Working Paper: CEPR ID: DP8209
Authors: Mario Forni; Luca Gambetti
Abstract: We derive necessary and sufficient conditions under which a set of variables is informationally sufficient, i.e. it contains enough information to estimate the structural shocks with a VAR model. Based on such conditions, we suggest a procedure to test for informational sufficiency. Moreover, we show how to amend the VAR if informational sufficiency is rejected. We apply our procedure to a VAR including TFP, unemployment and per-capita hours worked. We find that the three variables are not informationally sufficient. When adding missing information, the effects of technology shocks change dramatically.
Keywords: FAVAR models; information; nonfundamentalness; structural VAR; technology shocks
JEL Codes: C32; E32; E62
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| Technology shocks (D89) | Structural shocks (E32) |
| Total factor productivity (TFP) (O49) | Structural shocks (E32) |
| Unemployment (J64) | Structural shocks (E32) |
| Per capita hours worked (J29) | Structural shocks (E32) |
| Technology shocks (D89) | Hours worked (J22) |
| Technology shocks (D89) | Unemployment (J64) |
| Technology shocks (with principal components) (E39) | Hours worked (J22) |
| Technology shocks (with principal components) (E39) | Unemployment (J64) |