Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/234814 
Authors: 
Year of Publication: 
2020
Series/Report no.: 
Document de travail No. 2020-14
Publisher: 
Université du Québec à Montréal, École des sciences de la gestion (ESG UQAM), Département des sciences économiques, Montréal
Abstract: 
This paper pursues two objectives. First, we determine the sufficient condition for local, statistical identification of SVAR processes through the third and fourth unconditional moments of the reduced-form innovations. Our findings provide novel insights when the entire system is not identified, as they highlight which subset of structural parameters is identified and which is not. Second, we elaborate a tractable testing procedure to verify whether the identification condition holds, prior to the estimation of the structural parameters of the SVAR process. To do so, we design a new bootstrap procedure that improves the small-sample properties of rank tests for the symmetry and kurtosis of the structural shocks.
Subjects: 
Bootstrap procedure
excess kurtosis
identification condition
rank test
skewness
structural vector autoregression
JEL: 
C12
C32
C51
Document Type: 
Working Paper

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