Natural resources commodity prices volatility and economic performance: Evidence from China pre and post COVID-19

Impact of energy imports, renewable electricity production, alternative, and nuclear energy sources on natural gas resource rents

The world faces several problems related to natural gas resource rents and energy production from renewable sources. One of the main problems is the influence of energy imports, manufacturing exports, and alternative energy sources on natural gas and electricity production from renewable sources. Energy imports, manufacturing exports, and alternative energy sources can impact natural gas and electricity production. This paper examines natural gas resource rents and electricity production from renewable sources nexus from 1971 to 2021, using energy imports, manufacturer's exports, and alternative energy sources in China. Electricity production from renewable sources and manufacturing exports are negatively associated with natural gas resource rents. Energy imports and alternative energy sources positively relate to natural gas resource rents in China. These results suggest that the energy sector in China is highly interconnected and that policies that seek to promote renewable energy sources and other alternatives can positively affect natural gas resource rents. China needs to develop an energy policy considering the policy implications of energy imports and natural gas resource rents. Such a policy should focus on increasing domestic production, reducing energy imports, and ensuring adequate revenue from natural gas resource rents. Additionally, regulations could be implemented that support the development of alternative energy sources, such as requiring utilities to purchase a certain percentage of their power from renewable sources.

Green finance, renewable energy investments, natural resources, and sustainable economic advancements in China: evidence from pre-post COVID-pandemic

Since the start of twenty-first century, the globe has bumped into several crises, such as the sudden rise of oil prices in 2003 and the large-scale global financial crisis in 2007-2008. However, the most recent COVID-19 outbreak has slowed fiscal progress and initiated instability in the prices of commodities-based natural resources. The instability of prices of natural resources attracted the focus of academicians and policymakers. Moreover, the recent pandemic also pushed up the need of green finance and renewable energy investment for renewable energy development. The current study, thus, explores sustainable economic advancements via natural resource rents, green financing, renewable electricity energy, and investment in renewable energy projects in China over the period of 2000 to 2023 including years of pre-post COVID-pandemic. The current paper used CCR (canonical cointegrating regression), DOLS (dynamic ordinary least squares), and FMOLS (fully modified ordinary least squares), for its empirical investigation. The results demonstrate the cointegration of first-differenced stationary variables in the longer run. The parameter of natural resource rents shows that the volatility of natural resource prices adversely influences the sustainable economic advancement of China. Findings also demonstrate that green finance strategy can simultaneously control the high-emission situation and increase economic development of country. Additionally, the findings reveal the positive effects of renewable electricity energy output, and investment in renewable energy projects for sustainable economic advancements.

Natural resources for policy makers: Revisiting COVID-19 perspective of aggregate South Asian economies

The global pandemic of covid-19 affected human lives and the global environment. Further, literature on the nexus of natural resources and economic growth, initiating the pandemic in the 21st century has confronted policymakers with uncertainty. This requires revisiting the link between natural resources and the economic performance of the South Asian economies. For this purpose, the present study has tried to investigate the role of natural resources in the economic growth of the aggregate South Asian economies during the Covid-19 challenge. The analysis has been completed by a novel approach of MMQR taking data from 1980 to 2021. The oil rents have negatively affected the economic growth may be due to its lower demand during the pandemic caused by lockdown activity. The trade and electricity produced from renewable improve the economic performance of the designated sample economies. The results provide evidence of the irreversible investment theory. The analysis implies that efficient policies for natural resources, specifically oil prices, are required to encourage the South Asian economies' role. Further, the positivity of electricity production from renewable gives rise to the growth hypothesis, which depicts that using renewable energy enhances the economic growth of South Asian economies.

Impact of COVID-19 on China's business and economic conditions: the importance of quantile asymmetries

China has remained a growth engine for the global economy for the last several years. In this study, we assess the impact of COVID-19 on China's business and economic conditions; employing the quantile-on-quantile (QQ) regression and the quantile causality approaches. These econometrics batteries suit our research postulation, as they are capable to delineate underlying asymmetries across the whole distribution, based on which we can infer whether the response of China's business and economic conditions towards COVID-19 is heterogenous or homogenous. Utilizing the novel business and economic conditions measures, we observed that COVID-19 had initially disrupted both business and economic conditions in China. However, they showcased recovery over time. Our in-depth analysis allowed us to infer that the effect of COVID-19 on China's business and economic conditions is heterogeneous across different quantiles, and there is reliable evidence of asymmetry. The outcomes of quantile causality in mean and variance corroborate our primary estimations. These findings educate policymakers, companies, and other stakeholders to understand the nuances of China's business and economic conditions vis-a-vis COVID-19 in the short-run and as time elapsed.

A water pricing model for urban areas based on water accessibility

Water resource, with properties of scarcity, is one of the vital resource endowments. Like land resources, the prices of these resource endowments should be correlated to their locations to follow fair and reasonable principles. The current water price systems are mainly policy-oriented fixed regimes. And the water use was charged according to the regional-average situation with scarce consideration of the fine-scale geographical water accessibility. With a combination of the water accessibility and the current water pricing regime, this paper first proposed a novel water pricing model, the Water Price at Grid-scale (WPG) model, to dynamically allocate water prices to fine grids for urban residents. The WPG model was examined in the case study of the Han River Basin in the Hubei province of China. The specific results were: (1) the P_grid of Tier I is between 0.66 and 3.94 yuan/m³, the P_grid of Tier II is between 0.57 and 5.44 yuan/m³, and the P_grid of Tier III is between 0.47 and 6.94 yuan/m³ in the study area. (2) the grids with more water acquisition generally have lower water prices than others and vice versa. (3) the average water prices in tiers obtained by the WPG model are generally higher than that derived from the current water pricing system. The results proved that the proposed WPG model spatially allocates the three-tier water prices into grids of urban areas. The WPG framework can be adopted in any society by involving its water price regimes and adjusting the scale of grids and the pricing year. This study provided a new viewpoint of domestic water pricing involving fine-scale water accessibility. The WPG model has great potential to ease water shortage pressure in water-limited societies and can be utilized and loaded into the current smart-city network for efficient and fine-scale water resource management.

Deliver Smart, Not More! Building Economically Sustainable Competitiveness on the Ground of High Agri-Food Trade Specialization in the EU

Competitiveness has always been a multifaceted illusive concept, which has made it a real challenge for scholars and practitioners to find the most suitable measurement tools to completely encapsulate all the complex nuances of competitiveness. This becomes even more of a challenge when approached in relation to particular economic sectors. The agri-food sector is no exception, especially when considering all its interconnections with the other sectors: water, energy, transport, waste. All of them impact the achievement of the Sustainable Development Goals (SDGs). Similarly, scholars have been debating the meaning of sustainability for decades, some even arguing that it is a political, subjective, and, in some cases, self-contradictory concept. As far as the sustainability of agricultural competitiveness is concerned, the literature is still developing. It is much more focused on fostering environmental competitiveness, and less attention was paid to the strategies designed to capitalize on sustainable economic competitiveness-a concept that has attracted divergent opinions in the literature, mainly due to ambiguity. Thus, instead of falling into the pitfall of vagueness, this paper was aimed at bringing its contribution to this field by undertaking the research objective of exploring a single facet of sustainable agricultural competitiveness: the economic facet. Hence, this paper proposes the construction of the sustainable economic competitiveness index (SECI) with direct application for agri-food value chains. It consists of three attributes: (a) factor endowments, resource independence; (b) agricultural chain performance; and (c) national agricultural chain strategies and policies. In this study, SECI was tested against the cereal chain for a selection of EU countries, based on the data taken over from FAOSTAT and INTRACEN Trade Map, in the case of the 2011-2020 period. Various statistical and econometric methods were used to test the robustness of SECI. Results stand as proof that building sustainable agricultural economic competitiveness relies on a mix of strategic actions. The key vector in this mix is that trade flow patterns and policies must be calibrated in accordance with national factor endowments in order to achieve high levels of SECI. To add more managerial implications, this paper argues for the smart delivery of agri-food products with high added value instead of focusing on exporting big volumes of raw agricultural materials with little added value.

