概率评估的聚合：欧元区通货膨胀和实际利率预测密度的正则化混合
On the Aggregation of Probability Assessments: Regularized Mixtures of Predictive Densities for Eurozone Inflation and Real Interest Rates
摘要：
我们提出了构造正则化混合密度预测的方法。我们探索了各种目标和正则化惩罚，并将其用于对欧元区通胀和实际利率密度预测的实质性探索。所有的通货膨胀预测者（即使是事后最好的预测者）都被我们的正则化混合模型所超越。从大衰退开始，最优正则化倾向于将密度预测的概率质量从中心移动到尾部，纠正过度自信。
英文摘要：
We propose methods for constructing regularized mixtures of density forecasts. We explore a variety of objectives and regularization penalties, and we use them in a substantive exploration of Eurozone inflation and real interest rate density forecasts. All individual inflation forecasters (even the ex post best forecaster) are outperformed by our regularized mixtures. From the Great Recession onward, the optimal regularization tends to move density forecasts' probability mass from the centers to the tails, correcting for overconfidence.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
