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Desirability of Nominal GDP Targeting Under Adaptive Learning Author info | Abstract | Publisher info | Download info | Related research | Statistics Kaushik Mitra
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Nominal GDP targeting has been advocated by a number of authors since it produces relative stability of inflation and output. However, all of the papers assume rational expectations on the part of private agents. In this paper I provide an analysis of this assumption. I use stability under recursive learning as a criterion for evaluating nominal GDP targeting in the context of a model with explicit micro- foundations which is currently the workhorse for the analysis of monetary policy. The results of the paper provide support for such a monetary policy.
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Keywords: Nominal GDP ; learning ; expectational stability. ; Other versions of this item:
Find related papers by JEL classification: E4 - Macroeconomics and Monetary Economics - - Money and Interest Rates E5 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit
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236/2004, Department of Economics, University of Hohenheim, Germany.
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Eijffinger, Sylvester C W & Schaling, Eric & Tesfaselassie, Mewael F., 2004.
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Royal Holloway, University of London: Discussion Papers in Economics
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George W. Evans & Seppo Honkapohja, 2002.
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