Numerical Dynamic Programming on Parallel Computing Clusters : A 'MacGyver' Approach

Economists who want to numerically approximate an elaborate dynamic stochastic programming problem (DSPP), either for structural estimation or policy evaluation purposes, are often confined by the curse of dimensionality: richer models with various state and control variables cannot be solved on standard pc's in reasonable time. Parallel computation offers a back door to escape from this dilemma (see e.g. Rust (1996). In this note, I illustrate how such a parallel computation can be implemented by applied economists using simple household items. Specifically, I present a simple Mathematica code to approximate a canonical DSPP on a parallel computing cluster. My code achieves a significant reduction in computation time relative to the standard serial solution, is very intuitive and can easily be extended to the most complicated problems