This paper assesses the applicability of the Hotelling model to non-renewable resource extraction in Africa by examining seven key minerals (bauxite, copper, gold, iron, nickel, phosphate, and tin) across 18 major producing countries. Our findings systematically reject the Hotelling model’s predictions: estimated discount rates are significantly negative across most countries and commodities, contradicting the theoretical assumption of intertemporal profit maximization. Furthermore, observed depletion times (averaging 105 years) fall markedly short of theoretical optima (240–256 years), suggesting systemic over-extraction. Results vary substantially by mineral and country, with phosphate reserves (e.g., Morocco) showing slower depletion, while copper and gold sectors (e.g., DRC, Ghana) exhibit faster extraction. These deviations suggest that the Hotelling model may be inadequate for capturing the complex realities of resource extraction in developing economies, where factors such as widespread illegal mining, institutional rigidities, political instability, and regulatory weaknesses that facilitate resource predation create different optimization conditions than those assumed by the classical model.
{"title":"Exploring mining extraction dynamics in Africa: A Hotelling model perspective with non-linear costs","authors":"Sassire Napo , Didier Tatoutchoup , Eloi Somtinda Sondo","doi":"10.1016/j.resourpol.2025.105745","DOIUrl":"10.1016/j.resourpol.2025.105745","url":null,"abstract":"<div><div>This paper assesses the applicability of the Hotelling model to non-renewable resource extraction in Africa by examining seven key minerals (bauxite, copper, gold, iron, nickel, phosphate, and tin) across 18 major producing countries. Our findings systematically reject the Hotelling model’s predictions: estimated discount rates are significantly negative across most countries and commodities, contradicting the theoretical assumption of intertemporal profit maximization. Furthermore, observed depletion times (averaging 105 years) fall markedly short of theoretical optima (240–256 years), suggesting systemic over-extraction. Results vary substantially by mineral and country, with phosphate reserves (e.g., Morocco) showing slower depletion, while copper and gold sectors (e.g., DRC, Ghana) exhibit faster extraction. These deviations suggest that the Hotelling model may be inadequate for capturing the complex realities of resource extraction in developing economies, where factors such as widespread illegal mining, institutional rigidities, political instability, and regulatory weaknesses that facilitate resource predation create different optimization conditions than those assumed by the classical model.</div></div>","PeriodicalId":20970,"journal":{"name":"Resources Policy","volume":"110 ","pages":"Article 105745"},"PeriodicalIF":10.2,"publicationDate":"2025-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145159020","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-25DOI: 10.1016/j.resourpol.2025.105750
Jamal Alnsour
Social development plays a crucial role in shaping societies, enhancing the overall quality of life, addressing social challenges, strengthening social structures, boosting economic performance, improving human resource skills, stimulating creative solutions, and creating sustainable development. The Social Progress Index (SPI) encompasses all these characteristics. The aim of this research is to investigate the effect of natural resource extraction on social development in a quadratic manner across Gulf Cooperation Council (GCC) countries from 2011 to 2023. We use energy efficiency as a social development factor and a moderator of the relationship between natural resource consumption and sustainable social development. Previous studies have hardly linked these dynamics to each other, and none have focused on GCC countries. Assessing the quadratic relationship contributes to understanding the nonlinear relationships between the variables, determining how the impacts can vary in strength or direction at different levels of the variables. To this end, we employ Bayesian regression. The empirical outcomes show that the link between natural resource extraction and social development follows a U-shaped curve. Energy efficiency improves sustainable social development and increases natural resource sustainability. We also use several control variables, including population density and technological innovation, with both factors showing a positive impact on social development. Based on these results, this study suggests establishing a comprehensive program to invest in environmental technologies that reduce energy use and improve energy efficiency. The details of this program were discussed in depth.
