Table 4 Results from Metropolis-Hastings...

Table 4

Results from Metropolis-Hastings (standard deviation of structural shocks)

	Prior			Posterior
	Dist	Param.1	Param.2	Mean	Stdev	HPD inf	HPD sup
ζ^r	invg	0.100	Inf	0.018	0.0024	0.0146	0.0223
ϵ^0,AT	invg	0.100	Inf	0.019	0.0027	0.0149	0.0235
$ϵ_{- 4}^{news,AT}$	gamm	0.041	0.0100	0.014	0.0030	0.0090	0.0187
$ϵ_{- 8}^{news,AT}$	gamm	0.041	0.0100	0.015	0.0031	0.0096	0.0199
ϵ^0,AN	invg	0.100	Inf	0.017	0.0021	0.0139	0.0207
$ϵ_{- 4}^{news,AN}$	gamm	0.041	0.0100	0.011	0.0023	0.0076	0.0151
$ϵ_{- 8}^{news,AN}$	gamm	0.041	0.0100	0.011	0.0023	0.0077	0.0152
ϵ^0,AC	invg	0.100	Inf	0.036	0.0089	0.0222	0.0497
$ϵ_{- 4}^{news,AC}$	gamm	0.041	0.0100	0.031	0.0071	0.0196	0.0425
$ϵ_{- 8}^{news,AN}$	gamm	0.041	0.0100	0.032	0.0073	0.0207	0.0445
ϵ^0,CM	invg	0.100	Inf	0.051	0.0056	0.0422	0.0603
$ϵ_{- 4}^{news,CM}$	gamm	0.041	0.0100	0.025	0.0051	0.0166	0.0332
$ϵ_{- 8}^{news,CM}$	gamm	0.041	0.0100	0.031	0.0055	0.0220	0.0400

	Prior			Posterior
	Dist	Param.1	Param.2	Mean	Stdev	HPD inf	HPD sup
ζ^r	invg	0.100	Inf	0.018	0.0024	0.0146	0.0223
ϵ^0,AT	invg	0.100	Inf	0.019	0.0027	0.0149	0.0235
$ϵ_{- 4}^{news,AT}$	gamm	0.041	0.0100	0.014	0.0030	0.0090	0.0187
$ϵ_{- 8}^{news,AT}$	gamm	0.041	0.0100	0.015	0.0031	0.0096	0.0199
ϵ^0,AN	invg	0.100	Inf	0.017	0.0021	0.0139	0.0207
$ϵ_{- 4}^{news,AN}$	gamm	0.041	0.0100	0.011	0.0023	0.0076	0.0151
$ϵ_{- 8}^{news,AN}$	gamm	0.041	0.0100	0.011	0.0023	0.0077	0.0152
ϵ^0,AC	invg	0.100	Inf	0.036	0.0089	0.0222	0.0497
$ϵ_{- 4}^{news,AC}$	gamm	0.041	0.0100	0.031	0.0071	0.0196	0.0425
$ϵ_{- 8}^{news,AN}$	gamm	0.041	0.0100	0.032	0.0073	0.0207	0.0445
ϵ^0,CM	invg	0.100	Inf	0.051	0.0056	0.0422	0.0603
$ϵ_{- 4}^{news,CM}$	gamm	0.041	0.0100	0.025	0.0051	0.0166	0.0332
$ϵ_{- 8}^{news,CM}$	gamm	0.041	0.0100	0.031	0.0055	0.0220	0.0400

Note(s): Posterior statistics are generated using 2 million draws from the posterior distribution. Invg refers to Inverse gamma distribution. For uniform prior distributions, Param.1 and Param.2 refer to the lower and upper bound of the support of the distribution, respectively. For Beta, Gamma and Inverse Gamma distributions, they refer to the mean and standard deviation, respectively

Source(s): Prepared by the authors

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