Machine learning the macroeconomic effects of financial shocks
提出用神经网络学习结构性冲击的非线性脉冲响应的方法，并用于分析美国金融冲击的影响，发现负面冲击对经济影响大而正面冲击影响小，但冲击大小没有明显不对称。
We propose a method to learn the nonlinear impulse responses to structural shocks using neural networks , and apply it to uncover the effects of US financial shocks. The results reveal substantial asymmetries with respect to the sign of the shock. Adverse financial shocks have powerful effects on the US economy, while benign shocks trigger much smaller reactions. Instead, with respect to the size of the shocks, we find no discernible asymmetries.