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Placement

Placement

  • Students on the Job Market

Students on the Job Market

Students on the Job Market

Please note this page will be updated throughout the fall.

Business Economics

Gianluca Rinaldi

Abstract:

Learning from Liquidation Prices
I develop a model of investor learning driven by mistaken inference from market prices. Investors have different beliefs about the worst case return of a risky asset and take on leverage to buy it. In states in which the worst case becomes more likely, forced liquidations result in price crashes, which investors mistake for negative information about the worst case. They therefore revise cash flow expectations downwards, henceforth requiring larger returns in normal times. The model has implications for the magnitude and persistence of changes in the yields of quasiarbitrage strategies. Empirically, I examine the returns to various strategies which experienced dramatic losses around episodes of financial distress. Option selling strategies didn't deliver large returns before the Black Monday crash of 1987 but have been profitable since. This return increase is linked to the substantial losses experienced in 1987, which were exacerbated by the leverage of option market makers. I also document a strong relationship between the cross section of Bond-CDS bases after the financial crisis and the performance of corresponding convergence trades in the weeks around the Lehman bankruptcy. While strategy returns during this tight window arguably reflected deleveraging, the convergence trades displaying the largest losses in September 2008 are also the most profitable years later, consistent with investors learning about the risk in those strategies from this deleveraging episode.
Faculty Advisor(s): J. Campbell, J. Campbell, and A. Sunderam
Curriculum Vitae   |  Email

Andreas Schaab

Abstract:

Micro and Macro Uncertainty
This paper studies the interaction between uncertainty at the micro and macro level in a globally solved Heterogeneous Agent New Keynesian (HANK) model with aggregate risk. Its direct effect on micro uncertainty, thus far ignored by the literature, becomes the dominant transmission channel of a macro uncertainty shock. Macro uncertainty itself becomes endogenous to aggregate demand. The resulting GE feedback loop between macro uncertainty on the one hand, and micro uncertainty and aggregate demand on the other generates large endogenous spikes in uncertainty during economic crises. The model matches the skewness and kurtosis exhibited by macro uncertainty in the data even in the absence of exogenous second-moment shocks. The interplay between micro and macro uncertainty has substantial ramifications for the nature of ZLB spells, the welfare cost of business cycles, the effectiveness of stabilization policy, asset pricing dynamics and other applications.
Faculty Advisor(s): X. Gabaix, M. Maggiori, and L. Straub
Curriculum Vitae   |  Website   |  Email

Gregor Schubert

Abstract:

House Price Contagion and U.S. City Migration Networks
Why do some cities experience much larger housing booms than others - and how do economic shocks spread between cities? This paper proposes an explanation of house price contagion based on migration spillovers between U.S. cities. I use the network structure of inter-city migration to develop an instrument for identifying causal spillover effects between cities. The estimated spillover effects show house price movements propagate through migration links: An exogenous increase in other cities' house prices by 10% in the long run causes a 6.3% house price move in a city exposed to the shock through migration links. Applying this framework to historical shocks, I show that spillovers from the effect of interest rate declines on house prices in other cities can explain 32% of the cross-sectional variation in house price growth during the run-up to the housing boom of the 2000s. To quantify the effect of changes in migration costs and housing supply constraints on the house price spillover effects across U.S. cities, I develop and estimate a dynamic spatial equilibrium model that incorporates forward-looking migration choices and heterogeneity in housing supply constraints. I use this model to simulate the effect of economic shocks on the distribution of house price growth across cities and the co-movement of city-level effects with the national cycle during the 2000s and 2010s. I find that lower migration costs substantially reduce the dispersion in house price growth: without worker mobility, the spread in house price growth across cities in response to wage shocks would be 65-70% larger. Moreover, I show that declines in worker mobility increase the impact of housing policy on differences in house price outcomes between cities.
Faculty Advisor(s): J. Stein, L. Katz, E. Glaeser, and A. Sunderam
Curriculum Vitae   |  Website   |  Email

Allen T. Zhang

Abstract:

Estimation of High-Dimensional Dynamic Games: Fintech Lenders and Bank Branch Closures”
This paper studies long-run implications of bank branch closures stemming from the digitization of banking services and increased competition from fintech mortgage lenders. In the last decade, nonbank lenders have doubled their market share and now originate more than half of mortgages in the US. Meanwhile, banks have closed more than 13,000 (13%) branches. Reduced form evidence shows this rise in nonbank origination is responsible for a large proportion of the observed decline in bank branching. Furthermore, this led to a reduction in the banks' deposit taking and small business loan origination. I build a new dynamic structural model of bank branching. In the model, banks earn flow profits from taking deposits and providing lending services, and dynamically adjust their branch networks in response to market conditions. As each bank faces substantial heterogeneity in its competitive environment over time, the branching equilibrium is characterized by a high-dimensional dynamic game where banks must properly account for the evolution of state variables including demographics, fintech competition, and the branch networks of its rivals. I estimate and solve the model using a new dimensionality-reduction technique, and evaluate the long-run impact of policies such as capital requirements and conforming loan limits. My work suggests that endogenous branching responses can have significant implications for policy analysis in banking markets.
Faculty Advisor(s): A. Pakes (Chair), R. Lee, D. Scharfstein, and A. Sunderam
Curriculum Vitae   |  Website   |  Email

