✦ LIBER ✦

Efficient representation of state spaces for some dynamic models

✍ Scribed by Gautam Gowrisankaran

Publisher: Elsevier Science
Year: 1999
Tongue: English
Weight: 177 KB
Volume: 23
Category: Article
ISSN: 0165-1889
DOI: 10.1016/s0165-1889(98)00057-8

No coin nor oath required. For personal study only.

✦ Synopsis

Many important economic problems require computation over state spaces that are not hypercubes. Examples include industry models of multi-product di!erentiated product "rms, Bayesian learning problems with noisy signals and real business cycle models with heterogeneous agents. These problems have not been analyzed partly because of the di$culty in e$ciently representing their state spaces on a computer. I develop a representation algorithm for the state spaces of the above problems, which potentially allows them to be solved with computational methods such as dynamic programming. I "nd that using this representation reduces the computation time and space by several orders of magnitude relative to a namK ve representation.

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