Refining Set Identification in VARs through Independence

Working Paper: NBER ID: w29316

Authors: Thorsten Drautzburg; Jonathan H. Wright

Abstract: Identification in VARs has traditionally mainly relied on second moments. Some researchers have considered using higher moments as well, but there are concerns about the strength of the identification obtained in this way. In this paper, we propose refining existing identification schemes by augmenting sign restrictions with a requirement that rules out shocks whose higher moments significantly depart from independence. This approach does not assume that higher moments help with identification; it is robust to weak identification. In simulations we show that it controls coverage well, in contrast to approaches that assume that the higher moments deliver point-identification. However, it requires large sample sizes and/or considerable non-normality to reduce the width of confidence intervals by much. We consider some empirical applications. We find that it can reject many possible rotations. The resulting confidence sets for impulse responses may be non-convex, corresponding to disjoint parts of the space of rotation matrices. We show that in this case, augmenting sign and magnitude restrictions with an independence requirement can yield bigger gains.

Keywords: No keywords provided

JEL Codes: C32; C51


Causal Claims Network Graph

Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.


Causal Claims

CauseEffect
structural shocks (t) (E32)forecast errors (ut) (C53)
higher moments (C69)structural shocks (t) (E32)
independence requirement + sign restrictions (C22)structural shocks (t) (E32)
traditional identification methods (C26)structural shocks (t) (E32)
higher moments (C69)impulse response functions (IRFs) (F47)
non-normality (C46)robustness of identification (C50)

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