A Flexible Finite-Horizon Identification of Technology Shocks

Recent empirical studies using infinite horizon long-run restrictions question the validity of the technology-driven real business cycle hypothesis. These results have met with their own controversy, stemming from their sensitivity to changes in model specification and the general poor performance of long run restrictions in Monte Carlo experiments. We propose a alternative identification that maximizes the contribution of technology shocks to the forecast error variance of labor productivity at a long, but finite horizon. In small samples, our identification outperforms its infinite horizon counterpart by producing less biased impulse responses and technology shocks that are more highly correlated with the technology shocks from the underlying model. For U.S. data, we show that the negative hours response is not robust to allowing a greater role for non-technology shocks in the forecast error variance share at a ten year horizon.