Learnability of an equilibrium with private information
Ryuichi Nakagawa ()
Journal of Economic Dynamics and Control, 2015, vol. 59, issue C, 58-74
Abstract:
This paper investigates the learnability of an equilibrium with private information. Agents of each type have their own private information about an exogenous variable and conduct adaptive learning with a heterogeneously misspecified perceived laws of motion (PLM) that includes only this variable. The paper shows that the existence of private information has a nonnegative impact on the learnability of the equilibrium; that is, the condition for learnability is unaffected or relaxed by heterogeneity and/or misspecification in PLMs caused by private information. In a New Keynesian model with private information about fundamental shocks, the learnability of the equilibrium is ensured by the Taylor principle of monetary policy. The paper also confirms that these results hold true not only in the presence of private information, but also in a variety of informational structures.
Keywords: Adaptive learning; Private information; Heterogeneous misspecification; Taylor principle (search for similar items in EconPapers)
JEL-codes: C62 D83 E52 (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0165188915001190
Full text for ScienceDirect subscribers only
Related works:
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:eee:dyncon:v:59:y:2015:i:c:p:58-74
DOI: 10.1016/j.jedc.2015.06.010
Access Statistics for this article
Journal of Economic Dynamics and Control is currently edited by J. Bullard, C. Chiarella, H. Dawid, C. H. Hommes, P. Klein and C. Otrok
More articles in Journal of Economic Dynamics and Control from Elsevier
Bibliographic data for series maintained by Catherine Liu ().