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Elsevier Science
Resources policy

Elsevier Science

0301-4207

Resources policy/Journal Resources policySCISSCIISSHPEIAHCI
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    Forest and mineral volatility and economic performance: Evidence from frequency domain causality approach for global data

    Xie, MingtingRazzaq, AsifDagar, VishalIrfan, Muhammad...
    8页
    查看更多>>摘要:It is evident that countries with abundant natural resources have comparatively higher wealth sources. However, there is no conclusive evidence regarding the impact of natural resources on economic performance. Therefore, this study aims to analyze the impact of mineral and forestry resources volatility on economic performance using a frequency domain causality approach and Breitung-Candelon spectral ganger causality for global data. For this purpose, we employ Autoregressive conditional heteroskedasticity (ARCH), Threshold Generalized ARCH (TARCH), and the exponential general ARCH (EGARCH) methods. The results confirm an uni-directional causality from mineral and forestry resources volatility to economic performance in the short, medium, and long run. There is no feedback effect observed from economic growth to volatility in mineral and forestry resources. The results suggest that sustainable use of material resources is imperative to achieve green growth agenda.

    Gold price forecasting using multivariate stochastic model

    Madziwa, LawrencePillalamarry, MallikarjunChatterjee, Snehamoy
    12页
    查看更多>>摘要:Commodities prices are pivotal to the mineral investment decision and have a considerable impact on mining companies' financial performance and countries that depend on mineral resources. Therefore, understanding the future mineral price movement is critical for revenue-based planning both for the company and the country. In this article, the Autoregressive Distribution Lag (ARDL) model was used to forecast annual gold prices using gold demand, treasury bills rates, and lagged gold prices as covariates. Augmented Dickey Fuller and the Phillips Perron methods were used to test for unit roots and found that all the variables were integrated of order one. Subsequently, the cointegration test was undertaken, which indicated that there is no cointegration between the variables. This entailed application of the short-run version of the ARDL to forecasts and consequent analysis. A Granger causality analysis show that gold demand Granger causes gold price; and that treasury bill rates do not Granger cause gold price. Lastly, the ARDL (4, 4, 2) model, which provides best ARDL forecast results, was evaluated against two other forecasting methods namely stochastic mean reverting, and Autoregressive Integrate Moving Average (ARIMA). Results showed that the ARDL model emerged as a best of all the three forecasting methods to forecast annual gold prices.

    Perspectives and strategies for LNG expansion in Qatar: A SWOT analysis

    Meza, AbelKoc, MuammerAl-Sada, Mohammed Saleh
    15页
    查看更多>>摘要:During the 2010s, the global LNG markets, production, and infrastructure went through a remarkable evolution. Countries like Australia, the US, and Russia have registered records of sanctioned LNG capacity to export all over the world, pushing Qatar to reconsider of expanding its LNG production in the market. Nevertheless, an unexpected blow came in early 2020 with the COVID19 pandemic, which resulted in a demand shock in the LNG market. With the LNG exporters locked in a boom and bust cycle for the next years, it is time to make an in-depth SWOT analysis of the LNG market, exporters, importers, production, and capacity. We analyze challenges and opportunities the exporters would likely face in their future expansion projects. This analysis identifies the internal and external factors playing a crucial role in expanding LNG infrastructure to formulate strategies from Qatar's perspectives to strengthen its position in the market. The paper concludes that, in the short term, even under the heightened competition of new LNG oversupply, the COVID-19 economic shock and collapsing demand reinforced some trends and threats, but the LNG market would recover faster than other energy sectors. Qatar will continue to be a reliable, responsive, and low-cost supplier due to its strengths such as large and efficient production capacity, flexible and agile logistics network, long-term market relations, and leadership position in the market. In the long-term, it is expected that the crisis may act to balance out the market in supply and demand terms, generating new opportunities and leading from the punctual but significant effects of the pandemic to a regrowth of the market, with reaping benefits for Qatar.

