Natural Resource Prices Research Articles

Assessing the impact of geopolitical, economic, and institutional factors on China's environmental management in the Russian-Ukraine conflicting era

In contemporary times, geopolitical risk, and natural resources prices are susceptible due to the Russian-Ukraine conflict. In the meantime, emerging economies are struggling to explore the factors that could reduce ecological challenges and enhance environmental management. This research aims to analyze several economic, environmental, political, and institutional variables to ascertain their influence on greenhouse gas emissions in China. Covering the latest period from 1990 to 2022, various time series tests, including normality, stationarity, and cointegration tests. The results confirm that the variables studied have a stable pattern over time and are connected in the long run. The non-normal distribution of variables leads to opt novel moment quantile regression, where the results are tested for robustness via parametric approaches. The empirical results asserted that economic growth, natural resource prices, and trade significantly enhance ecological challenges (emissions). However, globalization, geopolitical risk, and institutional quality significantly reduce such environmental challenges. The results are robust, and both unidirectional and bidirectional causal associations confirm the importance of these variables in environmental management. Based on the results, this study recommends engagement in environmentally-friendly trading, investment in clean and green energy, and strengthening institutional quality for the region's environmental recovery.

Who moves first? Resource price interdependence through time‐varying Granger causality

AbstractThis paper investigates the interdependence among natural resource prices. Commodities belonging to three different groups (energy commodities, metals, agricultural commodities) are considered. The analysis is performed via a battery of time‐varying Granger causality tests. They allow to assess whether price interdependence occurs and to identify the candidate first movers. These tests also allow observing how long and in which subperiods these causality relationships occur. The approach is applied to the monthly prices of 11 natural resources over the 1980–2021 period. Results suggest that interdependence is weak for energy and agricultural commodities and often concerns limited time periods, while it seems stronger and longer lasting among metals. Moreover, if an overall price driver has to be identified, agricultural commodities more than oil seem to be the best candidates.

The impact of trade on environmental quality and sustainable development in Ghana

Since gaining independence in 1957, Ghana has significantly increased its economic ties with the global community through trade liberalization policies. However, this integration has profoundly affected the environment, particularly in utilizing natural resources, and has subsequently impacted sustainable development. This study examines the relationship between trade, environmental considerations, and sustainable development within the Ghanaian context. Using the autoregressive distributed lag (ARDL) error correction estimation technique, we found that trade positively impacts sustainable development in Ghana despite causing adverse environmental effects. This suggests that economic gains are prioritized over environmental preservation, indicating weak sustainability. However, sustainable development requires a balance between economic, social, and environmental factors, and a shift towards strong sustainability may be necessary for long-term sustainability. Therefore, pivotal policy interventions are warranted to navigate the path toward strong sustainability. Mechanisms that ensure the judicious pricing of Ghana's forest and natural resources are necessary to optimize resource exploitation while mitigating negative externalities. Ghana can promote inclusive and sustainable development by establishing a delicate balance between economic expansion and environmental stewardship.

Effect of geopolitical risk on resources prices in the global and Russian-Ukrainian context: A novel Bayesian structural model

This study evaluated the impact of geopolitical risk (GPR) on natural resources (NRs) by employing monthly from January 1990 to January 2023 and daily data from 3rd January 2022 to 31st March 2022. The outcomes using wavelet QQ and novel Bayesian structural model reveal that GPR has a more profound impact on oil prices (in a quantile range of 0.4–0.8), natural gas prices (range of quartiles from 0.4 to 0.8) and gold prices (in a range of lower to upper quantiles) exhibiting that they are more sensitive to geopolitical uncertainties at all levels. The effects of geopolitical risk are also prominent on palm oil in lower to upper quantile (0.2–0.7) and urea in medium or upper quantile, showing that higher uncertainty drives their prices. In contrast, the response of iron ore (IO) was observed only in upper quantiles (0.7–0.8). The results of the causal analysis reveal that the Russia-Ukraine conflict positively impact NRs prices and that there was a rapid divergence from counterfactual projections. Our findings bear significant implications for sample economies highlighting the alternatives to cope with the GPR and its consequences for natural resource prices.

