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This study aims to investigate the predictors of reading performance and how reading performance predicts mathematics and science performances in PISA 2018 study. For this purpose, the country in the focus (Turkey), the highest performer (China [B-S-J-Z]) in the world, and the lowest performer (Mexico) among the OECD members countries were selected as the research sample. A total of 12058 students participated from China (Male=6283, Female=5775), 6890 students from Turkey (Male=3494, Female=3396), and 7299 students from Mexico (Male=3473, Female=3826) in PISA 2018 study. The results revealed that 'Index of economic, social and cultural status', 'Meta-cognition: assess credibility', and 'Meta-cognition: summarizing' are the most significant factors affecting students' reading literacy in all three countries. Total explained variance explained is 41%, 41%, and 39% for Turkey, China (B-S-J-Z) and Mexico, respectively. 'Index highest parental occupational status', 'Duration in early childhood education and care', 'Attitude towards school: learning activities', and 'Subjective well-being: Sense of belonging to school' are not significant predictors for reading literacy of students from all three countries. In addition, regarding the predictivity of reading literacy, total variance explained is 65% in mathematics performance and approximately 77% in science performance for all three countries.

This study investigated Chinese and Turkish prospective geography teachers' use of computer and internet applications as indispensable instruments in and out of education. 292 prospective geography teachers students from Shanghai, China, and Izmir, Turkey, participated in this study. The aim of this study was to examine the use of computers and internet by prospective teachers in both Turkey and China. Hence, this study aimed to propound the similarities and disparities between Turkish and Chinese geography students in computer and internet use. The results of this research show that there are meaningful differences between prospective geography teachers in Turkey and China in terms of purpose of computer and internet usage. Although both Turkish and Chinese prospective geography teachers have used most "education aimed media" Turkish female prospective teachers in Turkey have been using the internet and the computer less than those of its Chinese counterparts. In addition, this research showed with the use of observation, interview and literature review that while internet use of prospective geography teachers in Turkey is largely affected by social-economic and cultural factors, the use of the internet of those in China is decided by political decisions taken by the Chinese government.

Rapid modernization and industrialization have significantly intensified carbon emissions and worsened environmental sustainability around the globe. Despite the significant importance of green innovation, clean energy consumption, and education in every aspect of life, the role of all these variables in determining environmental sustainability has not been explored quite extensively in case of China. Under this premise, the present study aims to investigate the role of green innovation, clean energy investment, and education on environmental sustainability in highly polluted Asian economies for the period of 1991–2019 by employing the autoregressive distributed lag (ARDL) model. The findings infer that increase in green innovation reduces CO2 emissions in China, India, and Japan in the long-run. However, an increase in clean energy investment and education tends to decline CO2 emissions in Russia and Japan. The findings confirm that green innovation, clean energy investment, and education improve environmental sustainability in long-run, while short-run estimates are diverse. Thus, governments of highly polluted economies should increase investment in education, clean energy, and technology to mitigate CO2 emissions. [ABSTRACT FROM AUTHOR]

A better understanding of the dynamics involved in grain production is critical for food security and poverty reduction. To this end, several factors influence grain production, including capital (i.e. R&D investment and agricultural credit), agriculture environment (i.e. CO2 emissions), and technical progress (i.e. fertilizers and agricultural machinery). This paper analyses the combined effects of these factors on China's grain crops output from 1990 to 2017 by using the autoregressive distributed lag (ARDL) approach. The ARDL‐bounds testing approach provided the long‐run connection amid the variables. The findings include: (i) agricultural R&D spending has an encouraging and meaningful influence on grain crops yield in the long‐run and short‐run; (ii) agricultural credit significantly and positively stimulates grain crops output; (iii) CO2 emissions negatively impact grains' output in the short‐ and long‐run; (iv) area under grain crops and fertilizers used also endure a positive spur on grain crops production in the long‐run and short‐run; and (v) short‐run nexus among the variables is navigated for robustness rationale via the vector error correction model Granger causality practice. Hence, the strategy specialists should also acquaint finances through prescribed organizations on comfortable provisions and minimal interests. In addition, the Chinese Governments and agricultural extension organizations should support the easy acquisition of high‐tech cultivating machinery to harvest crops swiftly and explore substantial markets for further business. [ABSTRACT FROM AUTHOR]

