John O. Ledyard
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| John O. Ledyard | |
|---|---|
| File:JohnLedyard.jpgJohnLedyard.jpg | |
| Born | April 4, 1940 Detroit, Michigan |
| 🏡 Residence | U.S. |
| 🏳️ Nationality | American |
| 🎓 Alma mater | Purdue University MS (Economics), 1965 PhD (Economics) 1967 Wabash College BA 1963 |
| 💼 Occupation | |
| Known for | Mechanism Design Game Theory Market Design Public Goods and Cooperation Information Aggregation |
John O. Ledyard (born April 4, 1940) is an American economist, the Alan and Lenabelle Davis Professor of Economics and Social Sciences at the California Institute of Technology.[1]
Early life and education[edit]
Ledyard was born on April 4, 1940, in Detroit, Michigan.
Academic career[edit]
He became an assistant professor of Economics at Carnegie-Mellon University in 1967, and then he moved to the Economics Department at Northwestern University in 1969. He was the Sydney G. Harris Professor of Social Sciences at Northwestern until he moved permanently to the Division of the Humanities and Social Sciences at the California Institute of Technology in 1985. He had previously visited Caltech as the Sherman Fairchild Distinguished Scholar during the 1977–78 academic year. he later served as Chairman of the Division of the Humanities and Social Sciences (1992–2002), and currently holds the Alan and Lenabelle Davis Professor of Economics and Social Sciences.[2]
Research[edit]
This section is organized into four distinct parts, as a reflection of the broad range of his research contributions: Mechanism Design; Voting and Elections; Public Goods and Cooperation; and Information Aggregation. Much of his research on public goods, for example, has been very influential in the development of mechanism design theory. His work on information aggregation also has substantial overlap with market design, a key subfield of mechanism design. His political science work on voter turnout addresses classic free-rider incentive problems of public good provision but in the context of electoral competition. While he is widely known and admired as a theorist, his impact in experimental economics is nearly as impressive.
Mechanism Design[edit]
Ledyard made seminal contributions to the filed of mechanism design. He is most well known for the Groves–Ledyard mechanism (Groves and Ledyard, 1977a), where Groves and Ledyard propose a mechanism in an environment with public goods, whose Nash equilibria are Pareto efficient.
In Ledyard (1986), he explores the properties of mechanisms that must be incentive compatible for a broad range of priors.
In Krajbich et al., 2009), Ledyard and his co-authors use physical measurements of the brain to augment standard mechanisms for eliciting valuations of public goods.
Ledyard has a longstanding research interest in the design of mechanisms without side payments, and the relationship between efficiency and equilibrium, depending on whether transfers are feasible. Examples include Ledyard et al. (1996, 1997), Groves and Ledyard (1977b, 1977c), and Ledyard and Palfrey (1994, 2002).
Voting and Elections[edit]
Ledyard's pioneering work applying Bayesian game theory to voting and candidate competition (Ledyard, 1984) was the start of a major development in formal political theory: the explicit modeling of private information in political games. It is now mainstream and leading approach in the field.
Public Goods and Cooperation[edit]
Ledyard has made significant contributions to the theory of public goods. Of his seminal contributions to the theoretical public goods literature, Groves and Ledyard (1977a) characterize a family of Nash-efficient public goods mechanisms, and in doing so, move the theoretical mechanism design literature from impossibility (using the dominant strategy as the solution concept) to positive results, all of which preserve efficiency at the cost of non-manipulability.
In addition to mechanism design under complete information, he has made fundamental contributions to Bayesian games (Ledyard, 1986) and Bayesian mechanism design (Ledyard and Palfrey, 1994, 2007). Using this Bayesian mechanism design approach,
More than three decades before the modern development of the social preference literature in behavioral economics, he analyzed resource allocation in unselfish environments (Ledyard, 1968, 1971).