{"title":"Natural resource extraction, energy efficiency moderation, and sustainable development in the Gulf Cooperation Council countries","authors":"Jamal Alnsour","doi":"10.1016/j.resourpol.2025.105750","DOIUrl":"10.1016/j.resourpol.2025.105750","url":null,"abstract":"<div><div>Social development plays a crucial role in shaping societies, enhancing the overall quality of life, addressing social challenges, strengthening social structures, boosting economic performance, improving human resource skills, stimulating creative solutions, and creating sustainable development. The Social Progress Index (SPI) encompasses all these characteristics. The aim of this research is to investigate the effect of natural resource extraction on social development in a quadratic manner across Gulf Cooperation Council (GCC) countries from 2011 to 2023. We use energy efficiency as a social development factor and a moderator of the relationship between natural resource consumption and sustainable social development. Previous studies have hardly linked these dynamics to each other, and none have focused on GCC countries. Assessing the quadratic relationship contributes to understanding the nonlinear relationships between the variables, determining how the impacts can vary in strength or direction at different levels of the variables. To this end, we employ Bayesian regression. The empirical outcomes show that the link between natural resource extraction and social development follows a U-shaped curve. Energy efficiency improves sustainable social development and increases natural resource sustainability. We also use several control variables, including population density and technological innovation, with both factors showing a positive impact on social development. Based on these results, this study suggests establishing a comprehensive program to invest in environmental technologies that reduce energy use and improve energy efficiency. The details of this program were discussed in depth.</div></div>","PeriodicalId":20970,"journal":{"name":"Resources Policy","volume":"110 ","pages":"Article 105750"},"PeriodicalIF":10.2,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145159638","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-25DOI: 10.1016/j.resourpol.2025.105752
Mehdi Farhadkhani , Andrzej Kraslawski
In the era of emerging green technologies, climate-related crises are intensifying the challenges facing critical material supply chains by increasing demand for strategic minerals such as lithium. As an essential element of electric vehicles and energy storage technologies, lithium supply chain has also become a geopolitical focal point, demanding closer examination of its weaknesses and resilience.
While the importance of supply chain resilience is widely recognized, much of the existing literature relies on qualitative insights rather than quantitative assessments. This study addresses that gap by presenting a quantitative analysis of climate change impacts on the lithium supply chain, using a hybrid approach that combines Bayesian network and system dynamics modeling. This method captures both probabilistic disruptions and dynamic feedback effects, offering a more comprehensive understanding of resilience.
The research evaluates the effectiveness of three resilience-enhancing strategies—recycling, substitution, and stockpiling—under both normal and severe climate change scenarios. Simulation results indicate that climate change could raise lithium prices by 22 %–38 %, with disruptions to logistics, production, and mining as the main drivers. Recycling and substitution are shown to significantly reduce supply chain vulnerability, whereas stockpiling has minimal impact.
These findings highlight the critical role of circular economy practices and material innovation in ensuring long-term supply stability. By tackling these fundamental issues, this work contributes to resilience theory and provides actionable insights for policymakers and industry leaders preparing for climate-driven supply chain disruptions.
{"title":"Quantitative analysis of climate change impacts on the resiliency of lithium supply chain","authors":"Mehdi Farhadkhani , Andrzej Kraslawski","doi":"10.1016/j.resourpol.2025.105752","DOIUrl":"10.1016/j.resourpol.2025.105752","url":null,"abstract":"<div><div>In the era of emerging green technologies, climate-related crises are intensifying the challenges facing critical material supply chains by increasing demand for strategic minerals such as lithium. As an essential element of electric vehicles and energy storage technologies, lithium supply chain has also become a geopolitical focal point, demanding closer examination of its weaknesses and resilience.</div><div>While the importance of supply chain resilience is widely recognized, much of the existing literature relies on qualitative insights rather than quantitative assessments. This study addresses that gap by presenting a quantitative analysis of climate change impacts on the lithium supply chain, using a hybrid approach that combines Bayesian network and system dynamics modeling. This method captures both probabilistic disruptions and dynamic feedback effects, offering a more comprehensive understanding of resilience.