Finite Horizon Learning
AbstractIncorporating adaptive learning into macroeconomics requires assumptions about how agents incorporate their forecasts into their decision-making. We develop a theory of bounded rationality that we call finite-horizon learning. This approach generalizes the two existing benchmarks in the literature: Euler equation learning, which assumes that consumption decisions are made to satisfy the one-step-ahead perceived Euler equation; and infinite-horizon learning, in which consumption today is determine optimally from an infinite-horizon optimization problem with given beliefs. In our approach, agents hold a finite forecasting/planning horizon. We find for the Ramsey model that the unique rational expectations equilibrium is E-stable at all horizons. However, transitional dynamics can differ significantly depending upon the horizon.
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Bibliographic InfoPaper provided by University of Oregon Economics Department in its series University of Oregon Economics Department Working Papers with number 2010-15.
Date of creation: 14 Nov 2010
Date of revision:
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Planning horizon; Expectations; Learning dynamics;
Other versions of this item:
- Branch, William & Evans, George W & McGough, Bruce, 2012. "Finite Horizon Learning," SIRE Discussion Papers 2012-16, Scottish Institute for Research in Economics (SIRE).
- William Branch & George W. Evans & Bruce McGough, 2012. "Finite Horizon Learning," CDMA Working Paper Series 201204, Centre for Dynamic Macroeconomic Analysis.
- D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
- D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search, Learning, and Information
- E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
- C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
- C62 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Existence and Stability Conditions of Equilibrium
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