Uncertainty Over Models and Data: The Rise and Fall of American Inflation

43 Pages Posted: 27 Jan 2009

See all articles by Seth Pruitt

Seth Pruitt

Arizona State University (ASU) - Finance Department

Date Written: December 23, 2008

Abstract

An economic agent who is uncertain of her model updates her beliefs in response to the data. The updating is sensitive to measurement error which, in many cases of macroeconomic interest, is apparent from the process of data revision. I make this point through simple illustrations and then analyze a recent model of the Federal Reserve's role in U.S. inflation. The existing model succeeds at fitting inflation to optimal policy, but fails to link inflation to the economic trade-off at the heart of the story. I modify the model to account for data uncertainty and find that doing so ameliorates the existing problems. This suggests that the Fed's model uncertainty is largely overestimated by ignoring data uncertainty. Consequently, now there is an explanation for the rise and fall in inflation: the concurrent rise and fall in the perceived Philips curve trade-off.

Keywords: Data uncertainty, data revisions, real time data, optimal control, parameter uncertainty, learning, extended kalman filter, Markov-chain monte carlo

JEL Classification: E01, E58

Suggested Citation

Pruitt, Seth, Uncertainty Over Models and Data: The Rise and Fall of American Inflation (December 23, 2008). FRB International Finance Discussion Paper No. 962, Available at SSRN: https://ssrn.com/abstract=1333328 or http://dx.doi.org/10.2139/ssrn.1333328

Seth Pruitt (Contact Author)

Arizona State University (ASU) - Finance Department ( email )

W. P. Carey School of Business
PO Box 873906
Tempe, AZ 85287-3906
United States

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