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Recursive Thick Modeling and the Choice of Monetary Policy in Mexico Author info | Abstract | Publisher info | Download info | Related research | Statistics Arnulfo Rodriguez () (Economic Studies Division Bank of Mexico)
Pedro N. Rodriguez (Universidad Complutense de Madrid)
By following the spirit in Favero and Milani (2005), we use recursive thick modeling to take into account model uncertainty for the choice of optimal monetary policy. We consider an open economy model and generate multiple models for only the aggregate demand and aggregate supply. Models are constructed by matching the rankings of aggregate demand and aggregate supply and adding other specifications for the rest of the variables. The main results show that recursive thick modeling with equal and different weights approximates the recent historical behavior of nominal interest rates in Mexico better than recursive thin modeling
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Paper provided by Society for Computational Economics in its series Computing in Economics and Finance 2006 with number
30.
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Date of creation: 04 Jul 2006Date of revision:
Handle: RePEc:sce:scecfa:30Contact details of provider: Email: Web page: http://comp-econ.org/ More information through EDIRC
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Keywords: model uncertainty ; optimal control ; out-of-bag ; thin modeling and thick modeling ; Other versions of this item:
Find related papers by JEL classification: C61 - Mathematical and Quantitative Methods - - Mathematical Methods and Programming - - - Optimization Techniques; Programming Models; Dynamic Analysis E61 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - Policy Objectives; Policy Designs and Consistency; Policy Coordination
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