How to Use Decision Theory to Choose Among Mechanisms

We extend a recently introduced approach to the positive problem of game theory, Predictive Game Theory (PGT Wolpert (2008). In PGT, modeling a game results in a probability distribution over possible behavior profiles. This contrasts with the conventional approach where modeling a game results in an equilibrium set of possible behavior profiles. We analyze three PGT models. Two of these are based on the well-known quantal response and epsilon equilibrium concepts, while the third is entirely new to the economics literature. We use a Cournot game to demonstrate how to use our extension of PGT, concentrating on model combination, modeler uncertainty, and mechanism design. In particular, we emphasize how PGT allows a modeler to perform prediction and mechanism design in a manner that is fully consistent with decision theory. We do this even in situations where conventional approaches yield multiple equilibria, an ability that is necessary for a fully decision theoretic mechanism design. Where possible, PGT results are compared against equilibrium set analogs.

Optimal Assignment of Durable Objects to Successive Agents

This paper analyzes the assignment of durable objects to successive generations of agents who live for two periods. The optimal assignment rule is stationary, favors old agents and is determined by a selectivity function which satisfies an iterative functional differential equation. More patient social planners are more selective, as are social planners facing distributions of types with higher probabilities for higher types. The paper also characterizes optimal assignment rules when monetary transfers are allowed and agents face a recovery cost, when agents' types are private information and when agents can invest to improve their types.Dynamic Assignment ; Durable Objects ; Revenue Management ; Dynamic Mechanism Design ; Overlapping Generations ; Promotions and Intertemporal Assignments

Implementation Theory

This surveys the branch of implementation theory initiated by Maskin (1977). Results for both complete and incomplete information environments are covered

Government intervention in production and incentives theory : a review of recent contributions

Includes bibliographical references.Work supported by the National Science Foundation, the Commissariat Général du Plan, and the Center for Energy Policy Research at M.I.T.by B. Caillaud ... [et. al.]

Formulation of tradeoffs in planning under uncertainty

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1988.Includes bibliographical references.by Michael Paul Wellman.Ph.D

Optimal Use of Labour Market Policies

Labour market policies for the unemployed combine passive income support with active measures that aim at improving jobseekers' employment prospects. This paper extends the theoretical framework developed by Pavoni and Violante (2005a) for the optimal choice between different active and passive policies for the unemployed to a setting which allows for the use of a job search assistance programme that affects the exit rate to employment by raising search effectiveness but not productivity in the job. These programmes are one of the most widely used activation measures in OECD countries and should, therefore, be taken into account when considering the optimal design of labour market policies. The enriched model allows to answer a wide range of interesting policy questions. It is used to assess the optimality of the West German policy in the period 2000-2002 as well as the benefits from introducing tight monitoring. It is shown that sizeable budget savings could have been realised by switching to the optimal scheme, but that the net gains from monitoring are only small. In addition, some interesting results on the optimal use of job search assistance and training are derived. It is shown that existing policies already share some but not all features of the optimal scheme.Unemployment insurance, active labour market policies, recursive contracts, job search, human capital

Examination of planning under uncertainty algorithms for cooperative unmanned aerial vehicles

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2005.Includes bibliographical references (p. 121-124).(cont.) of UAVs and targets. Additionally, sensitivity trials are used to capture each algorithm's robustness to real world planning environments where planners must negotiate incomplete or inaccurate system models. The mission performances of both methods degrade as the quality of their system models worsenCooperation is essential for numerous tasks. Cooperative planning seeks actions to achieve a team's common set of objectives by balancing both the benefits and the costs of execution. Uncertainty in action outcomes and external threats complicates this task. Planning algorithms can be generally classified into two categories: exact and heuristic. In this thesis, an exact planner, based on Markov decision processes, and a heuristic, receding horizon controller are evaluated in typical planning problems. The exact planner searches for an optimal policy with global contingencies, while the heuristic controller sequentially approximates the global plans over local horizons. Generally, the two planners trade mission and computational performance. Although the results are limited to specific problem instances, they provide characterizations of the algorithms' capabilities and limitations. The exact planner's policy provides an optimal course of action for all possible conditions over the mission duration; however, the algorithm consumes substantial computational resources. On the other hand, the heuristic approach does not guarantee optimality, but may form worthy plans without evaluating every contingency. On a fully-observable battlefield, the planners coordinate a team of unmanned aerial vehicles (UAVs) to obtain a maximum reward by destroying targets. Stochastic components, including UAV capability and attrition, represent uncertainty in the simulated missions. For a majority of the examined scenarios, the exact planner exhibits statistically better mission performance at considerably greater computational cost in comparison to the heuristic controller. Scalability studies show that these trends intensify in larger missions that include increasing numbersby Rikin Bharat Gandhi.S.M

