Machine learning versus econometrics: prediction of box office

作者：Yan Liu, Tian Xie · 发表于：Applied Economics Letters · 年份：2018 · DOI：10.1080/13504851.2018.1441499 · 被引用次数：31 · 研究领域：Sports Analytics and Performance、Complex Systems and Time Series Analysis、Financial Markets and Investment Strategies

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.