社交互动强度与投资者行为

Michael Gelman, David Hirshleifer, Yaron Levi, and Liron Reiter-Gavish #32772

Abstract: We document a causal effect of social interactions on investor behavior using the number of local soccer games as a measure of social interaction intensity. Social transmission is identifiable in buy but not sell trades. The effect of Social Interaction Intensity (SII) on the sensitivity of buying to past buys is greater for riskier and high-return stocks. Social interactions cause an extremity shift wherein existing shareholders increase their positions, especially within demographically homogeneous communities. There is suggestive evidence that investor mood may modulate the effectiveness of transmission. Higher social interaction intensity increases the sensitivity of investors' trading volume, and portfolio riskiness to past trades. SII also increases the sensitivity of stock trading volume and retail ownership percentage to past buys.

摘要：我们使用本地足球比赛的数量作为衡量社交互动强度的指标，记录了社交互动对投资者行为的因果影响。社交传播在买入交易中可以识别，但在卖出交易中不可识别。社交互动强度（SII）对买入行为对过去买入行为的敏感性影响更大，尤其是在风险较高和高回报股票的情况下。社交互动导致了极端偏移，现有股东会增加他们的持股量，特别是在人口结构同质化的社区中。有证据表明，投资者情绪可能会影响传播的有效性。较高的社交互动强度增加了投资者交易量和投资组合风险对过去交易的敏感性。SII 还提高了股票交易量和散户持股比例对过去买入行为的敏感性。

关于药品处方目录和回扣的合同签订

Kate Ho and Robin S. Lee #32790

Abstract:We investigate how formularies used by pharmacy benefit managers (PBMs) can affect manufacturer rebates for branded drugs. We first present a theoretical model of multidimensional contracting in which a PBM negotiates with drug manufacturers over menus of formulary-contingent rebate payments and then selects a formulary. We then estimate how formulary placement affects drug demand for statins using data from Princeton University, a large employer that contracts with a single PBM to offer prescription drug coverage to its employees. Using our theoretical model and demand estimates, we predict how rebates are affected by the use of a preferred tier in the formulary or the ability to exclude a drug from coverage. Our predictions align with aggregate rebate data, and we find that allowing a PBM to place branded drugs on preferred and non-preferred tiers can substantially increase negotiated rebate payments.

摘要：我们研究了药房福利管理者（PBMs）使用的处方目录如何影响品牌药品的制造商回扣。我们首先提出了一个多维合同的理论模型，其中 PBM 与药品制造商就与处方目录相关的回扣支付菜单进行谈判，然后选择处方目录。接着，我们利用普林斯顿大学的数据（该大学是一个与单一PBM签订合同以为其员工提供处方药保险的大雇主）来估计处方目录的放置如何影响他汀类药物的需求。使用我们的理论模型和需求估计，我们预测处方目录中的首选层级的使用或排除某药品的能力如何影响回扣。我们的预测与总体回扣数据相符，发现允许 PBM 将品牌药物放置在首选和非首选层级上，可以显著增加谈判的回扣金额。

就业与社区：社会经济合作及其瓦解

Daron Acemoglu and Alexander Wolitzky #32773

Abstract: We propose a model of the interplay of employment relationships and community-based interactions among workers and managers. Employment relations can be either tough (where workers are monitored intensively and obtain few rents, and managers do not provide informal favors for their workers) or soft (where there is less monitoring, more worker rents, and more workplace favor exchange). Both workers and managers also exert effort in providing community benefits. The threat of losing access to community benefits can motivate managers to keep employment soft; conversely, the threat of losing future employment or future workers' trust can motivate workers and managers to exert effort in the community. Improvements in monitoring technologies; automation, outsourcing, and offshoring; declines in the minimum wage; and opportunities for residential segregation or for privatizing community-provided services can make both workers and managers worse-off by undermining soft employment relations and community cooperation.

