Multi-Frequency Information Flows between Global Commodities and Uncertainties: Evidence from COVID-19 Pandemic

Table 2

Non-linearity tests for global commodities and uncertainties.

Returns	Teraesvirta’s neural network test	White neural network test	Keenan’s one-degree test for non-linearity	Tsay’s test for non-linearity	Likelihood ratio test for threshold non-linearity
Aggregated commodities
Acommodity	17.319	19.247	0.036	4.395	3.624
Aenergy	9.803	8.238	0.014	0.086	4.960
Ametals	0.113	0.091	1.396	2.090	10.698
Imetals	0.313	0.353	0.018	0.244	2.736
Energy
Brent	9.058	7.807	0.393	0.134	2.170
Gasoline	7.287	6.471	0.001	0.050	1.582
Htoil	0.792	0.586	0.085	0.184	2.060
Ngas	0.856	0.916	2.940	1.748	17.061
Petroleum	12.271	9.671	1.058	2.351	18.076
Agricultural
Cocoa	3.002	2.879	0.839	0.912	1.800
Coffee	0.619	0.519	0.001	1.378	1.114
Corn	0.767	0.792	0.003	0.028	4.294
Cotton	1.282	1.174	0.001	0.306	1.069
Soybeans	2.063	1.989	0.001	0.156	3.164
Wheat	0.386	0.390	3.137e − 07	2.167	2.123
Metals
Gold	2.478	3.109	5.493	0.304	2.053
Lead	6.485	4.559	0.126	0.123	13.472
Nickel	3.450	2.868	1.620	1.933	4.078
Palladium	0.836	4.285	15.793	3.55	31.494
Zinc	1.763	1.843	0.013	0.163	1.238
Uncertainties
EPU	3.691	2.596	2.413	3.142	7.467
Gvolatility	5.631	5.623	0.004	0.273	3.469
OVX	2.566	1.746	0.050	0.280	2.883
VCRIX	1.066	1.308	4.893e − 05	57.75	1.609
VIX	1.199	2.819	0.150	0.209	4.980

Note. ^∗, ^∗∗, and ^∗∗∗ indicate significance at 10%, 5%, and 1% levels, respectively.