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- Kim, Youngdae
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Solving Stochastic Dynamic Programming Problems: A Mixed Complementarity Approach
- Issued Date
- 2020-03
- Citation
- COMPUTATIONAL ECONOMICS, v.55, no.3, pp.925 - 955
- Abstract
- We present a mixed complementarity problem (MCP) formulation of continuous state dynamic programming problems (DP-MCP). We write the solution to projection methods in value function iteration (VFI) as a joint set of optimality conditions that characterize maximization of the Bellman equation; and approximation of the value function. The MCP approach replaces the iterative component of projection based VFI with a one-shot solution to a square system of complementary conditions. We provide three numerical examples to illustrate our approach.
- Publisher
- SPRINGER
- ISSN
- 0927-7099
- Keyword (Author)
- Computable general equilibrium, Complementarity, Computational methods, Dynamic Programming
- Keyword
- EQUILIBRIUM, GAMS, MODELS
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