摘要：我们提出了一个关于员工与管理者之间就业关系和基于社区的互动相互作用的模型。就业关系可以是严格的（工人受到严格监控，获得的租金很少，管理者不给工人提供非正式的好处）或宽松的（监控较少，工人获得更多租金，工作场所的好处交换较多）。工人和管理者也会在提供社区利益方面付出努力。失去社区利益的威胁可以激励管理者保持宽松的就业关系；相反，失去未来就业或工人信任的威胁可以激励工人和管理者在社区中付出努力。监控技术的进步、自动化、外包和离岸外包的增加、最低工资的下降以及住宅隔离或将社区提供的服务私有化的机会可能通过破坏宽松的就业关系和社区合作，使工人和管理者的处境都变得更糟。

禁止美国高等教育中的平权行动的长期影响

Francisca M. Antman, Brian Duncan, and Michael F. Lovenheim #32778

Abstract: This paper estimates the long-run impacts of banning affirmative action on men and women from under-represented minority (URM) racial and ethnic groups in the United States. Using data from the US Census and American Community Survey, we use a difference-in-differences framework to compare the college degree completion, graduate degree completion, earnings, and employment of URM individuals to non-URM individuals before and after affirmative action bans went into effect across several US states. We also employ event study analyses and alternative estimators to confirm the validity of our approach and discuss the generalizability of the findings. Results suggest that banning affirmative action results in a decline in URM women’s college degree completion, earnings, and employment relative to non-Hispanic White women, driven largely by impacts on Hispanic women. Thus, affirmative action bans resulted in an increase in racial/ethnic disparities in both college degree completion and earnings among women. Effects on URM men are more ambiguous and indicate significant heterogeneity across states, with some estimates pointing to a possible positive impact on labor market outcomes of Black men. These results suggest that the relative magnitude of college quality versus mismatch effects vary for URM men and women and highlight the importance of disaggregating results by gender, race, and ethnicity. We conclude by discussing how our results compare with others in the literature and directions for future research.

摘要：本文估计了在美国禁止平权行动对来自代表性不足的少数族裔（URM）的男性和女性的长期影响。利用美国人口普查和美国社区调查的数据，我们采用差异法比较平权行动禁令在多个美国州生效前后，URM个体与非URM个体在大学学位完成率、研究生学位完成率、收入和就业方面的差异。我们还采用事件研究分析和替代估计方法来验证我们方法的有效性，并讨论研究结果的普遍性。结果表明，相对于非西班牙裔白人女性，禁止平权行动导致URM女性的大学学位完成率、收入和就业有所下降，主要是由于对西班牙裔女性的影响。因此，平权行动禁令增加了女性在大学学位完成率和收入方面的种族/族裔差异。对URM男性的影响更为模糊，显示出各州之间的显著异质性，一些估计指出对黑人男性的劳动市场结果可能产生积极影响。这些结果表明，大学质量与不匹配效应的相对大小在URM男性和女性中存在差异，强调了按性别、种族和族裔细分结果的重要性。最后，我们讨论了我们的研究结果与文献中其他研究的比较以及未来研究的方向。

政治极化与金融

Elisabeth Kempf and Margarita Tsoutsoura #32792

Abstract: We review an empirical literature that studies how political polarization affects financial decisions. We first discuss the degree of partisan segregation in finance and corporate America, the mechanisms through which partisanship may influence financial decisions, and available data sources to infer individuals' partisan leanings. We then describe and discuss the empirical evidence. Our review suggests an economically large and often growing partisan gap in the financial decisions of households, corporate executives, and financial intermediaries. Partisan alignment between individuals explains team and financial relationship formation, with initial evidence suggesting that high levels of partisan homogeneity may be associated with economic costs. We conclude by proposing several promising directions for future research.

摘要：我们回顾了一些实证文献，这些文献研究了政治极化如何影响财务决策。首先，我们讨论了金融领域和美国企业中的党派隔离程度、党派倾向可能影响财务决策的机制，以及用于推断个人党派倾向的数据来源。接着，我们描述并讨论了实证证据。我们的回顾表明，家庭、企业高管和金融中介在财务决策中存在经济上显著且经常扩大的党派差距。个人之间的党派一致性解释了团队和金融关系的形成，初步证据表明，高水平的党派同质性可能与经济成本相关联。最后，我们提出了一些未来研究的有前景方向。

工会与社会保险

Naoki Aizawa, Hanming Fang, and Katsuhiro Komatsu #32793

Abstract: The United States has experienced a significant decline in labor unions over the past half-century. We examine the aggregate labor market impact of labor unions, the causes of their decline, and their welfare and distributional consequences, accounting for unions’ effects on wages and employers’ insurance provisions. We first provide descriptive evidence that social insurance expansions contribute to the union’s decline. We then develop and estimate an equilibrium labor search model where unionization, wages, employers’ insurance provisions, and job security are endogenously determined. We find that, while skill-biased technological changes and Right-to-Work laws respectively explain 32% and 7% of the union decline from 1955 to 2019, social insurance expansions account for 15%. Our analysis also indicates that social insurance expansion can affect inequality through (de)unionization, and inequality may increase or decrease depending on how social insurance is targeted. Subsidizing unions lowers overall social welfare but increases the welfare of low-skilled workers.

