查看更多>>摘要：? 2022 Elsevier LtdRecent studies show that El Ni?o episodes are generally inflationary because they tend to increase the prices of agricultural commodities and crude oil. Given this, in this paper we examine the inflation-hedging property of gold (along with silver) from a novel perspective by analysing the impact of a negative shock to the negative component of Southern Oscillation Index (SOI) anomalies, i.e., El Ni?o shock. To this end, we apply a large-scale global vector autoregressive (GVAR) model to 33 countries covering both developed and emerging markets using quarterly data from 1980:Q2 to 2019:Q4. The GVAR methodology provides an appropriate framework to capture the transmission of global climate-related shocks while simultaneously accounting for individual country peculiarities. The results show that both gold and silver serve as good hedges in periods of inflation and rare disaster risks resulting from El Ni?o negative shocks. Interestingly, silver is a better hedge than gold, as implied by bigger positive real returns in response to El Ni?o shock. At the same time, La Ni?a shocks, captured by a positive effect to the positive component of SOI anomalies, fail to have a statistically significant impact on either gold or silver real returns. Overall, our results confirm the inflation-hedging benefits offered by the two precious metals, suggesting that investors can offset losses resulting from inflation-related risks stemming from El Ni?o events by investing not only in gold, but more so in silver.
查看更多>>摘要：? 2022 Elsevier LtdThe economic and political literature is not conclusive about whether large natural resource endowments diminish growth and development prospects, about the diverse political, economic, and institutional causal mechanisms that lead to Resource Curse and Dutch Disease phenomena, and about the most suitable and effective counteracting measures against these problems. This article adds further evidence to the debate through the linkages approach, primarily associated with Albert Hirschman. By calculating Rasmussen-Hirschman linkages for 42 countries from the WIOD database for 2000–2014, which are subdivided into two groups of countries - one with above and another with below OECD average fuel exports, it suggests that there is a larger likelihood that countries that export fewer fossil fuels to experience higher growth in their manufacturing sector linkages. However, because these two groups are not homogeneous in their relationship between GDP per Capita growth, the size of their linkages, and the growth of the size of their manufacturing value-added in their GDPs, a panel data econometric exercise further subdivides the two country groups in above and below-average GDP per capita. It regresses the manufacturing sector's backward and linkages with selected variables. The econometric exercise presents evidence that countries with higher GDP per capita and that export more fuels than the OECD average have a larger probability of success than countries with above-average fossil fuels exports and below OECD average GDP per capita. This shows that natural resource exploitation and fuel exports are more likely to be a curse in countries that have not reached a certain threshold of institutional quality, physical and intangible capital accumulation, making it more difficult for them to reap the fruits of natural resource exploitation fully.
查看更多>>摘要：? 2022 Elsevier LtdThis study sсrutinizеs thе financial rеsоurсе сursе hypоthеsis in Irаn frоm 1979–2018, inсоrpоrаting rеаl GDP (RGDP), real grоss fixеd саpitаl fоrmаtiоn (RGFCF), аnd humаn саpitаl (HC) into the finance dеmаnd funсtiоn. The natural resource index (NRI) is constructed using principal component analysis through oil, coal, forest, natural gas, and mineral rents. Multiple econometrics methods were used to provide a more accurate and consistent analysis, including the dynamic autoregressive distributed lag, error correction model, three cointegration regressions: fully-modified ordinary least square, dynamic OLS, and canonical cointegrating regression. Thе еmpiriсаl findings validated thе lоng-run соintеgrаtiоn bеtwееn vаriаblеs. In thе lоng run, thе financial rеsоurсе сursе hypоthеsis is rеjесtеd. It implies the blessing role of nаturаl rеsоurсеs in developing Iran's financial system. Furthеrmоrе, HC and RGFCF are pоsitivеly аnd signifiсаntly linked to finаnсiаl dеvеlоpmеnt (FD). In соntrаst, RGDP is linkеd invеrsеly tо FD, whiсh соuld bе аttributеd tо thе gоvеrnmеnt's lеаding rоlе in thе finаnсiаl systеm аnd сlаssifying Irаn аs а lоwеr-middlе-inсоmе есоnоmy. Furthеrmоrе, this study provides pоliсymаkеrs with new frеsh insights into how tо use nаturаl rеsоurсеs аs an есоnоmiс policy instrument to improve the financial sector's performance. Finаlly, аpprоpriаtе pоliсy impliсаtiоns аrе prоvidеd fоr thе gоvеrnmеnt аnd pоliсymаkеrs.
