Abstract:
We propose a method for solving continuous-state and action-stochastic dynamic programs that is a hybrid between the continuous space projection methods introduced by Judd and the discrete space methods introduced by Bellman. Our hybrid approach yields a smooth representation of the value function while preserving the computational simplicity of discrete dynamic programming. Our method is especially well suited for implementation in a vector processing environment such as MATLAB or GAUSS, and makes it possible to automate the setup and solution of continuous space dynamic programs in a way that previously seemed elusive.
More papers in Computing in Economics and Finance 1999 from Society for Computational Economics Address: CEF99, Boston College, Department of Economics, Chestnut Hill MA 02467 USA Contact information at EDIRC. Series data maintained by Christopher F. Baum ().
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