ABSTRACT
In this chapter I examine in greater detail the basic structure of the generic successive approximation method as it is used in the solution of dynamic programming functional equations. I begin with an investigation of those elements of the successive approximation method that are pivotal in the solution of a nontruncated dynamic programming functional equation, namely convergence and uniqueness. After that I outline in broad terms an alternative method for nontruncated dynamic programming functional equations — which I call truncation method . Then, following a brief discussion on the nature of stationary models, I conclude with an examination of the relation between the generic successive approximation method and the truncation method.
