Publications

A seller wants to sell an item to n buyers. Buyer valuations are drawn i.i.d. from a distribution unknown to the seller; the seller only knows that the support is included in [a,b]. To be robust, the seller chooses a DSIC mechanism that optimizes the worst-case performance relative to the ideal expected revenue the seller could have collected with knowledge of buyers' valuations. Our analysis unifies the regret and the ratio objectives. 
For these objectives, we derive an optimal mechanism and the corresponding performance in quasi-closed form, as a function of the support information [a,b] and the number of buyers n. Our analysis reveals three regimes of support information and a new class of robust mechanisms. i.) When a/b is below a threshold, the optimal mechanism is a second-price auction (SPA) with random reserve, a focal class in earlier literature. ii.) When a/b is above another threshold, SPAs are strictly suboptimal, and an optimal mechanism belongs to a class of mechanisms we introduce, which we call pooling auctions (POOL); whenever the highest value is above a threshold, the mechanism still allocates to the highest bidder, but otherwise the mechanism allocates to a uniformly random buyer, i.e., pools low types. iii.) When a/b is between two thresholds, a randomization between SPA and POOL is optimal. 
We also characterize optimal mechanisms within nested central subclasses of mechanisms: standard mechanisms that only allocate to the highest bidder, SPA with random reserve, and SPA with no reserve. We show strict separations in terms of performance across classes, implying that deviating from standard mechanisms is necessary for robustness.

In most evaluation systems—such as those governing the allocation of prestigious awards—the evaluator’s primary task is to reward the highest quality candidates. However, these systems are imperfect; top performers may not be acknowledged and thus be underrecognized, and low performers may receive unwarranted recognition and thus be overrecognized. An important feature of many evaluation systems is that people alternate between being candidates and being evaluators. How does experiencing misrecognition as a candidate affect how people subsequently evaluate others? We develop novel theory that underrecognition and overrecognition lead people to reproduce those experiences when they are evaluators. Across three studies—a quasi-natural experiment and two preregistered, multistage experiments, we find that underrecognized evaluators are less likely to grant recognition to others—even to the highest-performing candidates. Conversely, overrecognized evaluators are more likely to grant rewards to others—even to the lowest-performing candidates. Whereas underrecognized evaluator behavior is driven by individuals’ perceptions that their experience was unfair, overrecognized evaluator behavior is driven by the informational cues people glean on how to evaluate others. Thus, in evaluation processes where people oscillate between being the evaluated and being the evaluator, we show how and why seemingly innocuous initial inefficiencies are reproduced in subsequent evaluations.

ob seekers often rely on help from social ties in the search for employment. Yet the job search is characterized by meritocratic ideals according to which candidates should be selected based on their qualifications, not their connections. How do people justify the use of connections given the conflicting cultural logics of social capital and meritocracy? We conduct an inductive analysis of 56 interviews with young Spaniards experiencing a difficult labor market and identify a novel process of justification, situational alignment, that reconciles these conflicting logics. Respondents justified situations in which connections provided assistance as legitimate when they perceived alignment among the job seeker, job, and type of help that connections provided. Respondents deemed illegitimate the situations in which these were not aligned. These justifications allowed respondents to embrace the social capital logic’s prescription to use connections, while upholding the meritocratic principle that jobs be awarded based on qualifications. We further find that situations involving close ties were more readily justified than those involving distant others. We test this inductively derived process using a survey experiment with 1,536 young Spaniards. This study demonstrates that perceptions of merit are situated, and advances the understanding of social capital by identifying a novel process of justification that contributes to labor market inequality.

Should central banks’ inflation targets remain set in stone? We study a dynamic mechanism
design problem between a government (principal) and a central bank (agent). The central
bank has persistent private information about structural shocks. Firms learn the state from the
central bank’s reports and form inflation expectations. A dynamic inflation target implements the
full-information commitment allocation. The central bank is delegated the authority to adjust
the level and flexibility of its target as long as it does so one period in advance. All history
dependence of the mechanism is summarized by the current period’s target. We show that
a declining natural interest rate and a flattening Phillips curve imply opposite optimal target
adjustments. We leverage our framework to study longer-horizon time consistency problems
and speak to practical policy questions of inflation target design.

