Working Paper
Alternative procedures for estimating vector autoregressions identified with long-run restrictions
Abstract: 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.
Keywords: Vector analysis; Vector autoregression; Econometric models;
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Bibliographic Information
Provider: Board of Governors of the Federal Reserve System (U.S.)
Part of Series: International Finance Discussion Papers
Publication Date: 2005
Number: 842