查看更多>>摘要：? 2022 Elsevier LtdThis study investigates the effect of natural resources rents and information and communications technology (ICT) infrastructure on the size of the informal economy in Sub-Saharan African countries. It does so by using different measures of the informal economy, resources rents, and ICT and employs pooled OLS and IV-2SLS estimators to estimate two-way fixed effects models. The study covers 42 countries and spans the period 1991–2015. The results reveal that while natural resources rents increase the size of the informal economy, ICT has a mixed direct effect on the informal economy. More interestingly, the results reveal that resources rents reduce the size of the informal economy in countries with higher accessibility to ICT. African states need to ensure transparent management of natural resources revenues but also use these revenues to increase public spending to support growth and diversification to create more jobs in the formal sector. They should also invest more in ICT infrastructure to help mobilize domestic resources.
查看更多>>摘要：? 2022 Elsevier LtdThe goal of carbon neutralization in 2060 in China have stressed the importance of increasing energy efficiency in energy-intensive industries, while the factor market distortion has seriously hindered the effective allocation of resources. Focusing on the metallurgical industry, this paper seeks to explore the influence of eliminating factor price distortion on energy efficiency, which could not only provide elaborate recommendations in this crucial sector but also have theoretical implications for building an efficient energy system in the future. To fulfill this goal, we first measure the relative price distortion of production factors in the metallurgical industry, and then explore the impact of dispelling the relative price distortion on total factor energy efficiency on the basis of inter-factor substitution elasticity. The results show that the relative price distortion among production factors exists in China's metallurgical industry, and the prices of labor and energy are relatively higher than that of capital. Eliminating factors price distortion would bring an 18.8% growth in energy efficiency in China's metallurgical industry. Hence, the process of market-oriented reform in the factor market should be accelerated to help construct an efficient energy system in China.
查看更多>>摘要：? 2022 Elsevier LtdNatural resource commodities are considered an important factor for economic growth and development. However, volatility in these commodities is a topic of interest, which currently has the attention of scholars. In this regard, the current study investigates volatility in global natural resource commodities while undertaking the Covid-19 pandemic. This study used coal rents (CR), forest rents (FR), mineral rents (MR), natural gas rents (NGR), oil rents (OR), and total natural resource rents (TNRR) to comprehensively measure volatility in natural resource commodities during the period from 1971 to 2020. For empirical investigation of volatility, this study employed autoregressive conditional heteroscedasticity (ARCH) specification, which indicates that CR, FR, MR, and NGR hold no volatility throughout the study period. However, OR and TNRR are found to be volatile throughout the period and during the Covid-19 pandemic. Besides, the generalized threshold ARCH (TGARCH) and exponential generalized ARCH (EGARCH) provide no evidence of positive-negative shocks asymmetry. Also, the results do not provide evidence that negative shock enhances volatility in natural resource commodities more than that of positive shock having the same magnitude. Based on the empirical findings, this study recommends some policy implications in the end.
查看更多>>摘要：? 2022 Elsevier LtdChina's economy is experiencing a rapid revival in the post Covid-19 era, while energy consumption is surging and environmental pressure is prominent. Environmental protection expenditure is an important means for local governments to improve environmental quality; it plays a crucial role in guiding market investment, providing environmental treatment funds and energy conservation and utilization. Based on a sample of 286 prefecture-level cities in China from 2007 to 2017, this study analyzes environmental governance effects of local environmental protection expenditure while considering the time duration, regional differences, and spatial spillover characteristics of industrial pollution emissions. The results reveal that local environmental protection expenditure could help reduce industrial pollution emissions in Chinese cities; however, the governance effects were heterogeneous in different clustering city groups. In addition, the effects of environmental protection expenditure at the neighborhood level varied greatly; the results showed that the stronger the spillover of pollutants, the more significant was the trans-regional governance effect of local environmental protection expenditure. Therefore, local governments should promote a cooperative mode of “joint prevention and control and cross-regional governance” when treating pollutants with strong spillover potential.
查看更多>>摘要：? 2022In the period of extreme events, this paper aims to study the extreme risk transmission between Bitcoin and crude oil market by using the extreme Granger causality test to test their causal relationship under extreme and non-extreme shocks. First, we can obtain different shocks of Bitcoin and crude oil returns based on empirical quantiles. Second, considering the different role that these shocks played in the causality between Bitcoin and crude oil, we conduct our research by testing the causality among different pairwise shocks. Further, given that these relationships may be changed at different time horizons, we also detect them from a frequency-domain perspective. Hence, we not only find the strong evidence of extreme risk transmission between Bitcoin and crude oil but also investigate the time-varying characteristic of this transmission, which may have a great impact on market participants and scholars related to Bitcoin-oil relations.
查看更多>>摘要：? 2022 Elsevier LtdThis study proposes a new method for crude oil future price forecasting. The original crude oil futures price series is decomposed into a series of sub-sequences using the improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) method, and the permutation entropy (PE) method is employed to reconstruct these sub-sequences into high-frequency, low-frequency, and trend components. Using the kernel extreme learning machine (KELM) optimised by the chaotic sparrow search algorithm (CSSA), the low-frequency component and trend component are predicted. However, the high-frequency component is decomposed secondary to the empirical mode decomposition (EMD) method, and the PE and CSSA-KELM models are employed again to obtain the linear integrating prediction result for the high-frequency component. Finally, the forecasting results of the high-frequency, low-frequency, and trend components are nonlinearly integrated with the CSSA-KELM model, and the final forecasting value for crude oil futures prices is obtained. To verify the effectiveness of the proposed model, we empirically forecast the Brent and WTI crude oil futures prices. The empirical results show that the approach proposed in this study improves forecasting accuracy compared to other benchmark models and has good robustness.