Robust optimization, game theory, and variational inequalities

Thesis (Ph. D.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2005.Includes bibliographical references (p. 193-109).We propose a robust optimization approach to analyzing three distinct classes of problems related to the notion of equilibrium: the nominal variational inequality (VI) problem over a polyhedron, the finite game under payoff uncertainty, and the network design problem under demand uncertainty. In the first part of the thesis, we demonstrate that the nominal VI problem is in fact a special instance of a robust constraint. Using this insight and duality-based proof techniques from robust optimization, we reformulate the VI problem over a polyhedron as a single- level (and many-times continuously differentiable) optimization problem. This reformulation applies even if the associated cost function has an asymmetric Jacobian matrix. We give sufficient conditions for the convexity of this reformulation and thereby identify a class of VIs, of which monotone affine (and possibly asymmetric) VIs are a special case, which may be solved using widely-available and commercial-grade convex optimization software. In the second part of the thesis, we propose a distribution-free model of incomplete- information games, in which the players use a robust optimization approach to contend with payoff uncertainty.(cont.) Our "robust game" model relaxes the assumptions of Harsanyi's Bayesian game model, and provides an alternative, distribution-free equilibrium concept, for which, in contrast to ex post equilibria, existence is guaranteed. We show that computation of "robust-optimization equilibria" is analogous to that of Nash equilibria of complete- information games. Our results cover incomplete-information games either involving or not involving private information. In the third part of the thesis, we consider uncertainty on the part of a mechanism designer. Specifically, we present a novel, robust optimization model of the network design problem (NDP) under demand uncertainty and congestion effects, and under either system- optimal or user-optimal routing. We propose a corresponding branch and bound algorithm which comprises the first constructive use of the price of anarchy concept. In addition, we characterize conditions under which the robust NDP reduces to a less computationally demanding problem, either a nominal counterpart or a single-level quadratic optimization problem. Finally, we present a novel traffic "paradox," illustrating counterintuitive behavior of changes in cost relative to changes in demand.by Michele Leslie Aghassi.Ph.D

Essays in labor economics

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Economics, 2011.Cataloged from PDF version of thesis.Includes bibliographical references.This dissertation consists of three chapters on topics in labor economics. In the first chapter, I present a model in which firms under-invest in hiring novice workers because they don't receive the full benefit of discovering novice talent. A firm must pay a cost to hire a novice worker. When it does, it obtains both labor services and information about the worker's productivity. This information has option value as a productive novice can be rehired. However, if competing firms also observe the novice's productivity, the option value of hiring accrues to the worker, not the employer. Firms will accordingly under-invest in discovering novice talent unless they can claim the benefit from doing so. I test this model's relevance in an online labor market by hiring 952 workers at random from an applicant pool of 3,767 for a 10-hour data entry job. In this market, worker performance is publicly observable. Consistent with the model's prediction, novice workers hired at random obtained significantly more employment and had higher earnings than the control group, following the initial hiring spell. A second treatment confirms that this causal effect is likely explained by information revelation rather than skills acquisition. Providing the market with more detailed information about the performance of a subset of the randomly-hired workers raised earnings of high-productivity workers and decreased earnings of low-productivity workers. Due to its scale, the experiment significantly increased the supply of workers recognized as high-ability in the market. This outward supply shift raised subsequent total employment and decreased average wages in occupations affected by the experiment (relative to non-treated occupations), implying that it also increased the sum of worker and employer surplus. Under plausible assumptions, this additional total surplus exceeds the social cost of the experiment. In the second chapter, I estimate the sensitivity of students' college application decisions to a small change in the cost of sending standardized test scores to colleges. In 1997, the ACT increased the number of free score reports it provided to students from three to four, maintaining a $6 marginal cost for each additional report. In response to this$6 cost change, ACT-takers sent more score reports and applications, while SAT-takers did not. ACT-takers also widened the range of colleges to which they sent scores. I show that students' response to the cost change is inconsistent with optimal decision-making but instead suggests that students use rules of thumb to make college application decisions. Sending additional score reports could, based on my estimates, substantially increase low-income students' future earnings. In the third chapter, I analyze the effects of the Tennessee Education Lottery Scholarships, a broad-based merit scholarship program that rewards students for their high school achievement with college financial aid. Since 1991, over a dozen states, comprising approximately a quarter of the nation's high school seniors, have implemented similar merit scholarship programs. Using individual-level data from the ACT exams, I find that the program did not achieve one of its stated goals, inducing more students to prefer to stay in Tennessee for college, but it did induce large increases in performance on the ACT. This suggests that policies that reward students for performance affect behavior and may be an effective way to improve high school achievement.by Amanda Dawn Pallais.Ph.D