A strategic tension between consumers in a monopolistic market arises when many high-value consumers want to pool with a few lower-value consumers in order to obtain low prices from the seller. We study the interaction between consumers and the resulting market segmentation into consumer groups as the outcome of a cooperative game between the consumers. We introduce two new solution concepts, the weakened core and stability, which coincide with the core whenever it is nonempty. We show that these concepts are in fact equivalent and non-empty, and are characterized by efficiency and saturation. A segmentation is saturated if shifting consumers from a segment with a higher price to a segment with a lower price leads the seller to optimally increase the lower price. We show that stable segmentations that maximizes average consumer surplus (across all segmentations) always exist

This paper develops a theory-based, explainable deep learning convolutional neural network (CNN) classifier to predict the time-varying emotional response to music. We design novel CNN filters that leverage the frequency harmonics structure from acoustic physics known to impact the perception of musical features. Our theory-based model is more parsimonious, but it provides comparable predictive performance with atheoretical deep learning models while performing better than models using handcrafted features. Our model can be complemented with handcrafted features, but the performance improvement is marginal. Importantly, the harmonics-based structure placed on the CNN filters provides better explainability for how the model predicts emotional response (valence and arousal) because emotion is closely related to consonance—a perceptual feature defined by the alignment of harmonics. Finally, we illustrate the utility of our model with an application involving digital advertising. Motivated by YouTube’s midroll ads, we conduct a laboratory experiment in which we exogenously insert ads at different times within videos. We find that ads placed in emotionally similar contexts increase ad engagement (lower skip rates and higher brand recall rates). Ad insertion based on emotional similarity metrics predicted by our theory-based, explainable model produces comparable or better engagement relative to atheoretical models.

This article concerns itself with fees that Apple and Google might charge to business users in their respective mobile ecosystems. We lay out the economic analysis behind the goals of the DMA—contestability and fairness—as they apply to third-party app store access fees. We focus on the access fees for alternatives to the Apple App Store, as this has become contentious in the early enforcement of the DMA. Much of our analysis, however, also applies also to Google and/or any other designated gatekeeper.

For more than 150 years, the founding mission of the American Society for the Prevention of Cruelty to Animals (ASPCA) guided the organization while enabling it to address evolving challenges in animal welfare. Under Matt Bershadker, ASPCA’s president and CEO, the company faced mounting pressure to engage with a growing stream of societal matters far afield from its core purpose. The case explores Bershadker’s initiative to develop a clear, strategic framework for considering which societal issues to address. This effort would clarify the ASPCA’s approach to these issues by evaluating them against the organization’s strategy, history, policies, and key stakeholder relationships, ensuring consistency, transparency, and mission-driven decision-making.

We study a retirement savings plan with a default contribution rate of 12% of income, which is much higher than previously studied defaults. Twenty-five percent of employees had not opted out of this default 12 months after hire; a literature review finds that the corresponding fraction in plans with lower defaults is approximately one-half. Because only contributions above 12% were matched by the employer, 12% was likely to be a suboptimal contribution rate for employees. Employees who remained at the 12% default contribution rate had average income that was approximately one-third lower than would be predicted from the relationship between salaries and contribution rates among employees who were not at 12%. Defaults may influence low-income employees more strongly in part because these employees face higher psychological barriers to active decision making.

Bayer AG is a German multinational pharmaceutical and life sciences company founded in 1863. It operates globally in over 90 countries with approximately 100,000 employees as of 2024. Bayer is structured into three main business segments: Pharmaceuticals, Consumer Health, and Crop Science, with significant global operations and an extensive patent portfolio. The company is a leader in agricultural products, prescription medicines, and over-the-counter health products. It also focuses on innovative solutions for healthcare and agricultural challenges.

The current dilemma for students to address are issues related to Bayer’s transition to a new operating model called Dynamic Shared Ownership (DSO). This model, introduced under the leadership of CEO Bill Anderson, aims to flatten the corporate hierarchy and create a nimbler, customer-centric organization. The transition involves removing the existing hierarchical structure, which previously consisted of 12 management layers, and replacing it with self-managed teams. This structural change was referred to internally as the "hardware."

