Alternative procedures for estimating vector autoregressions identified with long-run restrictions
Work detail
"We show that the standard procedure for estimating long-run identified vector autoregressions uses a particular estimator of the zero-frequency spectral density matrix of the data. We develop alternatives to the standard procedure and evaluate the properties of these alternative procedures using Monte Carlo experiments in which data are generated from estimated real business cycle models. We focus on the properties of estimated impulse response functions. In our examples, the alternative procedures have better small sample properties than the standard procedure, with smaller bias, smaller mean square error and better coverage rates for estimated confidence intervals"--Federal Reserve Board web site.
Overview
Shared work-level identity and catalog context.
Contributors
People credited with this work in the active catalog.
- Open Author
Lawrence J. Christiano
Editions
Publication-specific versions linked to this work only.