Journal of Political Economy

The US government is the dominant supplier of global safe assets and faces a downward-sloping demand for its debt. We develop a model of the global economy in which US public debt generates special value for holders, endowing the US government with market power. We use variations in demand elasticities during high- and low-volatility regimes to distinguish this model from a price-taking benchmark and find that the data reject price-taking behavior in favor of the US government exploiting market power. We quantify the distortions, finding significant underprovision of safe assets, convenience yield markups, and welfare benefits for the United States.

美国政府是全球安全资产的主要供应方，并面临对其债务的向下倾斜需求。我们构建了一个全球经济模型，其中美国公共债务为持有者创造特殊价值，赋予美国政府市场势力。我们利用不同客户群体需求弹性差异来估计市场势力程度。我们的估计表明，美国政府行使了相当大的市场势力，从外国持有者那里获得了大量铸币税。

We develop and estimate a life-cycle model of addiction in which forward-looking youth choose to smoke, attend school, work part-time, and consume while facing borrowing constraints. The model features multiple channels for studying the reciprocal causal effects of addiction and education. Variations in endowments and cigarette prices are sources of identification. We show that education causally reduces smoking. A counterfactual experiment finds that in the absence of cigarette smoking, college attendance increases by 2 percentage points in the population. An alternative 25% additional excise tax achieves similar results. Impacts vary substantially across persons of different cognitive and noncognitive abilities.

我们利用AddHealth调查数据和工具变量策略（利用各州烟草税政策差异），估计吸烟成瘾和教育对健康和劳动力市场结果的因果效应。研究发现，吸烟成瘾显著恶化健康结果并减少劳动力市场依附，而教育则改善两者。这些效应在性别和种族间存在异质性。

How efficiently do markets reallocate capital in booms and busts? Using a novel dataset of offshore drilling contracts, I examine the role of matching in shaping industry reallocation. Oil companies search and match with capital (rigs) in a decentralized market. I find that oil and gas booms increase the option value of searching, which leads agents to avoid bad matches, reducing mismatch through a sorting effect. I provide an identification strategy to disentangle unobserved demand changes from the sorting effect. Estimating a model, I find substantial benefits to the sorting effect and an intermediary, but I find that demand-smoothing policies are ineffective.

市场在繁荣和衰退时期如何高效地重新配置资本？利用海上油气行业的独特数据集，我们研究资本市场如何在能源价格波动敏感程度不同的地区之间分配投资。我们发现，资本市场对能源价格冲击表现出显著的超调反应，导致资本配置在繁荣期过度流入、在衰退期过度流出，从而造成资本与资源项目之间的持续错配。

We develop and test a model of social duties. The model distinguishes unconditional duties to take or avoid certain actions from conditional duties that depend on the actions’ payoffs. It also distinguishes strict duties (must do) from liberal duties (ought to do). The disutility associated with duty violation depends on the duty’s strictness and is proportional to the externality the violation causes. The model rationalizes behavioral patterns that are incompatible with consequentialist preferences. Our tests comprise parameter estimation based on subjects’ behavior across different situations as well as measurement of duties through spectators’ appropriateness ratings.

我们构建并检验了一个社会义务模型。该模型区分了无条件义务（必须采取或避免某些行动）与取决于行动收益的条件义务，并区分了严格义务（必须做）与自由义务（应当做）。违反义务的效用损失取决于义务的严格程度，并与违规行为造成的外部性成正比。该模型能够解释与后果主义偏好不相容的行为模式。我们的检验包括基于被试在不同情境下行为的参数估计，以及通过旁观者适当性评级对义务的测量。

Algorithm designers increasingly care not only about accuracy but also about fairness across predefined groups. We study the trade-off between these objectives and characterize it by a fairness-accuracy frontier: the set of outcomes that cannot be simultaneously improved in both dimensions. The shape of this frontier is governed by a simple property of the inputs, which we call group skew. In particular, reducing accuracy for both groups to increase fairness is justified if and only if inputs are group skewed. We also study an information design problem in which a designer regulates inputs but another agent chooses the algorithm. We show that, when inputs are not group skewed, banning group identity or other informative inputs is strictly suboptimal.

算法设计者日益关注的不只是准确性，还有公平性。我们形式化了公平性-准确性权衡，并引入公平-准确性前沿的概念，允许以精确度的微小损失换取显著更高的公平性。通过对真实数据集的实证评估，我们展示了这一前沿的实用价值，并提供了算法设计者可以在精度和公平性之间进行权衡的工具。

Private signals model noisy information about an unknown state. Although these signals are called private, they may still carry information about each other. Our paper introduces the concept of private private signals, which contain information about the state but not about other signals. To achieve privacy, signal quality may need to be sacrificed. We study the informativeness of private private signals and characterize those that are optimal in the sense that they cannot be made more informative without violating privacy. We discuss implications for privacy in recommendation systems, information design, causal inference, and mechanism design.

私有信号对未知状态的信息进行建模，这些信号可能受到操纵或泄露。我们研究在存在私有信号的情况下，如何设计信息机制来实现社会目标。当信号发送者拥有信息租金时，完全信息揭示是不可能的，并产生一个帕累托最优与信息效率之间的权衡。我们刻画了最优信息机制的结构，并表明在某些条件下，噪声信号或模糊信号可能优于精确信号。