of firms’ economic activities. We also find that the quality and informativeness of adjusted earnings information increases with accounting complexity, consistent with motives to better inform investors when accounting disclosures are complex. Overall, our results suggest that managers use non-GAAP earnings disclosure to mitigate the adverse informational effects of accounting complexity. Data Availability: All data are available from sources identified in the paper.