Macroeconomic Responses to Uncertainty Shocks: The Perils of Recursive Orderings
Lutz Kilian,
Michael D. Plante and
Alexander Richter
Journal of Applied Econometrics, 2025, vol. 40, issue 4, 395-410
Abstract:
A common practice in empirical macroeconomics is to examine alternative recursive orderings of the variables in structural vector autoregressive (VAR) models. When the implied impulse responses look similar, the estimates are considered trustworthy. When they do not, the estimates are used to bound the true response without directly addressing the identification challenge. A leading example of this practice is the literature on the effects of uncertainty shocks on economic activity. We prove by counterexample and show by simulation that this practice is invalid, whether the data generating process is a structural VAR model or a dynamic stochastic general equilibrium model. Simulation evidence suggests that the underlying identification challenge can be addressed using an instrumental variables estimator.
Date: 2025
References: Add references at CitEc
Citations:
Downloads: (external link)
https://doi.org/10.1002/jae.3113
Related works:
Working Paper: Macroeconomic Responses to Uncertainty Shocks: The Perils of Recursive Orderings (2022) 
Working Paper: Macroeconomic Responses to Uncertainty Shocks: The Perils of Recursive Orderings (2022) 
Working Paper: Macroeconomic Responses to Uncertainty Shocks: The Perils of Recursive Orderings (2022) 
Working Paper: Macroeconomic responses to uncertainty shocks: The perils of recursive orderings (2022) 
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:wly:japmet:v:40:y:2025:i:4:p:395-410
Ordering information: This journal article can be ordered from
http://www3.intersci ... e.jsp?issn=0883-7252
Access Statistics for this article
Journal of Applied Econometrics is currently edited by M. Hashem Pesaran
More articles in Journal of Applied Econometrics from John Wiley & Sons, Ltd.
Bibliographic data for series maintained by Wiley Content Delivery ().