Regulatory programs that restrict output levels often impose restrictions on the transfer of rights to produce or to use particular inputs. In this paper, we use a unique cross-section, time-series data set from North Carolina to quantify the welfare effects of transfer restrictions for poundage quota under the U.S. flue-cured tobacco program. We find that the deadweight costs of such restrictions are small but that the distributional effects are substantial. We analyze congressional testimony on quota transfer legislation and conclude that our estimates of the distributional effects are consistent with expressed views of market participants.

This paper reexamines the relation between firm value and board structure. We find that complex firms, which have greater advising requirements than simple firms, have larger boards with more outside directors. The relation between Tobin's Q and board size is U-shaped, which, at face value, suggests that either very small or very large boards are optimal. This relation, however, arises from differences between complex and simple firms. Tobin's Q increases (decreases) in board size for complex (simple) firms, and this relation is driven by the number of outside directors. We find some evidence that R&D-intensive firms, for which the firm-specific knowledge of insiders is relatively important, have a higher fraction of insiders on the board and that, for these firms, Q increases with the fraction of insiders on the board. Our findings challenge the notion that restrictions on board size and management representation on the board necessarily enhance firm value.

We provide empirical evidence of a strong causal relation between managerial compensation and investment policy, debt policy, and firm risk. Controlling for CEO pay-performance sensitivity (delta) and the feedback effects of firm policy and risk on the managerial compensation scheme, we find that higher sensitivity of CEO wealth to stock volatility (vega) implements riskier policy choices, including relatively more investment in R&D, less investment in PPE, more focus, and higher leverage. We also find that riskier policy choices generally lead to compensation structures with higher vega and lower delta. Stock-return volatility has a positive effect on both vega and delta.

This paper reports a laboratory experiment that examines price formation in the single call market. The experiment design is intended to enhance the predictive power of the Bayesian Nash equilibrium (BNE) theory for this trading institution. The data support several qualitative implications of the BNE, especially when subjects compete against Nash 'robot' opponents, but subjects' behavior is not as responsive to changes in the pricing rule as the BNE predictions. Offers tend to reveal more of the underlying values and costs than predicted, particularly when subjects are experienced. A simple learning model accounts for several of the deviations from BNE.

This study examines whether we can learn from the behavior of blockchain‐based transfers to predict the financing of terrorist attacks. We exploit blockchain transaction transparency to map millions of transfers for hundreds of large on‐chain service providers. The mapped data set permits us to empirically conduct several analyses. First, we analyze abnormal transfer volume in the vicinity of large‐scale highly visible terrorist attacks. We document evidence consistent with heightened activity in coin wallets belonging to unregulated exchanges and mixer services—central to laundering funds between terrorist groups and operatives on the ground. Next, we use forensic accounting techniques to follow the trails of funds associated with the Sri Lanka Easter bombing. Insights from this event corroborate our findings and aid in our construction of a blockchain‐based predictive model. Finally, using machine‐learning algorithms, we demonstrate that fund trails have predictive power in out‐of‐sample analysis. Our study is informative to researchers, regulators, and market players in providing methods for detecting the flow of terrorist funds on blockchain‐based systems using accounting knowledge and techniques.

We report a continuous-time experiment studying the Burdett-Judd model, whose unique Nash equilibrium (NE) features dispersed prices. Adaptive dynamics predict that the NE is stable for one of our parameter sets and unstable for another. The empirical price distribution is close to the NE distribution for the stable parameter set, but for the unstable parameter set it skews toward higher prices in its NE support interval. We offer an empirical definition of price cycles in terms of changes over time in robust measures of central tendency and dispersion, by which the data exhibit persistent cycles in both treatments but larger cycles for the unstable parameters. Results are roughly similar for professional and student sellers and for limited-information treatments.

Regulatory programs that restrict output levels often impose restrictions on the transfer of rights to produce or to use particular inputs. In this paper, we use a unique cross-section, time-series data set from North Carolina to quantify the welfare effects of transfer restrictions for poundage quota under the U.S. flue-cured tobacco program. We find that the deadweight costs of such restrictions are small but that the distributional effects are substantial. We analyze congressional testimony on quota transfer legislation and conclude that our estimates of the distributional effects are consistent with expressed views of market participants.