Estimating Macroeconomic Models: A Likelihood Approach |
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Authors: | JESÚS FERNÁNDEZ-VILLAVERDE JUAN F RUBIO-RAMÍREZ |
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Institution: | University of Pennsylvania, NBER, and CEPR; Duke University and Federal Reserve Bank of Atlanta |
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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. |
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