Hafner, Christian
[UCL]
Herwartz, Helmut
Wang, Shu
Independent component analysis has recently become a promising data-based approach to detect structural relations in multivariate dynamic systems in cases when apriori knowledge about causal patterns are scant. This paper suggests a kernel-based ML estimation that is largely agnostic with regard to the distributional features of the structural origins of data variation and enables causal analysis under the assumption of having only a subset of independent shocks. In an empirical application to the global oil market model of Kilian (2009) we illustrate the benefits of allowing for an unmodelled higher-order dependence among the oil supply and speculative oil demand shocks.
Bibliographic reference |
Hafner, Christian ; Herwartz, Helmut ; Wang, Shu. Causal inference with (partially) independent shocks and structural signals on the global crude oil market. LIDAM Discussion Paper ISBA ; 2023/04 (2023) 48 pages |
Permanent URL |
http://hdl.handle.net/2078.1/271450 |