Publications

How should the federal government respond to the collapse of the Silicon Valley Bank (SVB), the 16th largest bank in the United States?

SVB collapsed on Friday, March 10, 2023, after an unprecedented run on deposit during which customers requested $42 billion of withdrawals in a single day. The value of SVB’s securities portfolio had declined severely. The bank had bet on long-term government securities, and when the Fed raised interest rates, the mark-to-market value of this asset had dropped precipitously. Ninety-Four percent of the bank’s deposits were uninsured, so customers reacted quickly when rumors spread that the bank might be insolvent.

The Federal Deposit Insurance Corporation (FDIC) had taken the unusual action of closing the bank on a Friday morning. Now, the Biden administration, the Federal Reserve and the FDIC had the weekend to decide what to do and coordinate a response. SVB’s collapse had sent shock waves through the banking sector. A few other banks with a large percentage of uninsured deposits and exposure to the hike in interest rates were rumored to be in trouble. Financial pundits were raising the question of whether this might lead to a financial crisis as occurred  after the failure of Lehman Brothers in 2008. There were also the SVB depositors who had not been able to get their money out of the bank in time – many of them tech start-ups that were a major driver of the economy.

Senior policymakers at the Treasury, the Fed, and the FDIC faced decisions that were politically fraught. Obviously, a recession would be politically unpopular. But the decision in 2008 to provide subsidies to banks had also proved contentious. Both the left and right had decried what they perceived to be “bank bailouts.”

Policymakers knew they had to react quickly. Before them, they had a number of options that could limit the fallout from SVB’s collapse. They also had to devise a communications strategy that calmed the markets and the public. Finally, they had to start the long process of examining what went wrong at SVB in order to ensure that it did not happen again.  

Operations research, originating during World War II, is the scientific study of operations aimed at improving decision-making and organizational performance. Initially focused on military logistics, its scope has expanded to address diverse operational problems in business, government, and non-profit sectors. These include scheduling, capacity planning, routing, and resource allocation. Through mathematical modeling and analysis, operations research seeks not just to describe but to optimize operations by aligning them with organizational goals such as maximizing profit, minimizing costs, or enhancing effectiveness. The field has evolved from simple problem identification to complex mathematical modeling, emphasizing the importance of framing the right problem within a well-understood system context. Applied operations research assumes that the identified problem can be modeled mathematically, that the models and assumptions are valid, and that organizational objectives and constraints are clearly defined and quantifiable. The ultimate aim is actionable recommendations that improve real-world decision-making. Grounded in the belief in mathematical rigor, operations research integrates objectives and constraints to deliver feasible solutions. By leveraging analytical tools, it supports better decision-making, ensuring that operations are not only efficient but also aligned with strategic priorities, making it a practical and impactful discipline across sectors.

Consensus analyst target prices are widely available online at no cost to investors. In this paper we examine how the amount of dispersion in the individual target prices comprising the consensus affects the predictive association between the consensus target price and future returns. We find that returns implied by consensus target prices and realized future returns are positively correlated when dispersion is low, but they become highly negatively correlated when dispersion is high. Further analyses suggest that the differing effect of dispersion stems from incentive-driven staleness in price targets by some analysts after bad news. As a stock performs poorly and some analysts are slow to update their target prices, dispersion increases, and the consensus target price becomes too high. This has important implications for how consensus analyst target prices should inform investment decisions. We show that a hedge strategy taking a long (short) position in stocks with the highest predicted returns among stocks with the lowest (highest) dispersion earns more than 11% annually. Finally, we show that the negative correlation between consensus-based predicted returns and future realized returns for high-dispersion stocks exists mainly for stocks with high retail interest, suggesting that unsophisticated investors are misled by inflated target prices that are available freely online.

Firms' diversity, equity, and inclusion (DEI) policies have received significant scrutiny in recent years, including their efficacy and role in long-term value creation. We provide new evidence on these issues by studying what is arguably the most important group of firms-those with identified problems. We find that in the wake of DEI controversies, firms shift their hiring practices toward recruiting diverse employees to presumably improve public perception of their DEI profiles. However, these effects are economically small and largely superficial. Despite these limited firm responses, we find these controversies have important negative stock price implications, which are largely offset when firms make more meaningful DEI investments. Our findings suggest firms currently often do little to address public concerns regarding their DEI activities, despite their significant value implications.

