Vector autoregressions and reality

David E. Runkle

No 107, Staff Report from Federal Reserve Bank of Minneapolis

Abstract: The statistical significance of variance decompositions and impulse response functions for unrestricted vector autoregressions is questionable. Most previous studies are suspect because they have not provided confidence intervals for variance decompositions and impulse response functions. Here two methods of computing such intervals are developed, one using a normal approximation, the other using bootstrapped resampling. An example from Sims? work illustrates the importance of computing these confidence intervals. In the example, the 95 percent confidence intervals for variance decompositions span up to 66 percentage points at that usual forecasting horizon.

Keywords: Econometric models; Vector autoregression (search for similar items in EconPapers)
Date: 1987
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Citations: View citations in EconPapers (252)

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