Exploring the influence of the geopolitical risks on the natural resource price volatility and correlation: Evidence from DCC-MIDAS-X model

This paper uses the expanded dynamic conditional correlation mixed data sampling (DCC-MIDAS-X) model to examine the impact of low-frequency geopolitical risks (GPR) on high-frequency volatility and the correlation of natural resource prices. The empirical results show that GPR and its sub-indices can significantly affect the volatility and correlation of natural resources. The increase in Geopolitical Threats (GPRT) significantly affects the long-run volatility of European Union Allowance (EUA) and Brent crude oil prices. Geopolitical Acts (GPRA) mainly affect the long-run volatility of natural gas prices. In addition, the long-run correlation coefficient, long-run correlation coefficient indicates a competitive relationship between natural resources. Finally, increased GPR and GPRT can significantly reduce the long-run correlation between natural resources. Based on its conclusions, this research makes policy suggestions for businesses and the government. Investors should effectively identify different types of geopolitical risks and their influences to reduce losses and optimize investments. Governments could adjust their policies appropriately to avoid economic shocks due to natural resource volatility caused by geopolitical risks and ensure a stable supply of natural resources.

Assessing the COVID-19 impact on economy, health and natural resource prices: An evidence from selected Asian economies

This study examines the impact of COVID-19 policies on industrial production and natural resource prices in four Asian economies, Bangladesh, China, India, and Pakistan. It examines the relationship between health indicators and economic performance. The data spans 2016M01 to 2022M12. The study finds that government response is most effective in controlling the epidemic, while economic support index is counterproductive. Panel cointegration technique under dynamic OLS assumption is used for empirical findings. We find robust results for the hypothesis that the infection outbreak is most commonly a result of economic activity. These results imply that the natural resource prices are subject to the pandemic outbreak. The hypothesis that these selected Asian economies show resilience to the future epidemic shocks is not supported and the preparedness for any future calamity is not observed. For short run, authorities should focus on reducing intensity and protecting vulnerable individuals during natural disasters. For medium term, government measures and economic support are crucial for controlling outbreaks, but they also affect the labor market. Long-term, governments should increase health budgets for infrastructure to mitigate future calamities.

Dynamic regime differences in the market behavior of primary natural resources in response to geopolitical risk and economic policy uncertainty

The study explores the dynamic effects of geopolitical risks and economic policy uncertainties on oil and natural gas prices in the US market's less volatile and highly volatile regimes, employing Markov regime-switching dynamic regression models (MS-DR) with monthly data from January 2000 to November 2022. Our empirical results demonstrate that a positive shock in the geopolitical risk of the USA (GPR_US) causes an increase in the growth rate of the prices of WTI at the high volatile periods (regime 1), and its one-period lagged effects are negative at time t in the less volatile periods (regime 0), and it cumulatively causes an increase in WTI price. GPR_US and one lagged effect negatively and positively natural gas prices (NGAS) at both regimes. respectively, where the dynamic cumulative impact of GPR_US causes NGAS to increase. World geopolitical risks (GPR) lead to an increase in WTI and natural gas prices. Furthermore, US economic policy exerts a reduction in WTI price at both less and highly volatile regimes, and its lag influences are positive at both regimes, where it cumulatively causes a decrease in WTI price. In a similar manner, global economic policy uncertainty also reduces WTI. US economic policy and its lag effects exhibit an increase and decrease in NGAS prices in the high volatile regime but exhibited a cumulatively positive response to shock in economic policy uncertainty. Global economic policy uncertainty causes nature gas prices to go up. Hence, geopolitical risks and economic policy uncertainty might have a complex impact on the prices of natural resources. It depends on the specific circumstances and the supply-demand dynamics in the market. Our findings offer insightful implications for economic agents.

Volatility challenges for natural resources during COVID-19 and its impact on economic development for sustainable economic repossession

Considering an economy with abundance of natural resources, one can perceive that the country has strong economic growth. However, it appears to be invalid in various cases Besides, efficient financial systems also play sincere role in natural resource export to spill a positive effect on country's economy. As of now, economic and financial growth are being significantly affected by the day-to-day increase in prices of natural resources as the rising eco-financial growth demands more natural resources. During pandemic, the economies of Asian countries are adversely affected due to slow economic activities. Thus, the current study offers policy recommendations for economic recovery through the investigation of dependency between the price volatilities of natural resources and financial/economic developments. By taking the data from the economies of six Asian countries, we link the proposed relationship during pandemic era. With the application of DOLS and FMOLS, we find that the volatility of natural resources and financial innovations have a determinantal effect on the financial and economic developments of Asian countries. We further identify that financial innovations have a positive impact on the economic recovery of the countries under study, while the proper management of natural resources and less volatility in price commodities could positively contribute towards economic repossession.

Economic performance and natural resources commodity prices volatility under COVID-19 perspective: Moderating role of economic freedom

Since the beginning of the 21st century, the Chinese economy has faced several economic and financial challenges, including the outbreak of COVID-19, which hinders growth both at the domestic and international levels. However, such uneven economic outcomes are not independent but are linked with the volatility in other economic and institutional factors. Therefore, this study examines the economic performance and uncertainties in the prices of natural resources while adding the role of governance indicators (control over corruption and the rule of law) and economic freedom from Q-1 1996 to Q-4 2021. Moreover, the moderating role of economic freedom has also been tested in the long and short run through Bootstrap Autoregressive Distributed Lagged (BARDL) estimation technique. The initial findings confirm the presence of the stationarity properties of the data and the long-term equilibrium relationship between the variables. Likewise, the long and short-run result confirms that volatility in the prices of natural resources and corruption impedes growth in China. Yet, the role of the rule of law and economic freedom has been observed as significantly productive in promoting economic growth over the long run. Additionally, the results show a significant moderating role of economic freedom in dampening/strengthening the negative/positive relationship between natural resources and economic growth and the rule of law and economic growth, respectively. Conversely, the short-term findings further reflect that economic freedom significantly moderates the relationship between the rule of law and economic progression. Overall, the study suggests that China should formulate resilient-based policies by promoting free economic conditions to mitigate the adverse shocks of COVID-19 on natural resource prices, empower the rule of law, and control corruption for economic advancement.

Sustainable economic performance and natural resource price volatility in the post-covid-pandemic: Evidence using GARCH models in Chinese context

Recent research demands the influence of COVID-19 on every field of life. Plenty of research work investigated the influence of the volatility of natural resources on economic advancements during COVID-19, though, the impact of the pandemic still persists in the post-pandemic era. Therefore, the current research aims to explore the connectedness of the volatility of oil prices and sustainable economic development during the era after the pandemic. The slump in prices of oil during the pandemic is subject to major concerns in the era after the pandemic. Although this connection is explored by recent researchers, current research work underwrites the prevailing literature by inspecting the connection between oil price volatility and sustainable economic performance during and post COVID-pandemic in China over the period comprising January 2020 to April 2023. The study employs the ordinary least squares regression (OLS), generalized Autoregressive conditional heteroskedasticity (GARCH) (1,1), and Threshold GARCH econometric models to explore the connection between the said constructs. The outcomes infer that the volatility of oil prices is negatively associated with the sustainable economic performance in China during Post COVID-pandemic. The research infers that the vulnerability of the oil prices is more during and after the pandemic eras in China. On the basis of the results, this research work recommends introducing technological innovations, and protective trials to avoid the impact of pandemics on the connection between natural resource volatility and sustainable economic performance.

The time-varying impact of geopolitical risk on natural resource prices: The post-COVID era evidence

The geopolitical risk plays a pivotal role in affecting commodity price variations, especially natural resource commodity prices. Geopolitical risk is sensitive to political environmental changes and geopolitical events, including COVID-19 and the Russia-Ukraine conflict. On this basis, our study attempts to scrutinize the time-varying characteristics of geopolitical risk impact on natural resource commodity prices against recent geopolitical events. By applying the data from natural resource commodity markets, we unravel the fact that U.S. geopolitical risk has a stronger impact on energy market prices, and this impact becomes even stronger after the Russia-Ukraine conflict. Finally, we unfold that the downside risk comovement between metal prices and China geopolitical risk is stronger. Further, the downside risk comovement between energy prices and United States geopolitical risk is more profound. Our paper could deliver implications for policymakers and investors. We notify that the establishment of an early warning system for geopolitical events can be useful to policymakers. Our result further motivates investors to rebalance their portfolios’ risk exposure in a time-varying way, especially after geopolitical events.

Relevance of hybrid artificial intelligence for improving the forecasting accuracy of natural resource prices

The prediction performance of traditional forecasting methods is low due to the high level of complexity in a series of energy prices. The present study attempts to compare the traditional regression, machine learning tools and hybrid models to conclude the outperforming model. The first step is to propose the effective denoising technique for Tadawul energy index, which has confirmed the superiority of CSD based denoising. However, we use the CSD-ARIMA, CSD-ANN, and CSD-RNN as hybrid models. As a result, CSD-RNN outperforms both other models in terms of MSE, MAPE, RMSE and Dstat. The findings are useful for policy makers, investors and portfolio managers to forecast the energy trends, and hedge the portfolio risk accordingly.

