Chinese Energy Industry Research Articles

Investing in green, sustaining the planet: The role of fintech in promoting corporate green investment in the Chinese energy industry

In recent years, fintech has rapidly developed on a global scale, bringing about significant transformations across various industries. Particularly in the energy sector, the potential of fintech to promote corporate green investment has increasingly become a focus. As the energy industry accounts for a significant proportion of global greenhouse gas emissions, guiding companies in implementing green investment has become an important issue for environmental protection and sustainable development. However, previous studies have rarely systematically investigated the influence of fintech on corporate green investment in the energy industry and the mechanisms involved. Hence, this study aims to bridge this research gap within the context of China. By utilizing valid survey data from 466 corporations in the Chinese energy industry and the method of structural equation modeling, the results indicate that: (1) Fintech can promote corporate green investment in the energy industry. (2) Fintech can promote corporate data-driven decision-making capability, information transparency, and sustainable development strategy. (3) Data-driven decision-making capability, information transparency, and sustainable development strategy can also promote corporate green investment in the energy industry. (4) Mediation analysis reveals that data-driven decision-making capability, information transparency, and sustainable development strategy each play a mediating role in the impact of fintech on corporate green investment. (5) Comparative analysis of the mediation effects indicates that there is a certain degree of difference among these three variables’ mediating effects, but it did not reach a statistically significant level. This study provides rich insights for business practices, encouraging companies to strengthen their focus on green investment in the fintech era and offer guidance and recommendations to relevant stakeholders, thereby providing practical guidance for corporate green transformation and sustainable development. Finally, this research also contributes to policy development and optimization.

Analysis on the synergy between markets of electricity, carbon, and tradable green certificates in China

China has integrated tradable green certificates and carbon markets with its electricity sector to promote renewable energy and reduce carbon emissions. However, the impact mechanism of decision-making behaviors of involved entities in these integrated markets on the market equilibrium is still unclear, hence limiting the further development of renewable energy industries and carbon reduction progress to some extent. Therefore, conducting in-depth research to inform policy makers about the impacts of entities' decision-making behaviors on market equilibrium within the context of integrated multiple markets is crucial. This study aims to analyze the characteristics of entities' decision-making behaviors and equilibrium states within the collaborative dynamics of carbon, electricity, and green certificate markets. Specifically, an optimal decision-making model for entities given the multi-market coupling was developed by employing mathematical programming methods to analyze market equilibriums across various market combinations and policy parameters. The conclusions underscore equilibrium price shifts and decision-making characteristics among entities across multiple markets. The result shows that the carbon market could increase power prices and decrease green certificate prices. To ensure sustainable energy development, policymakers should consider the decision-making behavior of entities under multi-market coupling, which can promote the low-carbon transformation of the Chinese energy industry.

Is the tone of the government-controlled media valuable for capital market? Evidence from China's new energy industry

This study examines the influence of the tone used by government-controlled media on the stock prices of new energy firms. By applying BERT, a large language model, we quantify the tone of the new-energy-related articles published by the primary government-controlled media of China. We find that the government-controlled media tone positively and significantly influences the short-term returns of new energy stocks. By comprehensively performing mechanism analysis, we show the government-controlled media tone plays a key role in communicating information rather than triggering stock price overpricing. We further find that the official media tone influences equity financing cash flows of new energy firms and in turn affects their asset expansion, investment and R&D activities. Overall, our findings reveal that the government-controlled media tone contains fundamental information valued by the investors and the information ultimately influences the development of Chinese new energy industry through affecting the corporate real activities.

Empirical study on the impact of tax reduction on the development of Chinese green energy industry.

The implementation of tax reduction policies in China represents a significant and effective strategy. Accordingly, this strategy has been designed to facilitate the development of a green economy by establishing a market-oriented allocation system for environmental and resource elements, while simultaneously invigorating microeconomic entities. As the nation navigates towards the adoption of green, low-carbon production, and lifestyles, the role of clean and green energy emerges as a vital necessity. Therefore, to explain the impact of tax reduction policies on the green energy industry, this study collected and compiled financial indicator data from 100 listed companies in the green energy sector, utilizing the China Stock Market Accounting Research database (CSMAR) as a source for research samples. A Panel Vector Auto Regression (PVAR) model was employed to observe the effects of tax reduction policies on the energy industry, while the dosage effects Difference in Difference (DID) model was utilized to verify and supplement the findings. In summary, the findings of this study can be summarized as follows: firstly, tax reduction policies exert a positive impact on the green energy industry by effectively mitigating the financial cost burden on green energy enterprises, thereby reducing production expenses and amplifying their profitability. Secondly, such policies bolster the capital turnover rate of enterprises in the short term, thereby enabling augmented research and development investments, refining production efficiency, and enhancing competitiveness. Through rigorous analysis and demonstration, the research findings accentuate the stimulative and propulsive impacts of tax reduction policies on the flourishing development of the green energy industry. Furthermore, this study provides relevant fiscal and tax policy recommendations, thoughtfully derived from the research findings.

