My research interests lie in microeconomic theory, industrial organization, and behavioral economics.

Economics (with)[note]:
  • (JMP) Competition and spatial efficiency (with Rebekah Dix) [a unification of three papers on the same agenda]

    • Optimizing spatial allocations: an implementation of Lloyd’s algorithm
      Computing optimal spatial allocations is important for two reasons. First, one may want to implement an optimal spatial allocation. For instance, when ride-sharing/sourcing firms use self-driving vehicles, they want to position those vehicles optimally to minimize wait-times for customers. Second, without a sense of an optimal spatial allocation, it is difficult to evaluate the efficiency of an observed spatial allocation. To compute near-optimal spatial allocations, I develop a numerical algorithm related to Lloyd's algorithm, which finds evenly-spaced sets of points in subsets of Euclidean spaces. While more commonly used in computer science and electrical engineering, Lloyd’s algorithm's underlying logic of reaching optimality through iterated local optimization is equally appropriate in the context of optimizing spatial allocations.

    • Measuring spatial inefficiency (with Rebekah Dix)
      We define a measure of spatial deadweight loss by comparing spatial allocations to optimized ones with the same cardinality. We then measure spatial deadweight loss empirically for several cases studies: allocations of gas stations on Interstate I90; and allocations of supermarkets, hospitals, and fire stations in each of Chicago, Atlanta, and Los Angeles. Contrary to intuition, our results suggest that competition may yield relatively inefficient spatial allocations.

    • Experimental evidence of myopia in dynamic spatial games (with Rebekah Dix)
      We offer a brief review of equilibrium analyses on games of spatial competition to highlight the associated challenges: non-robustness of equilibria to technical assumptions, multiplicity, non-existence, and intractability. We also pose an open question in computational geometry, maximizing a Voronoi region, and show how solving this problem is a necessary step towards extending equilibrium analysis to two-dimensional games of spatial competition. Given these challenges, we argue in favor of pursuing agent-based models, which could require strong behavioral assumptions. We test in an experiment the validity of a particular behavioral assumption, that agents optimize myopically, that would facilitate agent-based models. We find it broadly supported. In testing for myopia, we also present a unique experimental design that allows us to observe not only participants’ choices but also the considerations that went into those choices.

  • Please, raise my input prices (with Nathan Grawe) [a note, submitted]
    In this note we explain how and in what circumstances profits might increase with a positive shock to input prices.  Correlations between oil prices and average net farm incomes across commodity types are consistent with the theory and suggest that this paradoxical outcome is relevant in major markets.  We conclude by noting that the paradox could be a consideration in the ongoing consolidation of the agrochemical industry.

  • Determinants of NBA ticket prices (with Ezra Frankel and Emily Walden) [in progress]
    We use Stubhub secondary-market ticket data for NBA games combined with box score data to estimate the determinants of secondary-market NBA ticket prices. In particular, we can identify price impacts for some individual players, e.g. ticket prices are lower in Cavaliers games in which it is known beforehand that LeBron James will not play due to injury or rest. The remaining challenge on this project is identifying a good control for team quality. It can not be solely performance-based as a team's quality jumps discontinuously when trades occurs and in the off-season. But it must also take performances into account and be updated for each game. We continue to work on finding or constructing an appropriate measure.
Other (with)[note/link]: