This book presents the main applied aspects of stochas- tic optimization
in economic models. Stochastic processes and control theory are used
under optimization to illustrate the various economic implications of
optimal decision rules. Unlike econometrics which deals with estimation,
this book emphasizes the decision-theoretic basis of uncertainty
specified by the stochastic point of view. Methods of ap- plied
stochastic control using stochastic processes have now reached an exciti
g phase, where several disciplines like systems engineering, operations
research and natural reso- ces interact along with the conventional
fields such as mathematical economics, finance and control systems. Our
objective is to present a critical overview of this broad terrain from a
multidisciplinary viewpoint. In this attempt we have at times stressed
viewpoints other than the purely economic one. We believe that the
economist would find it most profitable to learn from the other
disciplines where stochastic optimization has been successfully applied.
It is in this spirit that we have discussed in some detail the following
major areas: A. Portfolio models in - finance, B. Differential games
under uncertainty, c. Self-tuning regulators, D. Models of renewable
resources under uncertainty, and ix x PREFACE E. Nonparametric methods
of efficiency measurement. Stochastic processes are now increasingly
used in economic models to understand the various adaptive behavior
implicit in the formulation of expectation and its application in
decision rules which are optimum in some sense.
