论文标题
潜在的DIRICHLET分配模型用于世界贸易分析
Latent Dirichlet Allocation Models for World Trade Analysis
论文作者
论文摘要
国际贸易是经济学研究领域之一。如今，鉴于数据的可用性，用于分析的工具可以得到补充和丰富的新方法和技术，这些方法和技术超出了传统方法。本文显示了潜在的Dirichlet分配模型的应用，这是一种自然语言处理领域的众所周知的技术，用于在国际贸易的产品空间中寻找潜在的维度，并随着时间的推移在国家 /地区的分布。我们将此技术应用于1962年至2016年的国家出口数据集的数据集。研究结果表明，根据经验证据，有可能生成更高级别的商品分类，并允许研究国家内部分类的分布。后者显示了有关国家贸易专业化的有趣见解。
The international trade is one of the classic areas of study in economics. Nowadays, given the availability of data, the tools used for the analysis can be complemented and enriched with new methodologies and techniques that go beyond the traditional approach. The present paper shows the application of the Latent Dirichlet Allocation Models, a well known technique from the area of Natural Language Processing, to search for latent dimensions in the product space of international trade, and their distribution across countries over time. We apply this technique to a dataset of countries' exports of goods from 1962 to 2016. The findings show the possibility to generate higher level classifications of goods based on the empirical evidence, and also allow to study the distribution of those classifications within countries. The latter show interesting insights about countries' trade specialisation.
