Indeterminacy and Learning: An Analysis of Monetary Policy in the Great Inflation
Thomas A. Lubik and
Christian Matthes
CAMA Working Papers from Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University
Abstract:
We argue in this paper that the Great Inflation of the 1970s can be understood as the result of equilibrium indeterminacy in which loose monetary policy engendered excess volatility in macroeconomic aggregates and prices. We show, however, that the Federal Reserve inadvertently pursued policies that were not anti-inflationary enough because it did not fully understand the economic environment it was operating in. Specifically, it had imperfect knowledge about the structure of the U.S. economy and it was subject to data misperceptions. The real-time data flow at that time did not capture the true state of the economy, as large subsequent revisions showed. It is the combination of learning about the economy and, more importantly, the use of data riddled with measurement error that resulted in policies, which the Federal Reserve believed to be optimal, but when implemented led to equilibrium indeterminacy in the economy.
Keywords: Federal Reserve; Great Moderation; Bayesian Estimation; Least Squares Learning (search for similar items in EconPapers)
JEL-codes: C11 C32 E52 (search for similar items in EconPapers)
Pages: 51 pages
Date: 2014-02
New Economics Papers: this item is included in nep-cba, nep-mac, nep-mon and nep-sog
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Citations: View citations in EconPapers (11)
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https://cama.crawford.anu.edu.au/sites/default/fil ... 14_lubik_matthes.pdf (application/pdf)
Related works:
Journal Article: Indeterminacy and learning: An analysis of monetary policy in the Great Inflation (2016) 
Working Paper: Indeterminacy and Learning: An Analysis of Monetary Policy in the Great Inflation (2014) 
Working Paper: Indeterminacy and Learning: An Analysis of Monetary Policy in the Great Inflation (2013)
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Persistent link: https://EconPapers.repec.org/RePEc:een:camaaa:2014-16
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