Common Components Structural VARs
针对结构VAR模型因变量选择导致结果不稳定的问题，提出用高维因子模型的共同成分替换原始变量，在共同成分数多于结构冲击数时解决信息不足，并证明估计的一致性。应用于货币政策冲击，发现结果稳健且消除了常见谜题。
Structural VAR models (SVAR) produce results that can vary dramatically with the choice of variables, because information is deficient. We argue that if the variables of interest belong to a High-Dimensional Factor Model and are replaced in the SVAR by their common components, the information issue finds a solution, provided that the number of common components is larger than the number of structural shocks, so that the SVAR is dynamically singular. This is the Common Components Structural VAR (CC-SVAR). Our main contribution is that we prove consistency of our CC-SVAR estimates, which is far from trivial as our estimated SVAR tends to dynamic singularity. We apply our procedure to monetary policy shocks, finding that, with the CC-SVAR, results are robust to the choice of variables and well-known puzzles disappear.