The initial steps under DSO included substantial organizational redesign, involving layoffs and the establishment of self-managed teams. The Board of Management successfully halved the number of management layers to five or six and replaced thousands of middle managers with self-managed teams. A complementary aspect of DSO, labeled the "software," focused on fostering cultural changes to promote new mindsets, norms, and behaviors among Bayer’s nearly 100,000 employees.

Notwithstanding several early wins, the Board of Management is now grappling with implementing new talent management and personnel policies that align with the DSO model. Existing HR processes and systems, which are designed for a hierarchical organization, need to be reinvented. Questions about compensation, career pathing, and performance metrics must be addressed to ensure these new systems support the DSO framework effectively.

A critical element of word of mouth (WOM) or buzz marketing is to identify seeds, often central actors with high degree in the social network. Seed identification typically requires data on the relevant network structure, which is often unavailable. We examine the impact of WOM seeding strategies motivated by the friendship paradox, which can obtain more central nodes without knowing network structure. Higher degree nodes may be less effective as seeds if these nodes communicate less with neighbors or are less persuasive when they communicate; therefore, whether friendship paradox–motivated seeding strategies increase or reduce WOM and adoption remains an empirical question. We develop and estimate a model of WOM and adoption using data on microfinance adoption across village social networks in India. Counterfactuals show that the proposed strategies with limited seeds are about 13%–30% more effective in increasing adoption relative to random seeding. These strategies are also on average 5%–11% more effective than the firm’s leader seeding strategy. We also find these strategies are relatively more effective when we have fewer seeds.

We hypothesize that “low-contrast categories” (those lacking sharp differentiation from adjacent categories) catalyze the creation of groundbreaking inventions by influencing two key stages in the life of an invention: (1) idea-creation and (2) idea-positioning. During “idea-creation,” low-contrast categories increase the likelihood that descendant inventions will combine the focal invention with more (a) boundary-spanning, (b) novel, (c) original, and (d) atypical knowledge inputs. During “idea-positioning,” they allow greater leeway in articulating how descendant inventions depart from the focal invention’s lineage and chart new technological directions. We find robust support for our hypothesis using data from the United States Patent and Trademark Office’s classification system spanning nearly four decades. Further analyses demonstrate that the catalyzing effect of low-contrast categories has important material consequences: inventions classified in low-contrast categories spur descendant inventions that generate substantially higher economic value and exert more enduring technological impact than those in high-contrast categories. By introducing the concept of catalyzing categories, this study offers a novel theoretical perspective on the genesis of groundbreaking inventions and the role of categorical structures in the inventive process.

The 2020 revisions to the Federal Reserve’s monetary policy framework included a shift in the Fed’s policy focus to shortfalls (rather than deviations) from maximum employment and a commitment to “flexible average inflation targeting.” The new framework, and the associated guidance and asset purchases with which it was implemented, were tested by the surge in inflation in 2021 and 2022. We consider the lessons learned from this experience. We conclude that the changes to the framework were too focused on the experience following the financial crisis and hence were not robust in the face of unexpected changes in economic circumstances. We also argue that the Fed made mistakes with the calibration and communication of the tools used to implement the framework—the forward guidance on the policy rate and the asset purchase program. We recommend a broad framework that would be appropriate in a wide range of policy environments, with the specific policy approach to be taken in any given circumstance to be communicated through forward guidance and asset purchase announcements. We suggest ways in which the Fed could implement these tools with better calibration and communication, in order to avoid having its policy commitments exacerbate costly economic outcomes.

Should Microsoft join a global moratorium on underwater mineral mining until the harm mining could do to the oceans is thoroughly assessed?

Global technology giant Microsoft designs, manufactures, and sells a range of software, services, and devices, including the Windows operating system, Microsoft Office, Azure cloud computing services, and hardware products such as Surface tablets and Xbox gaming consoles. Sourcing the cobalt for the lithium-ion batteries in its hardware products presents Microsoft with a dilemma. Terrestrial cobalt mining ravages environments and produces considerable emissions. In the Democratic Republic of the Congo, home of most of the world's cobalt, the metal is extracted with forced labor, child labor, and exploitation. Cobalt is also found in the deep oceans. However, environmentalists and many global governments decry undersea cobalt mining as unnecessary and damaging to precious deep ocean biospheres. Microsoft must balance its need for reliable cobalt supplies with company ethical and environmental standards, though terrestrial and ocean cobalt are both imperfect sources with ethical and environmental risks and controversies.

