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Precautionary Learning and Inflationary Biases

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  • Dave, Chetan
  • Feigenbaum, James

Abstract

Recursive least squares learning is a central concept employed in selecting amongst competing outcomes of dynamic stochastic economic models. In employing least squares estimators, such learning relies on the assumption of a symmetric loss function defined over estimation errors. Within a statistical decision making context, this loss function can be understood as a second order approximation to a von-Neumann Morgenstern utility function. This paper considers instead the implications for adaptive learning of a third order approximation. The resulting asymmetry leads the estimator to put more weight on avoiding mistakes in one direction as opposed to the other. As a precaution against making a more costly mistake, a statistician biases his estimates in the less costly direction by an amount proportional to the variance of the estimate. We investigate how this precautionary bias will affect learning dynamics in a model of inflationary biases. In particular we find that it is possible to maintain a lower long run inflation rate than could be obtained in a time consistent rational expectations equilibrium.

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Bibliographic Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 14876.

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Date of creation: 21 Oct 2007
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Handle: RePEc:pra:mprapa:14876

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Keywords: Least squares learning; time inconsistency; statistical decision making;

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  1. Alex Cukierman, 2002. "Are contemporary central banks transparent about economic models and objectives and what difference does it make?," Review, Federal Reserve Bank of St. Louis, issue Jul, pages 15-36.
  2. Francisco Javier Ruge-Murcia, 2001. "Inflation Targeting Under Asymmetric Preferences," IMF Working Papers 01/161, International Monetary Fund.
  3. Barro, Robert J & Gordon, David B, 1983. "A Positive Theory of Monetary Policy in a Natural Rate Model," Journal of Political Economy, University of Chicago Press, vol. 91(4), pages 589-610, August.
  4. Cho, In-Koo & Williams, Noah & Sargent, Thomas J, 2002. "Escaping Nash Inflation," Review of Economic Studies, Wiley Blackwell, vol. 69(1), pages 1-40, January.
  5. William Poole, 2002. "Flation," Speech 49, Federal Reserve Bank of St. Louis.
  6. Evans, George W. & Honkapohja, Seppo, 1999. "Learning dynamics," Handbook of Macroeconomics, in: J. B. Taylor & M. Woodford (ed.), Handbook of Macroeconomics, edition 1, volume 1, chapter 7, pages 449-542 Elsevier.
  7. Kydland, Finn E & Prescott, Edward C, 1977. "Rules Rather Than Discretion: The Inconsistency of Optimal Plans," Journal of Political Economy, University of Chicago Press, vol. 85(3), pages 473-91, June.
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