</div><div>The research evaluates the effectiveness of three resilience-enhancing strategies—recycling, substitution, and stockpiling—under both normal and severe climate change scenarios. Simulation results indicate that climate change could raise lithium prices by 22 %–38 %, with disruptions to logistics, production, and mining as the main drivers. Recycling and substitution are shown to significantly reduce supply chain vulnerability, whereas stockpiling has minimal impact.</div><div>These findings highlight the critical role of circular economy practices and material innovation in ensuring long-term supply stability. By tackling these fundamental issues, this work contributes to resilience theory and provides actionable insights for policymakers and industry leaders preparing for climate-driven supply chain disruptions.</div></div>","PeriodicalId":20970,"journal":{"name":"Resources Policy","volume":"110 ","pages":"Article 105752"},"PeriodicalIF":10.2,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145159019","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-24DOI: 10.1016/j.resourpol.2025.105748
Dragan Miljkovic , Puneet Vatsa
This paper examines the relationships between cycles in oil prices, oil output, and production tax revenue in North Dakota, the third-largest oil-producing state in the United States. The oil industry contributed over 50% to North Dakota's total tax revenue from 2018 to 2022, highlighting the importance of understanding these relationships. The analysis proceeds in two stages. First, we use the Hamilton filter to decompose the three time series to extract their cyclical components. Then, we employ Shannon transfer entropy, an information-theoretic non-parametric technique, to analyze the lead-lag relationships between these cycles. The results show significant information flow from oil price changes to oil production tax revenue and oil output, suggesting that oil market dynamics in North Dakota were primarily driven by price changes; the most considerable flow of information occurred contemporaneously. The results also point to limited feedback from production levels to prices. Overall, these findings underscore the critical role of oil prices in shaping the state's oil production and fiscal outcomes.
{"title":"Drilling down: Oil prices, oil production, and production taxes in North Dakota","authors":"Dragan Miljkovic , Puneet Vatsa","doi":"10.1016/j.resourpol.2025.105748","DOIUrl":"10.1016/j.resourpol.2025.105748","url":null,"abstract":"<div><div>This paper examines the relationships between cycles in oil prices, oil output, and production tax revenue in North Dakota, the third-largest oil-producing state in the United States. The oil industry contributed over 50% to North Dakota's total tax revenue from 2018 to 2022, highlighting the importance of understanding these relationships. The analysis proceeds in two stages. First, we use the Hamilton filter to decompose the three time series to extract their cyclical components. Then, we employ Shannon transfer entropy, an information-theoretic non-parametric technique, to analyze the lead-lag relationships between these cycles. The results show significant information flow from oil price changes to oil production tax revenue and oil output, suggesting that oil market dynamics in North Dakota were primarily driven by price changes; the most considerable flow of information occurred contemporaneously. The results also point to limited feedback from production levels to prices. Overall, these findings underscore the critical role of oil prices in shaping the state's oil production and fiscal outcomes.</div></div>","PeriodicalId":20970,"journal":{"name":"Resources Policy","volume":"110 ","pages":"Article 105748"},"PeriodicalIF":10.2,"publicationDate":"2025-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145159021","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-23DOI: 10.1016/j.resourpol.2025.105744
Konstantinos Eleftheriou , Peter Nijkamp , Michael L. Polemis
Assessing whether and how a country is achieving sustainable growth remains one of the most controversial issues in environmental and resource economics. In particular, there is no clear empirical consensus in the existing literature on the degree of substitutability (complementarity) between human and natural capital resources, especially when spatial spillovers are present. This challenging issue calls for further theoretical and empirical insights. To advance and highlight the ongoing debate, we use a sample of 124 countries for the period 1995–2018 and utilise both an Asymmetric Error Correction Model (AECM) and an Asymmetric Spatial Error Correction Model (ASpECM) to explore the degree of substitutability between the two forms of capital. The empirical findings unveil a short-run asymmetric behaviour between human and natural capital which is evident in both types of models (spatial and non-spatial). It is noteworthy that a complementarity relationship appears to be evident when natural capital increases. However, this result is reversed when natural capital decreases, indicating that the two forms of capital are then substitutes. Finally, we find that the existence of long-run symmetry in the non-spatial model embodies a strong bias, if we take account of the existence of spatial dependence, meaning that human capital adjusts more rapidly in response to a negative deviation from its long-run equilibrium with natural capital than to a positive deviation.
