Hello, and welcome back. People often associate decision making with reaching agreements. Especially to people raised in a more consensual environment, such as me as a good citizen, reaching an agreement is often associated with fair and providing to everyone. But why would decision making follow a path that leads to an outcome that is the best to all of us. Perhaps, decision making follows a different logic. An individual may choose what is best for her, and therefore collectively, they may not reach an agreement. In this module, I provide some of the tools to understand why this might be. And therefore introduce you to decision making in a rational choice tradition. Let's start with an example. The police catch two suspects of a crime and bring them to the station for further interrogation. Both suspects are being separated and asked whether the other one was involved in the crime. What to do? For it is well know prisoner's dilemma, the tools of game theory come in very handy. The decision making situation can be represented with a matrix in which we distinguish the two suspects as players. Each player has two options, which are called strategies. These are to deny the other's involvement, or to accuse him or her. Using these strategies lead to outcomes which are the four cells of the matrix. Each cell or outcome is associated with a payoff, which expresses the utility ranking of an outcome by the players. The first number refers to Player 1. The second number refers to Player 2. In the case of the dilemma, the players are best off not to accuse the other. The total utility of the first outcome is highest for both, that is four in total. This is called the social or Pareto optimum of the game, which is often associated with the values such as fairness or in the case of both suspects, splitting the spoils. However, this optimum is not the equilibrium in behavior. To find this equilibrium, we make use of the so called Nash equilibrium concept. This concept indicates that equilibrium exists when each player makes his or her best choice given the choice of the other player. In other words, in equilibrium, none of the players wants to change his or her choice. Going back to our matrix, Player 2 wants to change if Player 1 plays Deny. In that case, accusing 1 would get 2 off the hook and make them go to jail. This provides 2 with the higher payoff of 3, while 1 gets a lower payoff of 0. However, Player 1 makes a similar assessment when Player 2 plays Deny. Accusing 2 would get 1 off the hook, and make 2 go to jail. In the end, both will accuse the other suspect, which is the outcome. This is the Nash equilibrium in which both go to jail, providing an individual payoff of one. The total payoff is two, lower than four in the Pareto optimum states. This example shows nicely, that for group behavior, a behavioral equilibrium should not be confused with a Pareto optimum. The best for us is not necessarily the decision making outcome based on individual behavior. In the literature, various alternative theories have been suggested to circumvent this unpleasant outcome to both suspects. Institutions or socialization have been offered as ways to change this game and to force or guide players to choose and come closer to the better outcome. Still temptation, as suggested by the original game, remains lurking around the corner. To analyze decision making situations, we will occasionally use tools similar to our business dilemma game. We're going to use the spatial theory of preferences. Players are assumed to have a continuous set of options represented with an issue dimension, like in the figure. At the same time, these options are evaluation in terms of utility. Which is added as the vertical dimension in our figure. We also assume that preferences are single peaked, that is players have one most preferred position or ideal point on the issue dimension. This is the point the player prefers most. From this point, utility is continuously decreasing with distance, the further a point is, the lower is its utility. In the case of symmetric preferences, this makes the bell shaped curve as indicated in the figure. Based on any points, we can define a preferred to this point set, or a preference set in short. For point x, this set includes all points that are, in utility terms, better than x. In the figure, these are all points between x and the utility terms. It's equivalent point is x prime. x prime is also called the point of a player. For a group of players, like presented in the next figure, the tools help us to identify what these three players can do, if they have to agree on a new policy together. A decision can be made by a consensus or unanimity, so every player has a veto. Because we use this decision rule, these players are called veto players. Given some initial state of affairs of status quo q, these different preference sets can be drawn. Only when all agree, a policy can be adopted. In that case, the smallest preference set will determine the collective preferred two sets, or win set. This is the set indicated by U, that is based on unanimity. Only proposals in the unanimity set U will be accepted by all. Any proposal outside U will be rejected by one of the players, which means that there is no agreement on the adoption of such a proposal. This noting becomes clear when zooming in to the preference set of the first veto player. This player prefers all points in the green area to the status quo. This means that the proposal P1 which is outside the set is not preferred. This player will veto it. A proposal P2, however is preferred, it will not be vetoed, such a proposal will be adopted. Of course, the logic is based on the existing status quo. If the status quo changes, the preference set will change and also the win sets. In this video, a basic feature of decision making has been explained. And some of the tools to analyze it have been introduced. It is another theoretical pillar of this course stands on. The next video is about European policy process. Let's have a look at that.
