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- 2008613005 abstract "This paper studies adaptive learning in economic environments subject to recurring structural change. Stochastically evolving institutional and policy-making features can be described by regime-switching rational expectations models whose parameters evolve according to a finite state Markov process. We demonstrate that in non-linear models of this form, two natural schemes emerge for learning the conditional means of endogenous variables: under mean value learning, the equilibrium's lag structure is assumed exogenous and therefore known to agents; whereas, under vector autoregession learning (VAR learning), the equilibrium lag structure depends endogenously on agents' beliefs and must be learned. We show that an intuitive condition, analogous to the 'Long-run Taylor Principle' of Davig and Leeper (2007), ensures convergence to a regime-switching rational expectations equilibrium. However, the stability of sunspot equilibria, when they exist, depends on whether agents adopt mean value or VAR learning. Coordinating on sunspot equilibria via a VAR learning rule is not possible. These results show that, when assessing the plausibility of rational expectations equilibria in non-linear models, out of equilibrium behavior is important.".
- 2008613005 contributor B11371424.
- 2008613005 contributor B11371425.
- 2008613005 contributor B11371426.
- 2008613005 created "[2007]".
- 2008613005 date "2007".
- 2008613005 date "[2007]".
- 2008613005 dateCopyrighted "[2007]".
- 2008613005 description "Includes bibliographical references.".
- 2008613005 description "Mode of access: World Wide Web.".
- 2008613005 description "System requirements: Adobe Acrobat Reader.".
- 2008613005 description "This paper studies adaptive learning in economic environments subject to recurring structural change. Stochastically evolving institutional and policy-making features can be described by regime-switching rational expectations models whose parameters evolve according to a finite state Markov process. We demonstrate that in non-linear models of this form, two natural schemes emerge for learning the conditional means of endogenous variables: under mean value learning, the equilibrium's lag structure is assumed exogenous and therefore known to agents; whereas, under vector autoregession learning (VAR learning), the equilibrium lag structure depends endogenously on agents' beliefs and must be learned. We show that an intuitive condition, analogous to the 'Long-run Taylor Principle' of Davig and Leeper (2007), ensures convergence to a regime-switching rational expectations equilibrium. However, the stability of sunspot equilibria, when they exist, depends on whether agents adopt mean value or VAR learning. Coordinating on sunspot equilibria via a VAR learning rule is not possible. These results show that, when assessing the plausibility of rational expectations equilibria in non-linear models, out of equilibrium behavior is important.".
- 2008613005 hasFormat "Also available in print.".
- 2008613005 identifier RWP07-09v2.htm.
- 2008613005 isFormatOf "Also available in print.".
- 2008613005 isPartOf "RWP ; 07-09".
- 2008613005 issued "2007".
- 2008613005 issued "[2007]".
- 2008613005 language "eng".
- 2008613005 publisher "Kansas City [Mo.] : Research Division, Federal Reserve Bank of Kansas City,".
- 2008613005 relation "Also available in print.".
- 2008613005 requires "Mode of access: World Wide Web.".
- 2008613005 requires "System requirements: Adobe Acrobat Reader.".
- 2008613005 subject "E-stability ; adaptive learning ; regime switching ; sunspots".
- 2008613005 subject "HB1".
- 2008613005 title "Adaptive learning in regime-switching models [electronic resource] / William A. Branch, Troy Davig, Bruce McGough.".
- 2008613005 type "text".