Evaluating the performance of carbon tax on green technology: evidence from India

Environmental taxes and environmental quality in Canada

This paper aims to capture the effect of environmentally related taxes on environmental quality in Canada while controlling economic growth, financial development, and energy consumption over the period of 1990Q1 to 2020Q4. The present study employs novel econometric approaches, namely, the nonlinear autoregressive distributed lag (N-ARDL) test and the gradual shift causality (GS-C) test. The outcomes of the study reveal that (i) there is long-run cointegration equation between environmental taxes (E-TAX), carbon dioxide emissions (CO2E), economic growth (ECG), financial development (FD), and primary energy consumption (PREC); (ii) E-TAX causes to decrease in environmental degradation in Canada; (iii) PREC and ECG increase (and cause) environmental degradation in Canada; and (iv) financial development also positively affect the environmental sustainability. This effort may also be of great importance for policymakers and decision-makers to better understand the factors of environmental degradation for developing effective tax policies that will alleviate human impacts and contribute to reducing environmental degradation.

Rural electrification using renewable energy resources and its environmental impact assessment

Integrating a group of generation units and loads into a microgrid improves power supply sustainability, decreases greenhouse gas emissions, and lowers generating costs. However, this integration necessitates the development of an improved energy management system. The microgrid distributes electricity among energy resources to optimize either the generating cost or the quantity of greenhouse gas emissions, or both at the same time. The low-cost energy supply requires a precise cost model for each energy component. This article aims to develop the generation cost model that incorporates renewable energy to lower the total operating cost and curb greenhouse gas emissions. The suggested optimization problem deals with the low-cost energy solution for the rural area of India. The proposed system used particle swarm optimization, a global optimization strategy, in the study. Minimum cost and emission scenarios are objective issues while operating with tolerable emissions, and costs are multi-objective of the present study. The outcomes of the scenarios are used to provide viable optimized solutions to multi-objective problems using the optimization technique. Finally, a battery bank's potential to compensate for generation shortages while minimizing emissions is being studied. The study is performed on a microgrid comprising photovoltaic PV, diesel generator, battery, wind turbine, and an Indian rural scenario load profile. The finding suggested that the optimal configuration has a total net cost of operation is $59,195.61. The per-unit cost of energy is 0.20 $/kWh with a saving of [Formula: see text] emission is 5994 kg/year. This modular feasibility analysis demonstrates that utilizing a hybrid energy system to power the planning is cost-effective. This research is anticipated to aid rural communities and other stakeholders in making well-informed decisions throughout the planning stages of similar initiatives.

How to Efficiently Reduce the Carbon Intensity of the Heavy Industry in China? Using Quantile Regression Approach

This decoupling between carbon dioxide emissions and the heavy industry is one of the main topics of government managers. This paper uses the quantile regression approach to investigate the carbon intensity of China's heavy industry, based on 2005-2019 panel data. The main findings are as follows: (1) incentive-based environmental regulations have the greater impact on the carbon intensity in Jiangsu, Shandong, Zhejiang, Henan, Liaoning, and Shaanxi, because these provinces invest more in environmental governance and levy higher resource taxes; (2) the impact of mandatory environmental regulations on carbon intensity in Beijing, Tianjin, and Guangdong provinces is smaller, since these three provinces have the fewest enacted environmental laws and rely mainly on market incentives; (3) conversely, foreign direct investment has contributed most to carbon intensity reduction in Tianjin, Beijing, and Guangdong provinces, because these three have attracted more technologically advanced foreign-funded enterprises; (4) technological progress contributes more to the carbon intensity in the low quantile provinces, because these provinces have more patented technologies; (5) the carbon intensity of Shaanxi, Shanxi, and Inner Mongolia provinces is most affected by energy consumption structures because of their over-reliance on highly polluting coal.

Influence of carbon tariffs on China's export trade

The database of the Global Trade Analysis Project (GTAP) and its energy-environmental model, known as GTAP-E, are used in this study to simulate the effect of the simultaneous and separate carbon tariff impositions of EU, the USA, and Japan on the export and export structure in China. Simulation results show that the carbon tariff impositions of developed countries on China will decrease the export to EU, the USA, and Japan but increase the export of China to other countries associated with the trade diversion in China. The USA and EU impose carbon tariffs on China, which will have a serious impact on China's export trade, especially for the export trade of energy-intensive industries. When Japan imposes carbon tariff on the exports of China, the positive influence on the export trade is weaker compared to the situation that the USA and EU imposed on China. Furthermore, imposing carbon tariffs on China will improve its trade structure; promote its agriculture, petroleum, and natural gas exploration and electricity industries; reduce its export trade volume of coal mining, petroleum products, and energy-intensive and other industries; decrease the export trade share of energy-intensive industries; and increase the export trade share and services of other industries. In this regard, China should reduce the carbon content of export products initiatively. On the one hand, China can solve this problem by levying carbon tax, developing emerging industries, and strengthening the research and development of low-carbon technologies. On the other hand, China should actively participate in the formulation of international standards of carbon tariff and become a participant in the international emission reduction rules in the field of climate change.

Carbon tax policy analysis based on distribution channel strategy

This paper establishes a theoretical model to study the carbon tax policy based on a firm's different distribution channel strategy. First, we examine the firm's optimal distribution channel strategies in the absence of government policy intervention. Then, on the assumption that the firm is owned by the society as a whole and taking into account the environmental impact of the firm's decisions, we describe the product distribution strategy that optimizes social welfare. Through the comparison of the above two situations, we find that without the intervention of government policies, the firm's decision may deviate from the decision that optimizes social welfare. Finally, on the basis of the analysis, we propose a carbon tax policy for retailers in distribution channels under different firm distribution strategies. We hope that with the intervention of carbon tax policy, firm decisions can achieve optimal social welfare.

Financial implications of fourth industrial revolution: Can bitcoin improve prospects of energy investment?

Bitcoin and the blockchain technology on which it is based are the key drivers behind the accelerated pace of Fourth Industrial Revolution in the domain of Finance. The offshoots of this technology however are not limited and are rapidly spreading in other domains such as oil market. This paper investigates the causality or influences that both markets, Bitcoin price (BP) and oil price (OP) have on each other by applying the bootstrap Granger causal relationship tests considering full as well as sub-samples. Our analysis reveals that shocks originated in OP and transmitted towards BP can be both positive or negative. The positive impact indicates that Bitcoin can be viewed as an asset helpful in avoiding the risks of the high OP, which also indicates that Bitcoin and oil are in the same boat, however, the negative effects cannot support this view. The negative influence of OP on BP can be explained by the burst of the Bitcoin bubble which has weakened its hedging ability. In turn, there is also a negative influence or reverse causality running from BP to OP, highlighting that the demand for oil by investors can be threatened by the increasing BP. Keeping in view the more integrated and complexed financial dynamics which are the results of Fourth Industrial Revolution, investors can benefit from this interrelationship to diversify the risks and optimize their investment by building a more balanced portfolio. Also, governments could promote and protect the healthy development of the Bitcoin and energy market by preventing the Bitcoin bubbles and understanding the reasons of oil price volatility.