تقرير
International Trade Flow Prediction with Bilateral Trade Provisions
| العنوان: | International Trade Flow Prediction with Bilateral Trade Provisions |
|---|---|
| المؤلفون: | Pan, Zijie, Gordeev, Stepan, Zhao, Jiahui, Meng, Ziyi, Ding, Caiwen, Steinbach, Sandro, Song, Dongjin |
| سنة النشر: | 2024 |
| المجموعة: | Computer Science Quantitative Finance |
| مصطلحات موضوعية: | Quantitative Finance - Statistical Finance, Computer Science - Computational Engineering, Finance, and Science, Computer Science - Machine Learning |
| الوصف: | This paper presents a novel methodology for predicting international bilateral trade flows, emphasizing the growing importance of Preferential Trade Agreements (PTAs) in the global trade landscape. Acknowledging the limitations of traditional models like the Gravity Model of Trade, this study introduces a two-stage approach combining explainable machine learning and factorization models. The first stage employs SHAP Explainer for effective variable selection, identifying key provisions in PTAs, while the second stage utilizes Factorization Machine models to analyze the pairwise interaction effects of these provisions on trade flows. By analyzing comprehensive datasets, the paper demonstrates the efficacy of this approach. The findings not only enhance the predictive accuracy of trade flow models but also offer deeper insights into the complex dynamics of international trade, influenced by specific bilateral trade provisions. |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2407.13698 |
| رقم الأكسشن: | edsarx.2407.13698 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |