Working Paper: CEPR ID: DP10763
Authors: Paul Beaudry; Patrick Féve; Alain Guay; Franck Portier
Abstract: When a structural model has a nonfundamental VAR representation, standard SVAR techniques cannot be used to properly identify the effects of structural shocks. This problem is known to potentially arise when one of the structural shocks represents news about the future. However, as we shall show, in many cases the nonfundamental representation of a time series may be very close to its fundamental representation implying that standard SVAR techniques may provide a very good approximation of the effects of structural shocks even when the nonfundamentalness is formally present. This leads to the question: When is nonfundamentalness a real problem? In this paper we derive and illustrate a diagnostic based on a R2 which provides a simple means of detecting whether nonfundamentalness is likely to be a quantitatively important problem in an applied settings. We use the identification of technological news shocks in US data as our running example.
Keywords: business cycles; news; nonfundamentalness; SVAR
JEL Codes: E3
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| nonfundamental VAR representation (C32) | standard SVAR techniques cannot properly identify the effects of structural shocks (C22) |
| nonfundamentalness (D52) | identification of technological news shocks (O33) |
| nonfundamentalness (D52) | approximations of structural shocks' effects (C51) |
| $R^2$ from sufficient information test (C29) | quantifies severity of nonfundamentalness problem (C62) |
| relative bias in recovering true structural shocks (C51) | approximately half of $R^2$ of projection of misspecified structural shocks on true shocks (C59) |