Learning, large deviations and rare events
By: Jess Benhabib, Chetan Dave
Contributors: Dave, Chetan; National Bureau of Economic Research
Series: NBER working paper series -- working paper 16816; Working paper series (National Bureau of Economic Research : Online) -- working paper no. 16816.
Publisher: National Bureau of Economic Research
Published: 2011
Place of publication: Cambridge, MA
Language: eng
Format: Electronic resource
Description: "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 pricing models, that have been studied recently in the adaptive learning framework.  The asymptotic distributions of forecasts and endogenous variables are characterized using techniques from linear recursions with multiplicative noise and large deviations, and are shown to exhibit fat tails"--National Bureau of Economic Research web site.
Notes: Title from PDF file as viewed on 5/19/2011.

Includes bibliographical references.

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Mode of access: World Wide Web.