Can Long-Run Restrictions Identify Technology Shocks?
通过蒙特卡洛模拟检验Galí方法在标准商业周期模型中识别技术冲击的可靠性，发现估计的脉冲响应符号和模式基本正确，但存在小样本偏差和较大的估计不确定性，提醒不应将其结果视为模型无关的典型事实。
Galí's innovative approach of imposing long-run restrictions on a vector autoregression (VAR) to identify the effects of a technology shock has become widely utilized.In this paper, we investigate its reliability through Monte Carlo simulations of several relatively standard business cycle models.We find it encouraging that the impulse responses derived from applying the Galí methodology to the artificial data generally have the same sign and qualitative pattern as the true responses.However, we highlight the importance of small-sample bias in the estimated impulse responses and show that the magnitude and sign of this bias depend on the model structure.Accordingly, we caution against interpreting responses derived from this approach as "model-independent" stylized facts.Moreover, we find considerable estimation uncertainty about the quantitative impact of a technology shock on macroeconomic variables, and a corresponding level of uncertainty about the contribution of technology shocks to the business cycle.