BIO

I am a Post-Doctoral Associate in the Division of Social Sciences at New York University Abu Dhabi (NYUAD). Previously, I obtained my PhD in Social Sciences from California Institute of Technology and MS in Quantitative Economics from Indian Statistical Institute (Delhi). My research interests lie in the field of microeconomic theory, with a focus on mechanism design, contest design, matching, and social choice.

RESEARCH

Working papers

  • Contest design with a finite type-space: A unifying approach
    (with Andrzej Baranski)

    We study the classical contest design problem of allocating a budget across different prizes to maximize effort in a finite type-space environment. For any contest, we characterize the unique symmetric equilibrium. In this equilibrium, different agent types mix over contiguous intervals so that more efficient agents always exert greater effort than less efficient agents. We then solve for the expected equilibrium effort, investigate the effect of increasing competition under linear costs, and identify conditions under which this effect persists under general costs. As a result, we find that the winner-takes-all contest is optimal under linear and concave costs. Lastly, we obtain an equilibrium convergence result for the continuum type-space, and since the finite type-space encompasses the complete information environment as a special case, our analysis offers a unified approach to studying contests in these classical environments.

  • Optimality of weighted contracts for multi-agent contract design with a budget
    (with Wade Hann-Caruthers)
    Ext. abs. in Proc. of EC 2024

    We study a contract design problem between a principal and multiple agents. Each agent participates in an independent task, in which it may exert costly effort towards improving its probability of success, and the principal has a fixed budget which it can use to provide outcome-dependent rewards to the agents. Assuming the principal cares only about maximizing the agents' probabilities of success, and not how much of the budget it expends, we characterize the Pareto frontier of success probability profiles that can be implemented in Nash equilibrium as equilibria of successful-get-everything contracts. An immediate consequence of this result is that piece-rate contracts and bonus-pool contracts, two types of contracts which are well-studied and motivated in the literature on multi-agent contract design, are never optimal in this setting. We then identify a natural subclass called priority-based weighted contracts which we show is actually sufficient to implement the Pareto frontier, thus providing a significant reduction in the dimensionality of the principal's optimal contract design problem. Finally, we solve the design problem for the special case with two agents and quadratic costs where our results suggest that the structure of the optimal contract depends primarily on the bias in the principal's objective and is, to some extent, robust to the heterogeneity in the agents' cost functions.

  • Optimal grading contests
    Ext. abs. in Proc. of EC 2023
    R&R at Games and Economic Behavior

    We study the design of grading contests between agents with private information about their abilities under the assumption that the value of a grade is determined by the information it reveals about the agent’s productivity. Towards the goal of identifying the effort-maximizing grading contest, we study the effect of increasing prizes and increasing competition on effort and find that the effects depend qualitatively on the distribution of abilities in the population. Consequently, while the optimal grading contest always uniquely identifies the best performing agent, it may want to pool or separate the remaining agents depending upon the distribution. We identify sufficient conditions under which a rank-revealing grading contest, a leaderboard-with-cutoff type grading contest, and a coarse grading contest with at most three grades are optimal. In the process, we also identify distributions under which there is a monotonic relationship between the informativeness of a grading scheme and the effort induced by it.

  • Project selection with partially verifiable information
    (with Wade Hann-Caruthers)
    Ext. abs. in Proc. of WINE 2022
    R&R at Mathematical Social Sciences

    We study a principal-agent project selection problem with asymmetric information. The principal must choose exactly one of $N$ projects, each defined by the utility it provides to the principal and to the agent. The agent knows all the utilities, and the principal can commit to a mechanism (without transfers) that maps the agent's report about the utilities to a chosen project. Unlike the typical literature, which assumes the agent can lie arbitrarily, we examine the principal's problem under partial verifiability constraints. We characterize the class of truthful mechanisms under a family of partial verifiability constraints and study the principal's problem for the specific cases of no-overselling and no-underselling. Our results suggest significant benefits for the principal from identifying or inducing such partial verifiability constraints, while also highlighting the simple mechanisms that perform well.

Publications

  • Stable allocations in discrete exchange economies
    (with Federico Echenique and SangMok Lee)
    Journal of Economic Theory

    We study stable allocations in an exchange economy with indivisible goods. The problem is well-known to be challenging, and rich enough to encode fundamentally unstable economies, such as the roommate problem. Our approach stems from generalizing the original study of an exchange economy with unit demand and unit endowments, the housing model. Our first approach uses Scarf's theorem, and proposes sufficient conditions under which a ``convexify then round'' technique ensures that the core is nonempty. The upshot is that a core allocation exists in categorical economies with dichotomous preferences. Our second approach uses a generalization of the TTC: it works under general conditions, and finds a solution that is a version of the stable set.

  • Optimal tie-breaking rules
    (with Amit Goyal)
    Journal of Mathematical Economics

    We consider two-player contests with the possibility of ties and study the effect of different tie-breaking rules on effort. For ratio-form and difference-form contests that admit pure-strategy Nash equilibrium, we find that the effort of both players is monotone decreasing in the probability that ties are broken in favor of the stronger player. Thus, the effort-maximizing tie-breaking rule commits to breaking ties in favor of the weaker agent. With symmetric agents, we find that the equilibrium is generally symmetric and independent of the tie-breaking rule. We also study the design of random tie-breaking rules that are unbiased ex-ante and identify sufficient conditions under which breaking ties before the contest actually leads to greater expected effort than the more commonly observed practice of breaking ties after the contest.

  • Optimality of the coordinate-wise median mechanism for strategyproof facility location in two dimensions
    (with Wade Hann-Caruthers)
    Ext. abs. in Proc. of SAGT 2022
    Social Choice and Welfare

    We consider the facility location problem in two dimensions. In particular, we consider a setting where agents have Euclidean preferences, defined by their ideal points, for a facility to be located in \(\mathbb{R}^2\). We show that for the p-norm (\(p \geq 1\)) objective, the coordinate-wise median mechanism (CM) has the lowest worst-case approximation ratio in the class of deterministic, anonymous, and strategyproof mechanisms. For the minisum objective and an odd number of agents \(n\), we show that CM has a worst-case approximation ratio (AR) of \(\sqrt{2}\frac{\sqrt{n^2+1}}{n+1}\). For the p-norm social cost objective (\(p\geq 2\)), we find that the AR for CM is bounded above by \(2^{\frac{3}{2}-\frac{2}{p}}\). We conjecture that the AR of CM actually equals the lower bound \(2^{1-\frac{1}{p}}\) (as is the case for \(p=2\) and \(p=\infty\)) for any \(p\geq 2\).

TEACHING

Instructor at NYU Abu Dhabi

  • ECON-UH 2010: Intermediate Microeconomics (Spring 2024)

Instructor at Econschool

Econschool is an initiative to assist undergraduate students in India who wish to pursue higher studies in Economics. As an instructor, I've taught a course on mathematics for economists and also helped with the development and delivery of various online resources.

Teaching Assistant at Caltech

  • Ec 122: Econometrics
  • Ec 11: Introduction to economics [edX]
  • BEM 103: Introduction to finance
  • PS/Ec 172: Game theory [notes]
  • Ec 121A: Theory of value [notes]
  • CS/Ec 149: Algorithmic economics [notes]