Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/334990 
Year of Publication: 
2025
Series/Report no.: 
ECB Working Paper No. 3105
Publisher: 
European Central Bank (ECB), Frankfurt a. M.
Abstract: 
Local projections (LPs) are widely used in empirical macroeconomics to estimate impulse responses to policy interventions. Yet, in many ways, they are black boxes. It is often unclear what mechanism or historical episodes drive a particular estimate. We introduce a new decomposition of LP estimates into the sum of contributions of historical events, which is the product, for each time stamp, of a weight and the realization of the response variable. In the least squares case, we show that these weights admit two interpretations. First, they represent purified and standardized shocks. Second, they serve as proximity scores between the projected policy intervention and past interventions in the sample. Notably, this second interpretation extends naturally to machine learning methods, many of which yield impulse responses that, while nonlinear in predictors, still aggregate past outcomes linearly via proximity-based weights. Applying this framework to shocks in monetary and fiscal policy, global temperature, and the excess bond premium, we find that easily identifiable events-such as Nixon's interference with the Fed, stagflation, World War II, and the Mount Agung volcanic eruption-emerge as dominant drivers of often heavily concentrated impulse response estimates.
Subjects: 
Local projections
Monetary policy
Fiscal multipliers
Climate
Financial shocks
JEL: 
C32
C53
E31
E52
E62
Persistent Identifier of the first edition: 
ISBN: 
978-92-899-7427-1
Document Type: 
Working Paper

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