Tests of Equal Predictive Ability With Real-Time Data
研究了在实时修订数据下，对非嵌套和嵌套线性回归模型的多步预测进行等预测精度检验的渐近和有限样本性质，并通过蒙特卡洛模拟评估检验的尺寸和功效，最后用实时数据检验经济活动指标对通胀的预测能力。
This paper examines the asymptotic and finite-sample properties of tests of equal forecast accuracy applied to direct, multistep predictions from both nonnested and nested linear regression models. In contrast to earlier work in the literature, our asymptotics take account of the real-time, revised nature of the data. Monte Carlo simulations indicate that our asymptotic approximations yield reasonable size and power properties in most circumstances. The paper concludes with an examination of the real-time predictive content of various measures of economic activity for inflation. This article has supplementary material online.