Peyton Young

Infobox Scientist
name = H. Peyton Young


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field = Economics, Game Theory
work_institution = University of Oxford
alma_mater = Harvard University University of Michigan
doctoral_students = Dean P. Foster Rakesh Vohra
known_for = Evolutionary Game Theory Social Dynamics Learning in Games Distributive Justice
prizes = Fellow of the Econometric Society (1995) Fellow of the British Academy (2007) Lester R. Ford Award, Mathematical Association of America (1976)
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Hobart Peyton Young is an American game theorist known for his seminal contributions to evolutionary game theory and its application to the study of institutional and technological change, as well as the theory of learning in games. He holds the James Meade Professorship in economics at the University of Oxford and is a Professorial Fellow at Nuffield College. He was named a Fellow of the Econometric Society in 1995 and a Fellow of the British Academy in 2007.

Peyton Young is also a Senior Fellow for the Center on Social and Economic Dynamics at the Brookings Institution, an external faculty member at the Santa Fe Institute and Professor of Economics Emeritus as Johns Hopkins University. His term as president of the Game Theory Society began in 2006. [http://www.gametheorysociety.org/membership/officers.html] He has published widely on the evolution of social norms, game theory, bargaining and negotiation, taxation and cost allocation, political representation, voting procedures and distributive justice.

Education and Career

Peyton Young graduated cum laude in General Studies from Harvard University in 1966. He completed a PhD in Mathematics at the University of Michigan in 1970, where he graduated with the Sumner B. Myers thesis prize for his work in combinatorial mathematics.

His first academic post was at the Graduate School of the City University of New York as Assistant Professor and then Associate Professor with tenure, from 1971 to 1977. From 1976 to 1982, Young was Research Scholar and Deputy Chairman of the Systems and Decision Sciences Division at the Institute for Applied Systems Analysis, Austria. He was then appointed Professor of Economics and Public Policy in the School of Public Affairs at the University of Maryland, College Park from 1992 to 1994. Young was Scott & Barbara Black Professor of Economics at the Johns Hopkins University from 1994, until moving to Oxford as James Meade Professor of Economics in 2007.

Contributions

Evolutionary Game Theory

Conventional concepts of dynamic stability, including the "evolutionary stable strategy" concept, identify states from which small once-off deviations are self-correcting. These stability concepts are not appropriate for analyzing social and economic systems which are constantly perturbed by idiosyncratic behavior and mistakes, and individual and aggregate shocks to payoffs. Building upon Freidlin and Wentzell’s (1984) theory of large deviations for continuous time-processes, Dean Foster and Peyton Young (1990) developed the more powerful concept of "stochastic stability": “The stochastically stable set [SSS] is the set of states such that, in the long run, it is nearly certain that the system lies within every open set containing S as the noise tends slowly to zero” [p. 221] . This solution concept created a major impact in economics and game theory after Young (1993) developed a more tractable version of the theory for general finite-state Markov chains. A state is stochastically stable if it attracts positive weight in the stationary distribution of the Markov chain. Young develops powerful graph-theoretic tools for identifying the stochastically stable states.

In an influential book, "Individual Strategy and Social Structure", Young provides a clear and compact exposition of the major results in the field of stochastic evolutionary game theory, which he pioneered. He introduces his model of social interactions called ‘adaptive play.’ Agents are randomly selected from a large population to play a fixed game. They choose a myopic best response, based upon a random sample of past plays of the game. The evolution of the (bounded) history of play is described by a finite Markov chain. Idiosyncratic behavior or mistakes constantly perturb the process, so that every state is accessible from every other. This means that the Markov chain is ergodic, so there is a unique stationary distribution which characterizes the long-run behavior of the process.

The theory is used to show that in 2x2 coordination games, the risk-dominant equilibrium will be played virtually all the time, as time goes to infinity. It also yields a formal proof of Thomas Schelling’s (1971) result that residential segregation emerges at the social level even if no individual prefers to be segregated. In addition, the theory “demonstrates how high-rationality solution concepts in game theory can emerge in a world populated by low-rationality agents” [p. 144] . In bargaining games, Young demonstrates that the Nash (1950) and Kalai-Smorodinsky (1975) bargaining solutions emerge from the decentralized actions of boundedly rational agents without common knowledge.

