查看更多>>摘要：? 2022 Elsevier LtdThis paper investigates the predictive power of economic policy uncertainty on the Chinese low-carbon market volatility and takes into account realized measures. First, in-sample analysis shows that both economic policy uncertainty and intraday high-frequency information have a significant impact on low-carbon index volatility. Second, out-of-sample evaluations show that the model combining China's economic policy uncertainty and intraday high-frequency information has the best predictive power. Finally, we use several robustness tests of alternative macroeconomic variable, alternative forecasting window, and alternative realized measure to prove that the results of this study are robust. This study enriches the market volatility model research. In addition, it can also promote low-carbon investment and provide a reference for national macro-control.
查看更多>>摘要：? 2022 Elsevier LtdAchieving accurate exchange rate forecasts has a significant impact in construction of international trade and currency markets. However, because of the volatility of exchange rate series, accurate exchange rate prediction is still a difficult issue. In prior studies, researchers tend to conduct prediction research on individual variables of the real exchange rate and ignore the direct influence of other relevant economic factors on the real exchange rate forecasts, which leads to unsatisfactory prediction accuracy. At present, oil price shocks are often used as the dominant factor to explain the actual exchange rate behavior, and the analysis of the relationship between the two has become a hot issue. To explore the direct impact of oil prices on the real effective exchange rate forecast, a bivariate scheme is proposed, proving the important effect of oil price variable on exchange rate forecasting. The framework of this article starts from two aspects. First, several Copula functions are used to study the relationship between the two sequences, and the basic Copula functions including Clayton, Gumbel, and Frank functions are selected, and the three Copula functions are employed to obtain a hybrid Copula function using the improved Dragonfly optimization strategy. Next, a binary forecasting framework is constructed and a data preprocessing method is added to construct a forecasting model. Finally, this article demonstrates that the bivariate scheme achieves better forecasting capabilities than the univariate forecasting frame.
查看更多>>摘要：? 2022 Elsevier LtdRecent work has suggested that precious metals can be used as inflation hedges in several African nations. A closer examination of the data suggests there is little merit to using precious metals for this purpose. While consumer prices, platinum prices, and (potentially) the exchange rate may be threshold cointegrated in Ghana, Morocco, and Tanzania, whether platinum can be used as a respite from an inflation shock depends on the regime in which the shock occurs. Independently of the degree of central bank independence and the inflation targeting regime, the search for a suitable inflation hedge in many African nations continues.
查看更多>>摘要：? 2022 Elsevier LtdCrude oil is an important global commodity, and its price fluctuation affects the political and economic security of a country. Therefore, it is necessary to conduct crude oil price forecasting. Based on the forecasting research of multi-source information and decomposition-ensemble, we combine the two into a model and propose a multi-perspective crude oil price forecasting model under a new decomposition-ensemble framework. Specifically, the crude oil price series is decomposed and reconstructed into several modes through variational mode decomposition (VMD) and fuzzy entropy (FE). Further, we screen the effective predictors from structured and unstructured multi-source data using the Granger causality test, and select the optimal input features through random forest - recursive feature elimination (RF-RFE). Finally, each reconstruction mode is individually forecasted on the basis of the selected different input features and the forecasting values obtained are combined and integrated; the final result is obtained from the integrating prediction results through the error evaluation criterion. The West Texas Intermediate (WTI) daily spot price is adopted to validate the performance of our proposed model. The empirical results show that compared with the benchmark models, the proposed model can significantly improve forecasting accuracy.
查看更多>>摘要：? 2022 Elsevier LtdCoal mining has consumed a large amount of water resources in China, and the entire industrial chain of coal production has a larger consumption of water resources than the past especially in Shendong mining area. The water resources carrying capacity determines the scale of coal industry development. The previous research had been conducted at the national, provincial and municipal levels, but there were few studies on the water resources carrying capacity of coal mining areas. The Shendong mining area is located in the coal-rich and water-scarce western region, where precipitation is low and evaporation is high. As a water-scarce area, the development of Shendong mining area is inseparable from the support of coal resources and the rational use of water resources. Therefore, firstly, taking the Shendong mining area as the research object, this paper set high, medium and low scenarios according to the development goals of Shendong mining area, Shenhua Group and the plans of China. The gray forecast model was used to predict the water demand of the economic-social-ecological system of the mining area from 2020 to 2030 under different scenarios. Secondly, a multi-objective optimization model was established with the objective function to optimize the water resources allocation in Shendong mining area. Thirdly, based on the forecast and optimization results, a water resources carrying capacity evaluation model was constructed to evaluate the water resources carrying capacity of the Shendong mining area. Finally, based on the results, the suggestions for rational development and the utilization of water resources in the Shendong mining area were proposed.
