The aim of the paper is to examine the performance of bootstrap and as
ymptotic parametric inference methods in structural VAR analysis. The
results obtained through a Monte Carlo experiment suggest that the two
approaches are largely equivalent in most, but not all, cases. While
the asymptotic method turns out to be surprisingly robust with respect
to the distribution of the errors, the bootstrap does deliver results
superior in terms of both length of the confidence interval and cover
age when highly non-linear statistics (such as the components of the v
ariance of the forecast error) are considered.