George Georgiadis Kellogg

CV  |  Publications  |  Working Papers |  Teaching 

Associate Professor of Strategy
Kellogg School of Management
Northwestern University

Curriculum Vitae

Research Interests
Microeconomic Theory, Organization Economics, Industrial Organization

Contact Information
Kellogg School of Management
Office 4223
2211 Campus Drive
Evanston, IL 60208


Short Bio

    I am an applied microeconomic theorist with a focus on organizational economics and industrial organization. My recent research aims to understand how the design of incentives affects the behaviors of individuals in various settings, and develop insights that organizations can use to optimize their incentive systems.
    At Kellogg, I teach Strategy and Organizations (STRT 452), an elective MBA course on organizational economics, which aims to offer a micro-economic approach to both the internal organization of firms and its relationship with their rivals' overall strategies. Topics include incentive pay, decentralization (e.g., transfer pricing and coordination issues), horizontal mergers, and vertical integration.

Working Papers / Work in Progress

  • Optimal Monitoring Design  [Slides]
    with Balazs Szentes
    Econometrica, Accepted.
    Featured in: Kellogg Insight

    Abstract: This paper considers a Principal-Agent model with hidden action in which the Principal can monitor the Agent by acquiring independent signals conditional on effort at a constant marginal cost. The Principal aims to implement a target effort level at minimal cost. The main result of the paper is that the optimal information-acquisition strategy is a two-threshold policy and, consequently, the equilibrium contract specifies two possible wages for the Agent. This result provides a rationale for the frequently observed single-bonus wage-contracts.

  • Optimal Feedback in Contests  [Slides]
    with Jeffrey Ely, Sina Moghadas Khorasani, and Luis Rayo

    Abstract: We derive optimal contests for environments where contestants can strategically time their effort and their output takes the form of breakthroughs. Whether or not the designer is able to provide real-time feedback to contestants, the optimal prize allocation is egalitarian: all agents who have succeeded in a pre-specified time interval share the prize equally. When providing feedback is possible, the optimal contest takes a stark cyclical form: contestants are fully appraised of their own success, and at the end of each fixed-length cycle, they are informed about peer success as well.

  • Working to Learn  [Slides]  (Updated July 2020)
    with Drew Fudenberg and Luis Rayo

    Abstract: We study the joint determination of wages, effort, and training in "apprenticeships" where novices must work in order to learn. We introduce the idea of learning-by-doing as an inequality constraint, which allows masters to strategically slow training down. Every Pareto-efficient contract has an initial phase where the novice learns as fast as technologically feasible, followed by a phase where their master constrains how fast they learn. This latter phase mitigates the novice's commitment problem, and thus lets the novice consume more than they produce early on in the relationship. Our model also has novel implications for optimal regulation.

  • Optimal Project Design  [Slides]  (Updated July 2020)
    with Daniel Garrett, Alex Smolin, and Balazs Szentes

    Abstract: This paper considers a moral hazard model with (i) a risk-neutral agent and (ii) limited liability. Prior to interacting with the principal, the agent can choose the production technology, which is a specification of the agent's cost of generating each output distribution with support in [0,1]. After observing the production technology, the principal offers a wage scheme and then the agent implements a distribution over outputs. First, we show that there is an optimal design involving only binary distributions on {0,1}; that is, the cost of any other distribution is prohibitively high. Then, we characterize the equilibrium technology defined on the binary distributions and show that the equilibrium payoff of both the principal and the agent is 1/e. A notable feature of the equilibrium is that the principal is indifferent between offering the equilibrium bonus rewarding output one and anything less than that. Finally, the analysis of the model is shown to generalize to the case where the agent is risk averse.

  • A/B Contracts  [Slides]  (Updated May 2020)
    with Michael Powell
    American Economic Review, Revise & Resubmit.
    Featured in: Kellogg Insight

    Abstract: This paper aims to improve the practical applicability of the classic theory of incentive contracts under moral hazard. We establish conditions under which the information provided by an A/B test of incentive contracts is sufficient for answering the question of how best to improve a status quo incentive contract, given a priori knowledge of the agent's monetary preferences. We assess the empirical relevance of this result using data from DellaVigna and Pope's (2017) study of a variety of incentive contracts. Finally, we discuss how our framework can be extended to incorporate additional considerations beyond those in the classic theory.

  • The Absence of Attrition in the War of Attrition under Complete Information  (Updated June 2020)
    with Youngsoo Kim and Dharma Kwon

    Abstract: We consider a two-player game of war of attrition under complete information. It is well-known that this class of games admits equilibria in pure, as well as mixed strategies, and much of the literature has focused on the latter. We show that if the players' payoffs whilst in "war" vary stochastically and their exit payoffs are heterogeneous, then the game admits Markov Perfect equilibria in pure strategies only. This is true irrespective of the degree of randomness and heterogeneity, thus highlighting the fragility of mixed-strategy equilibria to a natural perturbation of the canonical model. In contrast, when the players' flow payoffs are deterministic or their exit payoffs are homogeneous, the game admits equilibria in pure and mixed strategies.


Teaching & Lecture Notes