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Blended identification in structural VARs
DOI:10.1016/j.jmoneco.2024.103581.png)
摘要
En 中文
The proposed blended approach combines identification via heteroskedasticity with sign/ narrative restrictions, and instrumental variables. Since heteroskedasticity can point identify shocks, its use results in a sharp reduction of the potentially large identified sets stemming from other approaches. Conversely, sign/narrative restrictions or instrumental variables offer natural solutions to the labeling problem and can help when conditions for point identification through heteroskedasticity are not met. Blending these methods together resolves their respective key issues and leverages their advantages. We illustrate the benefits of the approach in Monte Carlo experiments, and apply it to several examples taken from the literature.
Keyword:
SVAR
Identification
Heteroskedasticity
Sign restrictions
Proxy variables
期刊
IF:
4.1
论文数:
3.2K
被引数:
1.1W
机构
引用论文
What are the effects of monetary policy on output? Results from an agnostic identification procedure

