Stationarity of econometric learning with bounded memory and a predicted state variable

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.

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Year of publication:	2015
Authors:	Damjanovic, Tatiana ; Girdėnas, Šarūnas ; Liu, Keqing
Published in:	Economics Letters. - Elsevier, ISSN 0165-1765. - Vol. 130.2015, C, p. 93-96
Publisher:	Elsevier
Subject:	Econometric learning \| Bounded memory \| Random coefficient autoregressive process \| Stationarity

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Type of publication:	Article
Classification:	C22 - Time-Series Models ; C53 - Forecasting and Other Model Applications ; C62 - Existence and Stability Conditions of Equilibrium ; D83 - Search, Learning, Information and Knowledge ; E31 - Price Level; Inflation; Deflation
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10011263417