We aim to investigate the impact of environmental entrepreneurship and green innovations on CO2 emissions in highly polluting Asian economies. For empirical estimation, we have applied ARDL and NARDL models. In the short run, the linear estimates of environmental entrepreneurship are significant in China and India. The short-run non-linear estimates of environmental entrepreneurship are significant in the case of China, India, and Japan. Similarly, the short-run linear estimates of green innovations are significant in China, India, and Japan, whereas the non-linear estimated coefficients of green innovation appeared to be significant in India, Japan, and Russia. In the long run, the linear estimates of environmental entrepreneurship are negative and significant in three countries, namely China, Japan, and Russia. Similarly, the estimates of green innovations are negative and significant in China, India, Japan, and Russia. In the non-linear model, the estimated coefficients of positive shock in environmental entrepreneurship are significant and negative in the case of China, India, and Japan; while, the estimates of negative shock in environmental entrepreneurship are negative and significant in India only. [ABSTRACT FROM AUTHOR]

The notion of green growth has occurred as a leading policy response to environmental pollution. This study explores the dynamic impacts of green investment, financial institutions & markets on green growth based on a time series data set comprised of four high polluted Asian countries from 1995 to 2019. We found several important short and long-run results from the ARDL bounds testing approach. First, green investment has a positive long-run effect on green growth in China, India, and Russia. Second, financial institutions have positive long-run effects on green growth in China, India, and Japan; but financial markets improve only in China and Russia. The findings also propose that internet users and R&D foster green growth in mostly high polluted Asian countries. Thus, our findings offer some implications for high polluted Asian countries to stimulate green growth in the future. [ABSTRACT FROM AUTHOR]

Government investment in environmental protection (Govin) plays a key role in stimulating private green investment (Prinv) to preserve the ecological environment with economic profits. To examine the effect of Govin on Prinv, this study uses data from 2010 to 2020 on green A-listed companies in China and estimates a dynamic panel model by using both the difference generalized method of moments and system generalized method of moments. The results indicate that Govin has a crowding-in effect on Prinv, and this conclusion is confirmed by several robustness tests. Furthermore, we identify revenues as a potential mechanism variable to explain how Govin affects Prinv. In addition, this study finds regional and enterprise ownership differences in the crowding in effect of Chinese Govin. Finally, based on these outcomes, the study suggests that the government should rationally and dynamically adjust the contents of public environmental investment and optimise its structure to effectively promote the development of green, low-carbon, and circular economies. [ABSTRACT FROM AUTHOR]

The primary motive behind this research is to see the role of China's large agriculture sector in promoting or demoting CO2 emissions. Therefore, we applied linear and non-linear ARDL models by collecting data over the period 1971–2019 for China. The results of the linear model suggest that livestock production can help to reduce CO2 emissions both in the short and long run. In the non-linear model, the short-run estimates of livestock production are insignificant, however, in the long run, the positive shock in the livestock production helps to reduce the CO2 emissions and the negative shock is insignificant. On the other side, an increase in crop production deteriorates the environmental quality in the short run in both linear and non-linear models. In long run, the estimate of crop production in the linear model is insignificant and in the non-linear model, the estimated coefficients of both positive and negative shocks in crop production are negative implying that a positive shock reduces the CO2 emissions while the negative shock increases the CO2 emissions. [ABSTRACT FROM AUTHOR]

One of the strategic objectives of China is to increase renewable energy consumption by reducing non-renewable energy consumption. This motivates us to carefully investigate the asymmetric effects of financial deepening on renewable and non-renewable energy consumption for China, using annual data from 1990 to 2019. The results show that in China, a positive shock in bank deposits and broad money has a significant increasing effect on renewable energy consumption, while a negative shock in bank deposits and broad money has also a significant increasing effect on renewable energy consumption in the long-run. Moreover, positive change in bank deposits and broad money has an inverse impact on non-renewable energy consumption, while negative change has stimulating non-renewable energy consumption in long run. Thus, government and policymaker's policies aimed at promoting financial deepening in China must be persistent and sustainable to foster renewable energy consumption. [ABSTRACT FROM AUTHOR]

