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 ; Girdenas, Sarunas ; Liu, Keqing
Institutions:	Business School, University of Exeter
Subject:	econometric learning \| bounded memory \| random coefficient autoregressive process \| stationarity

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Extent:	application/pdf
Series:	Discussion Papers.
Type of publication:	Book / Working Paper
Notes:	Number 1502
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/10011183991