Natural resources volatility and causal associations for BRICS countries: Evidence from Covid-19 data

Natural resource price volatility has been a major concern in recent time, especially during the COVID 19 period. Although several empirical research have looked into the oil and natural resources prices nexus with economic growth, but, our study makes a significant contribution to the present literature by estimating the long run natural resource price volatility influence on economic growth as well as the causal associations between volatility of the prices of natural resources and economic growth for BRICS economies over 1995-2020 period. To conduct empirical estimation, the study has used new and advanced (CUP-FM) continuously updated fully modified and continuously updated bias-corrected (CUP-BC) estimators for long term influences of the natural resources prices and (Dumitrescu and Hurlin, 2012) heterogeneous test for panel causality for the estimation of the causal relationship between the variables. The results provide clear evidences about the negative influence of volatility in natural resources prices, whereas positive impact of gas and oil rents on economic growth or economic performance of the BRICS economies. Moreover, bidirectional causal association is also revealed from our empirical findings to exist between economic growth and price volatility of natural resources. The findings of our study are robust to various policy implementations. It is recommended to reduce the reliance of natural resources as well as the adoption of short run and long run natural resource hedging policies to mitigate the detrimental impacts of price volatility of natural resources on economic growth and environment.

Measuring the macroeconomic determinants of agricultural price volatility: Implications for natural resource commodity prices for green recovery

With rapid growth, green economic recovery has been a key agenda for the globe. However, the price volatility for natural resources plays a significant role in reshaping the green recovery. Therefore, the current study investigates the impact of green recovery, hum, a capital index, GDP growth, foreign direct investment and inflation on natural resource volatility in China from 1995 to 2020. In order to investigate the long-term association among selected variables, this study employs the Autoregressive Distributive Lag (ARDL) model. In addition, the current research uses the Aikaik information (AIC) criteria for the model selections. Obtained outcomes show the significant contribution of green recovery, human capital, GDP growth, FDI and inflation increase the natural resource price volatility level. However, to validate the results of ARDL, this study also used the ECM approach and validated the prior findings. On behalf of outcomes, the current study implies some imperative policies to attain the desired objective for green growth.

COVID-19 and China commodity price jump behavior: An information spillover and wavelet coherency analysis

Jumps in commodity prices can make asset risk management challenging. This study explores the influence feature of the COVID-19 epidemic on China's commodity price jumps, using 5-min intraday high-frequency futures data of three China's commodity markets (energy, chemical, and metal) from January 23, 2020 to June 10, 2022. We find that firstly the information spillover from the COVID-19 spread situation to China's energy price jumps is relatively weak, and the COVID-19 epidemic shows the most substantial jump information spillover pattern to China's chemical price. The information spillover pattern is time-varying across the COVID-19 spread situation phase. Secondly, there are co-movement patterns between China's commodity price and China/global COVID-19 confirmed cases. This co-movement feature mainly occurs at the medium- or long-run time scales, and varies across commodities. Thirdly, the demand elasticity for China's commodities and its dependence on imports and exports are the main factors influencing the sensitivity of its price jumps to the COVID-19 outbreak.

Hospital length of stay for COVID-19 patients: A systematic review and meta-analysis

The length of stay in the hospital for COVID-19 can aid in understanding the disease's prognosis. Thus, the goal of this study was to collectively estimate the hospital length of stay (LoS) in COVID-19 hospitalized individuals. To locate related studies, international databases (including Google Scholar, Science Direct, PubMed, and Scopus) were searched. The I² index, the Cochran Q test, and T² were used to analyze study heterogeneity. The mean LoS in COVID- 19 hospitalized patients was estimated using a random-effects model. COVID-19's total pooled estimated hospital LoS was 15.35, 95%CI:13.47-17.23; p<0.001, I² = 80.0). South America had the highest pooled estimated hospital LoS of COVID-19 among the continents, at 20.85 (95%CI: 14.80-26.91; p<0.001, I² = 0.01), whereas Africa had the lowest at 8.56 8 (95%CI: 1.00-22.76). The >60 age group had the highest pooled estimated COVID-19 hospital LoS of 16.60 (95%CI: 12.94-20.25; p<0.001, I² = 82.6), while the 40 age group had the lowest hospital LoS of 10.15 (95% CI: 4.90-15.39, p<0.001, I² = 22.1). The metanalysis revealed that COVID-19's hospital LoS was more than 10 days. However, it appears that this duration varies depending on a number of factors, including the patient's age and the availability of resources.

