Decision Theory in Econometrics∗

The decision-theoretic approach to statistics and econometrics explicitly specifies a set of models under consideration, a set of actions that can be taken, and a loss function that quantifies the value to the decision-maker of applying a particular action when a particular model holds. Decision rules, or procedures, map data into actions, and can be ordered according to their Bayes, minmax, or minmax regret risks. In complicated decision problems, large sample approximations can be used to approximate the decision problem by a simpler one which is easier to solve. Some examples of applications of decision theory in econometrics are discussed