October 2005

Alternative Procedures for Estimating Vector Autoregressions Identified with Long-Run Restrictions

Lawrence J. Christiano, Martin Eichenbaum, and Robert J. Vigfusson


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.

Full paper (screen reader version)

Keywords: Technology shocks, hours worked, frequency domain, spectral density matrix

PDF: Full Paper

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