We provide a framework for efficiently estimating impulse response functions with Local Projections (LPs). Our approach offers a Bayesian treatment for LPs with Instrumental Variables, accommodating multiple shocks and instruments per shock, accounts for autocorrelation in multi-step forecasts by jointly modeling all LPs as a seemingly unrelated system of equations, defines a flexible yet parsimonious joint prior for impulse responses based on a Gaussian Process, allows for joint inference about the entire vector of impulse responses, and uses all available data across horizons by imputing missing values.

翻译：本文提出了一种利用局部投影(LPs)高效估计脉冲响应函数的框架。该方法为含工具变量的局部投影提供贝叶斯处理方案，支持每个冲击对应多个冲击变量与工具变量；通过将全部局部投影联合建模为似不相关方程组，解决了多步预测中的自相关问题；基于高斯过程定义了灵活而简约的脉冲响应联合先验分布；支持对整个脉冲响应向量进行联合推断；并通过缺失值插补充分利用所有跨时域的可观测数据。