The Impact of Direct and Indirect COVID-19 Related Demand Shocks on Sectoral CO2 Emissions: Evidence from Major Asia Pacific Countries

Assessing the spillover effects of research and development and renewable energy on CO2 emissions: international evidence

The primary motivation of this paper is the lack of consensus on the impact of renewable energy (RE) and research and development (R&D) expenditure on CO2 emissions in the literature. Current literature has mostly ignored the spillover effect of R&D on CO2 emissions by increasing the intensity effect of technology, leading to biased results. Further, little is known about the impact of previous epidemics on CO2 emissions. This study fills these gaps by evaluating the spillover effects of RE and R&D on CO2 emissions in a global panel of 54 countries from 2003 to 2017. Using a two-way time- and spatial-fixed-effects panel analysis, we find both income-induced and scale effects of economic growth are present in our panel, though the scale effect is the dominant one. Our findings indicate that economic growth increases CO2 emissions at a decreasing rate, validating the Environmental Kuznets Curve hypothesis, and that urbanization and foreign trade worsen the environment. We also find that epidemic episodes before COVID-19 had a nonsignificant impact on CO2 emissions internationally. More importantly, our results confirm the presence of both the intensity and scale effects of R&D, with the intensity effect being the dominant one. We find overwhelming evidence that global R&D investment led to an overall (direct plus spillover) reduction of CO2 emissions, driven by its spillover effect, through two channels: RE and economic growth. Finally, we find that RE installations assist with reducing CO2 emissions internationally, though RE composition and state of R&D can lead to different findings. Our findings have significant policy implications for sustainable development. Our RE and R&D-spillover results support the policy recommendation of shifting to high-tech clean energy sources.

The long-term dynamic relationship between communicable disease spread, economic prosperity, greenhouse gas emissions, and government health expenditures: preparing for COVID-19-like pandemics

The spread of communicable diseases, such as COVID-19, has a detrimental effect on our socio-economic structure. In a dynamic log-run world, socio-economic and environmental factors interact to spread communicable diseases. We investigated the long-term interdependence of communicable disease spread, economic prosperity, greenhouse gas emissions, and government health expenditures in India's densely populated economy using a variance error correction (VEC) approach. The VEC model was validated using stationarity, cointegration, autocorrelation, heteroscedasticity, and normality tests. Our impulse response and variance decomposition analyses revealed that economic prosperity (GNI) significantly impacts the spread of communicable diseases, greenhouse gas emissions, government health expenditures, and GNI. Current health expenditures can reduce the need for future increases, and the spread of communicable diseases is detrimental to economic growth. Developing economies should prioritize economic growth and health spending to combat pandemics. Simultaneously, the adverse effects of economic prosperity on environmental degradation should be mitigated through policy incentives.

Identifying contributing factors to China's declining share of renewable energy consumption: no silver bullet to decarbonisation

Renewable energy consumption (REC) holds the key to sustainable development. Therefore, many studies have considered the role of REC. However, the factors influencing the REC share in total energy usage (SREC) are not well investigated. Especially, the factors of China's fast-shrinking SREC are understudied. This research void on the world's largest renewable energy producer and consumer, i.e., China's decreasing SREC, is alarming and requires thorough investigation. Our study intends to fill this gap by analyzing the factors of China's decreasing SREC. The study uses both the conventional (descriptive and directional correlational analyses) and some unconventional (automatic linear modeling (ALM) and Artificial neural network (ANN) multilayer perceptron (MLP)) approach to investigate the factors of China's decreasing SREC. The initial hypothesis testing and most reliable model validation were achieved via directional correlational (Pearson and Spearman) and ALM analyses. The ANN MLP (two hidden layers) indicated that the most critical factor is "Combustible renewables and waste," with a 100% normalized importance. It was followed by "urbanization (64.2%), gross savings (56.1%), and alternative and nuclear energy (38%)," respectively. It is suggested that the Chinese government and private investors prioritize their investments based on factors' importance ranking.

The socioeconomic factors of investment-induced petroleum consumption: case of fast developing Chinese economy

Capital investment stimulates a sizable portion of petroleum consumption, especially in emerging economies. However, investment-embedded petroleum consumption (IEPC) and the socioeconomic factors that influence it are not well studied. Our study's objective is to close this research gap. Our article estimates the effects of petroleum intensity, technology, investment structure, and economic development on China's IEPC using input-output and bipolar structural decomposition analysis. Additionally, our article develops a previously mostly unknown index of investment intensity. The findings indicated that, on average, between 1990 and 2016, investment induced nearly 30% of China's total final demand-embedded petroleum consumption. On average, petroleum intensity had the most significant decreasing effect on the Chinese IEPC. Averagely, technology had a positive impact, but from 2010 to 2016, it had a noticeable negative impact (- 1.51 exajoule). Both investment intensity and economic development had a significant upward effect. The impact of investment intensity was the smallest of all the factors. Disaggregation of the effects of socio-economic factors at the sectoral level revealed distinct patterns. Thus, by focusing on the socioeconomic dynamics of key sectors, the factors' current decreasing effects can be maximized, and their increasing effects minimized.

