A Stochastic Lake Game

W. Davis Dechert

No 264, Computing in Economics and Finance 2001 from Society for Computational Economics

Abstract: In this paper we extend the deterministic model of Dechert and Brock (forthcoming) to stochastic models. First, we consider the lake game in a Brock and Mirman framework and show what happens to the Skiba point when there is uncertainty in the model. Second, we develop the model as an optimally controlled Markov process following the style of Easley and Kiefer (Econometrica 1988). In this case the lake parameters are unknown and have to be learned over time. When a Skiba point is present, learning affects the estimation problem of the parameters in that it may not be optimal to gather information about the lake when the system might be close to the (unknown) Skiba point.

Keywords: Skiba point; stochastic dynamic programming (search for similar items in EconPapers)
JEL-codes: C73 Q25 Q26 Q28 (search for similar items in EconPapers)
Date: 2001-04-01
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sce:scecf1:264

Access Statistics for this paper

More papers in Computing in Economics and Finance 2001 from Society for Computational Economics Contact information at EDIRC.
Bibliographic data for series maintained by Christopher F. Baum ().