查看更多>>摘要：? 2022This paper combines the ensemble empirical mode decomposition(EEMD) method, the transfer entropy(TE) method and complex network theory to analyze the causal relationships among Chinese mining stock prices on multiple time scales. The results show that the strength of the causal relationship among mining stocks increases with cycle growth and that the causal relationship between stocks and subindustries is asymmetric and time-varying. On the three time scales, the weighted in-degree, weighted out-degree and weighted betweenness centrality of the five subindustries all show a trend of increasing and decreasing at the same time. In addition, we construct high and low transfer entropy portfolios and find that the high transfer entropy portfolio has higher investment returns when the stock market is good, and the low transfer entropy portfolio has less investment loss when the stock market is bad. Investors are advised to pay attention to the stocks included in the high transfer entropy portfolio when the market is good, and vice versa when the market is bad. Regulators are advised to pay attention to the subindustries with heavy positions in the high transfer entropy portfolio.
查看更多>>摘要：? 2022 Elsevier LtdThe wide range of natural resource usage in economic, political and financial plans requires a complete assessment in economies like China and Brazil in order to design long-term strategies for economic stability and progress that contribute to global wealth. To serve this purpose, this study analyzes the impact of risk on volatility in natural resources in case of Brazil and China. The purpose is to make a comparative analysis of the two major economies such as Brazil and China. To serve this purpose, we employ Frequency Domain Causality (FDC) test, which can check the causal nexus between variables at three different runs. Our findings suggest that political risk index, economic and financial risks granger cause natural resource volatility at all three runs in Brazil. In case of China, economic and financial risk granger cause natural resource volatility at all three runs. However, political risk index causes natural resource volatility only in medium run to long run. In short run, PRI does not cause natural resource volatility. To sum up, this study concludes that economic, financial and political risks are considered leading challenges with significant implications for natural resource rents in Brazil and China. This study proposes that Brazil and China need to provide the foundation for sustainable development and poverty eradication by managing natural resources responsibly.
查看更多>>摘要：? 2022 Elsevier LtdThe nexus between natural resource depletion and environmental quality has been a heated topic of debate among policy experts in recent years. This nexus is crucial to achieve Sustainable Development Goal (SDG) 13 which deals with climate change mitigation. However, the extant literature has not paid due attention to this nexus, particularly in the case of Mexico. Against this backdrop, the present study examines the relationship between ecological footprint and natural resource depletion, economic growth, energy consumption, technological innovation, and foreign direct investment in the Mexican economy. The present research leverages the novel dynamic autoregressive distributed lag (ARDL) simulations approach and uses annual frequency data from 1980 to 2018. Empirical findings from the ARDL bounds test substantiate the presence of long-run association among studied variables. Furthermore, the result of the novel dynamic ARDL simulation does not validate the Environmental Kuznets curve (EKC) hypothesis. Thus, implying that Mexico's economy remains at the scale stage, with a scope of economic expansion relative to environmental quality. However, the Pollution Haven Hypothesis (PHH) is validated. Interestingly, natural resource rent accompanied with energy use and foreign direct investment deteriorate the environmental quality in the short-and long-run. However, technological innovation seems to emanate as a panacea for environmental degradation in the long-run. Result analysis also demonstrates that 10% positive and negative simulation graphs for the studied variables. The Frequency Domain Causality analysis also corroborates the above findings. These findings have far-reaching policy implications for Mexico's sustainable environment amid prudent use of natural resources, which are prescribed in the final section.
查看更多>>摘要：? 2022 Elsevier LtdThe focus on sustainable development and a green perspective is increasing for minimizing the effects of resource depletion and pollution in the economies. China has been pushing green practices to remedy the damage to the environment it has contributed in the past. There is a direct association between the stock market trading activities and surplus of current accounts on the natural resources and green environmental practices. Thus, the present study was performed to study the relationship between the stock markets and natural resource dependency in China. This study extracted the data from the Statistical yearbook of China, World Banks, and Shanghai Stock Exchange from 1981 to 2020. The novel approach of the ARDL was used to study the long-run and short-run relationships between the stock market and the natural resource dependency of China. The data of the last four decades was employed to study the variation and association between the research variables. The ARDL bounds test informed of significant cointegration among the research variables. The estimation indicated direct associations between the stock market value traded and capitalization in the long-run and short-run. The stock market capitalization and value traded of the stocks in China represent significant affluence over the dependency on natural resources. This study presents a new vision for China to develop its economic and environmental policies.
查看更多>>摘要：? 2022To cope with environmental degradation, countries around the globe are devising policies such as renewable energy, eco innovation and green financing, etc. Investment in renewable energy sources is crucial for achieving development. An increase in investment in renewable energy in the development goals are turn out to be the main concern of countries. This study examines the elements that influence the investment in renewable energy sources, as well as the importance of each aspect in case of China for the period of 1990–2020. We use Bayer-Hanck cointegration and Quantile Regression method to estimate the long run coefficients. To check the causal relationship among variables, this study employs Frequency Domain Causality (FDC) test. The results show that natural resource volatility is negatively related with investment in renewable energy. However, economic performance, technological innovation and energy efficiency have positive impact on investment in renewable energy. From results of quantile regression, it is inferred that as long as the effect of economic performance on investment in renewable energy loses trace of significance, the negative effect of natural resource volatility attains stronger statistical evidence. It implies that the positive impact of economic performance and negative impact of natural resource volatility on IRE changes its significance after a certain threshold level is achieved. There is evidence of uni-directional causality from GDP, TNR, TI and ENEF to IRE in all three runs. The findings of this study have important implications that can also be used by international organizations and other stakeholders in developing policies to improve the environment through renewable energies.
