Glossary

Impulse Response Function

A function that traces the dynamic effect of a one-unit shock to one variable in a VAR system on all variables over subsequent time periods. IRFs are essential for understanding the propagation and persistence of shocks.

Definition

Why It Matters

Policymakers need to know not just whether a variable responds to a shock, but how the response unfolds over time and how long it persists. IRFs provide precisely this information, tracing the full dynamic path from shock to new equilibrium. They are indispensable in monetary policy analysis, fiscal impact studies, and any setting where the timing and magnitude of policy effects matter.

Example

In a three-variable VAR with Turkish GDP growth, inflation, and the policy rate, an IRF shows that a one-standard-deviation shock to the policy rate reduces GDP growth for two quarters before the effect dissipates, while inflation declines gradually over four quarters. The confidence bands around the response widen over time, reflecting increasing uncertainty about long-horizon effects.

Related Terms

Software Notes

SPSS: Not natively available; use R integration for IRF estimation.
R: After estimating a VAR with VAR() from the vars package, use irf() to compute and plot impulse response functions with confidence bands.
Stata: After var estimation, use irf create to compute IRFs, then irf graph to plot them. Orthogonalised IRFs require Cholesky ordering specified via irf create, order().