This paper offers an introduction to game theory for applied economists. I try to give simple definitions and intuitive examples of the basic kinds of games and their solution concepts. There are four kinds of games: static or dynamic, and complete or incomplete information. ( Complete information means there is no private information.) The corresponding solution concepts are: Nash equilibrium in static games of complete information; backwards induction (or subgame-perfect Nash equilibrium) in dynamic games of complete information; Bayesian Nash equilibrium in static games with incomplete information; and perfect Bayesian (or sequential) equilibrium in dynamic games with incomplete information. The main theme of the paper is that these solution concepts are closely linked. As we consider progressively richer games, we progressively strengthen the solution concept, to rule out implausible equilibria in the richer games that would survive if we applied solution concepts available for simpler games. In each case, the stronger solution concept differs from the weaker concept only for the richer games, not for the simpler games.
Source: Robert Gibbons, 1997. "An Introduction to Applicable Game Theory," NBER Technical Working Papers 0199, National Bureau of Economic Research, Inc.
Game theory is a big interest to a lot of people, mainly because they know it's powerful and complicated. However, I think that introductions like Gibbons' are useful for getting this across to a lot of smart people. Follow the citations of this paper and you'll get a wonderful tour of modern applied game theory.
