000			02112cam a22003377 4500
001			w16816
003			NBER
005			20211020110944.0
006			m o d
007			cr cnu||||||||
008			210910s2011 mau fo 000 0 eng d
100	1		_aBenhabib, Jess. _96017
245	1	0	_aLearning, Large Deviations and Rare Events / _cJess Benhabib, Chetan Dave.
260			_aCambridge, Mass. _bNational Bureau of Economic Research _c2011.
300			_a1 online resource: _billustrations (black and white);
490	1		_aNBER working paper series _vno. w16816
500			_aFebruary 2011.
520	3		_aWe 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.
530			_aHardcopy version available to institutional subscribers
538			_aSystem requirements: Adobe [Acrobat] Reader required for PDF files.
538			_aMode of access: World Wide Web.
588	0		_aPrint version record
690		7	_aD83 - Search • Learning • Information and Knowledge • Communication • Belief • Unawareness _2Journal of Economic Literature class.
690		7	_aD84 - Expectations • Speculations _2Journal of Economic Literature class.
700	1		_aDave, Chetan.
710	2		_aNational Bureau of Economic Research.
830		0	_aWorking Paper Series (National Bureau of Economic Research) _vno. w16816.
856	4	0	_uhttps://www.nber.org/papers/w16816
856			_yAcceso en línea al DOI _uhttp://dx.doi.org/10.3386/w16816
942			_2ddc _cW-PAPER
999			_c331306 _d289868