{"title":"A global analysis of asymmetric sustainability effects of human and natural capital resources","authors":"Konstantinos Eleftheriou , Peter Nijkamp , Michael L. Polemis","doi":"10.1016/j.resourpol.2025.105744","DOIUrl":"10.1016/j.resourpol.2025.105744","url":null,"abstract":"<div><div>Assessing whether and how a country is achieving sustainable growth remains one of the most controversial issues in environmental and resource economics. In particular, there is no clear empirical consensus in the existing literature on the degree of substitutability (complementarity) between human and natural capital resources, especially when spatial spillovers are present. This challenging issue calls for further theoretical and empirical insights. To advance and highlight the ongoing debate, we use a sample of 124 countries for the period 1995–2018 and utilise both <em>an Asymmetric Error Correction Model</em> (AECM) and an <em>Asymmetric Spatial Error Correction Model</em> (ASpECM) to explore the degree of substitutability between the two forms of capital. The empirical findings unveil a short-run asymmetric behaviour between human and natural capital which is evident in both types of models (spatial and non-spatial). It is noteworthy that a complementarity relationship appears to be evident when natural capital increases. However, this result is reversed when natural capital decreases, indicating that the two forms of capital are then substitutes. Finally, we find that the existence of long-run symmetry in the non-spatial model embodies a strong bias, if we take account of the existence of spatial dependence, meaning that human capital adjusts more rapidly in response to a negative deviation from its long-run equilibrium with natural capital than to a positive deviation.</div></div>","PeriodicalId":20970,"journal":{"name":"Resources Policy","volume":"110 ","pages":"Article 105744"},"PeriodicalIF":10.2,"publicationDate":"2025-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145110044","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-23DOI: 10.1016/j.resourpol.2025.105747
Seyi Saint Akadiri , Oktay Ozkan
Commodity markets are becoming increasingly interdependent, exposing investors and policymakers to systemic risks that intensify during financial crises, geopolitical shocks, and the global energy transition. However, most analyses examine energy, critical minerals, and precious metals in isolation, overlooking how shocks in one market propagate to others. This study addresses this gap by integrating these three asset classes into a single connectedness framework. Using a Quantile Vector Autoregression (QVAR) model and monthly data from January 1984 to December 2024, the results show that energy commodities consistently act as the primary transmitters of spillovers, while critical minerals and precious metals play a dual role, sometimes cushioning portfolios against shocks, but at other times amplifying contagion depending on macroeconomic conditions. Evidence from the Total Connectedness Index and network visualisations highlights shifting spillover patterns, with systemic risk concentrated in coal, aluminium, copper, and silver. Portfolio-based cumulative return analysis further demonstrates that incorporating critical minerals and precious metals enhances resilience against energy-driven volatility. Robustness checks across three- and five-year horizons confirm these dynamics. These findings underscore the need to manage commodity interdependencies to mitigate systemic risk, strengthen financial stability, and build resilient investment strategies in an era of accelerating energy transition and heightened resource dependency.
{"title":"Energy, critical minerals, and precious metals: Navigating interconnectedness and portfolio strategies in investment risk management","authors":"Seyi Saint Akadiri , Oktay Ozkan","doi":"10.1016/j.resourpol.2025.105747","DOIUrl":"10.1016/j.resourpol.2025.105747","url":null,"abstract":"<div><div>Commodity markets are becoming increasingly interdependent, exposing investors and policymakers to systemic risks that intensify during financial crises, geopolitical shocks, and the global energy transition. However, most analyses examine energy, critical minerals, and precious metals in isolation, overlooking how shocks in one market propagate to others. This study addresses this gap by integrating these three asset classes into a single connectedness framework. Using a Quantile Vector Autoregression (QVAR) model and monthly data from January 1984 to December 2024, the results show that energy commodities consistently act as the primary transmitters of spillovers, while critical minerals and precious metals play a dual role, sometimes cushioning portfolios against shocks, but at other times amplifying contagion depending on macroeconomic conditions. Evidence from the Total Connectedness Index and network visualisations highlights shifting spillover patterns, with systemic risk concentrated in coal, aluminium, copper, and silver. Portfolio-based cumulative return analysis further demonstrates that incorporating critical minerals and precious metals enhances resilience against energy-driven volatility. Robustness checks across three- and five-year horizons confirm these dynamics. These findings underscore the need to manage commodity interdependencies to mitigate systemic risk, strengthen financial stability, and build resilient investment strategies in an era of accelerating energy transition and heightened resource dependency.</div></div>","PeriodicalId":20970,"journal":{"name":"Resources Policy","volume":"110 ","pages":"Article 105747"},"PeriodicalIF":10.2,"publicationDate":"2025-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145119726","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-22DOI: 10.1016/j.resourpol.2025.105726
