Adaptive and statistical expectations in a renewable resource market

Ilaria Foroni, Laura Gardini () and J. Barkley Rosser

Mathematics and Computers in Simulation (MATCOM), 2003, vol. 63, issue 6, 541-567

Abstract: Rational expectations models have increasingly been replaced by models with various forms of learning. This paper studies the global dynamics of a model of renewable resource markets due to Hommes and Rosser [Macroecon. Dyn. 5 (2001) 180] under adaptive and statistical learning systems. The statistical learning system is seen to generate greater complexity of the structures of the basins of attraction, especially at higher discount rates. An element of particular interest is that bifurcations generating lobes in the basins arise from particular focal points, associated with prefocal sets at infinity on the Poincaré equator in the statistical learning model.

Keywords: Adaptive models; Statistical learning; Fishery models; Complex basins; Global bifurcations (search for similar items in EconPapers)
JEL-codes: C62 D83 D84 E31 E32 M30 (search for similar items in EconPapers)
Date: 2003
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Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:63:y:2003:i:6:p:541-567

DOI: 10.1016/S0378-4754(03)00063-6

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