Two-sided Learning and Optimal Monetary Policy in an Open Economy Model
AbstractIn this paper, we consider a dynamic New Keynesian model of the small open economy in the light of bounded rationality. This entails private agents and the central bank updating their beliefs about the laws of motion of inflation, the output gap and real exchange rate, when forming their optimal decisions. It is shown that when all players learn using recursive least-squares or stochastic-gradient adaptive algorithms, the optimal policy steers the economy towards a rational expectations equilibrium (REE) with probability one in some cases. This is also the case when only private agents are learning. However there also exists structural parameter values in the true model such that learning converges with probability zero to REE.
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Bibliographic InfoPaper provided by The University of Western Australia, Department of Economics in its series Economics Discussion / Working Papers with number 04-07.
Length: 27 pages
Date of creation: 2004
Date of revision:
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More information through EDIRC
Optimal monetary policy; Small open economy; Learning; Stochastic approximation;
Find related papers by JEL classification:
- D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search, Learning, and Information
- E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
- F41 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Open Economy Macroeconomics
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