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Inferring monetary policy objectives with a partially observed state

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  • Givens, Gregory
  • Salemi, Michael

Abstract

Accounting for the uncertainty inherent in real-time perceptions of the state of the economy is believed to be critical for the analysis of historical monetary policy. We investigate this claim through the lens of a small-scale new-Keynesian model with optimal discretionary policy and partial information about the state. The model is estimated using maximum likelihood on US data over the Volcker-Greenspan-Bernanke regime. A comparison of our estimates to those from a version of the model with complete information reveals that under partial information: (i) the Federal Reserve demonstrates a significant concern for stabilizing fluctuations in the output gap, and (ii) the discrepancy between optimal and observed policy behavior is smaller.

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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 39353.

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Date of creation: 30 May 2012
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Handle: RePEc:pra:mprapa:39353

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Keywords: Partial Information; Optimal Monetary Policy; Central Bank Preferences;

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Cited by:
  1. Thomas A. Lubik & Christian Matthes, 2014. "Indeterminacy and Learning: An Analysis of Monetary Policy in the Great Inflation," CAMA Working Papers 2014-16, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.

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