Learning with Bounded Memory in Stochastic Models
AbstractThere exists by now a sizeable literature that studies the dynamics of adaptive learning in stochastic macroeconomic models. A common starting point is to postulate that economic agents use standard econometric techniques to estimate the unknown parameters of the stochastic process of the relevant variables and forecast the future values using these estimated parameter values. A feature of learning is that, in the limit, agents are assumed to have access to an infinite amount of data. Our goal here, by contrast, is to analyze finite memory rules in stochastic economic models. We consider a wide variety of macroeconomic models, both linear and nonlinear, where agents are learning steady states. We study some basic issues here. Does the state of the economy have some invariant distribution in the long run? Is there convergence of the moments of the forecast? What is the influence of memory length on the residual variance of these forecasts? What can one say about these moments in nonlinear models? We provide answers to these questions for the models we analyze.
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Bibliographic InfoPaper provided by Society for Computational Economics in its series Computing in Economics and Finance 1999 with number 221.
Date of creation: 01 Mar 1999
Date of revision:
Other versions of this item:
- Seppo Honkapohja & Kaushik Mitra, . "Learning with Bounded Memory in Stochastic Models," Discussion Papers 00/42, Department of Economics, University of York.
- Honkapohja, S. & Mitra, K., 1999. "Learning with Bounded Memory in Stochastic Models," University of Helsinki, Department of Economics 456, Department of Economics.
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search, Learning, and Information
- E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
- E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
This paper has been announced in the following NEP Reports:
- NEP-ALL-1999-07-12 (All new papers)
- NEP-ETS-1999-07-12 (Econometric Time Series)
- NEP-EVO-1999-07-12 (Evolutionary Economics)
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