Jong-Hyo Lee  Hong-Yoon Kang  Yong Woo Hwang  and Sang-Hyun Oh

Vol. 30,  No. 3, pp. 276-286, Sep.  2024
10.7464/ksct.2024.30.3.276

Resource Productivity Gross Domestic Product (GDP) Domestic Material Consumption (DMC) multiple regression analysis Value-added from metal/non-metal resources

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Since the Paris Agreement and the surge in global interest in climate change, the importance of measuring and managing national-level resource productivity has steadily grown. However, concerns about the reliability of productivity indicators persist due to inherent uncertainties. This study estimated the metal and non-metal resource productivities of 38 OECD countries through multiple regression analysis and conducted a comparative analysis of their ranking changes according to their current resource productivities. The study results revealed that the 38 OECD countries could be classified into four categories. First, countries with low overall resource productivities due to a high economic dependence on low-value metal resources by weight exhibited a substantial rise in their non-metal resource productivity rankings. Second, countries that have minimal metal industries in their national economies but generate high value-added from these sectors showed a notable increase in their metal resource productivity rankings. Third, countries with a low proportion of metal industry in their economies and low metal resource productivities experienced significant declines in their metal resource productivity rankings. Fourth, countries with a small disparity between their metal and non-metal resource productivities showed minimal changes in their rankings for both categories. These results highlight that changes in metal resource productivity rankings were more pronounced than those for non-metal resources, which implies that the influence of non-metal resources (biomass, fossil fuels, non-metallic minerals) dominates national-level resource productivity because their economic value is higher than metal resources. These findings suggest that it is necessary to manage the economic value of each resource type as distinct statistical data to provide a more nuanced understanding of national resource productivity.