查看更多>>摘要：? 2022 Elsevier LtdIn order to promote the adjustment of energy consumption structure and achieve the national emission reduction target, the paper takes China as the research object, collects data from 2007 to 2019, and uses ARDL (autoregressive distributed lag) model and Granger causality test methods to explore the equilibrium relationship of regional renewable energy consumption and carbon dioxide emissions. Conclusions as follows: (1) The boundary test of the ARDL model confirms that when renewable energy consumption is used as the explained variable, the boundary test results are not significant, and when carbon emissions are used as the explained variable, the boundary test results are significant, confirming the impact of China's renewable energy consumption on carbon emissions is significant; (2) The long-term elasticity coefficient of China's renewable energy consumption on carbon emissions is negative, and passed the significance test, indicating that renewable energy consumption has a significant negative effect on carbon emissions in long-term. The short-term elasticity coefficient is also negative, but did not pass the significance test, indicating that the short-term impact on renewable energy consumption is not statistically significant. (3) when the lag period is 1, 2, 3, and 4 years, Chinese renewable energy consumption constitutes the Granger reason for the carbon emission intensity; when the lag period is 3, 4 years, the carbon emission intensity constitutes the Granger reason for the change in renewable energy consumption; and when the lag period is one or two years, the carbon emission intensity does not constitute the Granger reason for the change in renewable energy consumption. Understanding the relationship between regional renewable energy consumption and carbon emissions in China is conducive to balancing regional and alleviating the conflict between regional low-carbon development and instability, helping to achieve nationwide carbon emission reduction commitments in advance, and formulating regional development policies according to local conditions.
查看更多>>摘要：? 2022The current study investigates volatility in natural resources commodity prices by estimating volatility in oil rents, natural gas rents, and total natural resources rents. This study utilized data for two developed economies, namely: Japan and the United Kingdom (UK), covering the period from 1990 to 2020. In order to analyze volatility, we utilized autoregressive conditional heteroscedasticity (ARCH), threshold generalized autoregressive conditional heteroscedasticity [TGARCH(1, 1)], and exponential generalized autoregressive conditional heteroscedasticity [EGARCH(1, 1)] specifications. The empirical findings reveal that only natural gas is volatile in Japan. Also, natural gas showed asymmetry, where negative shock severely affects natural gas volatility. In the case of the UK, all the three rents are found volatile. However, oil rents and total natural resources rents are symmetric throughout the period. While natural gas rents are asymmetric, the negative shock highly influences volatility during the study period. Besides, there is a negative association of current variance with the past variances of natural gas rents. Based on the empirical findings, this study suggests the stabilization of the financial system, recovery from the Covid-19 pandemic crisis, adoption of price ceiling policies, and regulation of natural resources prices.
查看更多>>摘要：? 2022This research analyzes the embodied environmental impacts in the global trade network of aluminum in 2020. To do so, we combine life cycle assessment with complex network analysis. The global trade of aluminum is subdivided into ores and concentrates, compounds, products, and waste. The end goal of this study is to identify the key countries of the aluminum trading network and to aid policymakers in creating sound trade policies that lower global environmental impacts. We find that the trade of highly processed products has limited influence on the trade of environmental impacts, while raw materials and metal scraps have a large contribution. Mainland China, India, Turkey, Germany, the United States, Spain, and Belgium are key intermediate countries and act as transferring hubs of environmental impacts from neighboring countries to emerging economies. To reduce the environmental impacts embedded in the trade of aluminum, we recommend for the key intermediate countries to monetize the embedded environmental impacts in the form of tariffs. We also suggest that upstream countries with low-emission technologies should support—and be supported by—downstream countries in a concerted effort to reduce environmental pressure.
查看更多>>摘要：? 2022 Elsevier LtdNew technologies have significant effects on increasing efficiency and improving the productivity of industries, especially the mining industry. Nevertheless, selecting and applying new technologies is a multi-criteria decision-making issue. As mines constitute an important part of a country's economy with a considerable impact on socio-economic development, mining smartening should be carried out to increase efficiency. This research proposes a novel framework for assessing and prioritizing smart mining strategies by integrating the Z-number theory and fuzzy-VIKOR technique. Eight copies of a questionnaire containing five strategies (alternatives) and 11 criteria were presented to an eight-member team of experts. The strategies comprised “A1 provision of government incentives to mines to use up-to-date technologies”, “A2 development of mining cooperation with research centers and R&D to develop new technologies required by mines”, “A3 investment of mine owners in providing the required infrastructure”, “A4 development of green mining and safe operations”, and “A5 training and improving active human resources”. Moreover, the criteria consisted of “C1 employment”, “C2 energy consumption”, “C3 hazards”, “C4 trained human resources”, “C5 marketing and sales”, “C6 environment”, “C7 risk”, “C8 culture”, “C9 technology”, “C10 quality of mineral products”, and “C11 legislations”. Furthermore, a parametric sensitivity analysis was performed to determine the effectiveness and robustness of the five suggested strategies. The results of the proposed hybrid model confirm that the third strategy (A3) is the most appropriate alternative for implementing Industry 4.0 technologies in the large-scale mines of Iran. The results revealed that the presented approach provided a stationary ranking mechanism for smart mining engineering strategies and that the weight of the maximum group utility measure did not substantially affect ranking strategies. An expert group confirmed the obtained results and the evaluation and validation made of the influential factors and conditions of the study area.
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