Resources Policy最新文献

{"title":"Assessing the dual impact of gold mining on local communities: Socio-economic benefits and environmental challenges","authors":"Muhammad Haroon,&nbsp;Muhammad Hayyat","doi":"10.1016/j.resourpol.2025.105559","DOIUrl":"10.1016/j.resourpol.2025.105559","url":null,"abstract":"<div><div>This research evaluates the environmental and socio-economic effects of gold mining in the local community of Baiyun'ebo in China, where mining-induced economic growth is coupled with considerable environmental and social issues. This research combines quantitative environmental evaluations with qualitative socio-economic analysis to determine the dual consequences of gold mining. Research indicates significant environmental degradation, encompassing water contamination, soil erosion, and deforestation, with arsenic and cyanide concentrations in local rivers surpassing WHO and EPA safety limits. Socio-economic evaluations reveal that mining substantially enhances family incomes, accounting for up to 74 % of wages for artisanal miners; yet, these advantages are inequitably allocated. Community surveys reveal discontent with mining companies' practices, specifically insufficient corporate social responsibility efforts and neglect of environmental and social repercussions. Approximately 58 % of respondents had unfavorable attitudes toward mining owing to its environmental and infrastructural consequences. The research highlights the critical need for sustainable mining techniques, more stringent regulatory frameworks, and improved community involvement. Policy recommendations encompass the implementation of sophisticated environmental assessment techniques, the encouragement of alternative livelihoods, and the equitable allocation of resources to harmonize economic growth with environmental and social sustainability. Future studies should use longitudinal studies and comparative analysis across various mining locations to investigate the long-term effects and effectiveness of suggested remedies. This study offers practical insights for policymakers and stakeholders seeking to alleviate the negative impacts of gold mining while optimizing its advantages.</div></div>","PeriodicalId":20970,"journal":{"name":"Resources Policy","volume":"103 ","pages":"Article 105559"},"PeriodicalIF":10.2,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143697665","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}

{"title":"Critical minerals and structural oil shocks: Evidence from wavelet cross-quantile correlation","authors":"Seyi Saint Akadiri ,&nbsp;Oktay Ozkan","doi":"10.1016/j.resourpol.2025.105570","DOIUrl":"10.1016/j.resourpol.2025.105570","url":null,"abstract":"<div><div>Over the past decade, the intersection of energy and mineral markets has emerged as a key research focus. Transitions to renewable energy drive economic growth, reduce environmental impacts, and enhance energy diversity. Critical minerals are integral to renewable energy technologies and mitigate fossil-fuel dependence. It is against this backdrop that this study examines the dynamic interconnections between critical minerals and structural oil shocks, specifically oil supply shocks (OSSs) and oil demand shocks (ODSs), using a novel Wavelet Cross-Quantile Correlation (WCQC) approach complemented by Cross-Quantile Coherency (CQC) for robustness. Analyzing monthly data from 1975 to 2024 reveals significant long-term relationships, particularly at low frequencies, with OSSs predominantly impacting minerals linked to energy infrastructure and ODSs influencing broader industrial and economic activities. Geopolitical risks amplify these interdependencies, emphasizing the critical role of resource security in a globally interconnected economy. Policy recommendations advocate resource diversification, sustainable extraction, and innovation to mitigate the adverse impacts of energy and resource market volatility, fostering resilience and economic stability in the face of global uncertainty.</div></div>","PeriodicalId":20970,"journal":{"name":"Resources Policy","volume":"103 ","pages":"Article 105570"},"PeriodicalIF":10.2,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143679993","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}

