Various Applications of Game Theories in Macro and Micro Economics - Literature review Example

Game theory Introduction Game theory is a branch of economics that is concerned with assessing strategies for dealing with situations that are termed competitive and in cases where the action of one of the participants will be affected by a decision form the other participants. Game theory has been applied in economics. Game theory entails understanding the ways in which interactive choices of economic agents produce outcomes in relation to the utilities of those agents and where the results in question might have been planned by none of the participants. Game theory is considered a science of strategy. It seeks to determine logically and mathematically the actions taken by players in order to secure the best results for themselves in a wide variation of games. The outcome of each agent depends on the strategies of all the individuals. For example, in the zero sum games, the players’ interests tend to conflict totally so that the gains of an individual leads to another individual’s loss. More typical examples are potential gains with mutual harm and gains as well as some conflicts. The paper will discuss various applications of game theories in macro and micro economics (Mas-Colell et al, 12). Simultaneous-move games with complete information  Dominance and Nash equilibrium  Nash equilibrium is an expression utilized in game theory to describe equilibrium where the strategy of each player is best possible given the strategies of all the other players. Nash equilibrium exists in situations where there is no unilateral profitable deviation from the participants who were involved. Nash equilibrium is self enforcing with players having no desire to move to the next step since they will be worse off. Nash equilibrium often takes place in cases where there are no unilateral profitable deviations from any of the participants involved (Kuhn et al, 21). Equilibrium refinements and mixed strategies Game theory deals with decisions arrived at by different people in varying interaction situations. As opposed to other multi-persons decision theories; this one has two main distinguishing characteristics. First is the explicit consideration of strategies available from different persons and the possible outcome that may appear as a result of combining their choices. That majorly takes place in a complete detailed type of game. The other feature is focusing on optimal individual choice which is done separately. In this case an individual’s choice is optimal if a person’s expected utility of outcome is maximized (Bolton, Patrick and Mathias, 29). A mixed strategy is a probability assignment to each pure strategy. It enables the participants to randomly a strategy that is considered pure. There are often numerous strategies available for the participants since the probability is continuous. It is a strategy that is made up of a possible move and a probability distribution that corresponds to how frequently the moves are played. A player would only utilize a mixed strategy when she is indifferent between various pure strategies and when keeping the opponent guessing and when the opponent has advantage of getting to know the next move (Fudenberg, Drew, and Jean Tirole, 16). . Simultaneous-move games with incomplete information  Bayesian Nash equilibrium Bayesian Nash equilibrium is often defined as a strategy beliefs and profiles that are specified for each participant about the types of the participants who maximizes the payoff that is expected for each player with concerns about the beliefs of the other players. The results often yield a lot of equilibrium in the dynamic games when no further restrictions target the beliefs of the players. The approach therefore makes Bayesian Nash equilibrium is a mean that can be utilized to analyze dynamic games that are related to incomplete information (Bolton, Patrick and Mathias, 31). Participants in Bayesian Nash equilibrium often take turns sequentially and not in simultaneous manner. Implausible equilibrium often takes place in the same manner that Bayesian Nash equilibrium takes place in games of complete and perfect information such as promises and incredible threats. Such equilibrium can be eliminated by in complete and perfect information by employing sub game perfect Nash equilibrium. In order to apply the equilibrium that is often generated by Nash equilibrium solution sub games and concepts, one has to employ the Perfect Nash equilibrium. Application: auctions  Nash equilibrium is a game theory concept in which the optimal results of the game is one in which no player has an incentive to deviate from their chosen strategy after the choice of the opponent is put into consideration. Assuming that the other player’s remains stagnant towards their strategies, a participant can obtain no incremental benefits from the changing actions. A game may present various Nash equilibria or none at all. In order to test this type of equilibria, the strategy of each participant has to be revealed to all the players. Nash equilibria can only exist in situations where the players do not change their strategy despite getting to know the actions of their competitors or their opponents. An example involves Sam and Tom in which all the players are allowed to choose (Salanié, 24). A may receive one dollar while B may lose the same dollar. Logically both players decide to choose the first strategy and end up receiving a payoff of one dollar. If the strategy of tom is reveled to Sam, no player will be able to deviate from the original the first choice. Getting to identify the strategy of another player does not change the behavior or mean less. The Nash equilibrium is represented by A, A. Tom Sam Sequential-move games with complete information Sub-game perfect Nash equilibrium is a type of equilibrium such that the strategies of the participants constitute Nash equilibrium in every original game’s sub game. It is an iterative process for dealing with sequential games and extensive forms which may be found by backward induction. The first step is often associated with determining the most favorable strategy of the