Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/208341
Authors: 
Chudik, Alexander
Georgiadis, Georgios
Year of Publication: 
2019
Series/Report no.: 
ECB Working Paper No. 2307
Abstract: 
This paper proposes mixed-frequency distributed-lag (MFDL) estimators of impulse response functions (IRFs) in a setup where (i) the shock of interest is observed, (ii) the impact variable of interest is observed at a lower frequency (as a temporally aggregated or sequentially sampled variable), (iii) the data generating process (DGP) is given by a VAR model at the frequency of the shock, and (iv) the full set of relevant endogenous variables entering the DGP is unknown or unobserved. Consistency and asymptotic normality of the proposed MFDL estimators is estab- lished, and their small-sample performance is documented by a set of Monte Carlo experiments. The proposed approach is then applied to estimate the daily pass-through of changes in crude oil prices observed at the daily frequency to U.S. gasoline consumer prices observed at the weekly frequency. We find that the pass-through is fast, with about 23% of the crude oil price changes passed through to retail gasoline prices within five working days, representing about 42% of the long-run pass-through.
Subjects: 
Mixed frequencies
temporal aggregation
impulse response functions
estimationand inference
VAR models
JEL: 
C22
Persistent Identifier of the first edition: 
ISBN: 
978-92-899-3569-2
Document Type: 
Working Paper

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