We consider the estimation of the location parameter θ in the normal location model and study the sampling properties of shrinkage estimators derived from a non-standard Bayesian approach that places the prior on a scaled version of θ, interpreted as the ‘population t-ratio.’ We show that the finite-sample distribution of these estimators is not centred at θ and is generally non-normal. In the asymptotic theory, we prove uniform n^(1/2)-consistency of our estimators and obtain their asymptotic distribution under a general moving-parameter setup that includes both the fixed-parameter and the local-parameter settings as special cases.
Giuseppe De Luca, Jan R. Magnus, Franco Peracchi (2025). Bayesian Estimation of the Normal Location Model: A Non-Standard Approach. OXFORD BULLETIN OF ECONOMICS AND STATISTICS [10.1111/obes.12672].
Bayesian Estimation of the Normal Location Model: A Non-Standard Approach
Giuseppe De Luca
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Membro del Collaboration Group
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2025-01-01
Abstract
We consider the estimation of the location parameter θ in the normal location model and study the sampling properties of shrinkage estimators derived from a non-standard Bayesian approach that places the prior on a scaled version of θ, interpreted as the ‘population t-ratio.’ We show that the finite-sample distribution of these estimators is not centred at θ and is generally non-normal. In the asymptotic theory, we prove uniform n^(1/2)-consistency of our estimators and obtain their asymptotic distribution under a general moving-parameter setup that includes both the fixed-parameter and the local-parameter settings as special cases.File | Dimensione | Formato | |
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