We study the informational value of trading networks in over-the-counter (OTC) markets. Using detailed transaction-level data from the corporate bond market, we show that investors with larger dealer networks make superior trading decisions before changes in credit fundamentals, resulting in better risk-adjusted performance. We trace these investors’ superior trading decisions to trading connections where dealers are most likely to have access to novel credit-relevant information, supporting the interpretation that these investors obtain private information through their trading networks. Collectively, our evidence highlights the importance of trading relationships for investors’ private information acquisition.

While the Dodd–Frank Act (DFA) mandates board risk committees for large banks, we argue that such committees do not benefit all banks. Banks forced by the DFA to adopt a board risk committee do not experience a reduction in risk following adoption. In contrast, banks that voluntarily established risk committees before the DFA exhibit lower risk, especially when these committees possess greater risk expertise. Using unique interview data, we find that board risk committees serve as active monitors rather than merely rubber-stamping management proposals. However, regulatory-mandated tasks limit their monitoring role.

This study examines turnover experiences in public accounting, including the exit phase (from public accountants' initial thoughts of leaving to their exit) and the post‐exit phase (from their exit to the present moment) of the turnover process. Drawing on social exchange theory and organizational support theory, we also investigate the relationship between these phases by exploring how turnover characteristics within the exit phase impact alumni's decisions to engage in post‐employment citizenship in the post‐exit phase (e.g., recommending the firm's services to others). Using the experiential questionnaire method, we rely upon two separate surveys to investigate the turnover process from the perspective of 284 firm alumni (“leavers”) and 83 experienced public accountants (“stayers”). Our process‐based research method allows us to gather a large and rich data set that provides multiple perspectives on the turnover experience in public accounting. Our results not only provide insights into the underlying factors influencing turnover but also indicate several places in the turnover decision process where firms can strategically intervene. Finally, our results show that several turnover characteristics within the exit phase impact post‐employment citizenship behaviors in the post‐exit phase. Consequently, our results demonstrate that the characteristics that drive employees' decisions to leave the firm also play a significant role in shaping their post‐employment citizenship behaviors following their departure.

This article provides a unified framework for studying the identification of counterfactual parameters in a general class of discrete outcome models, allowing for endogenous regressors and multidimensional latent variables, all without parametric distributional assumptions. Our main theoretical result is that, when the covariates are discrete, the infinite-dimensional latent variable distribution can be replaced with a finite-dimensional version that is equivalent from an identification perspective. The finite-dimensional latent variable distribution is constructed in practice by enumerating regions of the latent variable space with a new and efficient cell enumeration algorithm for hyperplane arrangements. We then show that bounds on a certain class of counterfactual parameters can be computed by solving a sequence of linear programming problems, and show how the researcher can introduce additional assumptions as constraints in the linear programmes. Finally, we apply the method to a mobile phone choice example with heterogeneous choice sets, and to an airline entry game example.

Mergers and acquisitions are often motivated by an intention to create value from intangible assets. We develop a word list of intangibles and apply it to takeover announcements. One standard deviation more in intangible-related language (“intangibles talk”) lowers announcement returns for the acquirer by 0.53 percentage points and predicts worse operating performance. Bidder managers appear to believe in the deals nonetheless, as evidenced by insider trades, payment choices, and completion probabilities and speed. Overall, takeover announcement texts reveal important information about hard-to-measure aspects of deal quality.

Biopharmaceuticals advance health and economic growth. Unlike central bargaining abroad, the United States uses private firms, pharmacy benefit managers (PBMs), to manage medicine access and spending. Yet, PBMs' roles in advancing efficiency are understudied. Ho and Lee model PBMs' use of tiered formularies, lists of covered medicines, without the use of proprietary data on the price concessions drug makers offer for preferred placement. They find PBMs' use of tiered formularies generate significant payor savings through competition. Complementing Ho and Lee, Feng and Maini (2024) model how patient demand inertia limits PBMs' ability to extract price concessions from drug makers which consequently erodes the efficacy gains of PBM formularies. Conti, Frandsen, Powell, and Rebitzer (2021) model formulary auctions where PBM size drives payor savings, but also spurs endogenously set high list prices, reducing patient access. Future economic research should focus on PBM market entry and vertical integration, pharmacy steering, and effects on innovation.

Pandemic fraud is geographically concentrated and stimulated local purchases, with effects on prices. Recipients of fraudulent Paycheck Protection Program (PPP) funds significantly increased their home purchasing rate compared to recipients of non-fraudulent PPP funds, and house prices in high-fraud ZIP codes increased 5.8 percentage points more than in low-fraud ZIP codes within the same county. In a horse race, pandemic fraud is one of the largest and most robust factors explaining house price appreciation during COVID. ZIP codes with fraud also experienced heightened vehicle purchases and other consumer spending in 2020-21, with a return to normal in 2022.