How does green digital finance drive the low-carbon energy transition in China?

In the modern world, green digital financing is believed to be an efficient, resilient, and viable source of funding for crisis conditions and to solve the preceding issues in a timely manner. It is a modern tool of financing mainly introduced by the World Bank and the International Monetary Fund. Following the paths, most economies started considering it to solve their national economic issues. Thus, to fulfill the requirements of the modern world, current research aims to study the driving role of green digital financing on low-carbon energy transition in China. Using the generalized method of moments (GMM) model based on data collected from 2015 to 2020, this research made an effort to determine the empirical nexus between the green digital financing index and the low-carbon energy transition index and to recommend the possible policy implications to the policymakers and other practitioners. Results have shown that a 0.27% rise in green digital financing is observed in the Chinese economy from scratch, and it resulted from a 0.365% efficiency in the low-carbon energy transition in China. Accordingly, the study resulted that the role of green digital finance is clustering in the Chinese renewable energy industry, which impacts both the performance of the Chinese renewable energy industry and the economy. For more resilience, extended efficiency and viable energy transition study suggested the practical implications for the stakeholders to consider for practice. The novelty of the study is its motivation, findings, and solutions.

Does oil price volatility and financial expenditures of the oil industry influence energy generation intensity? Implications for clean energy acquisition

This study examines the nexus between financial expenditures within the Chinese oil business, the volatility of oil prices, and the energy-generating sector. This research examines Chinese oil and energy industry statistics from 1980 to 2020, drawing upon resource curse and energy transition theories. The results of this study are generated by using correlation analysis, quantile process estimation, autoregressive distributed lag (ARDL), and sensitivity analysis. The nexus among variables is seen across all quantiles, ranging from 22% to 81%. On the contrary, a negative association exists between oil price volatility and industrial financial expenditures, with the magnitude of the correlation ranging from 19% to 90%. Significantly, these connections exhibit statistical significance in short-term and long-term scenarios. This paper proposes implications to enhance financial expenditures in the Chinese oil business. These strategies include diversification, hedging via futures contracts and swaps, and short-term forecasts of oil price movements.

The impact of government subsidies on capacity utilization in the Chinese renewable energy industry: Does technological innovation matter?

With the rapid increase in China's installed capacity of renewable energy (RE), there has been growing concern regarding the problem of overcapacity in China's RE industry. However, there is ongoing debate regarding the influence of government subsidies (GS) on the RE industry's capacity utilization (CU), and the role of technological innovation in this aspect has been overlooked. This study utilizes panel data from 114 Chinese RE-listed companies spanning from 2011 to 2021, aiming to uncover the impact of GS on the CU of RE. The findings show that GS reduces the CU of RE firms. Specifically, GS has not only facilitated investments in RE but also bolstered enterprises' market share. However, the former effect is stronger, reducing the CU of RE companies. In addition, our findings reveal that when the technological innovation capability of RE companies surpasses a certain threshold, the negative impact is weakened. Finally, for non-state-owned, growth-stage, low R&D subsidy proportion, and western region-based RE firms, the adverse effect of GS on their CU is particularly prominent, but no statistically significant evidence to suggest such an effect for state-owned, non-growth-stage, high R&D subsidy proportion, and non-western region-based RE firms. Accordingly, we present targeted policy recommendations.

The main trends in the development of China's fuel and energy complex: Prospects for Russian-Chinese energy cooperation

Subject. This article discusses the issues of environmental safety and strengthening Russia's economic position in Asia. Objectives. The article aims to identify promising areas of cooperation between Russia and China in the energy sector. Methods. For the study, we used the methods of statistical analysis, induction and deduction. Results. Based on the analysis of the problems of the Chinese energy industry in the current conditions, as well as plans for the medium and long-term development of the fuel and energy complex of China, the article finds that at present, the gas industry determines the nature of cooperation between Russia and China in the energy sector to the greatest extent. Conclusions. In the coming decades, renewable energy sources will become one of the main factors in the development of the economy.

