工具箱
范围(计算机科学)
经济一体化
人工智能
政策学习
光学(聚焦)
机器学习
推论
区域一体化
经济模型
计算机科学
经济
区域科学
管理科学
社会学
宏观经济学
国际贸易
物理
光学
程序设计语言
作者
Philippe De Lombaerde,Dominik Naeher,Hung Trung Vo,Takfarinas Saber
标识
DOI:10.1016/j.jpolmod.2023.07.001
摘要
Due to its focus on prediction rather than causal inference, machine learning has long been treated somewhat neglectfully in the economic literature. For several reasons, however, interest in machine learning has surged recently and is slowly finding its way into the econometric toolbox. Within the economic literature, regional integration has been one of the research areas at the forefront of this development, with various studies experimenting with different machine learning techniques to shed light on the complex dynamics governing regional integration processes. This paper provides the first systematic review of the literature that uses machine learning to study regional economic integration. The focus is twofold, first analysing studies along various thematic and methodological features (and the links between them), and then discussing the scope and nature of policy insights derived from the surveyed body of literature.
科研通智能强力驱动
Strongly Powered by AbleSci AI