Informal Environment Regulation, Green Technology Innovation and Air Pollution: Quasi-Natural Experiments from Prefectural Cities in China

Facing informal environment regulation carried out by the environmental protection organizations, we study and judge its inhibitory effect on air pollution and the acting path. Based on panel data of 285 cities in China from 1998 to 2018, a time-varying difference-in-difference model is used to estimate the effect of informal environment regulation on air pollution. The estimation results show that informal environment regulation can inhibit air pollution significantly under different scenarios. Green technology innovation is introduced into the research and a mediating effect model is used to investigate the influencing mechanism. Informal environment regulation strengthens pressure on pollutant emissions. This forces enterprises to enhance the investment and application of green technology innovation during production. Mechanism analysis shows that informal environment regulation inhibits air pollution by encouraging the application of green technology innovation. The above conclusions are still valid after a series of robustness tests, including parallel trend, placebo test and instrumental variables. The research conclusions provide empirical evidence for the construction of a diversified air-pollution control system and demonstrate the practical significance of informal environment regulation to improve air quality.

CO2 behavior amidst the COVID-19 pandemic in the United Kingdom: The role of renewable and non-renewable energy development

The spread of the COVID-19 pandemic since the end of 2019 has forced an unprecedented lockdown worldwide, and environmental quality was significantly affected by the pandemic and its induced lockdown. The objective of this study is to examine the role of renewable energy, non-renewable energy and COVID-19 case on CO₂ emission in the context of United Kingdom. Several non-linear techniques such as Fourier ADL cointegration test, Non-Linear ARDL, Markov switching regression, and Breitung and Candelon (BC) causality test are employed to attain this objective. The result reveals that there is long run cointegration among the variables in this study. The results demonstrate that positive (negative) shift in renewable energy development decrease (increase) CO₂ emissions while positive (negative) shocks in fossil fuel energy increase CO₂ emissions. Moreover, negative (positive) variation in COVID case leads to a decrease (increase) in CO₂ emissions. Moreover, an uni-directional causal impact was found to run from all the variables - renewable energy, fossil fuel, and COVID-19 case to CO₂ emissions. Finally, several policy recommendations are provided.

The Coal, Petroleum, and Gas Embedded in the Sectoral Demand-and-Supply Chain: Evidence from China

The United Nations’ Sustainable Development Goal (SDG) number seven expressly calls for universal access to affordable and sustainable energy. Energy sustainability will require a reduction in energy consumption, including embedded energy consumption in sectoral demand and supply chains. However, few studies have estimated the amount of coal, petroleum, and gas (fossil fuel) embedded in demand-and-supply chains (FFEDS). Furthermore, the inter-and intra-sectoral energy linkages are understudied. This study quantifies China’s FFEDS, the world’s largest energy consumer. According to the findings, the highest levels of coal, natural gas, and petroleum consumption (CNGPC) are embedded in the construction sector’s input demand. “Electricity and steam production and supply” total intermediate exports (internal plus inter-sectoral) stimulated the highest coal consumption. “Crude petroleum products and natural gas products” and “railway freight transport” aggregate supplies induced the highest volume of natural gas and petroleum consumption. Compared to intra-sectoral demand, inter-sectoral demand stimulated significantly larger CNGPCs. In contrast, CNGPC’s inter- and inter-sectoral supplies were nearly identical. Modifying current carbon taxation and credit mechanisms to include energy embedded in demand and supply can help to achieve SDG 7.

The Nexus between Environmental Impact and Agricultural Sector Linkages: A Case Study of Pakistan

Agriculture has a substantial environmental impact. However, little research has been conducted on the relationship between agriculture’s environmental impacts and linkages, particularly for the key agriculture-based Pakistani economy. Additionally, the literature on environmental linkages rarely estimates multiple types of linkages in a single study. This study fills these critical research gaps. The study estimates the land, water, nitrogen, and CO2 impacts and linkages of Pakistan’s agriculture sector using an input–output model and the hypothetical extraction method. The results indicated that agriculture directly accounted for approximately 27%, 93%, 92%, and 1% of Pakistan’s total sectoral land, water, nitrogen, and CO2 impacts (LWNC), respectively. While the sector indirectly contributed almost 2%, 0.3%, 0.4%, and 0.4% of Pakistan’s total LWNC. The bulk of direct LWNC impacts were caused by agricultural purchases from downstream sectoral importers. The majority of the indirect LWNC impacts were induced by agriculture’s re-imports. The agricultural purchases from the downstream sector of “Food and Beverages” induced the greatest environmental impact. To ensure sustainable agriculture, particularly in Pakistan, the agriculture sector’s direct and indirect environmental impacts should be reduced not only through better management practices and technology, but also by focusing on intermediate sectoral sources of direct and indirect environmental impacts.