Asymmetrically examining the impact of green finance and renewable energy consumption on environmental degradation and renewable energy investment: The impact of the COVID-19 outbreak on the Chinese economy

The recent global recession due to Covid-19 has led to a drop in natural resource prices, which has contracted energy demand. Amid this concern, environmentally sustainable renewable energy projects have become uncompetitive and an obstacle to achieving the Sustainable Development Goals (SDGs). Following the nonlinear autoregressive distributed lag (NARDL) model proposed by Shin et al. (2014), to asymmetrically explore the impact of green bonds on renewable energy investment and environmental pollution and the impact of renewable energy consumption on environmental degradation in China over the period 1970–2020.​ The results show that the expansion of green bonds (GB+) significantly promotes renewable energy investment and reduces environmental pollution, while the contraction of green bonds (GB−) significantly reduces renewable energy investment and stimulates environmental damage. Likewise, expansion of renewable energy consumption (REC+) significantly reduced environmental degradation, while contraction of renewable energy consumption (REC−) significantly contributed to environmental degradation. Moreover, the result also validates the existence of inverted U-shaped EKC hypothesis in China The VECM Granger causality test indicate that renewable energy investment, green finance, renewable energy consumption, CO2 emission, and Gross Domestic Product (GDP) have long term causality. Chinese policymakers must focus on strengthening green finance, which will encourage renewable energy investment and renewable energy generation. Moreover, renewable electricity output greatly facilitates renewable energy investment, so China must innovate policies to take into account renewable electricity rather than fossil fuel generation in order to achieve the Sustainable Development Goals (SDGs).

Managing natural resource prices in a geopolitical risk environment

In this paper, we analyze the potential impact of geopolitical risks on various natural resources such as oil, coal, copper, and zinc, from January 2005 to September 2022. Firstly, we employ an event study analysis to detect the impact of selected geopolitical events by assessing the significance of the abnormal returns and their cumulative effect. Secondly, we use the Time-Varying Parameter Vector-Autoregression estimation method to investigate the possible time-varying impact. Our empirical results from both methods indicate a significant impact of the ongoing Russia–Ukraine conflict on the energy commodity markets. Moreover, our findings reveal that metal prices exhibit a more stable behavior in terms of stochastic volatilities compared to natural gas and oil prices. Furthermore, the response curves of oil and natural gas prices to geopolitical index shocks suggest a downward trend, indicating a negative linear relationship between the geopolitical index and the energy market. In contrast, copper and zinc prices show a non-linear and negative relationship with the geopolitical index, although they are not very responsive to it. Overall, our study provides important implications for policymakers, investors, managers, and consumers to consider geopolitical risks while managing natural resource prices.

Role of financial inclusion and natural resources for green economic recovery in developing economies

The role of natural resources in economic growth has been a topic of contention for almost three decades. Financial growth and natural resource prices are closely intertwined, but the relationship between the two has been relatively understudied. In the context of green economic recovery in developing economies, the importance of managing price volatility of natural resources and building financial inclusion has become increasingly evident. As natural resources play a critical role in the economies of developing countries, promoting sustainable practices through financial inclusion policies is essential for green economic recovery. Therefore, this study assesses the significance of green technology in developing economies from 1990 to 2020, focusing on the connection between natural resources and the media economy. Short- and long-term economic efficiency was shown to be positively affected by natural resource volatility, oil rents, gas rents, the media economy, and green innovation. These results are supported by the long-run estimator improved mean group (AMG). Furthermore, Dumitrescu and Hurlin's Granger panel causality heterogeneity test demonstrated a bidirectional causal link between the examined variables and financial development. Green marketing, price limits, and natural resource hedging are discussed as potential solutions to a region's financial inefficiency and natural resource price volatility.

Dynamic time-frequency connectedness and risk spillover between geopolitical risks and natural resources

Geopolitical risks (GPR) affect the price of natural resources, which are important for survival and sustainable economy. Different from previous studies, we examine the relationship between GPR and natural resource prices from the perspective of time-varying dynamics and time-frequency analysis. The correlations and risk spillover are measured through Empirical Mode Decomposition, TVP Coefficient of Rank Correlation and TVP-Copula-CoVaR model. The results show that GPR have time-varying and heterogeneous characteristics on the volatility of different natural resource prices. First, high frequency component has a stronger impact than the low frequency component. The short-term impact of GPR on natural resource prices is stronger than the long-term. Second, there is a stronger correlation between gold and silver. Crude oil and natural gas markets are more closely related. GPR have a positive relationship with precious metals and crude oil prices. The position of natural gas in the energy market has been significantly improved. GPR have a negative effect on common metal and natural gas. Third, the increase of GPR has significantly affected the stability of the market and intensified the risk spillover of the natural resource prices. Finally, there are asymmetric upside and downside risk spillovers among natural resource markets. The downside risk spillovers of high frequency and low frequency components are more significant.

