Showing 1 - 10 of 22
We study how the use of judgement or “add-factors” in macroeconomic forecasting may disturb the set of equilibrium outcomes when agents learn using recursive methods. We isolate conditions under which new phenomena, which we call exuberance equilibria, can exist in standard macroeconomic...
Persistent link: https://www.econbiz.de/10011604601
adaptive learning. We reconsider this issue and analyze the full set of solutions for the linearized model. Our main focus is … learning if agents can utilize contemporaneous data. However, in an economy populated by a mixture of agents, some of whom only …
Persistent link: https://www.econbiz.de/10010298287
(X), provided F´(X)> 1. We show that there exist Markov SSEs that are E-stable, and therefore locally stable under adaptive learning …
Persistent link: https://www.econbiz.de/10011398793
We consider the stability under adaptive learning of the complete set of solutions to the model when . In addition to … representation used by agents in the learning process. Only the finite-state Markov sunspot solutions can be stable under learning. …
Persistent link: https://www.econbiz.de/10011398912
structure, forecasts, and adaptive learning rules affect the conditions for convergence of adaptive learning towards rational …
Persistent link: https://www.econbiz.de/10011541172
stable under adaptive learning, taking the form of noisy finite state Markov processes at resonant frequencies. For a range …
Persistent link: https://www.econbiz.de/10011408407
We study the properties of generalized stochastic gradient (GSG) learning in forward-looking models. We examine how the … conditions for stability of standard stochastic gradient (SG) learning both differ from and are related to E-stability, which … governs stability under least squares learning. SG algorithms are sensitive to units of measurement and we show that there is …
Persistent link: https://www.econbiz.de/10010261355
We study the properties of generalized stochastic gradient (GSG) learning in forward-looking models. We examine how the … conditions for stability of standard stochastic gradient (SG) learning both differ from and are related to E-stability, which … governs stability under least squares learning. SG algorithms are sensitive to units of measurement and we show that there is …
Persistent link: https://www.econbiz.de/10013318147
adaptive learning. We reconsider this issue and analyze the full set of solutions for the linearized model. Our main focus is … learning if agents can utilize contemporaneous data. However, in an economy populated by a mixture of agents, some of whom only …
Persistent link: https://www.econbiz.de/10013319951
structure, forecasts, and adaptive learning rules affect the conditions for convergence of adaptive learning towards rational …
Persistent link: https://www.econbiz.de/10013320362