The usefulness of SVARs for developing empirically plausible models is actually subject to controversies in macroeconomics. We propose a two-step SVARs-based procedure which consistently estimates the effect of permanent technology shocks on aggregate variables. Simulation experiments from a standard business cycle model and a sticky prices model show that our approach outperforms standard SVARs. The two-step procedure, when applied to actual data, predicts a significant short-run decrease of hours after a technology improvement followed by a hump-shaped positive response. Additionally, the rate of inflation and the nominal interest rate displays a significant decrease after this shock.