BEE3049 Behaviour, Decisions and Markets Miguel A. Fonseca.

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Presentation transcript:

BEE3049 Behaviour, Decisions and Markets Miguel A. Fonseca

Recap Last week we looked at how individuals process new information to update their beliefs about a given process – Bayes’ rule. We also looked at a very simple model of search and saw the implications of different costs of searching for length of search and optimal reservation value.

Games Today we are going to have a look at behaviour in strategic settings. We will look at the fundamental building block of non-cooperative game theory – the Nash equilibrium. We will focus our attention at games where there is more than one equilibrium.

The basics A game is defined by three basic elements: –A set of players: N –A set of strategies: S –A rule (or function), F, that maps strategies to outcomes. Game theory’s objective is to analyse the game’s outcome given a set of preferences. –Traditionally, game theorists assume agents seek to maximise their own payoffs – more on this later.

The basics In particular, game theory is interested in finding outcomes from which players have no incentive to deviate. –i.e. outcomes in which my actions are optimal given what the other players are doing (and vice versa). Such an outcome is a Nash Equilibrium (NE) of a game. –Some games have unique NE; others have many NE.

Example 1 Two farmers rely on water to irrigate their crops. –They rely on a common well for their water supply; –They can extract a high or low amount of water; –Individual profits go up the more water is used; –Extracting too much water is harmful for everyone; How would we model this?

Example 1 N={1,2}; Si = {High, Low}, i = 1, 2. F is displayed along the normal form of the game. This is a classical social dilemma: –Prisoner’s dilemma; –Common Pool Resource game. Player 2 HighLow Player 1 High10, 1020, 5 Low5, 2015, 15

Example 1 The equilibrium is found where players are picking a strategy which maximises their profits, given what their counterparts are doing. –(Low, Low) In this game, there is a dominant strategy: Low In most social dilemmas strategies are strategic substitutes: –Player 2’s best response to a rise (drop) in player 1’s “action” is a drop (rise) in his “action” –Cournot oligopoly shares the same characteristics

Example 2 Take two workers operating in a factory. Their payoff is a function of joint output However each worker has a private cost of effort

Example 2 N={1,2}; Si = {High, Low}, i = 1, 2. F is displayed along the normal form of the game. Player 2 HighLow Player 1 High20, 205, 15 Low15, 510, 10

Example 2 There are two Nash equilibria in pure strategies: –(High, High) and (Low, Low) In this game, strategies are strategic complements: –Player 2’s best response to a rise (drop) in player 1’s “action” is a rise (drop) in his “action”. Which equilibrium should be played?

Coordination Games This particular type of game is interesting to economists as it captures the idea of externalities: –Team production processes (e.g. min. effort game); –Industrial Organisation (e.g. market entry games); It is important to understand why would a set of agents be stuck in “bad” equilibria. –Is this due to strategic or behavioural reasons?

Equilibrium selection Common criteria for equilibrium selection: –Focal points; –Payoff dominance; –Risk dominance.

Focal points Suppose you had to meet up with your classmates to work on a project next Tuesday. You need to set up a time and place in Exeter.

Focal points Suppose you had to meet up with your classmates to work on a project next Tuesday. You need to set up a time and place in Exeter. Thomas Schelling ran a similar thought experiment with his class (the city was NY…) –The majority of people chose Grand Central Station at 12 noon. Certain equilibria are “intuitive” or naturally salient and as a result get chosen more often.

Payoff dominance Payoff dominance is a relatively intuitive concept; If an equilibrium is Pareto superior to all other NE, then it is payoff dominant. –An outcome Pareto-dominates another if all players are at least as well off and at least one is strictly better off. It is intuitively appealing, but the data does not seem to fully support it.

Risk dominance The concept of risk dominance is based upon the idea that a particular equilibrium may be “riskier” than another. –Though players need not be risk averse. In simple 2x2 games, RD could be thought as how costly are deviations from a particular equilibrium vis- à-vis the other? Although rational agents ought to follow payoff dominance, experimental data shows subjects often play the risk dominant (safer) equilibrium.

Risk dominance The general method to calculate risk dominant equilibrium is quite complex. –However, for the class of games we deal with in this class, there is a simple formula we can use. –If R>0, (A,a) is the risk dominant equilibrium. –If R<0, (B,b) is the risk dominant equilibrium. –If R=0, the MSNE is the risk dominant equilibrium.

Obstacles to coordination Larger N –The concept of coordination centres around beliefs –The choice of equilibrium will depend on what you think the other player will do. –The more players there are, the harder it is to coordinate: it is harder to form consistent beliefs about every player’s action – it only takes one player to destroy the equilibrium. Incentive structure –Are equilibria unfair? –Are there focal points? Does communication help? –Cooper et al. (1992)

Cooper et al. (1992) Run a simple coordination experiment. Vary the extent subjects can communicate with one another: –No communication; –One-way (non-binding) announcements; –Two-way (non-binding) announcements.

Cooper et al. (1992)