Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/81922
Authors: 
De Graeve, Ferre
Westermark, Andreas
Year of Publication: 
2013
Series/Report no.: 
Sveriges Riksbank Working Paper Series 271
Abstract: 
Macroeconomic research often relies on structural vector autoregressions to uncover empirical regularities. Critics argue the method goes awry due to lag truncation: short lag-lengths imply a poor approximation to DSGE-models. Empirically, short lag-length is deemed necessary as increased parametrization induces excessive uncertainty. The paper shows that this argument is incomplete. Longer lag-length simultaneously reduces misspeci.cation, which in turn reduces variance. For data generated by frontier DSGE-models long-lag VARs are feasible, reduce bias and variance, and have better coverage. Thus, contrary to conventional wisdom, the trivial solution to the critique actually works.
Subjects: 
VAR
SVAR
Lag-length
Truncation
JEL: 
C18
E37
Document Type: 
Working Paper

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