宏
生产(经济)
宏观层面
微观层面
计量经济学
经济
计算机科学
产业组织
宏观经济学
微观经济学
经济影响分析
程序设计语言
作者
Ilaria Fusacchia,Enrico Marvasi,Silvia Nenci,Federico Sallusti,Luca Salvatici
标识
DOI:10.1080/09535314.2025.2498172
摘要
This paper introduces a novel methodology to improve the accuracy of trade data for analyzing supply chain structures. Integration of micro-level information into Inter-Country Input-Output tables reveals previously overlooked variations in firms' sourcing patterns and the allocation of imported inputs across sectors. Applying this methodology to the Global Trade Analysis Project Data Base and leveraging Italian micro-level data, we identify the significance of within-sector variations in the role of trading partners. For instance, in the transport equipment sector, conventional models overestimate inputs from the United States and underestimate those from China, with discrepancies reaching up to 15 percentage points. These refinements improve the representation of trade patterns and the accuracy of policy-oriented economic models. Furthermore, the methodology's adaptability facilitates its application to other countries, fostering international research collaboration. Overall, this approach strengthens the reliability of supply chain research and offers valuable insights for industrial and trade policy design.
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