Tests of Predictive Ability for Vector Autoregressions Used for Conditional Forecasting
针对条件预测（如央行基于政策路径的预测）提出评估方法，通过蒙特卡洛模拟和实证分析检验VAR模型条件预测的偏差、效率和准确性，对宏观预测评估有参考价值。
Summary Many forecasts are conditional in nature. For example, a number of central banks routinely report forecasts conditional on particular paths of policy instruments. Even though conditional forecasting is common, there has been little work on methods for evaluating conditional forecasts. This paper provides analytical, Monte Carlo and empirical evidence on tests of predictive ability for conditional forecasts from estimated models. In the empirical analysis, we examine conditional forecasts obtained with a VAR in the variables included in the DSGE model of Smets and Wouters ( American Economic Review 2007; 97 : 586–606). Throughout the analysis, we focus on tests of bias, efficiency and equal accuracy applied to conditional forecasts from VAR models. Copyright © 2016 John Wiley & Sons, Ltd.