Using Polynomial Approximations to Solve Stochastic Dynamic Programming Problems: or A “Betty Crocker” Approach to SDP. Richard Howitt ^ , Siwa Msangi ^ , Arnaud Reynaud t , and Keith Knapp * 07/18/02 Abstract In this paper we put forward an easy-to-implement methodology for solving deterministic or stochastic dynamic programming problems within a standard optimization package such as GAMS. We’ve found the use of orthogonal polynomials to be especially helpful in implementing approximation methods for iterative computation of the infinite-horizon value function, due to their superior convergence properties over standard polynomials. We demonstrate this the properties of this methodology by application to both a standard neo-classical growth model and a natural resource management problem. Keywords: Dynamic Programming, Computational Economics, Approximation Theory, Natural Resource Management ^ Department of Agricultural and Resource Economics, University of California at Davis. t Department of Agricultural and Resource Economics, University of California at Davis and LEERNA- INRA, University of Social Sciences Toulouse. *Department of Environmental Science, University of California at Riverside