Stationarity of Econometric Learning with Bounded Memory and a Predicted State Variable

Tatiana Damjanovic (), Šarūnas Girdėnas () and Keqing Liu ()

No 201501, CDMA Working Paper Series from Centre for Dynamic Macroeconomic Analysis

Abstract: In this paper, we consider a model where producers set their prices based on their prediction of the aggregated price level and an exogenous variable, which can be a demand or a cost-push shock. To form their expectations, they use OLS-type econometric learning with bounded memory. We show that the aggregated price follows the random coefficient autoregressive process and we prove that this process is covariance stationary

Keywords: econometric learning; bounded memory; random coefficient autoregressive process; stationarity (search for similar items in EconPapers)
JEL-codes: C22 C53 C62 D83 E31 (search for similar items in EconPapers)
Date: 2015-02-01
New Economics Papers: this item is included in nep-mac
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link)
http://www.st-andrews.ac.uk/~wwwecon/repecfiles/2/1501.pdf (application/pdf)

Related works:
Journal Article: Stationarity of econometric learning with bounded memory and a predicted state variable (2015)
Working Paper: Stationarity of Econometric Learning with Bounded Memory and a Predicted State Variable (2015)
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:san:cdmawp:1501

Access Statistics for this paper

More papers in CDMA Working Paper Series from Centre for Dynamic Macroeconomic Analysis School of Economics and Finance, Castlecliffe, The Scores, Fife, KY16 9AZ. Contact information at EDIRC.
Bibliographic data for series maintained by The School of Economics and Finance ().