Research on the Influence of Volatility of International Energy Commodity Futures Market on CPI in China

Table 2

Average daily coal consumption of six power plants: the goodness of fit and in-sample and out-of-sample prediction accuracy at different lag orders.

Model	Index	Lag order
		15	22	25	30	35	40
Beta-MIDAS	R^2	0.8727	0.8728	0.8728	0.8685	0.8709	0.8709
	RMSE	0.5778	0.5829	0.5831	0.5444	0.5451	0.5451
	MSFE	0.3339	0.3398	0.3400	0.2964	0.2972	0.2972
	DMSFE	0.0947	0.0946	0.0946	0.0834	0.0840	0.0840
Beta-nonzero-MIDAS	R^2	0.8619	0.8599	0.8598	0.8598	0.8655	0.8652
	RMSE	0.5691	0.5496	0.5439	0.5396	0.5373	0.5412
	MSFE	0.3239	0.3021	0.2959	0.2912	0.2887	0.2929
	DMSFE	0.0972	0.0888	0.0865	0.0852	0.0858	0.0867
Exp Almon-MIDAS	R^2	0.8728	0.8728	0.8728	0.8728	0.8740	0.8740
	RMSE	0.5824	0.5824	0.5824	0.5824	0.5745	0.5745
	MSFE	0.3392	0.3392	0.3392	0.3392	0.3301	0.3301
	DMSFE	0.0945	0.0945	0.0945	0.0945	0.0924	0.0924
U-MIDAS	R^2	0.9034	0.9066	0.9093	0.9177	0.9302	0.9325
	RMSE	0.6375	0.5952	0.6266	0.5850	0.5734	0.5657
	MSFE	0.4064	0.3543	0.3927	0.3422	0.3288	0.3200
	DMSFE	0.1001	0.0936	0.1000	0.0506	0.0564	0.0700
Stepfun-MIDAS	R^2	0.8879	0.8896	0.8899	0.8898	0.9065	0.9059
	RMSE	0.5181	0.5055	0.5217	0.5231	0.5237	0.5171
	MSFE	0.2684	0.2555	0.2722	0.2736	0.2743	0.2674
	DMSFE	0.0806	0.0793	0.0858	0.0828	0.0790	0.0758
Almon-MIDAS	R^2	0.8862	0.8874	0.8873	0.8873	0.8987	0.8972
	RMSE	0.5168	0.5187	0.5202	0.5234	0.5184	0.5295
	MSFE	0.2671	0.2690	0.2706	0.2740	0.2688	0.2804
	DMSFE	0.0756	0.0791	0.0810	0.0758	0.0606	0.0772