Improved Inference for Moving Average Disturbances in Nonlinear Regression Models

Table 1

Simulation results for 𝑛=10, 95% CI.

𝛾	Method	Central coverage	Upper error	Lower error	Average bias
−0.9	LR	0.9120	0.0685	0.0195	0.0245
	Wald	0.9155	0.0405	0.0440	0.0173
	BN	0.9385	0.0285	0.0330	0.0058
−0.6	LR	0.9285	0.0655	0.0060	0.0298
	Wald	0.9250	0.0560	0.0190	0.0185
	BN	0.9390	0.0275	0.0365	0.0070
−0.3	LR	0.9180	0.0610	0.0210	0.0200
	Wald	0.9015	0.0690	0.0295	0.0243
	BN	0.9405	0.0260	0.0335	0.0047
0	LR	0.8510	0.0585	0.0905	0.0495
	Wald	0.8150	0.0805	0.1045	0.0675
	BN	0.9365	0.0280	0.0355	0.0068
0.3	LR	0.8650	0.0760	0.0590	0.0425
	Wald	0.8230	0.0825	0.0945	0.0635
	BN	0.9380	0.0295	0.0325	0.0060
0.6	LR	0.9090	0.0370	0.0540	0.0205
	Wald	0.8730	0.0410	0.0860	0.0385
	BN	0.9360	0.0305	0.0335	0.0070
0.9	LR	0.8890	0.0170	0.0940	0.0385
	Wald	0.8630	0.0215	0.1155	0.0470
	BN	0.9345	0.0295	0.0370	0.0083