A Bayesian approach to counterfactual analysis with an application to the volatility reduction in U.S. real GDP

A Bayesian approach to counterfactual analysi ...
Kim, Chang-Jin., Kim, Chang-Ji ...
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Last edited by MARC Bot
December 11, 2020 | History

A Bayesian approach to counterfactual analysis with an application to the volatility reduction in U.S. real GDP

"In this paper, we develop a Bayesian approach to counterfactual analysis. Contrary to standard analysis based on classical point estimates, this approach provides a measure of estimation uncertainty for the counterfactual quantity of interest. We apply the counterfactual analysis to examine the sources of the recent volatility reduction in U.S. real GDP growth. For the application, we consider Blanchard and Quah's (1989) structural VAR model of output growth and unemployment that incorporates a long-run restriction to identify aggregate supply and aggregate demand shocks. We find strong evidence that the change in volatility since 1984 reflects a reduction in the size of structural shocks, rather than a change in the propagation of the shocks. Looking deeper, we find that aggregate supply shocks have played a larger role than aggregate demand shocks in the overall volatility reduction"--Federal Reserve Bank of St. Louis web site.

Publish Date
Language
English

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Book Details


Edition Notes

Also available in print.
Includes bibliographical references.
Title from PDF file as viewed on 10/27/2004.
System requirements: Adobe Acrobat Reader.
Mode of access: World Wide Web.

Published in
[St. Louis, Mo.]
Series
Working paper ;, 2004-014B, Working paper (Federal Reserve Bank of St. Louis : Online) ;, 2004-014B.

Classifications

Library of Congress
HB1

The Physical Object

Format
Electronic resource

Edition Identifiers

Open Library
OL3390545M
LCCN
2004620277

Work Identifiers

Work ID
OL5812957W

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