Impact of water resources pricing mechanism on global agricultural economy based on CGE model

Abstract Water resource (WR) is a complex and interrelated system, which integrates human development and environment. Water price research is gradually carried out under the background of resource economy research, which is an important part of natural resource price research. The main goal of the water price mechanism is to solve the problem of water resource allocation under the pressure of water supply and demand and realize the sustainable development of agricultural economy (AE). Faced with the dual pressure of rising water demand and declining water supply, many regions have begun to reform the water price mechanism and use the CGE model for scientific and reasonable resource allocation. To this end, this paper analyzed the drawbacks and the factors of WR pricing mechanism and used the CGE (Computable General Equilibrium for short here) model to study the upper limit of the pricing of resources, and then analyzed the problems of WR CGE model in agriculture, and finally optimized the problems. According to the experimental analysis, the pricing mechanism of WR under the CGE model can reasonably allocate resources, reduce water demand and promote the development of AE.

Riding the Waves of Fluctuating Oil Prices: Decoding the Impact on Economic Growth

Oil price fluctuations have always been controversial and remain significant in how a country's economy develops. It is especially easy for the worldwide price of natural resources to fluctuate, putting developing nations at risk of economic instability. Consider Pakistan's economy, which is very sensitive to changes in oil prices due to its reliance on the commodity. This research analyses the effects of oil prices on several macroeconomic indicators, including inflation, imports, gross savings, domestic lending to the private sector (DCPS), and industrial value-added in Pakistan. The study uses an error-correcting framework known as autoregressive distributed lag (ARDL) modelling to examine long-term connections between variables and their short-term implications. Additionally, data acquired between 1970 and 2020 was analyzed using Granger causality tests, impulse response functions (IRFs), and variance decomposition analyses (VDAs). The study found that inflation and domestic loans to the private sector hampered economic development in the near run. Conversely, imports, gross savings, industrial value added, and oil rents have a positive effect. A long-term connection between these variables was verified using the boundaries test. A unidirectional link was found in the causality tests between economic growth and imports, inflation and economic growth, and gross saving and domestic credit. An inverse link between domestic credit and inflation was found. The effect of oil rents on economic development in Pakistan is expected to rise during the next four years, according to the forecasts, before levelling out. According to the VDA results, the most critical factor influencing Pakistan's economic development over the next decade would be domestic lending to the private sector. Following these empirical results, the study proposes policy adjustments that might help Pakistan's economy expand more quickly and sustainably.

How does natural resource price volatility affect economic performance? A threshold effect of economic policy uncertainty

The correlation between natural resource price volatility and economic performance has been broadly examined in recent decades. Policymakers and scholars have focus on the adverse implication of economic policy uncertainty (EPU) on economic performance. In the meantime, the sound institutions play a substantial role in mitigating the negative effect of economic policy uncertainty. Therefore, our study examines the threshold effect of economic policy uncertainty between natural resource price volatility and economic performance. The panel threshold models were used to capture the time-variant characteristic of natural resource price volatility, panel threshold models were utilized to conduct heterogeneous analyses on various groups of countries. The endogeneity effect was controlled through the panel least square estimators’ approach, which treated endogenous variables. Our empirical outcomes signify that economic policy uncertainty has a threshold effect between natural resource price volatility and economic performance. There is a positive association between natural resource price volatility and economic performance. Under the lower threshold value of economic policy uncertainty, the effect of natural resource price volatility on economic performance is higher than the above threshold value of the economic policy uncertainty regime. Natural resource price volatility heterogeneous impacts economic performance across developed and emerging economies under the high and lower threshold parameters. Emerging economies are more vulnerable to the threshold effect of economic policy uncertainty. Our empirical results possess important policy implications.

Crude oil price prediction using deep reinforcement learning

Crude oil price forecasting has received considerable attention owing to its significance in the commodity market and non-linear complexity in forecasting tasks. This study aims to develop a novel deep reinforcement learning algorithm for multi-step ahead crude oil price forecasting in three major commodity exchanges. The proposed algorithm includes two main improvements: (a) A dynamic action exploration mechanism based on the stochastic processes conforming to commodity price fluctuations is designed for accuracy and generalization. (b) A dynamic update policy of network parameters based on approximate optimization theory is developed to improve the network's learning efficiency. The algorithm's effectiveness is experimentally verified and compared with five state-of-the-art algorithms. The main findings are as follows. (a) DRL's forecasting ability is developed in crude oil price forecasting, which may be extended to the forecasting of other natural resource prices. (b) The proposed algorithm can be applied to the data of the world's three major crude oil price benchmarks with considerable universality. (c) The accuracy of the proposed algorithm declines indistinctively with the expansion of the forecasting step; however, it reflects the actual price and fluctuation. These findings have implications in accelerating the global economic recovery and exploring AI in the energy market.