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Learning with Heterogeneous Expectations in an Evolutionary World Author info | Abstract | Publisher info | Download info | Related research | Statistics Eran Guse
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This paper studies a game theoretic model where agents choose between two updating rules to predict a future endogenous variable. Agents rationally choose between these predictors based on relative performance. Conditions for evolutionary stability and stability under learning are found for the Nash solutions and corresponding parameter equilibria. Stability conditions are contingent upon parameter values and the initial distribution of heterogeneity. However, when the cost of using the more advanced updating rule is sufficiently large, all agents will asymptotically use the more parsimonious, or Minimum State Variable (MSV), updating rule.
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Paper provided by Society for Computational Economics in its series Computing in Economics and Finance 2004 with number
99.
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Date of creation: 11 Aug 2004Date of revision:
Handle: RePEc:sce:scecf4:99Contact details of provider: Email: Web page: http://comp-econ.org/ More information through EDIRC
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Keywords: Adaptive Learning ; Evolutionary Dynamics ; Heterogeneous Expectations ; Multiple Equilibria ; Rational Expectations. ; Other versions of this item:
Find related papers by JEL classification: C62 - Mathematical and Quantitative Methods - - Mathematical Methods and Programming - - - Existence and Stability Conditions of Equilibrium D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation
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