Learning and Macroeconomics

George Evans and Seppo Honkapohja

Annual Review of Economics, 2009, vol. 1, issue 1, 421-451

Abstract: Expectations play a central role in modern macroeconomic theories. The econometric learning approach models economic agents as forming expectations by estimating and updating forecasting models in real time. The learning approach provides a stability test for rational expectations and a selection criterion in models with multiple equilibria. In addition, learning provides new dynamics if older data are discounted, if models are misspecified, or if agents choose between competing models. This paper describes the expectational stability (E-stability) principle and the stochastic approximation tools used to assess equilibria under learning. Applications of learning to a number of areas are reviewed, including the design of monetary and fiscal policy, business cycles, self-fulfilling prophecies, hyperinflation, liquidity traps, and asset prices.

Keywords: E-stability; stochastic approximation; persistent learning dynamics; business cycles; monetary policy; asset prices (search for similar items in EconPapers)
JEL-codes: D83 E13 E32 E52 (search for similar items in EconPapers)
Date: 2009
References: Add references at CitEc
Citations: View citations in EconPapers (67)

Downloads: (external link)
http://www.annualreviews.org/doi/abs/10.1146/annurev.economics.050708.142927 (application/pdf)
Full text downloads are only available to subscribers. Visit the abstract page for more information.

Related works:
Working Paper: Learning and Macroeconomics (2008)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:anr:reveco:v:1:y:2009:p:421-451

Ordering information: This journal article can be ordered from
http://www.annualreviews.org/action/ecommerce

Access Statistics for this article

More articles in Annual Review of Economics from Annual Reviews Annual Reviews 4139 El Camino Way Palo Alto, CA 94306, USA.
Bibliographic data for series maintained by http://www.annualreviews.org ().