The world has seen a stunning rise in the willingness of great powers to use their trade and financial relationships for geopo- litical ends. This rise of “Geoeconomics” has the potential to reshape the interna- tional trade and financial system. Geoe- conomic policies include not only sanctions but also the strategic use of export controls, efforts to reshape supply chains for secu- rity purposes, the provision of foreign aid to secure political alignment, and the en- couragement or pressure on domestic and foreign firms to alter their business rela- tionships. While the foundation of a na- tion’s geoeconomic power is its economic strength, size and connections alone do not automatically translate into geoeconomic power. Instead, governments seeking to project geoeconomic power abroad need to be able to credibly co-opt or coerce their do- mestic firms and citizens, and perhaps crit- ical foreign allies, to take part in this power projection. Achieving this involves navigat- ing a range of political economy constraints at home, including legal restrictions, do- mestic political objectives, interest groups and other forces that limit a government’s ability to exert its influence. An important question for geoeconomic power projection is how far a government can push its own firms or allies to act against their private interests in pursuit of the country’s geopo- litical goals.

The Thorny Hill Club was established in 1901 to provide a welcoming and refined environment for faculty members to gather, dine, and engage in intellectual discourse. The Club quickly became a central hub for social activities, allowing faculty to entertain visiting scholars, friends, and alumni. Housed in a stately building featuring classic decor reminiscent of the early 20th century, the Club is furnished with 20 tables accompanied by 80 finely crafted chairs. Regular patrons of the Club include members from the Finance Department, the Sociology Department, and several members of the University Development Office.

At the heart of The Thorny Hill Club’s operations is a dedicated and skilled team led by General Manager Sue Fresco and Chef Tom Bilgewater. Fresco oversees the Club’s daily operations, while Chef Bilgewater, known for his culinary precision and creativity, commands the kitchen with authority. The Club also employees a 10-person hospitality staff comprised of cooks and food preparers, a half dozen servers, and a two-person maintenance staff. Recently, group dynamics have been challenging for Fresco to manage, as difficulties and dissent have arisen within the culinary team, within the server group, and between hospitality and maintenance staff, who serve in separate unions.

General Manager Sue Fresco is facing other significant challenges at Thorny Hill Club. One pressing issue is the implementation of a new kiosk system for take-out orders. This new system, while aimed at improving efficiency and expanding service, has been met with resistance from both kitchen and server staff who are struggling to adapt. Simultaneously, Fresco is also grappling with the financial strain caused by the persistently unprofitable catering business. For seven years, the catering division has posted losses, resulting in a $1.45 million shortfall in the latest financial cycle, which has pushed the Club’s overall financial performance into the red. The combined pressure of managing technological adoption and addressing the financial instability of the catering business is putting considerable strain on Fresco’s leadership.

The transparency and control of earnings are major concerns for gig economy workers across platforms such as ride-hailing and food delivery. While workers advocate for greater transparency, platforms selectively disclose information, shaping workers' decision-making and earnings. Recently, the Federal Trade Commission (FTC) has highlighted lack of transparency as a key issue, and platforms have responded by introducing upfront pay quotes that provide pertrip compensation details for workers. Using a game-theoretic model, we analyze the strategic interactions between the platform and workers, incorporating tools from information design to examine how different transparency policies-specifically, a fixed commission rate versus upfront pay quotes-shape equilibrium outcomes. We find that greater transparency can paradoxically increase platform control, as it allows platforms to fine-tune pay structures in ways that ultimately reduce worker autonomy. Moreover, while full information benefits the platform when it has flexibility in commission setting, it can backfire under commitment constraints, leading to lower profits than a no-information policy. Our findings highlight that transparency is not inherently beneficial for workers. Instead, its effects depend on how it interacts with pay policies. In particular, simple mechanisms, such as a fixed commission rate, can provide workers with more stability and bargaining power than per-trip transparency. These insights offer important guidance for policymakers and platform designers navigating the trade-offs of transparency in the gig economy. Keywords: Platforms, transparency, queueing, gig eco

Vital Farms operated in the premium egg market. It was founded in 2007 by Matt O'Hayer, who predicted a growing market of consumers willing to pay a premium price for ethically produced foods. O'Hayer built a network of small family farms committed to strict environmental standards, ensuring humane treatment of the hens and ethical practices. The company's high quality and clever marketing led to significant growth.

O'Hayer based the organization on "Conscious Capitalism" as espoused by John Mackey, co-founder of Whole Foods Market, and Professor Raj Sisodia. Under this model, the company sought to support the interests of diverse stakeholders — including investors, farmers, employees, consumers, communities, the environment, and the hens and cows that produced Vital Farms' products. To formalize its commitment to stakeholders, Vital Farms received certification as a B Corp and reincorporated as a Delaware Public Benefit Corporation.

