Statistical Learning With Time-Varying Parameters
AbstractIn their landmark paper, Bray and Savin note that the constant-parameters model used by their agents to form expectations is misspecified and that, using standard econometric techniques, agents may be able to determine the time-varying nature of the model s parameters. Here, we consider the same type of model as employed by Bray and Savin except that our agents form expectations using a perceived model with parameters that vary with time. We assume agents use the Kalman filter to form estimates of these time-varying parameters. We find that, under certain restrictions on the structure of the stochastic process and on the value of the stability parameter, the model will converge to its rational expectations equilibrium. Further, the restrictions on the stability parameter required for convergence are identical to those found by Bray and Savin.
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Bibliographic InfoArticle provided by Cambridge University Press in its journal Macroeconomic Dynamics.
Volume (Year): 7 (2003)
Issue (Month): 01 (February)
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- J. Huston McCulloch, 2005. "The Kalman Foundations of Adaptive Least Squares: Applications to Unemployment and Inflation," Computing in Economics and Finance 2005 239, Society for Computational Economics.
- Berardi, Michele & Galimberti, Jaqueson K., 2013.
"A note on exact correspondences between adaptive learning algorithms and the Kalman filter,"
Elsevier, vol. 118(1), pages 139-142.
- Michele Berardi & Jaqueson K. Galimberti, 2012. "A note on exact correspondences between adaptive learning algorithms and the Kalman filter," Centre for Growth and Business Cycle Research Discussion Paper Series 170, Economics, The Univeristy of Manchester.
- James B. Bullard & Jacek Suda, 2008.
"The stability of macroeconomic systems with Bayesian learners,"
2008-043, Federal Reserve Bank of St. Louis.
- Bullard, J.B. & Suda, J., 2011. "The Stability of Macroeconomic Systems with Bayesian Learners," Working papers 332, Banque de France.
- Carravetta, Francesco & Sorge, Marco M., 2013. "Model reference adaptive expectations in Markov-switching economies," Economic Modelling, Elsevier, vol. 32(C), pages 551-559.
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