    Digital transformation in the resource and energy sectors: A systematic review

    Maroufkhani, ParisaDesouza, Kevin C.Perrons, Robert K.Iranmanesh, Mohammad...
    11页
    查看更多>>摘要:The forces of digital transformation have delivered significant benefits like sustainable development and economic growth in a range of early adopter industries such as retail and manufacturing but, despite these potential benefits, the resource and energy sectors have been relative latecomers to digitalization simply because they are frequently slower to absorb new technologies. Here we present the results of a systematic literature review identifying the ways in which digital technologies have been applied in the oil and gas, mining, and energy domains. We applied content and descriptive analysis to evaluate and discuss 151 academic articles selected from the Scopus database. Two particularly interesting trends emerge from the analysis. First, over 75% of the papers were about the energy sector excluding the oil & gas industry, and only a small minority were from the mining or oil & gas sectors. Second, the most frequently discussed objective of digital transformation was the reduction of operational expenses. By surveying the different ways in which these innovations have been used in these industries and identifying trends and patterns in how digital technologies have been applied, the findings of this review deepen our understanding of the current state of digital technologies within the resource and energy sectors and, in so doing, shine a useful amount of light on the contributions that digital transformation has made to businesses in these sectors. This paper also highlights for future scholars, practitioners, and policymakers the six research areas that they should focus on in the future to help the resource and energy sectors accelerate the digital transformation process and improve their ability to deliver value with these innovations.

    A critical assessment of Guyana's sustainability pathway: Perspectives from a developing extractive economy

    Mentis, AlanMoonsammy, Stephan
    14页
    查看更多>>摘要:The primary purpose of this research article is to present existing and forecasted sustainability indicators for Guyana in order to assess the country's sustainable development pathway. Genuine Savings, Carbon Emissions and Forest Cover were selected as appropriate measures of weak sustainability to investigate the country's sustainability trajectory. Further exploration of macro-economic variables such as natural capital stocks, wealth accumulation, resource rents and economic growth as empirical indicators, revealed that despite the effective forest management policies currently implemented in the country, Guyana is not on a sustainable pathway especially on the outlook for Genuine Savings. The country will experience an increase in economic growth primarily from the expansion of its oil sector. The potential boom in the economy from the non-renewable oil industry will provide a surge in foreign exchange that will require a robust investment structure to utilize resource rents in building the country's renewable capital stock. Positive Carbon Emission predictive trends emerging from this study are indicative of the country's growth towards more carbon intensive industries as the potential oil industry can stimulate a positive emission rating globally, indirectly from downstream industries on the international markets that purchases the country's oil.

    Measuring natural resources rents volatility: Evidence from EGARCH and TGARCH for global data

    Ni, XiewenWang, ZanxinAkbar, AhsanAli, Sher...
    14页
    查看更多>>摘要:Natural resources and their impact on various economic and non-economic indicators have been a topic of interest for the last few decades. However, natural resources volatility has been relatively less explored by researchers. Following the recent trend, this study measures natural resource volatility from a global perspective. This study used the data for total natural resources rents (TNR), coal rents (CR) oil rents (ORR) and natural gas rents (NGR) over the extended period from 1970 to 2021. Appropriate measures of volatility in time variables, the threshold generalized autoregressive conditional heteroscedasticity (TGARCH) and the exponential generalized autoregressive conditional heteroscedasticity (EGARCH) models are used to measure volatility in the study variables. Empirical findings of the study asserted that the TNR, CR, and ORR are volatile in the selected time period. Instead of stability, these rents follow an unstable path during the study period. In contrast, no volatility has been observed in NGR. Besides, the TGARCH and EGARCH approach revealed that the influence of negative shock is greater and stronger on the three volatile variables. Events such as the energy price hike, Gulf war, Asian financial crisis, the global financial crisis, and others are the events that report higher volatility. Based on the empirical findings, this study suggests price ceiling or price freezing policies, natural resources hedging, isolation of natural resources rents from external shocks to tackle volatility in natural resources rents.

    Role of green finance, volatility and risk in promoting the investments in Renewable Energy Resources in the post-covid-19

    Li, ZeyunKuo, Tsung-HsienWei Siao-YunLuu The Vinh...
    10页
    查看更多>>摘要:Among the climate change policies, improving energy efficiency and investment in renewable sources are considered key driving forces that may lead to sustainable outcomes over a longer period. This study aims to provide new insight into the role of green financing, volatility, and geopolitical risk in dealing with the investment in renewable energy sources through micro and macro-level data during 2015-2020 in China. Several benchmarks and other regression estimation approaches were applied to address the study title while considering both direct and indirect association between the variables of interest. The study findings have shown that green financing (in the form of green bonds) and green regulations like environmental taxes play a significant and positive role in promoting investment in renewable energy sources. However, oil price volatility and geopolitical risk adversely impact the investment pattern for the clean energy sources in China when controlling the firm size and corporate governance practices. The study also justifies the moderating role of green regulations while strengthening the relationship between green financing and investment in renewable energy. Based on the study findings, it is recommended that green firms in China should be promoted so that investment in renewable energy sources would be considered as a long-term strategy. Comprehending both theoretical and empirical findings, the study has provided meaningful insights for policymakers and environmentalists to design and implement environmental practices that have sustainable returns.