Information Aggregation[edit]
An area of his applied mechanism design work is Information Aggregation. He is among the first to implement prediction markets to help corporations and governments improve decisions (Hanson et al., 2003).
Honors[edit]
Professor Ledyard’s list of honorary distinctions and service includes an Honorary Degree from Purdue University and being a Fellow of the Econometric Society, a Fellow of the American Academy of Arts and Sciences, a Fellow of the Public Choice Society, and a Fellow of the Society for the Advancement of Economic Theory. He has served on several editorial boards of economics and public choice journals, on advisory committees to the National Science Foundation and other organizations, and as the President of the Public Choice Society.[1]
His research has received numerous recognitions including election as a Fellow of the Econometric Society (1977), a Fellow of the American Academy of Arts and Sciences (1999), a Fellow of the Public Choice Society (2004), and a Fellow of the Society for the Advancement of Economic Theory (2011).[2]
Beyond his many research and teaching contributions, he has served on several editorial boards of economics and public choice journals, on advisory committees to the National Science Foundation and other organizations, and as the President of the Public Choice Society. In particular, he is one of the founding members of the Game Theory Society and has served as a Special Issue Editor for Games and Economic Behavior.[2]
Business[edit]
Publications (selected)[edit]
- Groves, Theodore, Ledyard, he O., 1977a. Optimal allocation of public goods: a solution to the ‘free-rider’ problem. Econometrica 45 (4), 783–809.
- Groves, Theodore, Ledyard, he O., 1977b. Some limitations of demand-revealing processes. Public Choice 29 (2), 107–124.
- Groves, Theodore, Ledyard, he O., 1977c. Some limitations of demand-revealing processes. Reply, Public Choice 29 (2), 139–143.
- Hanson, Robin, Polk, Charles, Ledyard, he O., Ishikida, Takashi, 2003. The policy analysis market: an electronic commerce application of a combinatorial information market. In: Proceedings of the ACM Conference on Electronic Commerce, pp. 272–273.
- Krajbich, Ian, Camerer, Colin, Ledyard, he O., Rangel, Antonio, 2009. Using neural measures of economic value to solve the public goods free-rider problem. Science 326, 596–599.
- Ledyard, he O., 1968. Resource allocation in unselfish environments. Amer. Econ. Rev. 58 (2), 227–237.
- Ledyard, he O., 1971. A convergent pareto-satisfactory non-tatonnement adjustment process for a class of unselfish exchange environments. Econometrica 39 (3), 467–499.
- Ledyard, he O., 1984. The pure theory of large two candidate elections. Public Choice 44, 7–41.
- Ledyard, he O., 1986. The scope of the hypothesis of Bayesian equilibrium. J. Econ. Theory 39, 59–82.
- Ledyard, he O., 1989. Information aggregation in two-candidate elections. In: Ordeshook, Peter (Ed.), Contemporary Contributions to Political Theory. University of Michigan Press.
- Ledyard, he O., 1995. Public goods: a survey of experimental research. In: Kagel, J., Roth, A. (Eds.), Handbook of Experimental Economics. Princeton University Press.
- Ledyard, he O., Noussair, Charles, Porter, David, 1996. The allocation of a shared resource within an organization. Econ. Design 2 (2), 163–192.
- Ledyard, he O., Palfrey, Thomas, 1994. Voting and lottery drafts as efficient public goods mechanisms. Rev. Econ. Stud. 61, 327–355.
- Ledyard, he O., Palfrey, Thomas, 2002. The approximation of efficient public good mechanisms by simple voting schemes. J. Public Econ. 83 (2), 153–171.
- Ledyard, he O., Palfrey, Thomas, 2007. A general characterization of interim efficient mechanisms for independent linear environments. J. Econ. Theory 133, 441–466.
- Ledyard, he O., Porter, David, Rangel, Antonio, 1997. Experiments testing multiobject allocation mechanisms. J. Econ. Manage. Strategy 6 (3), 639–675.
References[edit]
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