Ji Won Moon, Sean Y. Xun, Jaewon Chung, Steven D. Textoris
In this study, major global producers of the 50 critical minerals designated by the United States government in 2022 were investigated to analyze the supply chain vulnerability to the United States by screening a single foreign country’s role at extraction, processing, and trade. The “freedom in the world” indicator was integrated into these stages to calculate the score of potential risk (Spr), which this study introduced to assess the likelihood of supply chain disruptions. The commodities with high scores of Spr (Tier 1) matched the ones with existing export-controlled critical minerals imposed by China until 2023, which include gallium, germanium, graphite, rare earths, and tungsten. In order of Spr, the remaining minerals were classified into tiers of potential supply risk: Tier 1 (Spr ≥ 50%) indicates high risk (bismuth, magnesium, antimony, and tellurium); Tier 2 (50% > Spr ≥ 32%), moderate risk (indium, vanadium, arsenic, tantalum, and zirconium); and Tier 3 (Spr < 32% with high potential risk if geopolitical conditions change), low to sensitive risk (niobium and platinum). The effectiveness of the approach was further demonstrated by the 2024 export controls implemented by China on antimony, bismuth, and magnesium, which were all classified as Tier 1 prior to the restriction. A short list of critical minerals in this study may be monitored although the current risk is low. The Spr of critical minerals provided an indicator in determining the levels and sources of potential supply risk as well as informing mitigation strategies in the years ahead.
{"title":"Assessment of critical minerals supply chain for the United States in perspective of trade restriction by foreign countries","authors":"Ji Won Moon, Sean Y. Xun, Jaewon Chung, Steven D. Textoris","doi":"10.1016/j.resourpol.2025.105726","DOIUrl":"10.1016/j.resourpol.2025.105726","url":null,"abstract":"<div><div>In this study, major global producers of the 50 critical minerals designated by the United States government in 2022 were investigated to analyze the supply chain vulnerability to the United States by screening a single foreign country’s role at extraction, processing, and trade. The “freedom in the world” indicator was integrated into these stages to calculate the score of potential risk (<em>Spr</em>), which this study introduced to assess the likelihood of supply chain disruptions. The commodities with high scores of <em>Spr</em> (Tier 1) matched the ones with existing export-controlled critical minerals imposed by China until 2023, which include gallium, germanium, graphite, rare earths, and tungsten. In order of <em>Spr</em>, the remaining minerals were classified into tiers of potential supply risk: Tier 1 (<em>Spr</em> ≥ 50%) indicates high risk (bismuth, magnesium, antimony, and tellurium); Tier 2 (50% > <em>Spr</em> ≥ 32%), moderate risk (indium, vanadium, arsenic, tantalum, and zirconium); and Tier 3 (<em>Spr</em> < 32% with high potential risk if geopolitical conditions change), low to sensitive risk (niobium and platinum). The effectiveness of the approach was further demonstrated by the 2024 export controls implemented by China on antimony, bismuth, and magnesium, which were all classified as Tier 1 prior to the restriction. A short list of critical minerals in this study may be monitored although the current risk is low. The <em>Spr</em> of critical minerals provided an indicator in determining the levels and sources of potential supply risk as well as informing mitigation strategies in the years ahead.</div></div>","PeriodicalId":20970,"journal":{"name":"Resources Policy","volume":"110 ","pages":"Article 105726"},"PeriodicalIF":10.2,"publicationDate":"2025-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145110042","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-22DOI: 10.1016/j.resourpol.2025.105749
Dejan Živkov, Boris Kuzman, Jonel Subić
Despite the significant influence of global factors on metal markets, this area remains underexplored, particularly regarding the distinction between short-term and long-term effects. This study examines the multiscale risk spillover effect from factors such as interest rates, energy markets, and developed and emerging stock markets. Additionally, it analyzes the risk transmission between precious and industrial metals. In this process, the study constructs systemic risk time-series for all markets using the Mahalanobis Distance methodology. By transforming raw data into wavelet D6 signals, long-term time-series are generated. Both raw and wavelet-based data are then integrated into a smooth transition regression model to assess nonlinear spillover effects over different time horizons. The findings reveal that precious metal markets are exposed to risk spillovers from industrial metals, energy markets, and stock markets, but only in the low-volatility regime and over the short term. In contrast, industrial metals experience spillover effects across both low- and high-volatility regimes within the short-term horizon. The most pronounced spillover effects originate from BRICS stock markets to industrial metal markets during periods of low volatility. In the long term, the results indicate that risk spillovers from industrial to precious metals become more prominent, suggesting that both markets are heavily influenced by broader economic cycles. The paper provides a wide range of results, which can be valuable for investors, portfolio managers, and policymakers.