Initially funded by O'Hayer's resources, the company attracted private investors and impact funds aligned with its mission as it grew. In 2020, Vital Farms recognized the need for a significant capital infusion to maintain its growth trajectory. As it looked to raise capital, O'Hayer and Vital Farms CEO Russell Diez-Conseco faced the challenge of balancing its stakeholder interests against the pressures from capital markets, where investor priorities often dominated, while maintaining its commitment to conscious capitalism values. Potential options included seeking additional impact investors or venture capital, taking on debt, or considering public market offerings. Given the benefits and challenges inherent in each option, what path was best for the company, its investors, its stakeholders, and its mission?

The founders of Warby Parker had a clear vision of the kind of company they wanted to build: a novel business model that would disrupt a long-entrenched industry. The company’s values would create a culture that the founders themselves—and, they hoped, many others—would find meaningful and even fun. Their social impact mission wouldn’t be a philanthropic afterthought but an integral part of the business’s core. Purpose and profit would be pursued simultaneously, along with a commitment to building mutually beneficial relationships with customers, partners, communities, and other key stakeholders. They debated these and other critical details two years before the company was operational or even had a name.

The case examines the founders’ original business design for Warby Parker—a holistic approach that aligned and integrated purpose, a values-based culture, and business strategy with a commitment to building trusted relationships with stakeholders. The case also explores the actions taken by leadership to preserve this design as the company scaled, adapted and, ultimately, became a public corporation.

Consideration set models generalize discrete-choice models by relaxing the assumption that consumers consider all available options. Determining which options were considered has previously required either survey data or restrictions on how attributes affect consideration or utility. We provide an alternative route. In full-consideration models, choice probabilities satisfy a symmetry property analogous to Slutsky symmetry in continuous-choice models. This symmetry breaks down in consideration set models when changes in characteristics perturb consideration. We show that consideration probabilities are constructively identified from the resulting asymmetries. We validate our approach in a lab experiment where consideration sets are known and then apply our framework to study a “smart default” policy in Medicare Part D, wherein consumers are automatically reassigned to lower-cost prescription drug plans with the option of opting out. Full-consideration models imply that such a policy will be ineffective because consumers will opt out to avoid switching costs. Allowing for inattention, we find that defaulting all consumers to lower-cost options produces negligible welfare benefits on average, but defaulting only consumers who would save at least $300 produces large benefits.

This paper identifies which investments in school facilities help students and are valued by homeowners. Using novel data on school district bonds, test scores, and house prices for 29 U.S. states and a research design that exploits close elections with staggered timing, we show that increased school capital spending raises test scores and house prices on average. However, impacts differ vastly across types of funded projects. Spending on basic infrastructure (such as HVAC) or on the removal of pollutants raises test scores but not house prices; conversely, spending on athletic facilities raises house prices but not test scores. Socio-economically disadvantaged districts benefit more from capital outlays, even conditioning on project type and the existing capital stock. Our estimates suggest that closing the spending gap between high- and low-SES districts and targeting spending towards high-impact projects may close as much as 25% of the observed achievement gap between these districts.

Yale Athletics operates a comprehensive and diverse program including 35 NCAA Division I varsity sports, intramurals, and club sports, all coordinated under the direction of Victoria M. "Vicky" Chun, the Thomas A. Beckett Director of Athletics. The department oversees significant athletic facilities such as Payne Whitney Gymnasium, the Yale Bowl, the Yale Golf Course, and additional specialized fields and rinks. This operation is underpinned by approximately 170 full-time employees who manage athletic medicine, business operations, compliance, event management, sports performance, student-athlete development, sports performance, communication, marketing, and community engagement.

Current opportunities for Yale Athletics include:

1. Corporate Sponsorships: Yale Athletics aims to optimize its corporate sponsorship portfolio by analyzing current offerings and improving how media and sponsorships are packaged and priced. This area is crucial for securing financial support and enhancing the advertising value for partners.

2. Ticketing and Price Analytics: The department is reevaluating its ticket pricing strategies to both increase game attendance and revenue. Comparative market research is being used to consider pricing strategies.

3. Community Outreach and Fan Engagement:  Post-pandemic, there is an effort to attract more fans from the local community. Yale Athletics is working on a cohesive outreach strategy and defining goals for fan attendance, balancing innovative marketing practices with Yale’s mission.

4. Employee Outreach and Engagement: Enhancing internal engagement is a priority. Despite efforts to keep the university’s large on-campus population informed about sports events, there is a focus on leveraging new technologies, creating better game-day experiences, and ensuring effective communication.

5. Artificial Intelligence:  Exploring the use of AI technologies to improve operational efficiency and service delivery is on the agenda. This involves utilizing AI for better customer service, advanced market research, and provide further support of administrative functions.

These challenges reflect Yale Athletics' commitment to maintaining excellence and fostering a vibrant sports environment within the university and community.