Economic policy uncertainty and commodity market volatility: implications for economic recovery

As a consequence of the COVID-19 pandemic outbreak, most commodities experienced significant price drops, which were expected to continue well into 2020. As a result, the Markov switching model is used to study the influence of policy uncertainty and the COVID-19 pandemic on commodity prices in the USA. Commodity markets are stimulated by economic policy uncertainty, according to results from a two-state Markov switching model. In both high and low regimes, economic policy uncertainty (EPU) influences the commodity market, according to the study's findings. However, in the high regime, EPU has a greater influence on the energy and metal sectors. EPU has different influences on commodity markets in high- and low-volatility regimes, according to this study. There is a wide range of correlations between COVID-19 outcomes and EPU and how the prices of natural gas, oil, corn, silver, soybean, copper, gold, and steel respond to these tremors, in both high- and low-volatility tenure. Oil and natural gas, on the other hand, are unaffected by shifts in COVID-19 death rates under either regime. Results show that in both high- and low-volatility regimes, the demand and supply for most commodities are responsive to historical prices.

Does COVID-19 pandemic cause natural resources commodity prices volatility? Empirical evidence from China

COVID-19 pandemic caused havoc around the globe in both economic and non-economic sectors. This paper, unlike previous studies, evaluates the role of COVID-19 on the volatility in natural resources. The volatility of natural resources commodity prices has been the center of discussion, especially during the pandemic. Unlike previous studies, this study aims to evaluate the role of the pandemic, i.e., Covid-19 and its possible impact on volatility in natural resources commodity prices for China. China has been the center of this epidemic disease and is considered one of the major economies affected by the Covid-19; therefore, it is better to conduct this study for China. This study uses data from January 2020 till September 2021 to capture the peak time of Covid-19. Moreover, this study employs the novel wavelet power spectrum and wavelet coherence approach to better capture volatility within commodity prices volatility and Covid-19 and evaluate the association between both variables. The empirical results reveal that only natural resources commodity prices are volatile and only short. While Covid-19 positive cases and Covid-19 deaths are not vulnerable during the study period. Moreover, the wavelet coherence conforms that both Covid-19 positive cases and Covid-19 deaths significantly cause volatility in natural resources commodity prices. Although, volatility is found at different periods; still, volatility is observed only in the short-run. The study also provides relevant policy implications to ensure a relevant and timely solution for the existing issue. Moreover, future research guidelines and the study's limitations are also provided.

Volatility in natural resources, economic performance, and public administration quality: Evidence from COVID-19

The recent Covid-19 pandemic outbreak caused a global economic recession and promoted uncertainty in the natural resources. Also, this uncertainty is linked with the demand and supply of natural resources such as oil and natural gas, which is a substantial factor of industrial and economic activities. Declining natural resource demands substantially drop such activities that adversely affect economic performance. This attracts the attention of policy-makers and governors to efficiently tackle the issue. This study investigates the association of natural resources volatility, global economic performance, and public administration in earlier and Covid-19 pandemic peak periods. The study covers the period from 1990 to 2020 for the global data. The empirical findings of the cointegration test suggested that the variables are cointegrated. This study utilizes three long-run estimators, i.e., fully modified ordinary least square (FMOLS), dynamic OLS (DOLS), and Canonical Cointegrating Regression (CCR). The empirical findings suggest that natural resources volatility (TNR) negatively and significantly affect global economic performance. While natural gas rents, oil rents, and public administration quality (QPA) promote global economic performance. Besides, the results also indicate that the interaction of QPA and TNR enhances economic performance. This study demonstrates that volatility in natural resources is detrimental to global economic performance. However, improved public administrative quality could play a significant role in transforming the negative influence. of natural resources volatility into a positive effect. The findings are robust as validated by Robust regression. This study provides some practical policy insights for the governors and policy-makers to tackle the mentioned issues.

Covid-19 and the energy trade: Evidence from tanker trade routes

We employ a cointegration setup to explore route-specific off-equilibrium deviations related to Covid-19 that have affected clean (petroleum products) and dirty (crude oil) tanker freight rates, over and above the expected macroeconomic reactions. We find that the additional deviation caused by Covid-19 is route-specific. In particular, deviation caused by Covid-19 is found to be more significant for clean tankers, with an average impact of 0.15, an expected outcome given that these products are more reliant on economic developments because of their uses. The clean tanker impact is more evident in Japan-related routes, while no specific pattern can be extracted with regards to the additional off-equilibrium Covid-19 deviation for dirty tanker routes. Results suggest that time-charters and hedging against the stock markets can help ship-owners ameliorate demand-driven shocks.

