  An impulse response function describes the dynamic evolution of an outcome
variable following a stimulus or treatment. A common hypothesis of interest is
whether the treatment affects the outcome. We show that this hypothesis is best
assessed using significance bands rather than relying on commonly displayed
confidence bands. Under the null hypothesis, we show that significance bands
are trivial to construct with standard statistical software using the LM
principle, and should be reported as a matter of routine when displaying
impulse responses graphically.
