Bayesian Estimation of Archimedean Copula-Based SUR Quantile Models

Table 5

Absolute Bias and MSE of parameter estimates from the Bayesian estimation of the Clayton copula with different sample sizes.

Parameter	Absolute Bias			MSE
= 0.25	= 100	= 500	= 1000	= 100	= 500	= 1000
	0.0819	0.0172	0.0100	0.0912	0.0123	0.0060
	0.0598	0.0033	0.0010	0.0793	0.0141	0.0052
	0.0488	0.0130	0.0093	0.0641	0.0132	0.0058
	0.0171	0.0105	0.0026	0.0915	0.0153	0.0047
	0.0571	0.0114	0.0098	0.0682	0.0145	0.0060
	0.0114	0.0131	0.0016	0.0747	0.0162	0.0045
	0.7584	0.2990	0.2099	0.7940	0.8015	0.6381
= 0.50	= 100	= 500	= 1000	= 100	= 500	= 1000
	0.0414	0.0148	0.0098	0.0473	0.0101	0.0041
	0.0109	0.0010	0.0007	0.0650	0.0104	0.0044
	0.0405	0.0087	0.0015	0.0379	0.0091	0.0040
	0.0291	0.0087	0.0045	0.0750	0.0091	0.0037
	0.0328	0.0121	0.0095	0.0497	0.0104	0.0035
	0.0094	0.0016	0.0013	0.0535	0.0089	0.0040
	0.8278	0.4235	0.2075	0.7639	0.2002	0.1655
= 0.75	= 100	= 500	= 1000	= 100	= 500	= 1000
	0.0183	0.0026	0.0009	0.0646	0.0095	0.0049
	0.0059	0.0012	0.0013	0.0822	0.0158	0.0073
	0.0178	0.0048	0.0033	0.0533	0.0103	0.0056
	0.0252	0.0037	0.0013	0.0816	0.0104	0.0049
	0.0290	0.0190	0.0057	0.0709	0.0107	0.0054
	0.0061	0.0010	0.0010	0.0715	0.0164	0.0045
	0.5555	0.5387	0.4306	0.3322	0.2926	0.2831