摘要：在过去的半个世纪里，美国经历了工会的显著衰退。我们研究了工会对整体劳动力市场的影响、工会衰退的原因以及其对福利和分配的影响，特别是工会对工资和雇主保险供给的影响。首先，我们提供了描述性证据，表明社会保险的扩张对工会的衰退起到了作用。随后，我们开发并估计了一个均衡劳动力搜索模型，其中工会化、工资、雇主保险供给以及工作保障是内生决定的。我们的研究发现，从1955年到2019年，技能偏向型技术变革和“工作权利法”分别解释了32%和7%的工会衰退，而社会保险扩张则解释了15%的工会衰退。我们的分析还表明，通过工会化或去工会化，社会保险的扩张可以影响不平等，而不平等程度可能会根据社会保险的目标群体而增加或减少。补贴工会降低了整体社会福利，但增加了低技能工人的福利。

无条件现金转移对消费和家庭资产负债表的影响：来自美国两个州的实验证据

Alexander W. Bartik, Elizabeth Rhodes, David E. Broockman, Patrick K. Krause, Sarah Miller, and Eva Vivalt #32784

Abstract: We provide new evidence on the causal effect of unearned income on consumption, balance sheets, and financial outcomes by exploiting an experiment that randomly assigned 1000 individuals to receive $1000 per month and 2000 individuals to receive $50 per month for three years. The transfer increased measured household expenditures by at least $300 per month. The spending impact is positive in most categories, and is largest for housing, food, and car expenses. The treatment increases housing unit and neighborhood mobility. We find noisily estimated modest positive effects on asset values, driven by financial assets, but these gains are offset by higher debt, resulting in a near-zero effect on net worth. The transfer increased self-reported financial health and credit scores but did not affect credit limits, delinquencies, utilization, bankruptcies, or foreclosures. Adjusting for underreporting, we estimate marginal propensities to consume non-durables between 0.44 and 0.55, durables and semi-durables between 0.21 and 0.26, and marginal propensities to de-lever of near zero. These results suggest that large temporary transfers increase short-term consumption and improve financial health but may not cause persistent improvements in the financial position of young, low-income households.

摘要：我们通过一个实验提供了关于非劳动收入对消费、资产负债表和财务结果的因果效应的新证据。该实验随机分配了1000名个人每月获得1000美元，以及2000名个人每月获得50美元，为期三年。该转移支付至少使家庭开支增加了每月300美元。支出影响在大多数类别中是积极的，其中住房、食品和汽车开支的增幅最大。该措施增加了住房单位和社区的流动性。我们发现对资产价值的估计有一定的误差，但总体上是正面的，这主要是由金融资产推动的，但这些收益被更高的债务抵消，导致净资产接近于零的效果。转移支付提高了自我报告的财务健康状况和信用评分，但未对信用额度、拖欠、使用率、破产或止赎产生影响。调整低报后，我们估算非耐用品的边际消费倾向在0.44到0.55之间，耐用品和半耐用品在0.21到0.26之间，去杠杆化的边际倾向接近于零。结果表明，大规模的临时转移增加了短期消费并改善了财务健康状况，但可能不会对年轻低收入家庭的财务状况产生持久改善。

驱动零工经济

Katharine G. Abraham, John C. Haltiwanger, Claire Y. Hou, Kristin Sandusky, and James Spletzer #32766

Abstract: Using rich administrative tax data, we explore the effects of the introduction of online ridesharing platforms on entry, employment and earnings in the Taxi and Limousine Services industry. Ridesharing dramatically increased the pace of entry of workers into the industry. New entrants were more likely to be young, female, White and U.S. born, and to combine earnings from ridesharing with wage and salary earnings. Displaced workers have found ridesharing to be a substantially more attractive fallback option than driving a taxi. Ridesharing also affected the incumbent taxi driver workforce. The exit rates of low-earning taxi drivers increased following the introduction of ridesharing in their city; exit rates of high-earning taxi drivers were little affected. In cities without regulations limiting the size of the taxi fleet, both groups of drivers experienced earnings losses following the introduction of ridesharing. These losses were ameliorated or absent in more heavily regulated markets.

