Forecast Combination With Entry and Exit of Experts
针对调查数据中预测者频繁进出导致传统最小二乘加权不可行的问题，提出一种将实际结果对等权预测进行投影的新方法，通过模拟和通胀预测实证表明该方法能有效应对专家进出对实时预测组合性能的影响。
Combination of forecasts from survey data is complicated by the frequent entry and exit in real time of individual forecasters which renders conventional least squares regression approaches to estimation of the combination weights infeasible. We explore the consequences of this for a variety of forecast combination methods in common use and propose a new method that projects actual outcomes on the equal-weighted forecast as a means of adjusting for biases and noise in the underlying forecasts. Through simulations and an empirical application to inflation forecasts we show that the entry and exit of individual forecasters can have a large effect on the real time performance of conventional forecast combination methods. We also find that the proposed projection on the equal-weighted forecast works well in practice.