30418 - COMPUTATIONAL MICROECONOMICS - MODULE 1 (GAME THEORY)

The analysis of decision making is at the heart of economics. Decision can be studied in isolation, taking as given the environment faced by the agent, or in interactive situations, where such environment comprises the decisions of other agents. Decision theory focuses on the study of a single agent. Game theory extends this analysis to the study of interacting agents. All economic theory relies on the methods of decision and game theory. A familiarity with these methods is thus necessary to achieve a thorough theoretical understanding of economic phenomena. The course provides a rigorous introduction to the mathematical tools and the conceptual aspects of the theory of decision and games, with a focus on algorithmic solution procedures.

• Preferences, utility, and rational choice.
• The consumer: choice and demand.
• Choice under risk and uncertainty.
• Exchange economies.
• Introduction to interactive decision theory. Static games.
• Rationalizability: the algorithm of iterated dominance.
• Pure strategy Nash equilibrium, interpretation, existence, derivation.
• Oligopoly.
• Mixed strategy Nash equilibrium, interpretation, existence, algorithmic solution.
• Games with incomplete information: rationalizability and Bayesian equilibrium.
• Dynamic games: strategic form, rational planning.
• Iterated weak dominance, backward and forward induction algorithms.
• Subgame perfect equilibrium.
• Repeated games and collusion.
• Dynamic games with asymmetric or incomplete information.
• Perfect Bayesian equilibrium in signaling games: pooling and separation.

• Express a decision problem with the language and tool of decision theory.
• Express strategic interaction and strategic reasoning with the language and tools of game theory.
• Recognize the basic economic applications of the theory.
• Define and describe the different solution procedures provided by the theory.
• Identify their limitations and applicability.

• Analyze economic situations as decision problems and games.
• Predict behavior in economic situations by solving the game and decision problems that represent them.

• Face-to-face lectures
• Exercises (exercises, database, software etc.)

Students are reguralrly given exercises that illustrate the contents of the course.