查看更多>>摘要：? 2022 Elsevier LtdRussian economic growth relies much on natural resources, leading to large quantities of greenhouse gas emissions. Therefore, this article aims to explore the causal relationship between oil/coal/natural gas consumption, coal/oil/natural gas rents, and economic growth in the example of the Russian Federation. We used the data from 1992 to 2018 and the ARDL Bounds test. Our empirical findings lead us to conclude a long-run relationship between all variables in the Russian Federation. According to the results, when the oil rents affect the economic growth positively, the natural gas rents and coal rents affect the economic growth, negatively.
查看更多>>摘要：? 2022 Elsevier LtdEquity markets are prone to several external factors, especially in the lethal pandemic situation when the uncertainty regarding the spread of the COVID disrupts the daily financial and economic activities along with the sharp decline in the oil price causing severe devastations to people not just in terms of life and health but also in the form of finance. Therefore, to assess the presence of empirical association of the oil price, Covid-19, and news-based uncertainty with the equity market condition, the method of QARDL was applied in the current investigation. The results revealed that the relationship of OIL was found to be positive and significant across all of the quantiles of the Stock Price Index (SPI); news-based uncertainty was found to be negative and significant across all of the quantiles of SPI, whereas COVID19 has the negative and significant impact on SPI only in the bearish and stable market conditions. Based on the findings, balance government interventions are recommended, balancing the generation of economic activities and counter COVID spread.
查看更多>>摘要：? 2022 Elsevier LtdDue to the continuous increasing energy consumption demand and low carbon target, natural gas, regarded as a promising energy resource around the world, has been paid more attention. As the gap between China's natural gas production and consumption continues to rise, natural gas security becomes a key problem concerned by the whole society. This paper proposes a comprehensive evaluation criteria system, including four dimensions and eight indicators, and constructs an evaluation and prediction model based on set pair analysis, variable weight and high-order Markov chain. Firstly, the state sets of natural gas security evaluation criteria are formed to a set pair. Secondly, the variable weight method was used to calculate the association degree of the set pair and state transferring probability matrix in different time to overcome the problem that the constant weight can not reflect the order importance of the value of criteria. Thirdly, the higher-order Markov chain was proposed to predict the association degree of set pair and to analyze natural gas security situation. Finally, the proposed model is used for China's natural gas security evaluation based on data from 2014 to 2018. The result indicates that natural gas security level shows rising trend in general, and the prediction value shows the future security is still not safe. Thus, some suggestions for improving security are given. Furthermore, the risk attitude of experts has great influence on short-term security analysis and prediction, while the effects on long-term evaluation and prediction are less.
查看更多>>摘要：? 2022 Elsevier LtdChina is the biggest emitter in the world, and coal is dominant in China's energy structure. At present, China has used many strategies to reduce coal use, but their cost-effectiveness is controversial. This paper applies the China-Energy-Environment-Economy Analysis (CEEEA) model, a dynamic recursive computable general equilibrium model with multi-sectors and multi-residents, to simulate progressive policy mix to reduce coal consumption and CO2 emission during 2020–2030, and presents the impact on energy, environment, and economy. The results show that the coal resource tax and the renewable investment can significantly reduce coal share and CO2 emissions to different degrees. The producer price index increases a lot in coal-related industries. However, the consumer price index only increases by no more than 1%. After all, energy products account for a small proportion of the supply chain of bulk commodities. Another, this paper tests the boundary of Porter Hypothesis of such policy mix: it only requires an additional 0.09% increase of total factor productivity every year to cover the negative economic impact of the taxes.
查看更多>>摘要：? 2022 Elsevier LtdConsidering the importance of natural resources in output inequality across the globe which has socio-economic and political consequences, this paper examines the club convergence of natural resources rents across 108 countries for a period of 1970–2019 using clustering algorithms as propounded by Phillips and Sul (2007, 2009) to understand global convergence. The results derived from the analysis indicate that all countries together are not converging to one steady-state, but rather creating two distinct clubs. This suggests that countries are not using the same level of natural resources rents. In particular, countries that lie in club 1 are on the higher side in natural resources rents, whereas club 2 countries are at the lower natural resources rents as a percent of gross domestic product. This recommends that club 1 countries be careful in exploiting the natural resources rents as they are limited. It also leads to a decline in capital when the contribution of natural resources increases in the output. Further, our findings advise that club 1 countries can learn and implement the successful policies of club 2 countries for better and sustainable economic growth and diversification by carefully managing their scarce natural resources.
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