{"title":"Analysis of factors influencing metal markets across multiple scales – A smooth transition regression approach","authors":"Dejan Živkov, Boris Kuzman, Jonel Subić","doi":"10.1016/j.resourpol.2025.105749","DOIUrl":"10.1016/j.resourpol.2025.105749","url":null,"abstract":"<div><div>Despite the significant influence of global factors on metal markets, this area remains underexplored, particularly regarding the distinction between short-term and long-term effects. This study examines the multiscale risk spillover effect from factors such as interest rates, energy markets, and developed and emerging stock markets. Additionally, it analyzes the risk transmission between precious and industrial metals. In this process, the study constructs systemic risk time-series for all markets using the Mahalanobis Distance methodology. By transforming raw data into wavelet D6 signals, long-term time-series are generated. Both raw and wavelet-based data are then integrated into a smooth transition regression model to assess nonlinear spillover effects over different time horizons. The findings reveal that precious metal markets are exposed to risk spillovers from industrial metals, energy markets, and stock markets, but only in the low-volatility regime and over the short term. In contrast, industrial metals experience spillover effects across both low- and high-volatility regimes within the short-term horizon. The most pronounced spillover effects originate from BRICS stock markets to industrial metal markets during periods of low volatility. In the long term, the results indicate that risk spillovers from industrial to precious metals become more prominent, suggesting that both markets are heavily influenced by broader economic cycles. The paper provides a wide range of results, which can be valuable for investors, portfolio managers, and policymakers.</div></div>","PeriodicalId":20970,"journal":{"name":"Resources Policy","volume":"110 ","pages":"Article 105749"},"PeriodicalIF":10.2,"publicationDate":"2025-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145110043","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-20DOI: 10.1016/j.resourpol.2025.105746
Marco A. Cotrina-Teatino , Jairo J. Marquina-Araujo , Jose N. Mamani-Quispe , Jorge Chira-Fernandez , Cesar De la Cruz-Poma , Aldo R. Castillo-Chung , Solio M. Arango-Retamozo , Joe A. González-Vasquez , Salomon M. Ortiz-Quintanilla
Amid growing global concern over the security and sustainability of critical raw material supply, mine tailings deposits are increasingly being reconsidered as strategic secondary resources. This study evaluates the revalorization potential of Tailings Deposit I at La Cienega (northern Peru) through a comprehensive methodology that integrates geochemical and mineralogical characterization with geostatistical modeling, in support of circular economy frameworks and resource governance. A total of 68 samples from drill cores and trenches were analyzed, focusing on strategic elements such as silver (Ag), lead (Pb), molybdenum (Mo), copper (Cu), antimony (Sb), zinc (Zn), cadmium (Cd), scandium (Sc), and indium (In). Average concentrations were found to be 2293.60 ppm for Pb, 719.61 ppm for Zn, and 98.65 ppm for Cu, along with spatially structured trace levels of In (0.14 ppm) and Sc (9.00 ppm). Ordinary kriging modeling yielded high correlation coefficients (R > 0.8) for Cu, Cd, and Sc, enabling robust three-dimensional estimation of recoverable resources. Mineralogical analysis identified dominant phases such as pyrite and arsenopyrite, along with secondary minerals like jarosite, which influence metal availability. The results underscore the dual character of the deposit as both an environmental liability and a latent strategic asset. Within the context of Peru's evolving institutional and regulatory framework including the MINEM–INGEMMET agreements and the roadmap toward a circular economy in mining this study provides key technical evidence to support sustainable reindustrialization policies. The selective recovery of critical metals and mitigation of toxic elements position the La Cienega deposit as a replicable case of circular mining and integrated resource governance.