查看更多>>摘要：? 2022 The Author(s)Lithium is one of the rare raw materials needed to produce high-capacity batteries. Electric cars, said to be the future of automobility, have already begun to replace oil and gasoline-powered cars. This paper analyzes price sensitivity of the world's largest lithium producers in U.S. and China to the Brent crude oil price changes. Since there are no direct ways to invest in lithium commodity, investors might gain exposure to lithium prices thorough investments into lithium mining companies. We focus on the time-varying dependency between returns of lithium producers and Brent crude oil as well as the potential volatility spillover effect between lithium and oil. We find that returns of American lithium mining stocks are in general weakly correlated to the changes of oil prices, but they are still more strongly correlated than the returns of Chinese companies. The dynamics of correlations are similar within a market, but different across markets. The tail dependence is the strongest for the pairs of American and pair of Chinese companies, but no dependence is found for oil and lithium producers. From the portfolio management perspective oil and lithium stocks are good diversifiers, but as the correlations are time-varying such outcomes are temporary.
查看更多>>摘要：? 2022 Elsevier LtdIn this paper, we have constructed the physical and monetary asset account of mineral resources in India using the SEEA framework. We have used the Net Present Value approach to prepare the monetary asset account of Manganese Ore, Iron Ore, and Bauxite. We found that reserves of all three mineral resources have declined from 1995 to 2015 due to the steady growth of mineral extraction. The extraction rate of bauxite was faster than that of iron ore and manganese ore. Though all the minerals gave negative resource rents to the economy in 1995, it turned positive and recorded growth in the subsequent years. Because of negative resource rent in 1995, NPVs of all minerals were negative in 1995. Overall, the NPV of the resources has grown remarkably from 1995 to 2015. Our research contributes to the target two of SDG 12 which aims to achieve the sustainable management and efficient use of natural resources by 2030.
查看更多>>摘要：? 2022 Elsevier LtdThis study proposes a new hybrid model that combines LSTM and BiLSTM neural networks with GARCH type model forecasts using an ensemble approach to forecast volatility for one-day ahead 95% and 99% Value-at-Risk (VaR) estimates using the Parametric (PAR) and Filtered Historical Simulation (FHS) method. The forecasting abilities of the standard GARCH (GARCH), exponential GARCH (eGARCH), and threshold GARCH (tGARCH) models are combined with the LSTM networks to capture different characteristics of the underlying volatility. We evaluate the model using log returns on Crude Oil during two periods of extreme volatility: the 2007-09 Financial Crisis and the Covid Recession of 2020–21. The performance of hybrid models is compared against several traditional VaR methods like the Historical Simulation, Bootstrap, Age weighted method, and the volatility-based VaR models using the GARCH, LSTM, and BiLSTM model forecasts. The unconditional and conditional coverage tests and a combination of regulator and firm loss functions are used to evaluate the quality of VaR forecasts. We find a significant improvement in the quality and accuracy of the VaR forecasts of the hybrid models over all the other models across all loss functions and coverage tests. The FHS-BiLSTM-HYBRID, a proposed FHS-based hybrid model, combining the BiLSTM model with three GARCH-type models, is the best performing, with the lowest values for both loss functions. The traditional and GARCH-type models do not efficiently model volatility during the crisis periods resulting in poor VaR forecasts. The FHS consistently performs as the best method for generating VaR compared to all other approaches.
查看更多>>摘要：? 2022 Elsevier LtdOur work presents risk analysis for twelve major global commodity futures during the financial crises and post-crisis period. We perform in-sample and out-of-sample risk analysis which includes equal predictive accuracy model and univariate GAS models for during and post-crisis periods. We also perform a backtesting procedure for providing better information about the predictive strength. We report that the models of all commodities show equal predict accuracy except for Gold whose models exhibit differing predictive accuracies. Among all models, ALD appears as best fitted for Natural Gas, Crude Oil-WTI, Gold, Silver, Aluminum, and Zinc under crises (Eurozone and global financial crises) and post-crisis period. However, SNORM performs best for Diesel and Natural Gas under crises and post-crisis period, respectively. Our paper entails implications for policymakers and investors.
