Chapter 2 Forecasting and Decision Theory When forecasts of the future value of some variable or the probability of some event are used for purposes of ex ante planning or decision making then the preferences opportunities and constraints of the decision maker will all enter into the ex post evaluation of a forecast and the ex post comparison of alternative forecasts. After a presenting a brief review of early work in the area of forecasting and decision theory this chapter formally examines the manner in which the features of an agents decision problem combine to generate an appropriate decision based loss function for that agents use in forecast evaluation. Decision based loss functions are shown to exhibit certain necessary properties and the relationship between the functional form of a decision based loss function and the functional form of the agents underlying utility function is characterized. In particular the standard squared error loss function is shown to imply highly restrictive and not particularly realistic properties on underlying preferences which are not justified by the use of a standard local quadratic approximation. A class of more realistic loss functions (“location dependent loss functions”) is proposed.