{"title":"Waste as a resource in the green transition: Legal preconditions for secondary extraction","authors":"Maria Pettersson,&nbsp;Oskar Johansson","doi":"10.1016/j.resourpol.2025.105556","DOIUrl":"10.1016/j.resourpol.2025.105556","url":null,"abstract":"","PeriodicalId":20970,"journal":{"name":"Resources Policy","volume":"103 ","pages":"Article 105556"},"PeriodicalIF":10.2,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143680048","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Corruption, terrorism and illicit financial flows related to extractive commodity trade in Africa","authors":"Simplice A. Asongu ,&nbsp;Juste Somé","doi":"10.1016/j.resourpol.2025.105569","DOIUrl":"10.1016/j.resourpol.2025.105569","url":null,"abstract":"<div><div>The purpose of this study is to assess the incidence of illicit financial flows (IFFs) on terrorism in Africa, contingent on corruption-control. The study utilizes data from 38 African counties spanning from 2002 to 2021. In order to increase room for policy implications, the overall IFFs measure is decomposed into two main sub-components, namely: illicit financial inflows and illicit financial outflows. The empirical evidence is also based on: (i) baseline regressions, (ii) estimations with the lagged independent variables in order to control for the simultaneity dimension of endogeneity, as well as (iii) GMM in order to account for both the simultaneity and unobserved heterogeneity dimensions of endogeneity. The robustness of the empirical analysis is further improved by limiting the sample to the Sahel countries in which most of the terrorism has been documented over the past decades. It is apparent from the findings that corruption-control effectively moderates IFFs, especially illicit financial inflows, in order to engender an overall negative effect on the outcome variable or terrorism. For the most part, the corruption-control policy thresholds are within policy range. Policy implications are discussed.</div></div>","PeriodicalId":20970,"journal":{"name":"Resources Policy","volume":"103 ","pages":"Article 105569"},"PeriodicalIF":10.2,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143679992","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reducing density uncertainty in iron ore deposits: Taking advantage of the density and Fe grades correlation aiming to more accurate models","authors":"W. Emilio G. Moreno,&nbsp;Marcel Antônio Bassani,&nbsp;Diego Marques,&nbsp;João Felipe Coimbra Leite Costa","doi":"10.1016/j.resourpol.2025.105561","DOIUrl":"10.1016/j.resourpol.2025.105561","url":null,"abstract":"<div><div>This study addresses the critical role of density in the economic evaluation of mineral deposits and how uncertain could be the density models without considering the available secondary information. Most mining companies subjectively determine sample quantity and spatial distribution for density estimation. Usually, the density samples are sparser than the grade samples. Fewer samples tend to generate higher uncertainty as less information is available. Although the density has fewer samples, it is correlated positively with iron grades in an iron deposit. However, this correlation between density and grade is not considered to generate density models. In this context, this research aims to reduce the uncertainty associated with density in iron ore deposits by exploring the correlation between grades and density, using this information to create density models. Therefore, the iron grade was used as an auxiliary variable to create density models proposing different multivariate geostatistical techniques. Two cosimulation approaches were proposed. The first one uses simple cokriging to incorporate the auxiliary variable, while the second uses intrinsic collocated cokriging. These two approaches were compared against univariate geostatistical simulation, which ignores the correlation between density and grades. The results demonstrated the effectiveness of incorporating iron grades in density models, observing histogram matching, reproduction of spatial continuity, the possibility of using the E-Type as estimated models, conditional standard deviation reduction and better accuracy plots in ore and waste domains. Also, a mass analysis was performed in ore domains, making evident how consider Fe grades could change what to expect in future. The study concludes that leveraging iron grades significantly reduces uncertainty in density models, providing accurate and reliable models and proposing methodologies that could be extrapolated to estimates, being viable to create density estimated models for more effective mining planning and resource management in iron deposits.</div></div>","PeriodicalId":20970,"journal":{"name":"Resources Policy","volume":"103 ","pages":"Article 105561"},"PeriodicalIF":10.2,"publicationDate":"2025-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143679991","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}

