Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors
利用调查数据中不同预测期的观测误差，提出多期随机波动率模型来估计时变不确定性，相比简单方差方法提高了调查预测不确定性测度的准确性。
We estimate uncertainty measures for point forecasts obtained from survey data, pooling information embedded in observed forecast errors for different forecast horizons. To track time-varying uncertainty in the associated forecast errors, we derive a multiple-horizon specification of stochastic volatility. We apply our method to forecasts for various macroeconomic variables from the Survey of Professional Forecasters. Compared to simple variance approaches, our stochastic volatility model improves the accuracy of uncertainty measures for survey forecasts.