This chapter is devoted to a more detailed examination of game theory. Game theory is an important tool for analyzing strategic behavior, is concerned with how individuals make decisions when they recognize that their actions affect, and are affected by, the actions of other individuals or groups. Strategic behavior recognizes that the decision-making process is frequently mutually interdependent. Game theory is the study of the strategic behavior involving the interaction of two or more individuals, teams, or firms, usually referred to as players. Two game theoretic scenarios were examined in this chapter: Simultaneous-move and multi-stage games. In simultaneous-move games the players effectively move at the same time. A normal-form game summarizes the players, possible strategies and payoffs from alternative strategies in a simultaneous-move game. Simultaneous-move games may be either noncooperative or cooperative. In contrast to noncooperative games, players of cooperative games engage in collusive behavior. A Nash equilibrium, which is a solution to a problem in game theory, occurs when the players’ payoffs cannot be improved by changing strategies. Simultaneous-move games may be either one-shot or repeated games. One-shot games are played only once. Repeated games are games that are played more than once. Infinitely-repeated games are played over and over again without end. Finitely-repeated games are played a limited number of times. Finitely-repeated games have certain or uncertain ends.

An Introduction to Game Theory

We develop a model of matching with contracts which incorporates, as special cases, the college admissions problem, the Kelso-Crawford labor market matching model, and ascending package auctions. We introduce a new "law of aggregate demand" for the case of discrete heterogeneous workers and show that, when workers are substitutes, this law is satisfied by profit-maximizing firms. When workers are substitutes and the law is satisfied, truthful reporting is a dominant strategy for workers in a worker-offering auction/matching algorithm. We also parameterize a large class of preferences satisfying the two conditions.,

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Matching with Contracts

The concept of fair division is as old as civil society itself Aristotle's "equal treatment of equals" was the first step toward a formal definition of distributive fairness The concept of collective welfare, more than two centuries old, is a pillar of modern economic analysis Reflecting fifty years of research, this book examines the contribution of modern microeconomic thinking to distributive justice Taking the modern axiomatic approach, it compares normative arguments of distributive justice and their relation to efficiency and collective welfare The book begins with the epistemological status of the axiomatic approach and the four classic principles of distributive justice: compensation, reward, exogenous rights, and fitness It then presents the simple ideas of equal gains, equal losses, and proportional gains and losses The book discusses three cardinal interpretations of collective welfare: Bentham's "utilitarian" proposal to maximize the sum of individual utilities, the Nash product, and the egalitarian leximin ordering It also discusses the two main ordinal definitions of collective welfare: the majority relation and the Borda scoring method The Shapley value is the single most important contribution of game theory to distributive justice A formula to divide jointly produced costs or benefits fairly, it is especially useful when the pattern of externalities renders useless the simple ideas of equality and proportionality The book ends with two versatile methods for dividing commodities efficiently and fairly when only ordinal preferences matter: competitive equilibrium with equal incomes and egalitarian equivalence The book contains a wealth of empirical examples and exercises

Fair Division and Collective Welfare

Game-theoretic analysis of cooperation among supply chain agents: Review and extensions

Preliminary Definitions, Results and Motivation Stable Matching Problems: The Stable Marriage Problem: An Update SM and HR with Indifference The Stable Roommates Problem Further Stable Matching Problems Other Optimal Matching Problems: Pareto Optimal Matchings Popular Matchings Profile-Based Optimal Matchings.

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Algorithmics of Matching Under Preferences

https://ddd.uab.cat/pub/worpap/2007/hdl_2072_3645/67106.pdf

Constrained school choice

The literature on school choice assumes that families can submit a preference list over all the schools they want to be assigned to. However, in many real-life instances families are only allowed to submit a list containing a limited number of schools. Subjects' incentives are drastically affected, as more individuals manipulate their preferentes. Including a safety school in the constrained list explains most manipulations. Competitiveness across schools plays an important role. Constraining choices increases segregation and affects the stability and efficiency of the final allocation. Remarkably, the constraint reduces significantly the proportion of subjects playing a dominated strategy.

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Constrained School Choice: An Experimental Study

31 pages, 18 tables.-- JEL classification: C72, C78, D78, I20.-- Trabajo publicado como articulo en American Economic Review 100(4): 1860-1874 (2010).-- http://dx.doi.org/10.1257/aer.100.4.1860

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Constrained school choice: an experimental study

https://www.barcelonagse.eu/sites/default/files/working_paper_pdfs/117.pdf

Stable matchings and preferences of couples

We experimentally investigate in the laboratory prominent mechanisms that are employed in school choice programs to assign students to public schools and study how individual behavior is influenced by preference intensities and risk aversion. Our main results show that (a) the Gale–Shapley mechanism is more robust to changes in cardinal preferences than the Boston mechanism independently of whether individuals can submit a complete or only a restricted ranking of the schools and (b) subjects with a higher degree of risk aversion are more likely to play “safer” strategies under the Gale–Shapley but not under the Boston mechanism. Both results have important implications for enrollment planning and the possible protection risk averse agents seek.

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Flip Klijn

Papers

Constrained school choice

Constrained School Choice: An Experimental Study

Constrained school choice: an experimental study

Stable matchings and preferences of couples

Preference intensities and risk aversion in school choice: a laboratory experiment