Preview Citation
Format: Chicago
Michal Andrle, and Miroslav Plašil. System Priors for Econometric Time Series, (USA: International Monetary Fund, 2016) accessed April 21, 2025
Disclaimer: This Working Paper should not be reported as representing the views of the IMF.The views expressed in this Working Paper are those of the author(s) and do not necessarily represent those of the IMF or IMF policy. Working Papers describe research in progress by the author(s) and are published to elicit comments and to further debate
Summary
The paper introduces “system priors”, their use in Bayesian analysis of econometric time series, and provides a simple and illustrative application. System priors were devised by Andrle and Benes (2013) as a tool to incorporate prior knowledge into an economic model. Unlike priors about individual parameters, system priors offer a simple and efficient way of formulating well-defined and economically-meaningful priors about high-level model properties. The generality of system priors are illustrated using an AR(2) process with a prior that most of its dynamics comes from business-cycle frequencies.
Subject: Business cycles
Keywords: Time series, WP
Publication Details
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Pages:
18
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Volume:
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DOI:
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Issue:
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Series:
Working Paper No. 2016/231
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Stock No:
WPIEA2016231
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ISBN:
9781475555820
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ISSN:
1018-5941