Two kinds of properties of knowledge networks, knowledge diversity and recombinant innovation: a patent analysis in the wind energy field

PurposePrior literature has long argued that knowledge networks contain great opportunities for innovation, and researchers can identify these opportunities using the properties of knowledge networks (PKNs). However, previous studies have examined only the relationship between structural PKNs (s-PKNs) and innovation, ignoring the effect of qualitative PKNs (q-PKNs), which refer to the quality of the relationship between two elements. This study aims to further investigate the effects of q-PKNs on innovation.Design/methodology/approachUsing a panel data set of 2,255 patents from the Chinese wind energy industry, the authors construct knowledge networks to identify more PKNs and examine these hypotheses.FindingsThe results show that q-PKNs significantly influence recombinant innovation (RI), reflecting the importance of q-PKNs analysed in this study. Moreover, the results suggest that the combinational potential of an element with others may be huge at different levels of q-PKNs.Originality/valueThis study advances the understanding of PKNs and RI by exploring how q-PKNs impact RI. At different levels of PKNs, the potential of the elements to combine with others and form innovation are different. Researchers can more accurately identify the opportunities for RI using two kinds of PKNs. The findings also provide important implications on how government should provide support for R&D firms.

Voluntary environmental regulation and export performance of Chinese solar energy industry

The shortage of traditional fossil energy resources, together with the pressure of environmental pollution, has stimulated the growing trade of solar energy products in China. The purpose of this article is to examine the impact of voluntary environmental regulation on China's solar energy industry trade flows. To this aim, the paper selects panel data of Chinese solar energy industry exports to 46 countries from 2002 to 2020 and uses the fixed effect regression model. The results show that export destination countries' voluntary environmental regulation has a significant positive impact on China's exports, whereas the bilateral gap in voluntary environmental regulation has a negative effect. Further evidence suggests that reducing the bilateral gap in voluntary environmental regulation has more obvious promoting effect of the exports to developed countries than to developing countries, verifying that there is country heterogeneity. Besides, more trade friction weakens the role of the host countries' voluntary environmental regulations in promoting exports. The implication of this paper is that voluntary environmental regulation have economic effects including demand effect, information effect and the common language effect, which is incredibly significant to promoting the sustained and stable development of the solar energy trade.

US―China Green Trade Conflict and Implications for Low-Carbon Energy Transition: The Solar Energy Trade Dispute

Purpose - The purpose of this paper is to analyze the causes of Sino-U.S. solar PV trade disputes by adopting research, comparative research, and case study. It also proposes relevant resolutions over Sino-U.S. solar trade conflicts and the implications for low-carbon energy transition.
 Design/Methodology/Approach - Based on green trade protectionism and comparative advantage theory, this paper combines Chinese solar products export flows to the U.S. with cases of solar trade disputes from 2011 to 2022 to analyze the causes of Sino-U.S. solar trade conflict. Thus, from the perspective of international trade law, WTO reform on the relevant renewable energy agreements, international carbon border tax regime, and a bilateral clean agreement or EGA negotiations, it purposes the resolution of Sino-U.S. solar trade conflict.
 Findings - This paper studies factors leading to the Sino-U.S. solar trade conflict, which is mainly a bilateral trade imbalance, the game of interest groups within the US, non-standard support policies for Chinese solar energy industry, and geopolitical and national green energy security. There is no doubt that trade disputes had had a larger negative impact on Sino-U.S. solar trade flows from 2011 to 2019. Meanwhile, the solar PV trade policies of the US affected the global supply chain of solar PV products, thus hindering the progress of low-carbon energy transition.
 Research Implications - In the management of this paper, this study has important practical significance for the healthy and sustainable development of solar PV trade and achieving low-carbon energy transition for both countries. It can also provide references to solar energy trade disputes among other countries in a broader sense, and propose relevant recommendations for South Korea’s solar energy.

Do Factor Market Distortions and Carbon Dioxide Emissions Distort Energy Industry Chain Technical Efficiency? A Heterogeneous Stochastic Frontier Analysis