查看更多>>摘要：? 2022 Elsevier LtdRecently, nickel is a critical metal for manufacturing stainless steel, rechargeable electric vehicle batteries, and alloys utilized in the state-of-the-art technologies. The use of more environmentally friendly electric vehicles has become widespread and brought tackling climate change to forefront, especially for reducing greenhouse gas emissions. Therefore, the demand for rechargeable batteries that power electric vehicles and the need for the nickel in the production of these batteries will increase as well. In addition to those, nickel prices significantly impact mine investment decisions, mine planning, economic development of nickel companies, and countries that depend on nickel resources. However, there is uncertainty about how the nickel price will trend in the future, and the solution to this problem attracts the attention of researchers. For forecasting nickel price, this paper proposes recurrent neural networks-based on long short-term memory (LSTM) and gated recurrent unit (GRU) networks, classified as deep learning algorithms. Mean absolute percentage error (MAPE) was used as the performance measure to compute the accuracy of the proposed techniques. As a result, it has been determined that the LSTM and GRU networks are very useful and successful in forecasting the nickel price variations owing to having average MAPE values of 7.060% and 6.986%, respectively. Furthermore, it has been observed that GRU networks surpassed the LSTM networks by 33% in terms of average computational time.
查看更多>>摘要：? 2022 Elsevier LtdThe informal artisanal and small-scale mining (ASGM) sector in Ghana has been engrossed with grave environmental challenges and practices. Whereas some ideologies call for its perpetual banning, others believe efficient reformation of the sector is rather required. This study sought to assess the impacts of informal ASGM on the environment and the root causes of why these illegal mining activities are very prevalent after several attempts to formalize or ban them. It further sought to assess the mitigation measures to reduce their footprint for sustainable mineral extraction. A semi-structured interview guide, field observations, and sampling were used to obtain relevant data for further analysis. Results indicated that informal ASGM had detrimental impacts on water and soil resources. Although the miners were aware of the detrimental effects of their activities, the desire for basic life necessities for their families and survival remained their priority than the conservation of the environment. It was further revealed that the lack of sustainable alternative sources of livelihood, the general economic hardship and unemployment, the “quick and easy” way of making money in informal ASGM, and the political influence in the sector remains a major driving force for illegal mining in Ghana. So far as the cost of “action” on sustainable practices in ASGM is comprehended more than the benefits of reducing the adverse impacts, interventions for better practices will not be supported even at the government level. Purely political solutions will not fix what is basically an economic problem. This study, therefore, calls for broader and continual stakeholder engagements in developing workable policies that will not seek to outrightly criminalize informal mining but help improve it. This study recommends that informal ASGM should be harnessed to bring economic prosperity to stakeholder's rather than to be treated as an evil venture. The provision of sustainable alternative jobs, preferably in the mining sector, is encouraged to help reduce active participation in this illicit activity. Right technological, finance, and technical skills investments can be key to achieving this.
查看更多>>摘要：? 2022 Elsevier LtdEnvironmental degradation has continued to be a significant global challenge; hence, it is consistently drawing attention from policymakers and academics. Therefore, this study further contributes to the literature by investigating the contributions of natural resource rents and globalisation to environmental degradation in the 5 richest African economies from 1990 to 2019. Four techniques were applied: the fixed and random effect, feasible generalised least squares and the augmented mean group. The Hausman test was used to affirm the supremacy of the feasible generalised least squares outcomes and, consequently, its use to derive the study inferences. A Dumitrescu and Hurlin causality test was also employed to determine the direction of causality between the subject variables. Findings from the study showed that natural resource rents significantly contribute to environmental degradation. In contrast, globalisation reduces environmental degradation. Urbanisation, which served as a control measure, enhanced environmental sustainability. Robustness checks on the study models revealed the validity and reliability of the models' inferences. The Additional outcomes from the robustness checks revealed that while economic growth has no substantial effect on environmental degradation, human capital development significantly worsens the environment. The study highlights relevant policy actions that could substantially reduce environmental degradation.
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