Learning to Forecast and Cyclical Behavior of Output and Inflation

Klaus Adam

No 2003/01, CFS Working Paper Series from Center for Financial Studies (CFS)

Abstract: This paper considers a sticky price model with a cash-in-advance constraint where agents forecast inflation rates with the help of econometric models. Agents use least squares learning to estimate two competing models of which one is consistent with rational expectations once learning is complete. When past performance governs the choice of forecast model, agents may prefer to use the inconsistent forecast model, which generates an equilibrium where forecasts are inefficient. While average output and inflation result the same as under rational expectations, higher moments differ substantially: output and inflation show persistence, inflation responds sluggishly to nominal disturbances, and the dynamic correlations of output and inflation match U.S. data surprisingly well.

Keywords: Learning; Business Cycles; Rational Expectations; Inefficient Forecasts; Output and Inflation Persistence (search for similar items in EconPapers)
JEL-codes: E31 E32 E37 (search for similar items in EconPapers)
Date: 2003
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.econstor.eu/bitstream/10419/72652/1/03_01.pdf (application/pdf)

Related works:
Journal Article: LEARNING TO FORECAST AND CYCLICAL BEHAVIOR OF OUTPUT AND INFLATION (2005)
Working Paper: Learning to Forecast and Cyclical Behavior of Output and Inflation (2003)
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:zbw:cfswop:200301

Access Statistics for this paper

More papers in CFS Working Paper Series from Center for Financial Studies (CFS) Contact information at EDIRC.
Bibliographic data for series maintained by ZBW - Leibniz Information Centre for Economics ().