Benhabib, Jess. <br/><br/>
Learning, Large Deviations and Rare Events / 
Jess Benhabib, Chetan Dave. 
 - Cambridge, Mass.  National Bureau of Economic Research  2011. 
 - 1 online resource:  illustrations (black and white); 
 - NBER working paper series  no. w16816 .
 - Working Paper Series (National Bureau of Economic Research)  no. w16816. .
<br/><br/> February 2011. 
<br/><br/> 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 distribution even though the model is driven by thin tailed exogenous stochastic processes. We characterize these large deviations that are driven by sequences of consistently low or consistently high shocks. We then apply our model to the canonical asset-pricing model. We demonstrate that the tails of the stationary distribution of the price-dividend ratio will follow a power law. 
<br/><br/>
<br/><br/><br/>System requirements: Adobe [Acrobat] Reader required for PDF files. <br/>Mode of access: World Wide Web.