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Figure 1: Kernel density estimator (in full line) of the distribution of the EbEE errors for the estimation of the parameters involved vech(Ω). Figure 2: Kernel density estimator (in full line) of the distribution of the EbEE errors for the estimation of the parameters involved A. 13
Figure 3: Kernel density estimator (in full line) of the distribution of the EbEE errors for the estimation of the parameters involved diag(B). Figure 4: Kernel density estimator (in full line) of the distribution of the EbEE errors for the estimation of the parameters involved C. 14
Page 1 and 2: MPRA Munich Personal RePEc Archive
Page 3 and 4: matrix. Recent developments in the
Page 5 and 6: denoted by tr(A), the determinant i
Page 7 and 8: To ensure the positivity of the vol
Page 9 and 10: ⎛ ⎞ ⎛ ⎞ where Ω = ⎝ ω 1
Page 11 and 12: where ⎛ Γ = ⎜ ⎝ ⎞ −J −
Page 13: Table 1: Sampling distribution of t
Page 17 and 18: Table 2: Sampling distribution of t
Page 19 and 20: The proofs of i), iii) and i) are v
Page 21 and 22: For all δ > 0, there exists V(θ (
Page 23 and 24: By the similar arguments used to sh
Page 25 and 26: Under Assumption A11 and using the
Page 27 and 28: where Ψ is a d 1 ×d 2 matrix, d 1
Page 29: Hafner, C.M. and A. Preminger (2009

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