Learning, large deviations and rare events

Benhabib, Jess; Dave, Chetan

doi:10.1016/j.red.2013.09.004

Cited by 23 publications

(13 citation statements)

References 43 publications

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“…This keeps learning alive. For example, Benhabib and Dave (2014) show that constant gain learning can generate persistent excess volatility, and can explain why asset prices have fat-tailed distributions even when the distribution of fundamentals is thin-tailed.…”

Section: To Believe Is To Seementioning

confidence: 99%

“…Our paper builds on the work of Benhabib and Dave (2014). The key parameter in their analysis is the update gain.…”

Section: To Believe Is To Seementioning

confidence: 99%

“…There is also debate about its empirical validity (Rolnick and Weber (1986)). 3 Examples include: Sargent (1999), Cho, Williams, and Sargent (2002), Marcet and Nicolini (2003), Kasa (2004), Chakraborty and Evans (2008), and Benhabib and Dave (2014).…”

Section: Introductionmentioning

confidence: 99%

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Gresham's Law of Model Averaging

Cho

Kasa

2017

American Economic Review

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A decision maker doubts the stationarity of his environment. In response, he uses two models, one with time-varying parameters, and another with constant parameters. Forecasts are then based on a Bayesian model averaging strategy, which mixes forecasts from the two models. In reality, structural parameters are constant, but the (unknown) true model features expectational feedback, which the reduced-form models neglect. This feedback permits fears of parameter instability to become self-confirming. Within the context of a standard asset-pricing model, we use the tools of large deviations theory to show that even though the constant parameter model would converge to the rational expectations equilibrium if considered in isolation, the mere presence of an unstable alternative drives it out of consideration. (JEL C63, D83, D84)

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Section: To Believe Is To Seementioning

confidence: 99%

“…Our paper builds on the work of Benhabib and Dave (2014). The key parameter in their analysis is the update gain.…”

Section: To Believe Is To Seementioning

confidence: 99%

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Gresham's Law of Model Averaging

Cho

Kasa

2017

American Economic Review

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“…61 Contributions include Adam, Beutel and Marcet (2013), Adam, Marcet, and Nicolini (2012), CarcelesPoveda and Giannitsarou (2008), Benhabib and Dave (2014), Branch and Evans (2010, 2011), and Sinha (2014. 62 Recent studies on the interactions between monetary policy and asset pricing under learning include Airaudo, Nisticò, and Zanna (2014), Winkler (2015), Gelain, Lansing, and Mendicino (2013), Kitney (2014), Pintus and Suda (2014), Gelain, Lansing, andNatvik (2015), Dewachter, Iania, and Lyrio (2011), Milani (2008) and Caputo, Medina, and Soto (2011).…”

mentioning

confidence: 99%

The Science of Monetary Policy: An Imperfect Knowledge Perspective

Preston

Eusepi

2016

SSRN Journal

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. "I think of economics as studying decision rules that are steady states of some adaptive process, decision rules that are found to work over a range of situations and hence are no longer revised appreciably as more experience accumulates." Robert E. Lucas Jr "Rational expectations imposes two requirements on economic models: individual rationality and mutual consistency of perception about the environment. [...] I interpret a proposal to build models with 'boundedly rational'agents as a call to retreat from the second piece of rational expectations (mutual consistency of perceptions) by expelling rational agents from our model's environment and replacing them with 'arti…cially intelligent' agents who behave like econometricians." Terms of use: Documents inThomas Sargent "The traditional rational-expectations model of in ‡ation and in ‡ation expectations has been a useful workhorse for thinking about issues of credibility and institutional design, but, to my mind, it is less helpful for thinking about economies in which (1) the structure of the economy is constantly evolving in ways that are imperfectly understood by both the public and policymakers and (2) the policymakers'objective function is not fully known by private agents. In particular, together with the assumption that the central bank's objective function is …xed and known to the public, the traditional rational-expectations approach implies that the public has …rm knowledge of the long-run equilibrium in ‡ation rate; consequently, their long-run in ‡ation expectations do not vary over time in response to new information."Ben S. BernankeThe authors thank Jim Bullard, Marc Giannoni and Mike Woodford for on-going discussions about much of the material contained here-in, and also a number of anonymous referees and the editors Janet Currie and Steven Durlauf for constructive feedback.

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“…In a series of papers [25,31,54,70,106,126], the results of [56,86] and [58,61] have been extended to the case where the coefficients (ρ n , ξ n ) n∈Z in Equation (1.2) are modulated by a Markov chain. The extension is desirable in many, especially financial, applications, see for instance [9,10,25,67,118].…”

Section: Geometric Brownian Motion With Regime Switchesmentioning

confidence: 99%

Discrete Ornstein-Uhlenbeck process in a stationary dynamic enviroment

Qin

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This thesis is dedicated to my parents Tonglin and Xuelan and my sister Nana. Without their patience, understanding, support, and most of all love, the completion of this work would not have been possible. Also, this thesis is dedicated to my fiancé Darren who has been a great source of motivation and inspiration. Finally, this thesis is dedicated to all those who believe in the richness of learning. iii

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Learning, large deviations and rare events

Cited by 23 publications

References 43 publications

Gresham's Law of Model Averaging

Gresham's Law of Model Averaging

The Science of Monetary Policy: An Imperfect Knowledge Perspective

Discrete Ornstein-Uhlenbeck process in a stationary dynamic enviroment

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