【Abstract】In this note, we contrast prediction performance of nine econometric and machine learning methods, including a new hybrid method combining model averaging and machine learning, using data from the film industry and social media. The results suggest that machine learning methods have an advantage in addressing short-run noise, whereas traditional econometric methods are better at capturing long-run trend. In addition, once sample heterogeneity is controlled, the new hybrid method tends to strike a right balance in dealing with both noise and trend, leading to superior prediction efficiency.

　　【Keywords】Regression Tree, Bagging, Model Averaging, Big Data, Social Media Sentiment

　　该文于2018年3月在线发表于《Applied Economics Letters》，该期刊为经济与管理学院B类奖励期刊。

　　链接地址：https://www.tandfonline.com/doi/full/10.1080/13504851.2018.1441499