The credit-implied volatility (CIV) surface is introduced as an organizing framework for analysis of credit spreads, providing a description of CDS spreads for firms across the credit spectrum, of varying maturities, and at all points throughout the credit cycle.

We model the optimal resolution of insolvent firms in general equilibrium. Collateral- constrained banks lend to (i) solvent firms to finance investments and (ii) distressed firms to avoid liquidation. Liquidations create negative fire-sale externalities. Liquidations also re- lieve bank balance-sheet congestion, enabling new firm loans that generate positive collateral externalities by lowering bank borrowing rates. Socially optimal interventions encourage liqui- dation when firms have high operating losses, high leverage, or low productivity. Surprisingly, larger fire sales promote interventions encouraging more liquidations. We study synergies be- tween insolvency interventions and macroprudential regulation, bailouts, deferred loss recog- nition, and debt subordination. Our model elucidates historical crisis interventions.

Oprea argued that prospect theory’s risk attitudes reflect ''complexity'' rather than underlying risk preferences. A re-analysis reveals that this claim is driven by measurement error caused by a confusing experimental design. Participants valued risky lotteries and riskless ''mirrors'' similarly, but this was largely due to the 75% who failed comprehension checks. These subjects had noisy valuations and frequent dominance violations, which artifactually produce a fourfold pattern, loss aversion, and positive correlation between mirrors and lotteries. In contrast, participants who likely understood the task valued mirrors at expected value and lotteries in line with prospect theory.

Researchers were already expecting a gradual enrollment slowdown before the onset of COVID-19. Public school enrollment edged up only 2% between 2012 and 2019, holding near 50 million students, while the U.S. total fertility rate had slipped to 1.71 births per woman—well below the replacement level—foreshadowing a smaller school-age cohort. The pandemic turned that slow decline into a sudden shock. Studies document steep post-2020 losses in Massachusetts, Virginia, Michigan, and California. Research at the national level shows similar trends in urban and high-poverty districts, and a surge in both homeschooling and private-schooling that still leaves millions of children “missing” from any formal roll. In addition to concerns around student progress, shrinking headcounts also create immediate fiscal stress because most state and federal aid flows on a per-pupil basis. District leaders have already considered adjusting school capacity, redistricting, or even closing campuses to balance budgets— steps that are often politically sensitive but considered in response to fiscal pressures. Recent evidence confirms that steeper enrollment losses measurably raise the odds of permanent closure. Enrollment shifts have not fallen evenly across student groups. Recent evidence shows that kindergarten enrollment fell most sharply for black and low-income children, whereas the smaller declines observed in later grades were concentrated among white and higher-income students already enrolled in public schools. Such patterns may heighten long-standing worries about potential re-segregation and resource inequality. Against this backdrop, policymakers and district officials are experimenting with strategies to stem further enrollment losses or mitigate their effects. Some, like New York City, have pledged to preserve school budgets even as rolls shrink. Others hope new curricula or enhanced parent outreach will attract students back. This report provides detailed estimates of recent shifts in public school enrollment. By linking the latest National Center for Education Statistics data with federal population estimates, the report shows how enrollment shifts differ across districts with distinct racial and economic profiles. In addition, it projects how continued enrollment declines could drive future school closures and alter the number of seats traditional districts will need through 2050.

The origin of the modern joint-stock company is typically traced to the concomitant appearance of large-scale maritime trading companies in England and the Netherlands in the early seventeenth century. Highlighting medieval cases in southern Europe, we claim that the joint-stock company emerged earlier in history. These prior appearances support the theory of convergent evolution towards the joint-stock company. We document alternative and largely independent developmental paths that suggest the joint-stock company can emerge in a variety of legal, political and socioeconomic contexts. This evidence has implications for identifying the necessary background underlying the emergence of the joint-stock company, and for the debate regarding the link between business institutions and economic growth.