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Multidimensional Knowledge Graph Embeddings for International Trade Flow Analysis

Author

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  • Durgesh Nandini
  • Simon Bloethner
  • Mirco Schoenfeld
  • Mario Larch

Abstract

Understanding the complex dynamics of high-dimensional, contingent, and strongly nonlinear economic data, often shaped by multiplicative processes, poses significant challenges for traditional regression methods as such methods offer limited capacity to capture the structural changes they feature. To address this, we propose leveraging the potential of knowledge graph embeddings for economic trade data, in particular, to predict international trade relationships. We implement KonecoKG, a knowledge graph representation of economic trade data with multidimensional relationships using SDM-RDFizer, and transform the relationships into a knowledge graph embedding using AmpliGraph.

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  • Durgesh Nandini & Simon Bloethner & Mirco Schoenfeld & Mario Larch, 2024. "Multidimensional Knowledge Graph Embeddings for International Trade Flow Analysis," Papers 2410.19835, arXiv.org.
    • Handle: RePEc:arx:papers:2410.19835
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    References listed on IDEAS

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    1. Egger, Peter & Larch, Mario, 2008. "Interdependent preferential trade agreement memberships: An empirical analysis," Journal of International Economics, Elsevier, vol. 76(2), pages 384-399, December.
    2. di Giovanni, Julian & Levchenko, Andrei A. & Rancière, Romain, 2011. "Power laws in firm size and openness to trade: Measurement and implications," Journal of International Economics, Elsevier, vol. 85(1), pages 42-52, September.
    3. Simon Blöthner & Mario Larch, 2022. "Economic determinants of regional trade agreements revisited using machine learning," Empirical Economics, Springer, vol. 63(4), pages 1771-1807, October.
    4. Fally, Thibault, 2015. "Structural gravity and fixed effects," Journal of International Economics, Elsevier, vol. 97(1), pages 76-85.
    5. Jeroen Hinloopen & Charles van Marrewijk, 2006. "Comparative Advantage, the Rank-size Rule, and Zipf's Law," Tinbergen Institute Discussion Papers 06-100/1, Tinbergen Institute.
    6. Borchert, Ingo & Larch, Mario & Shikher, Serge & Yotov, Yoto V., 2021. "The International Trade and Production Database for Estimation (ITPD-E)," International Economics, Elsevier, vol. 166(C), pages 140-166.
    7. Luca De Benedictis & Lucia Tajoli, 2011. "The World Trade Network," The World Economy, Wiley Blackwell, vol. 34(8), pages 1417-1454, August.
    8. Jaideep Anand & Gerald McDermott & Ram Mudambi & Rajneesh Narula, 2021. "Innovation in and from emerging economies: New insights and lessons for international business research," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 52(4), pages 545-559, June.
    9. Peter Egger & Kevin Staub, 2016. "GLM estimation of trade gravity models with fixed effects," Empirical Economics, Springer, vol. 50(1), pages 137-175, February.
    10. Xavier Gabaix, 2009. "Power Laws in Economics and Finance," Annual Review of Economics, Annual Reviews, vol. 1(1), pages 255-294, May.
    11. Roberto Basile & Pasquale Commendatore & Luca De Benedictis & Ingrid Kubin, 2018. "The impact of trade costs on the European Regional Trade Network: An empirical and theoretical analysis," Review of International Economics, Wiley Blackwell, vol. 26(3), pages 578-609, August.
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