We use a Bayesian Markov Chain Monte Carlo algorithm to estimate a model that allows temporary gaps between a true expectational Phillips curve and the monetary authority's approximating non-expectational Phillips curve. A dynamic programming problem implies that the monetary authority's inflation target evolves as its estimated Phillips curve moves. Our estimates attribute the rise and fall of post WWII inflation in the US to an intricate interaction between the monetary authority's beliefs and economic shocks. Shocks in the 1970s altered the monetary authority's estimates and made it misperceive the tradeoff between inflation and unemployment. That caused a sharp rise in inflation in the 1970s. Our estimates say that policymakers updated their beliefs continuously. By the 1980s, their beliefs about the Phillips curve had changed enough to account for Volcker's conquest of US inflation in the early 1980s.
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Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number
10764.
Length: Date of creation: Sep 2004 Date of revision: Handle: RePEc:nbr:nberwo:10764
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Find related papers by JEL classification: E5 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit
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References listed on IDEAS Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
James D. Hamilton & Daniel F. Waggoner & Tao Zha, 2004.
"Normalization in econometrics,"
Working Paper
2004-13, Federal Reserve Bank of Atlanta.
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Other versions:
James D. Hamilton & Daniel F. Waggoner & Tao Zha, 2007.
"Normalization in Econometrics,"
Econometric Reviews,
Taylor and Francis Journals, vol. 26(2-4), pages 221-252.
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