China’s high-quality economic development is hampered by market distortions, and promises to achieve peak carbon emissions by 2030, meaning that its economic growth faces serious environmental constraints. We use a heterogeneous stochastic frontier model to analyze the impact of factor market distortions and carbon dioxide emissions on economic growth, and to evaluate the Chinese energy industry’s chain technical efficiency under the influence of factor distortions and carbon dioxide emissions. Finally, the counterfactual measurement method is used to calculate the factor market distortions and loss of the energy industry chain technology efficiency as a result of carbon dioxide emissions. The main research results show that China’s energy technology efficiency is 0.959, and the average energy industry chain technical efficiency for each region from the highest to the lowest is east (0.961), center (0.957), northeast (0.955), and west (0.950). The space for efficiency improvement is 3.6377%, 4.5151%, 4.7669%, and 5.2521%, respectively. Factor market distortion and carbon dioxide emissions are the main sources of losses of energy industry chain technical efficiency. Although the energy industry chain technical efficiency is subject to market factors, the structural factors caused by sustainable efficiency are more obvious. In the case of factor market distortions and carbon dioxide emissions, China’s energy industry chain technical efficiency slowly increased from 0.952 in 2000 to 0.964 in 2016. By reducing the degree of factor market distortion, China’s average energy industry chain technical efficiency will rise to 0.9651 from 0.9649, representing an improvement of 3.6162%.

Climate policy uncertainty and corporate investment: evidence from the Chinese energy industry

In recent years, with the increasing attention paid to climate risks, the changes in climate policies are also more full of uncertainties, which have brought tremendous impact to economic entities, including companies. Using the dynamic threshold model, this study investigates the nonlinear and the asymmetric effect of climate policy uncertainty on Chinese firm investment decisions with panel data of 128 Chinese energy-related companies from 2007 to 2019. The empirical findings indicate that the influence of climate policy uncertainty on firm investment is significantly nonlinear. Overall, climate policy uncertainty is not apparently related to corporate investments in the high-level range, while it negatively affects the investments in the low-level range. In addition, to be more specific, the negative impact of climate policy uncertainty on the mining industry is tremendous, while the influence on the production and supply of electricity, heat, gas, and water sector is remarkably positive. The results of this study could help the company managers and policymakers to arrange appropriate related strategies under different climate policy conditions.

How do carbon cap-and-trade mechanisms and renewable portfolio standards affect renewable energy investment?

In order to promote the low-carbon transformation, Chinese government plans to implement two policies in the power industry: carbon cap-and-trade mechanisms and renewable portfolio standards. However, whether their synergy can drive the development of Chinese renewable energy industry has become a key issue. Based on China’s renewable energy industry, this paper established an optimization model with the objective function for maximizing electricity company profits. The study further employed scenario analysis to design four policy scenarios: no-policy scenario, carbon cap-and-trade mechanisms scenario, renewable portfolio standards scenario and mixed scenario. The mentioned scenarios were used to explore the impact of various policy situations on electricity companies’ investment decisions, total carbon emissions, consumer surplus and social welfare when renewable energy, new conventional energy and conventional energy are available in the market. The research findings obtained thus showed that in terms of renewable energy promotion, mixed scenario is the best. Our results also showed that at the initial stage of China’s low-carbon transformation, the social welfare level under mixed scenario is the highest. The outlined findings provide some policy suggestions for promoting the rapid development of renewable energy and accelerating the low-carbon transformation with high quality.

Overnight-Intraday Mispricing of Chinese Energy Stocks: A View from Financial Anomalies

We verify the existence of firm-level “intraday return vs. overnight return” pattern and overnight-intraday effect of nine financial anomalies of Chinese energy industry stocks of the Chinese stock market. Though energy finance has been an independent research area, we also take Chinese A-shares stocks as samples for empirical analysis to avoid the so-called sample selection bias. Specifically, it verifies that the overnight returns are strongly negative and intraday returns are positive for energy industry stocks, which is totally contrary to the American stock markets. In addition, alphas of the zero-cost strategies based on nine classic financial anomalies are almost earned at night for energy industry stocks. Finally, it is risk-related anomalies that occur overnight for energy industry stocks, while both four risk-related anomalies and two firm characteristics related anomalies occur at night for all A-shares stocks. Our empirical findings based on Chinese financial markets enrich the existing research on the mispricing of financial anomaly and shed a new sight on the asset pricing in energy finance.

Interaction effects of government subsidies, R&D input and innovation performance of Chinese energy industry: a panel vector autoregressive (PVAR) analysis

ABSTRACT Purpose : This article investigates the interaction effects among government subsidies, research and development (R&D) input and innovation performance of the Chinese energy industry. Methodology This article establishes a panel vector autoregressive (PVAR) model and uses the impulse response function (IRF) tool and variance decomposition of all variables to reveal the evolution process of variables’ relationship in different time periods based on the data of 95 listed energy companies in China from 2010 to 2018. Findings : The results show that R&D input and innovation performance promote government subsidies; government subsidies and innovation performance promote R&D input; R&D input substantially promote innovation performance; and the dynamic interaction of the three variables differs for state-owned and non-state-owned companies. Originality : This article focuses on the Chinese energy industry and considers the ownership of companies. The PVAR model is used to establish a dynamic interactive system of variables, which considers the dynamic interaction relationship among government subsidies, R&D input and innovation performance in this specific industry.