    The role of renewable energy and natural resources for sustainable agriculture in ASEAN countries: Do carbon emissions and deforestation affect agriculture productivity?

    Chopra, RitikaMagazzino, CosimoShah, Muhammad IbrahimSharma, Gagan Deep...
    14页
    查看更多>>摘要:The adoption of Sustainable Development Goals (SDG) in 2015 shifted the attention towards sustainability-related concerns in both developing and developed counties. The aim of this paper is to examine how agricultural productivity - a key driver in achieving many of these SDGs - is affected by carbon emissions, deforestation, renewable energy consumption, natural resources, and regional integration for the ten Association of Southeast Asian Nations (ASEAN) countries. Using the Mean Group (MG) class estimators, able to tackle the cross-sectional dependence in the data, empirical findings reveal that environmental degradation (in the form of CO2 emissions) reduces agricultural productivity in the region. Both the forest area and natural resource variables negatively affect the productivity of the agricultural sector, while the use of renewable energy sources positively contributes to the agricultural sector. However, despite being one of the highest integrated regions in the world, regional integration among the ASEAN members does not boost their agricultural productivity. The causality tests confirm the existence of bidirectional causality between agricultural productivity and renewable energy consumption, and unidirectional causality across a few other variables. Accordingly, the study provides policy recommendations for the governments of ASEAN economies on improving the environmental performance of agriculture and achieving the SDGs by 2030.

    Improved Z-number based fuzzy fault tree approach to analyze health and safety risks in surface mines

    Jiskani, Izhar MithalYasli, FatmaHosseini, ShahabRehman, Atta Ur...
    15页
    查看更多>>摘要:Surface mining is vulnerable and subject to a wide range of risks, requiring extensive risk analysis to ensure mine health and safety (MHS). Fault tree analysis (FTA) is a graphic representation tool for conducting safety and reliability analyses by modeling causal chains that lead to failures. However, conventional FTA cannot deal with uncertain and imprecise information. Therefore, in order to handle the uncertainty arising from lack of complete information and to enhance the reliability of qualitative judgment of experts, the concepts of Z-numbers and fuzzy theory are combined with FTA. The proposed approach used expert elicitation to comprehensively analyze MHS risks related to machine/equipment, environment, and workplace. Through causal inquiries of the FTA, 8 undesired events and 65 underlying basic events are explored and analyzed, taking into account the probability of occurrence of all basic events. Further, a sensitivity analysis is performed using Fussell-Vesely Importance and Risk Reduction Worth Methods to verify the model and examine how each of the basic events contributes to the occurrence of any undesirable incident. Results reveal that issues associated with blasting, dust, and explosive fumes are the most probable incidents to occur among the undesired events. The main basic events causing MHS risks result from non-implementation of regulations, staff incompetence, improper safety perimeter setting, and explosive calculations. This study assists practitioners in making risk management decisions and implementing corrective measures. The proposed approach can also be applied to investigate similar risk factors in different industries.

    Dynamic connectedness in non-ferrous commodity markets: Evidence from India using TVP-VAR and DCC-GARCH approaches

    Mishra, Aswini KumarGhate, Kshitish
    14页
    查看更多>>摘要:This study seeks to conduct a comprehensive analysis of the return and volatility spillover dynamics between a network of base metals, in the Indian context, for the time period ranging from January 2011 to March 2020. This paper aims to study the dynamic connectedness between the metal markets by employing the time-varying parameter vector autoregressions (TVP-VAR) framework to analyze return spillovers and the dynamic conditional correlation-generalized autoregressive conditional heteroskedasticity (DCC-GARCH) approach to investigate the volatility spillovers. The results of the TVP-VAR approach show that Zinc, Lead and Nickel are the primary transmitters of disturbances that in turn affect the returns of other metals in the network. At the same time, Copper and Tin are the net receivers of return spillovers. The DCC-GARCH approach reveals that Tin, Aluminium and Zinc are continuous net transmitters of volatility shocks in the network, while Nickel and Lead are the net receivers. Overall, our analysis reveals a definite and substantial level of interconnectedness and implied market risk that exists within the base metal markets, both in terms of returns and volatility. This study therefore suggests a need to reduce the degree of portfolio diversification that involves base metals. These findings may be of particular relevance to policymakers and risk management professionals who seek to understand the risk associated with the base metal commodity markets in an emerging economy.