Bayesian Estimation of Inequality and Poverty Indices in Case of Pareto Distribution Using Different Priors under LINEX Loss Function

Table 5

Estimated loss functions for α, G, M, and using different priors under the assumptions of SELF.

			Uniform prior	Jeffrey’s prior	Conjugate prior
					= 0.5; = 2	= 2; = 2
For	40	2.5	0.198417	0.188773	0.105229	0.149043
		3.5	0.545553	0.315654	0.301779	0.303094
		4.5	0.636095	0.546807	0.511984	0.662855
	100	2.5	0.081056	0.080694	0.065290	0.072233
		3.5	0.178339	0.192881	0.138684	0.139510
		4.5	0.261753	0.299142	0.231038	0.215135
For	40	2.5	0.002541	0.002135	0.001879	0.053437
		3.5	0.001215	0.001071	0.001055	0.033683
		4.5	0.000989	0.000629	0.000222	0.026677
	100	2.5	0.001347	0.001311	0.001054	0.011318
		3.5	0.000604	0.000408	0.000407	0.006967
		4.5	0.000228	0.000236	0.000165	0.005405
For	40	2.5	0.085215	0.075152	0.061571	0.097215
		3.5	0.092519	0.085051	0.070570	0.102310
		4.5	0.157210	0.115720	0.095721	0.105721
	100	2.5	0.105721	0.097121	0.050712	0.098721
		3.5	0.097215	0.070125	0.033710	0.059713
		4.5	0.080712	0.052325	0.092530	0.082173
For	40	2.5	0.003513	0.004420	0.003916	0.005192
		3.5	0.001382	0.003596	0.002156	0.004921
		4.5	0.001224	0.001993	0.001057	0.003051
	100	2.5	0.001152	0.001907	0.001805	0.001982
		3.5	0.000538	0.000914	0.000705	0.001572
		4.5	0.000260	0.000896	0.000679	0.000971