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We study variational shrinkage in the sparse normal means model and compare it with the corresponding exact Bayes shrinkage rule. The focus is on the excess quadratic risk of the variational posterior mean. Using a squared-loss decomposition, we show that this excess risk is bounded by the discrepancy between the variational and exact Bayes estimators together with the benchmark Bayes risk. This y