摘要：我们利用丰富的行政税务数据，探讨了在线网约车平台的引入对出租车和豪华轿车服务行业的进入、就业和收入的影响。网约车显著加快了工人进入该行业的速度。新进入者更有可能是年轻、女性、白人和美国出生的，并且将网约车收入与工资收入相结合。被取代的工人发现，与开出租车相比，网约车是一个更具吸引力的后备选择。网约车也影响了现有的出租车司机队伍。在他们的城市引入网约车后，低收入出租车司机的退出率有所上升；而高收入出租车司机的退出率几乎没有受到影响。在没有限制出租车车队规模的城市，随着网约车的引入，两组司机的收入都出现了下降。这些损失在监管较严的市场中有所缓解或没有发生。

分布式账本和安全多方计算在财务报告与审计中的应用

Sean S. Cao, Lin William Cong, and Baozhong Yang #32763

Abstract: To understand the disruption and implications of distributed ledger technologies for financial reporting and auditing, we analyze firm misreporting, auditor monitoring and competition, and regulatory policy in a unified model. A federated blockchain for financial reporting and auditing can improve verification efficiency not only for transactions in private databases, but also for cross-chain verifications through privacy-preserving computation protocols. Despite the potential benefit of blockchains, private incentives for firms and first-mover advantages for auditors can create inefficient under-adoption or partial adoption that favors larger auditors. Although a regulator can help coordinate the adoption of technology, endogenous choice of transaction partners by firms can still lead to adoption failure. Our model also provides an initial framework for further studies of the costs and implications of the use of distributed ledgers and secure multi-party computation in financial reporting, including the positive spillover to discretionary auditing and who should bear the cost of adoption.

摘要：为了理解分布式账本技术对财务报告和审计的颠覆性影响及其意义，我们在一个统一的模型中分析了公司误报、审计师的监控与竞争以及监管政策。用于财务报告和审计的联合区块链不仅可以提高私有数据库中交易的验证效率，还可以通过隐私保护计算协议进行跨链验证。尽管区块链具有潜在的优势，企业的私人激励和审计师的先发优势可能导致低效的不足采纳或部分采纳，这对大型审计师有利。尽管监管机构可以帮助协调技术的采纳，企业的内生交易伙伴选择仍可能导致采纳失败。我们的模型还为进一步研究在财务报告中使用分布式账本和安全多方计算的成本和影响提供了初步框架，包括对选择性审计的正向溢出以及应由谁承担采纳成本的问题。

深度学习在经济学中的应用

Melissa Dell #32768

Abstract: Deep learning provides powerful methods to impute structured information from large-scale, unstructured text and image datasets. For example, economists might wish to detect the presence of economic activity in satellite images, or to measure the topics or entities mentioned in social media, the congressional record, or firm filings. This review introduces deep neural networks, covering methods such as classifiers, regression models, generative AI, and embedding models. Applications include classification, document digitization, record linkage, and methods for data exploration in massive scale text and image corpora. When suitable methods are used, deep learning models can be cheap to tune and can scale affordably to problems involving millions or billions of data points.. The review is accompanied by a companion website, EconDL, with user-friendly demo notebooks, software resources, and a knowledge base that provides technical details and additional applications.

摘要：深度学习提供了强大的方法，可以从大规模的非结构化文本和图像数据集中推断出结构化信息。例如，经济学家可能希望通过卫星图像检测经济活动的存在，或衡量社交媒体、国会记录或公司文件中提到的话题或实体。本文介绍了深度神经网络，涵盖了分类器、回归模型、生成式AI和嵌入模型等方法。应用包括分类、文档数字化、记录链接以及在大规模文本和图像语料库中的数据探索方法。使用合适的方法时，深度学习模型可以廉价地调整，并可负担地扩展到涉及数百万或数十亿数据点的问题中。该综述还附有一个名为 EconDL 的网站，提供用户友好的演示笔记本、软件资源以及提供技术细节和其他应用的知识库。

往期精选：

      重磅：学术财经•学术笔记全汇总

重磅：学术财经全球价值链专题学术笔记大汇总（附下载链接失效学术笔记推文）

重磅| 基金申请内部学习和交流

【学术笔记·第37篇】风险和全球供应链：我们知道什么和我们需要知道什么

【学术笔记·第36篇】各有所长：全球供应链风险敞口（Exposure）测度

【学术笔记·第35篇】日本生产者价格指数理论与实证：最终需求-中间需求加总系统

【学术笔记·第34篇】北美自由贸易的贸易和福利影响估计

【学术笔记 第33篇】 英属印度时期铁路：交通基础设施的影响评估（AER）

【学术笔记 第32篇】 技术、地理和贸易(经典EK模型）

【学术笔记 第31篇】2018年贸易战对美国物价和福利的影响

【学术笔记 第30篇】全球价值链和国家部门层面实际有效汇率