participant who makes the last move towards the game (Mas-Colell et al, 46). Then, the best action of the second to last moving player is often determined by focusing the action of the player. The process often continues in backwards in time until the actions of the participants have been determined. Subgame perfect equilibrium is usually considered a refinement of the Nash equilibrium that is often utilized in dynamic games. A strategy profile is said to be a sub game perfect equilibrium in cases where it represents Nash equilibrium of every original game’s sub game. Informally, it means that if the behavior of the participant is a sub game perfect equilibrium of the bigger game or the participants played any lesser game that consisted of only a single part of the larger game, then their behavior is considered a sub game perfect Nash equilibrium. Backward induction is a common method of determining sub game perfect equilibria. The last action of the game is often considered in order to determine the actions that should be taken by the final mover in order to maximize the utility of the participant (Salanié, 27). The process is often continued until an individual arrives at the 1st move of the game. Backward inductions cannot be employed to games of incomplete and imperfect actions since it entails cutting through information sets that are considered non-singleton. The game often satisfies one-shot deviation principle. Repeated games and applications  Repeated game offers a quite general and formal framework to examine why participants who are self interested manage to cooperate in a relationship that is considered long term. Repeated games often refer to a model class where the same set of participants repeatedly plays the same equal game known as stage game over a long infinite, typically time horizon (Mas-Colell et al, 37). In dissimilarity to the situation where the participant interacts only once, any outcome that is mutual beneficial can be sustained as equilibrium when the participants interact frequently and repeatedly. Sequential-move games with incomplete information  Perfect Bayesian equilibrium  Perfect Bayesian equilibrium was made-up to help refine Bayesian Nash Equilibrium in a manner that is equal to how sub game perfect Nash equilibrium refines the perfect Nash equilibrium. The first player often chooses among the 3 actions; R, M and L, id the first player chooses L then the game is completed without the move by the second player. If the first player chooses R and M, the second player learns that L was not chosen and then chooses between R and M after which the game ends (Salanié, 22). The payoffs will be offered in extensive manner. Job market signaling, cheap talk Signaling in game theory is the idea in which one party or participant credibly conveys some ideas about itself to other participants. In the job market signaling model, employees convey signals about their ability level to the owner by acquiring certain education by acquiring certain educational credentials (Mas-Colell et al, 41). The concept of signaling is often associated with transfer of information from one of the participant to the other. The agent is the party that is involved in transmitting the information. The party that evaluates and receives the information is often considered to be the principle. Adverse Selection and Mechanism Design  Monopoly screening  In applying game theory to the behavior of companies we can suggest that companies face a number of strategic choices that govern their ability to achieve pay-offs that is desired. Decisions on output and price such as whether to hold, lower, and rise. Monopolistic screening entails optimal contract cannot extract all surpluses from the other participants. The type that values insurance the most, gets the one that complete insurance (Fudenberg, Drew, and Jean Tirole, 14). Application: screening in the market for insurance  Screening focuses on identifying eligibility criteria for a program that is beneficial. The intensity of screening can be observed as a policy measure. In economics and contract theory, information asymmetry is associated with the study of decisions in transaction where one participant has more information than the other individuals. This develops an imbalance of transactional power, which can lead to the transaction going awry. Examples of such problems are moral hazard, adverse selection and informational monopoly. Information asymmetry leads to misinformation and is significant in any communicational process. In adverse selection, the ignorant participants lack information while negotiating an understanding to the transaction, where as in moral hazard the ignorant party lacks information on lack of performance or inadequate ability to retaliate for the breach of agreement (Mas-Colell et al, 28). Moral hazard and the principal-agent problem Moral hazard in economics occurs when an individual takes more risks because another individual bears the weight of those risks. A moral hazard often takes place when the action of one participant may change to the disadvantageous of another participant after a monetary transaction takes place. Moral hazard takes place under a type of informational irregularity. Moral hazard often arises in a principle-agent problem, where a certain participant, called an agent, acts on the behalf of another individual called a principle. The participants often have more data about their intentions and actions than the principle does, since the principle often cannot completely check the participants. The participant often has an enticement to act inappropriately if the interests of the principle and the agent are not aligned (Salanié, 21). Work cited Bolton, Patrick, and Mathias Dewatripont. Contract theory. MIT press, 2010. Fudenberg, Drew, and Jean Tirole. "Game theory mit press." Cambridge, MA (2011): 86. Kuhn, Harold W. "Introduction to John von Neuman and Oskar Morgensterns Theory of Games and Economic Behavior." (2009). Mas-Colell, Andreu, Michael Dennis Whinston, and Jerry R. Green. Microeconomic theory. Vol. 1. New York: Oxford university press, 2013. Salanié, Bernard. The economics of contracts: a primer. MIT press, 2011. Read More