Governments use their countries’ economic strength from financial and trade relationships to achieve geopolitical and economic goals. We provide a model of the sources of geoeconomic power and how it is wielded. The source of this power is the ability of a hegemonic country to coordinate threats across disparate eco- nomic relationships as a mean of enforcement on foreign entities. The hegemon wields this power to demand costly actions out of the targeted entities, including mark-ups, import restrictions, tariffs, and political concessions. The hegemon uses its power to change targeted entities’ activities to manipulate the global equilib- rium in its favor and increase its power. A sector is strategic either in helping the hegemon form threats or in manipulating the world equilibrium via input-output amplification. The hegemon acts a global enforcer, thus adding value to the world economy, but destroys value by distorting the equilibrium in its favor.

We develop a tractable dynamic contracting framework to study bank bail-in regimes. In the presence of a repeated monitoring problem, the optimal bank capital structure combines standard debt, which induces liquidation and provides strong incentives, and bail-in debt, which restores solvency but provides weaker incentives. When there are fire sales, optimal policy entails joint regulation: a bail-in regime reduces standard debt while leverage regulation reduces total debt. Bail-ins replace bailouts as a recapitalization tool.

We develop an economic model of autonomous vehicle (AV) ride-hailing markets, in which uncertain aggregate demand is served with a combination of a fixed fleet of AVs and a flexible pool of human drivers (HVs). Dispatch efficiencies increase with scale because of density effects. We analyze market outcomes in this setting under four market configurations, defined by two dispatch platform structures (common platform versus independent platforms) and two levels of supply competition (monopoly AV versus competitive AV). A key result of our analysis is that the lower cost of AVs does not necessarily translate into lower prices; the price impact of AVs is ambiguous and depends critically on both the dispatch platform structure and the level of AV supply competition. In the extreme case, we show that if AVs and HVs operate on independent dispatch platforms, there is a monopoly AV supplier, and labor supply elasticity is sufficiently high, then prices are even higher than in a pure-HV market. Indeed, to guarantee consistently lower prices (relative to a pure HV market) in all scenarios and under all supply and density elasticities, a common dispatch platform between AVs and HVs is required. Furthermore, competitive AVs lead to lower prices than monopoly AVs in every such scenario. Our results illustrate the critical role that market configuration plays in realizing potential welfare gains from AVs.

This paper examines the welfare implications of third-party informational interme- diation. A seller sets the price of a product that is sold through an intermediary, who discloses information about the product to consumers. In a model where the inter- mediary is consumer-minded—has a payoff that depends on both the seller’s revenue and the consumer surplus, we show that total welfare may decrease in the Pareto sense, as the intermediary’s consumer-mindedness increases. Furthermore, we show that consumer-mindedness emerges endogenously when a revenue-maximizing interme- diary is forward-looking and the consumer base is increasing in past consumer surplus.

The Securities and Exchange Commission (SEC) reviews firms’ financial reports and issues comment letters to ensure compliance with applicable disclosure and accounting requirements. We explore the nature, determinants, and consequences of SEC comment letters that refer to information disclosed in voluntary earnings conference calls. Using hand-collected data, we document that the SEC primarily references these voluntary disclosures to illustrate insufficiencies and, less commonly, inconsistencies in mandatory filings across a wide range of topics. These letters are more likely to be issued when filing reviews are more complex, SEC staff are less resource constrained, and for firms with more institutional investors and analysts. Conference call-related comments tend to occur during higher-quality review processes and require greater remediation costs than other comments. The SEC’s use of call disclosures also leads to more pronounced changes in firms’ subsequent mandatory filings, particularly when the firm indicates agreement with SEC comments. However, we observe a mixed effect on the overall information environment, consistent with possible unintended consequences for the quality of firms’ voluntary disclosures.

This article develops a method to automatically discover and quantify human-interpretable visual characteristics directly from product image data. The method is generative, and can create new visual designs spanning the space of visual characteristics. It builds on disentanglement methods in deep learning using variational autoencoders, which aim to discover underlying statistically independent and interpretable visual characteristics of an object. The impossibility theorem in the deep learning literature indicates that supervision with ground truth characteristics would be required to obtain unique disentangled representations. However, these are typically unknown in real world applications, and are in fact exactly the characteristics we want to discover. Extant machine learning methods require ground truth labels for each visual characteristic, resulting in a task requiring human evaluation and judgment to both design and operationalize. In contrast, this method postulates the use of readily available product characteristics (such as brand and price) as proxy supervisory signals to enable disentanglement. This method discovers and quantifies human-interpretable and statistically independent characteristics without any specific domain knowledge on the product category. It is applied to a dataset of watches to automatically discover interpretable visual product characteristics, obtain consumer preferences over visual designs, and generate new ideal point designs targeted to specific consumer segments.