{"title":"Globality in the metal markets: Leveraging cross-learning to forecast aluminum and copper prices","authors":"Konstantinos Oikonomou ,&nbsp;Dimitris Damigos ,&nbsp;Dimitrios Dimitriou","doi":"10.1016/j.resourpol.2025.105558","DOIUrl":"10.1016/j.resourpol.2025.105558","url":null,"abstract":"<div><div>Over the last 25 years, aluminum and copper prices have fluctuated significantly, impacting mining companies, economies of mining countries and global financial markets. Accurate price forecasting can be useful for better budget planning, strategic decision making and portfolio management. To bridge recent developments in time series forecasting with commodity price forecasting, we investigate the performance of a recently prominent framework called global forecasting or cross-learning. Juxtaposed to the local approach, under which one model would be used for each time series requiring forecasts, this framework involves the training of a single (global) model using a set of relevant time series to create future predictions. In our analysis, we assume that incorporating stock prices of mining companies into global forecasting models can enhance the prediction accuracy of aluminum and copper prices compared to traditional forecasting methods. In this direction, we use a pool of auxiliary time series that includes the prices of the two commodities and the stock prices of major companies involved in their production and processing to train global feed-forward neural networks. The models differ in their approach to selecting relevant time series used in training and are either used as standalones or in combination with standard univariate models to forecast the two commodities’ prices 3, 6 and 12 months ahead. The performance of the models is then compared to benchmark univariate (local) models, namely the naïve method, ARIMA, and autoregressive feed-forward neural networks. The analysis suggests that the incorporation of information from different (albeit related) markets achieved through cross-learning is beneficial for forecasting the prices of the two commodities since, for all forecast horizons examined, the models achieving the lowest out-of-sample error were either standalone global models or local-global ensembles.</div></div>","PeriodicalId":20970,"journal":{"name":"Resources Policy","volume":"103 ","pages":"Article 105558"},"PeriodicalIF":10.2,"publicationDate":"2025-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143679987","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}

{"title":"Exploring shock transmission and risk diversification in REIT, commodity, and green bond markets under extreme market conditions","authors":"Abdullah AlGhazali ,&nbsp;Houssem Eddine Belghouthi ,&nbsp;Mohamed Amine Nabli ,&nbsp;Walid Mensi ,&nbsp;Sang Hoon Kang","doi":"10.1016/j.resourpol.2025.105557","DOIUrl":"10.1016/j.resourpol.2025.105557","url":null,"abstract":"<div><div>This study analyzes the connectedness between international real estate investment trusts (REITs), commodity futures (Gold, Silver, WTI oil, and Brent oil), and green bonds using a quantile frequency connectedness approach. The results show a stronger connectivity during bearish and bullish market conditions. Moreover, the connectedness is more intense in the short term (medium and long terms) when markets are in a bearish (bullish) situation. The REIT markets in Canada, France, and the United States predominantly function as net shock transmitters, whereas the Hong Kong market serves as a net shock receiver. Using a quantile-on-quantile regression, we discern a positive relationship between markets during bear phases. However, this relationship reverses to a negative when REITs are bearish and other markets are bullish, indicating that commodities and green bonds serve as a safe haven and are effective for hedging and portfolio diversification. Precious metals and green bonds prove to be more effective than oil in minimizing risk in REIT-based portfolios. Overall, these findings have important implications on risk management and portfolio optimization, particularly in times of market volatility. Policy makers can utilize these findings to implement measures that alleviate the effects of cross-market shocks and strengthen financial stability.</div></div>","PeriodicalId":20970,"journal":{"name":"Resources Policy","volume":"103 ","pages":"Article 105557"},"PeriodicalIF":10.2,"publicationDate":"2025-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143679986","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}

