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Optimal Monetary Policy in a Small Open Economy with Home Bias

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Author Info
Ester Faia (Pompeu-Fabra University)
Tommaso Monacelli (Bocconi University)

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Abstract

We analyze optimal monetary policy in a small open economy characterized by home bias in consumption. Peculiar to our framework is the application of a Ramsey-type analysis to a model of the recent open economy New Keynesian literature. We show that home bias in consumption is a sufficient condition for inducing monetary policy-makers of an open economy to deviate from a strategy of strict markup stabilization and contemplate some (optimal) degree of exchange rate stabilization. We focus on the optimal setting of policy both in the case in which rms set prices one period in advance as well as in the case in which rms set prices in a dynamic forward-looking fashion. While the rst setup allows us to analytically highlight home bias as an independent source of equilibrium markup variability, the second setup allows to study the effects of future expectations on the optimal policy problem and the effect of home bias on optimal inflation volatility. The latter, in particular, is shown to be related to the degree of trade openness in a U-shaped fashion, whereas exchange rate volatility is monotonically decreasing in openness.

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Paper provided by Society for Computational Economics in its series Computing in Economics and Finance 2006 with number 521.

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Date of creation: 04 Jul 2006
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Handle: RePEc:sce:scecfa:521

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Keywords: Optimal Monetary Policy Ramsey Planner Home Bias Sticky Prices

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Find related papers by JEL classification:
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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  1. Michal Brzoza-Brzezina & Jesus Crespo Cuaresma, 2007. "Mr. Wicksell and the global economy: What drives real interest rates?," Working Papers 2007-06, Faculty of Economics and Statistics, University of Innsbruck. [Downloadable!]
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