Too Many Shocks Spoil the Interpretation
Adrian Pagan and
Tim Robinson
Melbourne Institute Working Paper Series from Melbourne Institute of Applied Economic and Social Research, The University of Melbourne
Abstract:
We show that when a model has more shocks than observed variables the estimated filtered and smoothed shocks will be correlated. This is despite no correlation being present in the data generating process. Additionally the estimated shock innovations may be autocorrelated. These correlations limit the relevance of impulse responses, which assume uncorrelated shocks, for interpreting the data. Excess shocks occur frequently, e.g. in UnobservedComponent (UC) models, filters, including Hodrick-Prescott (1997), and some Dynamic Stochastic General Equilibrium (DSGE) models. Using several UC models and an estimated DSGE model, Ireland (2011), we demonstrate that sizable correlations among the estimated shocks can result.
Keywords: Partial Information; Structural Shocks; Kalman Filter; Measurement Error; DSGE. (search for similar items in EconPapers)
JEL-codes: C51 C52 E37 (search for similar items in EconPapers)
Date: 2020-02
New Economics Papers: this item is included in nep-dge, nep-ets and nep-mac
References: Add references at CitEc
Citations: View citations in EconPapers (4)
Downloads: (external link)
https://melbourneinstitute.unimelb.edu.au/__data/a ... 336530/wp2020n02.pdf (application/pdf)
Related works:
Working Paper: Too many shocks spoil the interpretation (2020)
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:iae:iaewps:wp2020n02
Access Statistics for this paper
More papers in Melbourne Institute Working Paper Series from Melbourne Institute of Applied Economic and Social Research, The University of Melbourne Melbourne Institute of Applied Economic and Social Research, The University of Melbourne, Victoria 3010 Australia. Contact information at EDIRC.
Bibliographic data for series maintained by Sheri Carnegie (melb-inst@unimelb.edu.au).