"We examine the asymptotic distribution of estimated coefficients and endogenous variables in a dynamic self-referential model when agents learn adaptively using a constant gain stochastic gradient algorithm. The model environment can represent a number of economic models, including asset...

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...

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...

The volatility of growth in U.S. real GDP declined dramatically in the mid-1980s. Viewed through the lens of linear autoregressive models, this phenomenon appears to be the result of a structural break in the innovation process that drives GDP fluctuations. We present an alternative model that...