Does Public Health Influence Economic Performance? Investigating the Role of Governance and Greener Energies for the Case of China

In the last few decades, the world has faced some natural issues, due to which economic growth faces a severe threat. Natural disasters like pandemic outbreaks and man-made disasters like pollution emissions are very frequent in the current times, which also influenced the economic growth, where the institutes could play a primary role in economic growth stimulation. This study aims to analyze the association of public health expenditures, institutional quality, renewable energy, and economic performance in China. This study uses quarterly data covering the period from 1996Q1 to 2020Q4 and employs various time-series estimating approaches. The Augmented Dickey-Fuller estimates asserted that all the variables are stationary at first difference. Also, the Bayer-Hanck combined cointegration validates that all the variables are cointegrated. Employing the three long-run estimators, i.e., Fully Modified Ordinary Least Square, Dynamic Ordinary Least Square, and canonical cointegrating regression, the results asserted public health expenditures and institutional quality (including government efficiency and political stability) significantly enhances economic performance in China. Whereas two indicators of corruption control and regulatory quality do not play any significant role in promoting the economic performance of China. On the contrary, renewable energy is found negatively associated with economic performance. Also, the Pair-wise Granger causality validates mixed causal associations between the study variables. As a developing and fossil energy-dependent economy, this study provides relevant policy implications for maintaining economic growth and rebalancing economic performance in China.

China economic performance and natural resources commodity prices volatility: Evidence from China in COVID-19

Since the beginning of the 21st century, the world has faced many challenges, including the 2003 oil price hike, the 2007-08 global financial crisis, among others. While the recent Covid-19 outbreak slowdown economic performance and create uncertainty in natural resources commodity prices, which brought the attention of academic research. Current study examined economic performance and natural resource commodity price volatility in China over the period 1990-2020. Also, this study considers the role of renewable energy investment, renewable electricity output, and green finance in the pre and post Covid-19 pandemic periods. For empirical investigation, this study employed dynamic ordinary least square (DOLS), fully modified ordinary least square (FMOLS), and Canonical Cointegrating Regression (CCR). The outcomes reveal that the first-differenced stationary variables are all cointegrated in the long run. While these estimators confirmed that natural resources commodity price volatility negatively affects economic performance. Besides, the results validate the positive impact of renewable energy investment, renewable electricity output, and green finance on economic performance. The results are found robust and consistent, justified by Robust regression. These findings could have essential economic, natural resources, and energy implications for policymakers, governors, and researchers.

Natural resources volatility and South Asian economies: Evaluating the role of COVID-19

Since the emergence of the Covid-19 pandemic, global economic performance has been severely affected, which also causes natural resource price instability. Recently, scholars and policy-makers put more attention towards the global economic performance and natural resource volatility nexus. This study investigates four South Asian economies (Afghanistan, Bangladesh, India, and Pakistan) from 1991 to 2021. Using the (Pesaran, 2007) CIPS unit root test, the study found first differenced stationary data cointegrated as confirmed by the (Westerlund, 2007) cointegration test. However, this study employed the CCEMG approach to identify the association of natural resource volatility and economic performance in the selected region. Empirical results revealed that total natural resource rents, forest rents, and oil prices negatively and significantly affect economic performance. While oil rents, coal rents, and natural gas rents have a significant contribution to the region's economic performance. Results further illustrate a bidirectional causal association between economic performance and other variables except for coal rents, which is unidirectional. Based on the empirical findings, the current study acclaims some practical implications that could potentially reduce the negative influence of natural resources volatility on economic performance.

Natural resources rents and economic performance: Post-COVID-19 era for G7 countries

COVID-19 affected the economies of both developed and developing countries through multiple channels. However, the impact of this pandemic was also not so different for the developed world too. This study aims to evaluate the effect of the natural resources' rents such as oil, natural gas and energy rents on the economic performance of G7 economies from 1990 to 2020. This study uses updated panel data methods to identify the effect of COVID-19 by using novel diagnostic and unit root methods. The study found that during the COVID-19 and post pandemic, economic performance has been declined. This study found that natural resources rent, including oil and gas, help to improve the economic performance. Further, structural break for the year 2019 caused by COVID-19 also slowed down the economic performance of G7 economies. This study suggests more stabilization policies towards natural resources commodity prices and encouragement of active role from the G7 countries. This study further provides relevant policy implications in the concluding section for the selected group of countries.