Social Dynamics

In more recent work, Young has applied these and related techniques to explain spatial patterns in cropsharing contracts in Illinois (Young and Burke 2001), the diffusion of hybrid corn in the United States (Young 2005, 2007a) and the difficulty in screening and motivating hedge-fund managers (Foster and Young 2007). He has also developed the first application of strategic learning to behavioral economics and formal epistemology in a paper titled "Self-Knowledge and Self-Deception" (Young 2007b). Young shows that when an individual takes actions that generate consumption utility but also signal something about the agent’s identity to herself, then "there are very simple situations, involving just two actions and two possible identities, such that, if there is any initial uncertainty about one’s true identity, it will never be resolved even when one has an infinite number of opportunities to act."

Learning in Games

Whereas evolutionary game theory studies the behavior of large populations of agents, the theory of "learning in games" focuses on whether the actions of a small group of players end up conforming to some notion of equilibrium. This is a challenging problem, because social systems are self-referential: the act of learning changes the thing to be learned. There is a complex feedback between a player's beliefs, their actions and the actions of others, which makes the data-generating process exceedingly non-stationary. Young has made numerous contributions to this literature. Foster and Young (2001) demonstrate the failure of Bayesian learning rules to learn mixed equilibria in games of uncertain information, where the distribution of payoffs is not common knowledge. Foster and Young (2003) introduce a learning procedure in which players form an hypothesis of their opponents' strategies, which they occasionally test against past play. By backing off from rationality in this way, Foster and Young develop a more robust learning procedure than Bayesian learning.The entire literature on learning in games is elegantly reviewed in Young's 2004 book, "Strategic Learning and its Limits".

Selected Papers

"The Hedge Fund Game:Incentives, Excess Returns, and Piggy-Backing"(with Dean P. Foster), working paper, University of Oxford,March, 2008.

"Self-Knowledge and Self-Deception", working paper, University of Oxford, December 31, 2007. [Young 2007b]

"Innovation Diffusion in Heterogeneous Populations: Contagion, Social Influence and Social Learning", working paper, University of Oxford, August 21, 2007. [Young 2007a]

"The spread of innovations through social learning," Brookings Institution Center for Social and Economic Dynamics, Working Paper No. 43.

"Learning, Hypothesis Testing, and Nash Equilibrium," (with Dean P. Foster), Games and Economic Behavior, 45 (2003), 73-96.

"On the Impossibility of Predicting the Behavior of Rational Agents," (with Dean P. Foster), Proceedings of the National Academy of Sciences of the USA, 98, no. 22 (2001), 12848-12853.

"Competition and Custom in Economic Contracts: A Case Study of Illinois Agriculture," (with Mary A. Burke), American Economic Review, 91 (2001), 559-573.

"The Evolution of Conventions," Econometrica, 61 (1993), 57-84.

"An Evolutionary Model of Bargaining," Journal of Economic Theory, 59 (1993), 145-168.

"Stochastic Evolutionary Game Dynamics," (with Dean P. Foster), Theoretical Population Biology, 38 (1990), 219-232.

Books

* H. Peyton Young (2004). "Strategic Learning and Its Limits". Oxford UK: Oxford University Press. [http://www.econ.jhu.edu/People/Young/scans/strategiclearning.pdf Contents and introduction.]
*_____ (2001). "Fair Representation", 2nd edition (with M. L. Balinski). Washington, D. C.: The Brookings Institution. [http://www.econ.jhu.edu/People/Young/scans/FairRepresentation.pdf Contents and introduction.]
*_____ (1998). "Individual Strategy and Social Structure: An Evolutionary Theory of Institutions". Princeton, NJ: Princeton University Press. [http://www.econ.jhu.edu/People/Young/scans/IndividualStrategy.pdf Contents and introduction.]
*_____ (1994). "Equity: In Theory and Practice". Princeton NJ: Princeton University Press. [http://www.econ.jhu.edu/People/Young/scans/Equity.pdf Contents and introduction.]

External links

* [http://www.econ.jhu.edu/People/Young/ Young's page at Johns Hopkins] with his [http://www.econ.jhu.edu/People/Young/YoungCV.pdf CV] and full list of [http://www.econ.jhu.edu/People/Young/Publications.html publications] .