Global and Approximate Global Optimality of Myopic Economic Decisions*

A general discrete-time stochastic control model is developed which encompasses many wellknown economic models. In the context of the general model, sufficient conditions are derived for the equivalence and approximate equivalence of myopic (sequential single-period) and global (simultaneous multi-period) expected return maximization. A bound provided for the global return loss resulting from myopic optimization is shown to vary directly with the degree of uncertainty and inversely with the degree of positive correlation in period-by-period returns. Characteristics of intermediate-period return functions which partially order them in terms of final-period expected return performance are clarified. Results are illustrated by portfolio and macro policy model examples.