Rights statement: This is the author’s version of a work that was accepted for publication in Journal of Economic Dynamics and Control. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Journal of Economic Dynamics and Control, 71, 2017 DOI: 10.1016/j.jedc.2016.08.001
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Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
}
TY - JOUR
T1 - Measuring nonfundamentalness for structural VARs
AU - Soccorsi, Stefano
N1 - This is the author’s version of a work that was accepted for publication in Journal of Economic Dynamics and Control. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Journal of Economic Dynamics and Control, 71, 2017 DOI: 10.1016/j.jedc.2016.08.001
PY - 2016/10
Y1 - 2016/10
N2 - As nonfundamental vector moving averages do not have causal VAR representations, standard structural VAR methods are deemed inappropriate for recovering the economic shocks of general equilibrium models with nonfundamental reduced forms. In the previous literature it has been pointed out that, despite nonfundamentalness, structural VARs may still be good approximating models. I characterize nonfundamentalness as bias depending on the zeros of moving average filters. However, measuring the nonfundamental bias is not trivial because of the simultaneous occurrence of lag truncation bias. I propose a method to disentangle the bias based on population spectral density and derive a measure for the nonfundamental bias in population. In the application, I find that the SVAR exercises of Sims (2012) are accurate because the nonfundamental bias is mild.
AB - As nonfundamental vector moving averages do not have causal VAR representations, standard structural VAR methods are deemed inappropriate for recovering the economic shocks of general equilibrium models with nonfundamental reduced forms. In the previous literature it has been pointed out that, despite nonfundamentalness, structural VARs may still be good approximating models. I characterize nonfundamentalness as bias depending on the zeros of moving average filters. However, measuring the nonfundamental bias is not trivial because of the simultaneous occurrence of lag truncation bias. I propose a method to disentangle the bias based on population spectral density and derive a measure for the nonfundamental bias in population. In the application, I find that the SVAR exercises of Sims (2012) are accurate because the nonfundamental bias is mild.
KW - Nonfundamentalness
KW - SVAR
KW - DSGE
KW - News shocks
U2 - 10.1016/j.jedc.2016.08.001
DO - 10.1016/j.jedc.2016.08.001
M3 - Journal article
VL - 71
SP - 86
EP - 101
JO - Journal of Economic Dynamics and Control
JF - Journal of Economic Dynamics and Control
SN - 0165-1889
ER -