Abstract:
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Abstract: This paper proposes a new framework to study identification in structural
VAR models. The framework is based on the variance-frequency decomposition and
focuses on the contribution of the identified shock to the variance of model variables in
a given frequency range. We use the hours-productivity debate as a connecting thread in
our discussion since the identification problem has attracted a lot of attention in this
literature. To start, we employ the framework to study the business cycle properties of a
set of different identification schemes for technology shocks. Grounded on the
simulation results, we propose a new model-based procedure which delivers a precise
estimate of the response of hours. Finally, we put all the schemes to work with real data,
obtaining substantial evidence in favor of plausible RBC parametrizations, especially
from identification restrictions that perform better in simulations. This analysis also
reveals that the schemes that recover a very strong response of hours (higher than the
implied by typical RBC parameterizations) tend to overstate the contribution of the
technology shock to the fluctuations of hours worked at business cycle frequencies.
Keywords: Business cycle, frequency domain, hours worked, productivity, vector
autoregressions.
Classification: C1, E3 |