Estimating Macroeconomic Models: A Likelihood Approach

Jesus Fernandez-Villaverde and Juan F Rubio-Ramirez

The Review of Economic Studies, 2007, vol. 74, issue 4, 1059-1087

Abstract: This paper shows how particle filtering facilitates likelihood-based inference in dynamic macroeconomic models. The economies can be non-linear and/or non-normal. We describe how to use the output from the particle filter to estimate the structural parameters of the model, those characterizing preferences and technology, and to compare different economies. Both tasks can be implemented from either a classical or a Bayesian perspective. We illustrate the technique by estimating a business cycle model with investment-specific technological change, preference shocks, and stochastic volatility. Copyright 2007, Wiley-Blackwell.

Date: 2007
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Related works:
Working Paper: Estimating Macroeconomic Models: A Likelihood Approach (2006)
Working Paper: Estimating Macroeconomic Models: A Likelihood Approach (2006)
Working Paper: Estimating Macroeconomic Models: A Likelihood Approach (2006)
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Persistent link: https://EconPapers.repec.org/RePEc:oup:restud:v:74:y:2007:i:4:p:1059-1087

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