Industrial Policy-Making Using Big Data from the Product Space and Network Science
Keywords:
big data, network science, product space, economic complexityAbstract
The global trend of data production and expansion, along with the development of new methods for analyzing big data, has led to the practical application of these methods across various domains, including industrial policy-making. Most existing studies in the field of industrial policy-making have adopted qualitative approaches, with only a few employing quantitative methods. This study applies an economic complexity approach and the product space framework, utilizing big data from 235 countries in the year 2023 based on 1,224 four-digit product codes from the Harmonized System (HS), to design industrial policy for the Republic of Iraq. The findings reveal that Iraq has exhibited revealed comparative advantage (RCA) in the production and export of 15 products, which are primarily raw materials and primary commodities such as oil, minerals, and agricultural goods. By applying network science and the product space model developed by Alshamsi et al., it was also determined that there is potential for Iraq to develop a revealed comparative advantage in 88 additional products. Considering the criteria of positive opportunity gain, product complexity index, and proximity, a total of 11 products were ultimately identified and introduced as emerging opportunities for Iraq.
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Copyright (c) 2025 Yad Nawzad Abdullatif (Author); Anvar Khosravi; Kamaran Kasraei (Author)
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