查看更多>>摘要：? 2022 The AuthorsThe focus of this ongoing study has been on two rapakivi granites, wiborgite and pyterlite, that have been utilized in St Petersburg since the 1760s but originate from south-eastern Finland. The aims of this study have been to describe the two types of rapakivi granites in their geological settings, to assess the needs for restoration of stones utilized in constructions and to establish databases of stones utilized in historical buildings and of the original and alternative quarries. The focus of this study has been on defining the original quarries for the old building stones or finding other similar substitute granite deposits. Chemical analysis with a handheld XRF instrument was found to be the most promising approach when combined with multivariate mathematical tools. In addition, the applicability of chemical treatment of the surface of rapakivi granite for changing the appearance of stones was investigated. The visual appearance and texture of natural stones used in restoration are the key factors, in addition to the stone type and quality. The chemical treatment of stone surfaces using acidic or metal salt treatments altered the colour tone and visual pattern. Thermal treatment was also found to be effective, but it might be harmful to the surface structure. With further optimisation, chemical treatment could be a feasible method to change the visual appearance of fresh stone in the case of substitution of weathered stone. In addition, this project has initiated cross-border activities that aim to create opportunities for establishing first contacts between the authorities, construction companies, stone producers and the manufacturer who produces the needed high-quality stone pieces.
查看更多>>摘要：? 2022 Elsevier LtdNon-ferrous metals play a significant role in social development. It is important for policy makers and entrepreneurs to forecast non-ferrous metals price accurately. However, existing methods are hard to obtain satisfactory results because the fluctuation rule of non-ferrous metal price is increasingly complex. Therefore, it is necessary to develop more accurate and stable forecasting method. In this paper, a multi-model fusion based non-ferrous metal price forecasting method is proposed. The dual-stage signal decomposition algorithm which combines complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and variational mode decomposition (VMD) is innovatively introduced into non-ferrous metal price forecasting. First, CEEMDAN is used to decompose the original price into several subsequences. Second, the most complex subsequence with maximum sample entropy (SE) is further decomposed by VMD. Dual-stage decomposition reveals essential features such as long-term trend and periodic fluctuations hidden in original sequence and thus lowers prediction difficulty. Besides, particle swarm optimization (PSO) is used to select optimal parameters for VMD. Finally, all subsequences are predicted by long short-term memory network (LSTM) and the results are integrated as the final prediction result. In the empirical study of London Metal Exchange (LME)'s copper, aluminum and zinc price, the proposed method is superior to all benchmark methods in terms of RMSE, MAE and MAPE. The results demonstrate that the proposed method is effective and robust.
查看更多>>摘要：? 2022 Elsevier LtdWe examine the efficiency and herding behavior between four energy markets (Crude, Brent, Gasoline, and Natural gas), five agriculture markets (Corn, Wheat, Soybeans, Cocoa, and Coffee), and three metal markets (Gold, Silver, and Copper) using multifractal detrended fluctuation method. In addition to the full sample, the analysis also uses two most critical sub-periods of GFC 2007-09 and COVID-19 to reveal hidden features and herding patterns of the commodity markets. The results indicate existence of strong multifractality patterns and resultant inefficiency with varied degrees in the commodity markets. We find highest inefficiency in the copper market, followed by silver market. While cocoa remains most efficient commodity market during the entire period of study. In addition, energy markets remain more efficient compared to the rest of the two groups. Furthermore, the results confirm that crises events impact the efficiency of commodity markets significantly, and persistence behavior with a trace of herding is found in some of the markets. Whereas, silver and gold serve as useful hedging instruments during the crises. Our study is useful for risk management, regulatory supervision, and effective decision making for investors related to investments in the commodity markets.
查看更多>>摘要：? 2022 Elsevier LtdThe backward capacity to be cleared is the focus of attention under the background of carbon neutralization, while it is still unclear whether the de-capacity policy in 2016 improves the efficient and green development of China's coal industry under this background. We attempt to examine the changes in the economic benefits, labour efficiency, and green efficiency of the coal industry, and explore the impact of the policy on China's coal industry using the differences-in-differences (DID) methods with a series of robustness tests. The main results show that: (1) The implement of de-capacity policy in 2016 has significantly improved the economic benefits of the coal industry; (2) After the implement of de-capacity policy, the labour efficiency of the coal industry have increased multiply, and the effect of de-capacity policy is positive; (3) The dynamic effect of de-capacity on green efficiency is positive but unstable. Therefore, although the coal de-capacity policy has achieved certain results, it still needs to establish and perfect the long-term advancement-ship for eliminating backward production capacity and preventing the resumption of reduced production capacity under the background of carbon neutralization.
查看更多>>摘要：? 2022This study explores the dynamic and time-varying connectedness between the US stocks, financial sector, oil and gold markets, broad market volatilities, and financial stress. We examine if the traditional association between financial stress and its important factors and strategic commodities such as oil and gold has changed during the last decade, especially after the COVID-19. We use daily data set from July 2011 to June 2021, and employ the extended joint connectedness approach of Balcilar et al. (2021), which has several advantages over traditional connectedness models. Our findings show that traditional determinants of US financial stress are dynamic and change in response to the monetary injections in late 2019 more as compared with the COVID-19. In spite of the importance of COVID-19, our analysis points towards the enhanced significance of US monetary injections in driving joint connectedness between financial stress and its prominent factors and strategic commodities. Further, gold and oil show diversification potential in a portfolio of US stocks, financial sector and broad market volatilities. Therefore, important policy and investor implications are discussed for financial stability and portfolio choices.
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