Research

This paper studies how firms strategically manage a portfolio of supplier relationships to improve contracting outcomes. Using novel data from a buyer-supplier network in Indian manufacturing, I analyze a setting where the buyer uses a dynamic, tier-based policy to promise future business as a reward for better performance on quality checks. To quantify the value of this system, I estimate a dynamic principal-agent model with an endogenous set of competing suppliers. The model disentangles the policy’s dual purpose: it overcomes adverse selection by sorting suppliers based on persistent type, and it mitigates moral hazard by using relational value and induced competition to incentivize effort. I find that the estimated policy improves outcomes by 10% relative to random allocation, with 60% of this gain driven by selection and 40% by incentives. While the optimal policy in this setting can yield a 25% gain in outcomes relative to random allocation, the value of the current policy alone is substantial: to achieve the same improvement in outcomes via a linear monetary bonus in a series of one-off interactions, the buyer must pay a bonus of 1.6 times a supplier’s average order benefit. These findings show that governing relationships collectively, through the strategic allocation of business, is a powerful mechanism for creating value.

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How do firms adapt to ensure supply chain resilience? The typical answer, vertical integration, is limited in practice by its high costs and inflexibility. This paper introduces partial integration, defined as targeted buyer interventions across firm boundaries, as an effective alternative. Using novel daily timeline data from Indian manufacturing supply chains, we show that supplier underinvestment in key inputs, stemming from working capital constraints and noncontractibilities in input use, is the primary driver of supply chain disruptions. To overcome these issues, buyers exert control over supplier processes—through in-person monitoring, contingent contracts, and direct sourcing of raw materials—rather than merely advancing cash. This buyer involvement escalates as disruption risk increases: an unanticipated input cost shock leads to direct buyer control of inputs for the most constrained suppliers. We develop a three-stage model that rationalizes these strategies, which clarifies that buyers control input decisions to prevent resource diversion due to noncontractibility. The model predicts that relational buyers with low monitoring and sourcing costs enjoy a comparative advantage in fostering resilient trade with poor regions.

(with Vishan Nigam)

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This paper studies interest rate cap regulations in Kenya, which affected rates differentially across providers, to illustrate strategic borrower behavior and its interaction with market power. Using administrative data from a lending platform exempt from the caps, we show that regulation increased borrowing on this (more expensive) platform, but largely from high-risk borrowers. Strategic savings and other borrowing behavior, which affects credit limits, also adjusted accordingly: on the exempt platform, low-risk individuals saved less while high-risk individuals saved more. We also show that the lender responds by decreasing credit limits for high-risk borrowers and raising credit limits more for the low-risk borrowers.

(with Tavneet Suri and Prashant Bharadwaj)

Many economic decision-makers today rely on learning algorithms for important decisions. This paper shows that a widely used learning algorithm—ε-Greedy—exhibits emergent risk aversion, favoring actions with lower payoff variance. When presented with actions of the same expectated payoff, under a wide range of conditions, ε-Greedy chooses the lower-variance action with probability approaching one. This emergent preference can have wide-ranging consequences, from inequity to homogenization, and holds transiently even when the higher-variance action has a strictly higher expected payoff. We discuss two methods to restore risk neutrality. The first method reweights data as a function of how likely an action is chosen. The second method employs optimistic payoff estimates for actions that have not been taken often.

(with Andreas Haupt)

Games and Economic Behavior (2024) | Link

We characterize ex-post implementable allocation rules for single object auctions under quasi-linear preferences with convex interdependent value functions. We show that requiring ex-post implementability is equivalent to requiring that the allocation rule must satisfy a condition that we call eventual monotonicity (EM), which is a weakening of monotonicity, a familiar condition used to characterize dominant strategy implementation.

(with Saurav Goyal)

Games and Economic Behavior (2023) | Link

This paper studies single-peaked domains where the designer is uncertain about the underlying alignment according to which the domain is single-peaked. The underlying alignment is common knowledge amongst agents, but preferences are private knowledge. Thus, the state of the world has both a public and private element, with the designer uninformed of both. I first posit a relevant solution concept called implementation in mixed information equilibria, which requires Nash implementation in the public information and dominant strategy implementation in the private information given the public information. I then identify necessary and sufficient conditions for social rules to be implementable. The characterization is used to identify unanimous and anonymous implementable social rules for various belief structures of the designer, which basically boils down to picking the right rules from the large class of median rules identified by Moulin (1980), and hence this result can be seen as identifying which median rules are robust to designer uncertainty.

Social Choice and Welfare (2023) | Link 

The coverage probability of a user in a mmwave system depends on the availability of line-of- sight paths or reflected paths from any base station. Many prior works modelled blockages using random shape theory and analyzed the SIR distribution with and without interference. While it is intuitive that the reflected paths do not significantly contribute to the coverage (because of longer path lengths), there are no works which provide a model and study the coverage with reflections. In this paper, we model and analyze the impact of reflectors using stochastic geometry. We observe that the reflectors have very little impact on the coverage probability.

IEEE Global Communications Conference (2017) | Link

The literature generally associates markups to products or firms, conceptualizing them as being attributes that are unrelated to the composition of the firms or the people selling those products. We aim to show that, in fact, who is running the firms can have substantial explanatory power for the markups that are set for these products. We estimate a Two Way Fixed Effects (TWFE) model of firm markups on CEO and firm dummies. We calculate markups using the De Loecker et al. (2020) framework, and match markups to executives by year. After applying some state-of-the-art bias correction procedures and accounting for multiplicity of connected sets (see Best et al. (2023), Kline et al. (2020), and Bonhomme et al. (2023)), we obtain estimates that show a 10-15% variance share for CEO effects on markups.

(with Kartik Vira)

This project studies the role of information sharing in an undifferentiated goods industry where an intermediary charges its members a fee for the collection, aggregation, and dissemination of their detailed production data to each other. We make two main contributions. First, we show that volatility in the market can force firms in a competitive market to subscribe to the intermediary. Once there is enough subscription to the intermediary, a self-sustaining collusive equilibrium can form. Thus, large demand shocks can cause a shift from a competitive market to a collusive regime in the presence of an intermediary, even in the absence of explicit agreements. Second, we device empirical tests to separately identify conduct and information sharing, along with an application to the poultry industry. 

(with Lia Petrose)