{"title":"Recovery of strategic elements from mining tailings at La Cienega, Peru, through geochemical and mineralogical assessment: a focus on circular economy policy","authors":"Marco A. Cotrina-Teatino , Jairo J. Marquina-Araujo , Jose N. Mamani-Quispe , Jorge Chira-Fernandez , Cesar De la Cruz-Poma , Aldo R. Castillo-Chung , Solio M. Arango-Retamozo , Joe A. González-Vasquez , Salomon M. Ortiz-Quintanilla","doi":"10.1016/j.resourpol.2025.105746","DOIUrl":"10.1016/j.resourpol.2025.105746","url":null,"abstract":"<div><div>Amid growing global concern over the security and sustainability of critical raw material supply, mine tailings deposits are increasingly being reconsidered as strategic secondary resources. This study evaluates the revalorization potential of Tailings Deposit I at La Cienega (northern Peru) through a comprehensive methodology that integrates geochemical and mineralogical characterization with geostatistical modeling, in support of circular economy frameworks and resource governance. A total of 68 samples from drill cores and trenches were analyzed, focusing on strategic elements such as silver (Ag), lead (Pb), molybdenum (Mo), copper (Cu), antimony (Sb), zinc (Zn), cadmium (Cd), scandium (Sc), and indium (In). Average concentrations were found to be 2293.60 ppm for Pb, 719.61 ppm for Zn, and 98.65 ppm for Cu, along with spatially structured trace levels of In (0.14 ppm) and Sc (9.00 ppm). Ordinary kriging modeling yielded high correlation coefficients (R > 0.8) for Cu, Cd, and Sc, enabling robust three-dimensional estimation of recoverable resources. Mineralogical analysis identified dominant phases such as pyrite and arsenopyrite, along with secondary minerals like jarosite, which influence metal availability. The results underscore the dual character of the deposit as both an environmental liability and a latent strategic asset. Within the context of Peru's evolving institutional and regulatory framework including the MINEM–INGEMMET agreements and the roadmap toward a circular economy in mining this study provides key technical evidence to support sustainable reindustrialization policies. The selective recovery of critical metals and mitigation of toxic elements position the La Cienega deposit as a replicable case of circular mining and integrated resource governance.</div></div>","PeriodicalId":20970,"journal":{"name":"Resources Policy","volume":"110 ","pages":"Article 105746"},"PeriodicalIF":10.2,"publicationDate":"2025-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145097188","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-18DOI: 10.1016/j.resourpol.2025.105743
Tomoya Sugiyama , Xianlai Zeng , Kazuyo Matsubae
The United Nations Sustainable Development Goal 8 targets the eradication of child labor by 2050. Despite this goal, approximately 160 million children globally are engaged in child labor, with 79 million involved in hazardous work and 16.5 million in industrial sectors. Over a million children work in mining, which exposes them to significant health and safety risks and deprives them of educational opportunities. The anticipated increase in demand for minerals used in electric vehicles and batteries by 2040 will further elevate social risks in supply chains. This study quantifies the responsibility pathways of child labor within the transport equipment sectors in China, Germany, Japan, and the United States to enhance the management of human rights due to diligence. A multi-regional input–output (MRIO) model was developed to analyze child labor across agriculture, industry, and service categories, incorporating newly collected data on mining-related child labor. They also highlighted a significant link between child labor and gold mining operations. These findings underscore the urgent need to improve due diligence practices and investments in technologies that promote fair-trade and ethical sourcing. By recognizing interindustry connections and prioritizing ethical practices, this study establishes a foundation for future efforts to enhance transparency and sustainability in the transport equipment sector.
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