The risk spillover effect of the COVID-19 pandemic on energy sector: Evidence from China

Detecting the adverse effects of major emergencies on financial markets and real economy is of great importance not only for short-term policy reactions but also for economic and financial stability. This is the lesson we learnt from the COVID-19 pandemic. This paper focuses on the risk spillover effect of the COVID-19 on Chinese energy industry using a high-dimensional and time-varying factor-augmented VAR model. The results show that the net volatility spillovers of the pandemic remain positive to all underlying energy sectors during January to June of 2020 and February to April of 2021. For the former sub-period, the volatility spillover of the COVID-19 is not only the highest, but also lasts longest for oil exploitation sector, followed by the power and gas sectors. While for the latter sub-period, the COVID-19 has relatively higher volatility spillovers to the power, coal mining and petrochemical sectors. These findings suggest that the COVID-19 has significant risk spillover effects on Chinese energy sectors, and the effects vary among different energy sub-sectors and across different periods of time.

Examining the impact of factor price distortions and social welfare on innovation efficiency from the microdata of Chinese renewable energy industry

The marketization of factor prices is not only an important component of pricing reforms but also a decisive determinant of innovation efficiency (IE). A good social welfare (SW) system attracts talent and affects the labor market. Thus, it is important to explore the impact of factor price distortions (FPDs) and SW on IE. Based on panel data on the Chinese renewable energy industry covering 2010–2019, this paper uses the Cobb-Douglas production function to calculate FPDs, adopts stochastic frontier analysis to measure IE, and then employs the sys-GMM method for empirical testing. The empirical results show the following: 1) FPDs can significantly inhibit IE. Furthermore, if FPDs are divided into capital (CPDs) and labor price distortions (LPDs), CPDs have a greater inhibitory effect on IE than LPDs. 2) SW has a significantly negative impact on IE. Moreover, if SW is divided into SOE social welfare (SSW) and non-SOE social welfare (NSSW) on the basis of the enterprise's ownership structure, SSW is significantly negatively related to IE, while NSSW is significantly positively related to IE. 3) The moderating effects of SSW have a significantly negative impact on the relationship between FPDs and IE, while the moderating effects of NSSW have a significantly positive impact on the relationship between FPDs and IE. Based on the above research results, this paper puts forward a series of policies to improve the IE of the renewable energy industry.

A study of environmental disclosures practices in Chinese energy industry

In 2016, China increased sustainability practices among companies listed on China’s stock market, making environmental regulations one of their integral policies. This states that highly polluting industries like the energy industry are required to comply with the sustainability requirements set. Concerning this event, research was conducted in 2016 to 2017, on the development of environmental disclosure (ED) practices in China and the impact of different variables on environmental disclosure index (EDI). Focusing on 150 energy companies listed on the Shanghai and Shenzhen stock exchange, the findings show that if the company had a better ROA, firm size, leverage and environmental accreditation certificate, they would like to publish more relevant environmental information.

Business environment drivers and technical efficiency in the Chinese energy industry: A robust Bayesian stochastic frontier analysis

Improving the technical efficiency of the energy industry is a fundamental way to ensure energy security and sustainable development and is also a requirement of the supply-side structural reform of China’s energy. Although the business environment plays an important role in the energy industry, this relationship between efficiency and business environment has been scarcely studied. In addition, there has been no attempt made to link the financial sector and energy industry together. To this end, a novel Robust Bayesian Stochastic Frontier Analysis (RBSFA) is developed here, where DIC (Deviance Information Criteria) is minimized by the variance/covariance optimization of three classical distributional assumptions for the inefficiency term (u): Gamma, Exponential, and Half-Normal. The goal is to develop a RBSFA model to relate the technical efficiency of the energy industry in China with major business environment performance variables (financial sector variables, energy industry variables and macroeconomic variables). Results indicate that the efficiency level of the Chinese energy industry is quite high over the examined period, although there is a large variance between different companies. Our findings further show that increases in the efficiency of the Chinese energy industry can be achieved by increasing the level of inventories and fixed assets, as well as research and development expenses. Finally, we find that the efficiency level in the Chinese energy industry is affected by the business environment. In particular, we notice that financial sector development and competition are helpful to improve the efficiency of Chinese energy companies.