NATIONAL BUREAU OF ECONOMIC RESEARCH
NATIONAL BUREAU OF ECONOMIC RESEARCH

Estimating Macroeconomic Models: A Likelihood Approach

Jesus Fernandez-Villaverde, Juan F. Rubio-Ramirez

NBER Technical Working Paper No. 321
Issued in February 2006
NBER Program(s):   TWP

This paper shows how particle filtering allows us to undertake likelihood-based inference in dynamic macroeconomic models. The models can be nonlinear 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.

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Document Object Identifier (DOI): 10.3386/t0321

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