We examine the role of generalized constant gain stochastic gradient (SGCG) learning in generating large deviations of an endogenous variable from its rational expectations value. We show analytically that these large deviations can occur with a frequency associated with a fat tailed...

In this paper we provide an explicit characterization of the escape dynamics for the Phellps problem of government controlling inflation with adaptive learning of the approximate Phillips curve, alternative to the one considered by Cho, Williams and Sargent (2002) (CWS in sequel). Our approach...

In this paper we provide an explicit characterization of the escape dynamics for the Phellps problem of government controlling inflation with adaptive learning of the approximate Phillips curve, alternative to the one considered by Cho, Williams and Sargent (2002) (CWS in sequel). Our approach...

We use a continuous-time approximation approach to analyze dynamics of a model where government adaptively learns the Phillips curve while running monetary policy (Phellps problem). This approach is based on approximating the discrete-time dynamics with learning by a limiting continuous-time...

In this paper we provide explicit characterization of the escape dynamics for the Phellps problem of government controlling inflation with adaptive learning of the approximate Phillips curve, alternative to the one considered by Cho, Williams and Sargent (2002). Our approach is based on...

We study the extent to which self-referential adaptive learning can explain stylized asset pricing facts in a general equilibrium framework. In particular, we analyze the effects of recursive least squares and constant gain algorithms in a production economy and a Lucas type endowment economy....

In this paper we consider regression models with forecast feedback. Agents' expectations are formed via the recursive estimation of the parameters in an auxiliary model. The learning scheme employed by the agents belongs to the class of stochastic approximation algorithms whose gain sequence is...

This paper identifies two channels through which the economy can generate endogenous inflation and output volatility, an empirical regularity, by introducing model uncertainty into a Lucas-type monetary model. The equilibrium path of inflation depends on agents' expectations and a vector of...

We study the extent to which self-referential adaptive learning can explain stylized asset pricing facts in a general equilibrium framework. In particular, we analyze the effects of recursive least squares and constant gain algorithms in a production economy and a Lucas type endowment economy....

This paper develops an adaptive learning formulation of an extension to the Ball, Mankiw and Reis (2005) sticky information model that incorporates endogenous inattention. We show that, following an exogenous increase in the policymaker's preferences for price vs. output stability, the learning...