{"title":"Does third-party monitoring reduce environmental violations in mining firms?","authors":"Renjie Zhou ,&nbsp;Yongheng Luo ,&nbsp;Zhengye Gao","doi":"10.1016/j.resourpol.2025.105565","DOIUrl":"10.1016/j.resourpol.2025.105565","url":null,"abstract":"<div><div>Compared to air and water pollution, mining pollution is often more difficult to identify and monitor due to its inherent concealment and persistence. The inadequacy of government regulatory oversight also implies the potential to leverage the widespread and continuous benefits of third-party monitoring. This study conducts a quasi-natural experiment based on the Pollution Information Transparency Index (PITI) project launched by environmental organizations to observe the net impact of third-party monitoring on firms. Using longitudinal data (2006–2018) on Chinese listed firms in the mining industry, and based on a series of endogeneity and robustness tests, we observe robust evidence that third-party monitoring can significantly reduce corporate environmental violations in mining firms. Heterogeneity analysis shows that, compared to non-open-pit mining firms, open-pit mining firms show a more pronounced improvement in the impact of third-party monitoring on corporate environmental violations. And compared to non-coal mining firms, coal mining firms are more susceptible to third-party monitoring. Mechanism analysis shows that third-party monitoring works through promoting government environmental enforcement, broader public participation, and firms' disclosure quality. Further analysis suggests that third-party monitoring can still be effective in cases where environmental enforcement is weak.</div></div>","PeriodicalId":20970,"journal":{"name":"Resources Policy","volume":"103 ","pages":"Article 105565"},"PeriodicalIF":10.2,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143680050","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}

{"title":"The predictive power of the oil variance risk premium","authors":"David G. McMillan ,&nbsp;Salem Adel Ziadat","doi":"10.1016/j.resourpol.2025.105550","DOIUrl":"10.1016/j.resourpol.2025.105550","url":null,"abstract":"<div><div>This paper examines the ability of the oil market variance risk premium (VRP) to predict both financial and key macroeconomic series. Interest in understanding the movement of such variables increasingly involves considering measures of investor risk, for which the VRP, that incorporates both implied and realised variance, has recently come to the fore. It is well established that oil price movement impacts both the stock market and wider economy and thus, we examine whether this is also true of the oil VRP. Using monthly US data over the period from 2009 to 2021, we demonstrate the nature of oil VRP predictive power for oil and stock returns, as well as output growth, unemployment, and inflation. Of notable interest, while predictability from the oil VRP series dominates at the one-month horizon and (largely) wanes at over longer time periods, the reverse is found for the stock VRP. These results are robust to the inclusion of additional, established, predictor variables. This indicates that the impact of oil market risk has a more immediate effect on both the stock market and economy, with stock market risk reflecting longer term considerations. A simple out-of-sample exercise supports the view that the inclusion of oil VRP improves forecasts over alternative models that exclude this series.</div></div>","PeriodicalId":20970,"journal":{"name":"Resources Policy","volume":"103 ","pages":"Article 105550"},"PeriodicalIF":10.2,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143679984","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Price contagion and risk spillover in the global commodities market: COVID-19 pandemic vs. global financial crisis","authors":"Md Mostafa Kamal ,&nbsp;Eduardo Roca ,&nbsp;Bin Li ,&nbsp;Chen Lin ,&nbsp;Rajibur Reza","doi":"10.1016/j.resourpol.2025.105553","DOIUrl":"10.1016/j.resourpol.2025.105553","url":null,"abstract":"<div><div>Utilizing cross-correlation-based Planar Maximally Filtered Graph, and conditional Value-at-Risk-based extreme risk spillover network approaches, we analyze the structure and dynamics of price contagion and risk transmission between different commodity groups in the global commodity futures market during the Global Financial Crisis (GFC) and different phases of the COVID-19 pandemic. As expected, owing to the fundamental differences between the two crises, we find very divergent commodity network structures and non-identical direction of risk transmission between commodities in these two crises. Gold and silver, however, continued to play their role of risk transmitters based on several factors, including the severity of the economic or political crisis, prevailing market sentiment, and the distinctive attributes of the affected asset classes in both crisis—right at the beginning of the GFC but towards the latter part of the COVID19 crisis.</div></div>","PeriodicalId":20970,"journal":{"name":"Resources Policy","volume":"103 ","pages":"Article 105553"},"PeriodicalIF":10.2,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143679985","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}