Health Policy (Management)

Emilie Aguirre

Abstract:

Beyond Profit
Etsy was a crown jewel of socially responsible businesses. It prioritized female entrepreneurship, its employees, and environmental stewardship. It was widely admired as a company pursuing social goals alongside profit goals. But after scaling up through an IPO, Etsy fell apart both socially and financially. Similar stories proliferate in the world of socially conscious business. What happened? Standard accounts point to greedy investors, capitalism, and short-termism as the culprits.

But this paper identifies a more fundamental problem: business law is not designed to facilitate scale-ups for companies that articulate objectives beyond profit. It lacks a durable commitment mechanism for these companies to bind themselves to long-term pursuit of their multiple objectives. To help address this problem, the paper identifies potential solutions in corporate governance and corporate finance, and ultimately proposes providing a voluntary commitment mechanism in business law. The proposed commitment mechanism would require multiple stakeholder board representation and socially conscious executive compensation for public benefit corporations that IPO, get acquired, or exceed a certain size. Such legislation could better enable companies to bind themselves to their objectives beyond profit at scale — facilitating large-scale social impact instead of just large-scale profit.
Faculty Advisor(s): J. Battilana (Chair), D. Leonard, and A.J. Casey
Curriculum Vitae   |  Website   |  Email

A Jay Holmgren

Abstract:

Hospital Response to Quality Feedback: Evidence from Medication Safety Evaluation
The federal government has spent billions of dollars in incentives for health care delivery organizations, including acute care hospitals, to digitize their clinical records and workflow processes by adopting electronic health records (EHRs). However, to date, many of the proposed quality benefits of digitizing health care delivery have not been realized in practice. One reason for this may be the poor performance of clinical decision support systems, which were the primary mechanism by which digitization of health care delivery was expected to improve quality. Hospital scores on a national assessment of clinical decision support capabilities has been uneven, and there is significant variation in performance even within hospitals using the same EHR system. At the same time, there is an ongoing debate regarding the value of these national quality and safety measures and assessments, with many prominent industry voices stating that they do not see value in these types of performance assessments, and the empirical work on health care quality metrics has produced mixed findings. To date, however, there have been few studies regarding the value of quality measures that focus on EHR safety performance.

To determine the value of performance feedback for health care IT systems, I use national hospital data from 1,183 hospitals who participated in an EHR performance evaluation, the Leapfrog CPOE Safety Evaluation, in both 2017 and 2018. The Leapfrog CPOE Safety Evaluation uses simulated patients and orders based on historical adverse drug event cases to assess hospital clinical decision support performance at preventing potential inpatient drug errors. This voluntary self-assessment is taken by a wide array of hospitals annually. Hospitals receive categorical feedback based on their percentage score, i.e. “Full Demonstration of Safety Standards” for a score between 50-100%, compared to “Some Demonstration of Safety Standards” for a score between 30-49.99%. Using a sharp regression discontinuity design, I identify the causal impact of giving hospitals feedback on their quality performance on their improvement in the subsequent year. I then examine the mechanism by which improvement occurs between basic and advanced decision support capabilities.

I find that hospitals who receive non-perfect categorical feedback, “Some Demonstration of Safety Standards” improve 4.7% more in the subsequent year than hospitals who receive “Full Demonstration of Safety Standards” feedback. This effect is driven by improvement in basic clinical decision support capabilities, such as drug-drug or drug-allergy contraindications, rather than more advanced functions such as drug-diagnosis or drug-laboratory test value contraindications. These results have important implications regarding the value of quality assessment in health care. This study finds a small but significant “nudge” effect of providing hospitals with a categorical “non-perfect” score in a national quality measure on score improvement in the next year, and provide evidence that measurement and feedback can improve quality.
Faculty Advisor(s): R. Huckman, D. Bates, D. Cutler, and J. Adler-Milstein
Curriculum Vitae   |  Website   |  Email

Olivia Jung

Abstract:

Using Crowdsourcing to Activate Innovation by Frontline Workers: A Field Experiment in Community Health Centers
How should managers engage frontline workers to innovate—to think critically about established practices, identify problems, generate solutions, and voice suggestions—when that’s not part of their day-to-day job? Building on research on voice and on innovation contests that sheds light on motivating discretionary problem-solving efforts, I test whether and how administering an innovation contest energizes frontline workers to innovate. I recruited 53 community health centers at which workers’ primary job is delivering high-quality patient care and conducted a large-scale randomized controlled trial and a qualitative study. My experimental findings show that the contest increased workers’ innovative behaviors by more than 20 percent. My qualitative findings reveal that the contest exposed managers to the value of worker’s innovation and prompted workers to prioritize problem-solving. This led to increased solicitation and sharing of worker input. The increase was more marked in organizations whose managers had not routinely asked workers for ideas prior to the contest. My findings suggest that crowdsourcing can identify improvement opportunities and increase workers’ discretionary engagement in organizational improvement.
Faculty Advisor(s): A. Edmondson (Chair), K. Lakhani,  M. Kerrissey, and J. Lorsch
Curriculum Vitae   |  Website   |  Email

Marketing

Ximena Garcia-Rada

Abstract:

A Preference for Effort When Caring for Close Others (with M. Steffel, E.F. Williams, and M.I. Norton)
Many new products are designed to simplify caregiving and make consumers’ lives easier when providing direct care to close others, from premade meals to feed families to robo-cribs that automatically rock babies back to sleep. Yet, using these products may come with a cost: consumers feel they have not exerted enough effort because that very ease may signal that they are failing to be dedicated caregivers. Nine experiments show that consumers feel like worse caregivers when they use effort-reducing products to take care of close others (e.g., their partners, children, or family members) because they perceive that their caregiving lacks symbolic meaning. Specifically, choosing effort-reducing products makes consumers feel that they are doing a worse job of signaling that they care about their loved ones even when effort-reducing products provide similar quality of care. Taken together, these findings expand our current understanding of effort, caregiving, and, more broadly, the many choices that consumers make in the context of close relationships.
Faculty Advisor(s): M. Norton (Chair), L. John, R. Buell, J. Gourville, and R. Ratner
Curriculum Vitae   |  Website   |  Email

Organizational Behavior

Lumumba Seegars

Abstract:

Sanctioned Radicals: A comparative study of gender and race employee resource groups in tech
A key challenge that people of color and women face is their ability to contest racial and gender inequality within organizations. One prevalent approach that they have taken has been to collectively organize through formal groups within organizations that are organized around a particular identity, often known as Employee Resource Groups (ERGs). Despite the prevalence of people of color and women organizing through ERGs in order to contest racial and gender inequality within organizations, little is known about how the specific identities around which these groups are organized – race and gender (e.g., Black, Asian, women) – may shape their ability to contest inequality. In this dissertation, I use a qualitative inductive approach based primarily upon interviews with 159 employees across two tech companies in order to compare how race and gender shape the way people of color and women collectively organize within organizations to contest inequality. I primarily compare the Black, Asian, and women ERGs. I ask: How do women and people of color collectively organize around their identities within organizations in order to contest gender and racial inequality? Two questions stem from this overarching question. First, how is this process similar or different when organizing around gender versus race as well as across different racial groups? Second, how do individuals’ intersecting race and gender identities shape their experiences within these groups? This dissertation contributes to research on race and gender inequality inside organizations, intersectionality, and social movements within organizations.
Faculty Advisor(s): R. Ely (Chair), L. Ramarajan, and M. Lamont
Curriculum Vitae   |  Website   |  Email

Strategy

Young Hou

Abstract:

Vertical Coopetition between Firms: Incentives and Impact
Forthcoming.
Faculty Advisor(s): N/A, J. Alcacer, and J. Rivkin
Curriculum Vitae   |  Website   |  Email

Technology & Operations Management

Sourobh Ghosh

Abstract:

Think Before You Act: The Unintended Consequences of Inexpensive Experimentation
Scholars and practitioners recommend the use of inexpensive business experiments to evaluate new and uncertain strategic alternatives. While current thinking recommends that strategic alternatives be tested as independent decisions across many experiments, this contradicts scholarly understanding of strategy as the formulation of interdependent decisions that when combined together drive superior performance. To evaluate the tension between testing interdependent and independent decisions, I first conduct an exploratory analysis of 31,716 business experiments run on using the web experimentation platform, Optimizely. Contrary to popular wisdom, not only does testing a larger set of interdependent decisions in an experiment associate with breakthrough performance, but it also associates with reduced performance failure. To understand why firms vary in whether they test interdependent decisions, I find that cheaper testing leads firms to test experiments with fewer interdependent decisions. In contrast, when testing becomes more expensive, I find that firms increase interdependent decisions per experiment. This suggests a potential solution to alleviate an organization’s cognitive limits when experimenting: by restricting testing resources, firms can focus on testing interdependent decisions that have the potential to deliver outstanding performance. Overall, my findings demonstrate the underappreciated value of interdependent decisions and its performance benefits for business experimentation.
Faculty Advisor(s): J. Rivkin, N/A, R. McDonald, and S. Thomke
Curriculum Vitae   |  Website   |  Email
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