Forecasting the Forecasts of Others in the Frequency Domain
Kenneth Kasa
Review of Economic Dynamics, 2000, vol. 3, issue 4, 726-756
Abstract:
This paper studies a class of models developed by Townsend (1983) and Sargent (1991). These models feature dynamic signal extraction problems and an infinite regress in expectations. This paper uses frequency domain methods to compute an analytical solution to the fixed point problem posed by the infinite regress in expectations. The advantage of a frequency domain approach vis-a-vis a time domain approach derives for the fact that these models produce equilibrium with non-fundamental moving average representations, in which market observations do not reveal the underlying shocks to agents' information sets. As a result, decision rules contain moving average components that are more easily handled in the frequency domain than in the time domain. (Copyright: Elsevier)
Keywords: signal extraction; infinite regress; frequency domain (search for similar items in EconPapers)
Date: 2000
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (51)
Downloads: (external link)
http://dx.doi.org/10.1006/redy.1999.0085 Full text (application/pdf)
Access to full texts is restricted to ScienceDirect subscribers and ScienceDirect institutional members. See http://www.sciencedirect.com/ for details.
Related works:
Working Paper: Signal extraction and the propagation of business cycles (1995)
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:red:issued:v:3:y:2000:i:4:p:726-756
Ordering information: This journal article can be ordered from
https://www.economic ... ription-information/
DOI: 10.1006/redy.1999.0085
Access Statistics for this article
Review of Economic Dynamics is currently edited by Loukas Karabarbounis
More articles in Review of Economic Dynamics from Elsevier for the Society for Economic Dynamics Contact information at EDIRC.
Bibliographic data for series maintained by Christian Zimmermann ().