Intrinsic heterogeneity in expectation formation
AbstractWe introduce the concept of a Misspecification Equilibrium to dynamic macroeconomics. Agents choose between a list of misspecified econometric models and base their selection on relative forecast performance. A Misspecification Equilibrium is an equilibrium stochastic process in which agents forecast optimally given their choices, with the forecasting model parameters and predictor proportions endogenously determined. For appropriate conditions on the exogenous driving process and the degree of feedback of expectations, the Misspecification Equilibrium will exhibit Intrinsic Heterogeneity. With Intrinsic Heterogeneity more than one misspecified model receives positive weight in the distribution of predictors across agents, even in the neoclassical limit in which only the most successful predictors are used.
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Bibliographic InfoArticle provided by Elsevier in its journal Journal of Economic Theory.
Volume (Year): 127 (2006)
Issue (Month): 1 (March)
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Web page: http://www.elsevier.com/locate/inca/622869
Other versions of this item:
- George Evans & William Branch, 2003. "Intrinsic Heterogeneity in Expectation Formation," Computing in Economics and Finance 2003 312, Society for Computational Economics.
- Bill Branch & George W. Evans, 2003. "Intrinsic Heterogeneity in Expectation Formation," University of Oregon Economics Department Working Papers, University of Oregon Economics Department 2003-32, University of Oregon Economics Department, revised 04 Oct 2004.
- C62 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Existence and Stability Conditions of Equilibrium
- D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search, Learning, and Information
- D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
- E30 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - General (includes Measurement and Data)
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