Copyright of Gazi Medical Journal is the property of Galenos Yayinevi Tic. LTD. STI and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Içtimaiyat is the property of Ictimaiyat and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The dispute between economic growth and greenhouse gas emissions is one of the major challenges of the twenty-first century. The central issue of the emerging economies revolves around the decoupling of economic growth and the rising carbon dioxide (CO2) emissions. This study examines the decoupling the CO2 emissions from the economic growth through the employment of the Tapio decoupling index and decomposition of CO2 emissions into its pre-determined factors through the Log Mean Divisia Index (LMDI) decomposition technique for Pakistan, India, and China (PIC) for a time span of 1990–2014. The findings of the Tapio elasticity analysis depict that in a few years, environmental impact has been seen to be decoupled from the economic growth in the respective PIC countries. However, relatively Pakistan experienced expensive negative decoupling; India mostly experienced weak decoupling and expensive coupling, while China exhibited weak decoupling in multiple years. In addition, the analysis of Tapio decoupling elasticity showed that energy intensity is the key factor supporting the decoupling in PIC countries, while population, affluence (GDP per capita) and energy structure have weakened the progress of decoupling. Furthermore, the analysis of the LMDI decomposition suggested that population, energy structure and affluence in PIC countries increase the CO2 emissions, while energy intensity reduces CO2 emissions, while mixed effects are reflected by carbon intensity. [ABSTRACT FROM AUTHOR]

This work analyzed the long-run (LR) and short-run (SR) effects of renewable and non-renewable energy (RE and NRE) usage, economic development (ED), agricultural value-added (AVA), and forestry area (FA) on the environmental quality (EQ) in China spanning from 1990 to 2015. The autoregressive distributed lags (ARDL) bounds testing method and the Johansen cointegration approach are applied to produce empirical estimates. The empirical results of the ARDL and the fully modified ordinary least square (FMOLS) estimators established that renewable energy usage and forest area reduce CO2 emissions and improve the environmental quality, while non-renewable energy consumption, economic development, and agricultural output increase the level of CO2 emissions in China. The robustness of outcomes is checked through the Granger causality test, impulse response function (IRF), and variance decomposition method (VDM) suggesting that fossil fuel usage in the agriculture production process is mainly accountable for China's CO2 emissions. These findings have inherent policy implications for the central and local Chinese government, which are exhibited in the "Conclusions" section. [ABSTRACT FROM AUTHOR]

Globally, the use of modern technologies is increasing along with carbon emission due to the consumption of fossil fuels to operate modern technologies. Therefore, in this study, we aimed to investigate the relationship between carbon emission, renewable energy consumption, forestry, and agricultural value added per capita from 1998 to 2018. The auto-regressive distribution lag model was estimated for long-run and short-run correlation analysis. The results of this study revealed that carbon emission decreases owed increases in forest areas in the long and well as short-run nexus. Furthermore, in the short run, carbon emission decreases due to an increase in renewable energy consumption. In addition, the carbon emission was run in an upward direction parallel to agricultural financial development. Furthermore, this study confirmed that the unidirectional causality between variables by estimating the non-Granger causality test. Therefore, this study suggests that to combat carbon emissions with carbon emission, it is necessary to switch from nonrenewable energy to renewable energies and organic fertilizer consumption along with afforestation to make the climate free from carbon. [ABSTRACT FROM AUTHOR]

Copyright of International Journal of Economic & Social Research is the property of Abant Izzet Baysal University, Faculty of Economics & Administrative Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Carbon dioxide emission and climatic variation have a detrimental influence on the atmosphere as well as on agriculture production. The key aim of the present study was to investigate the influence of carbon dioxide emission on livestock, cereal crops production, rainfall and temperature in China by utilizing the vector autoregressive model and Granger causality test for the period 1988–2017. Variables stationarity was verified by using ADF, P-P and KPSS unit root tests. The outcomes through long-run dynamics exposed that agriculture value added and rainfall have a positive influence on carbon dioxide emission, while cereal crops production, livestock production and temperature have an adverse interaction with carbon dioxide emission. Similarly, the results of the short-run analysis also demonstrate that agriculture value added, cereal crops production, livestock production, rainfall and temperature have a significant influence on carbon dioxide emission with their p-values (0.0488), (0.0885), (0.0263), (0.0096) and (0.5141) respectively. Furthermore, the Granger causality test outcomes also exposed a unidirectional linkage amid the variables. In order to improve agricultural productivity, the Chinese government should take potential steps to minimize the carbon dioxide emission from various industries that trigger climate change. [ABSTRACT FROM AUTHOR]

The accelerated urbanization in China was already coupled with a steadily increasing demand for energy usage. The present study major aim was to determine the asymmetric influence of urbanization, energy utilization, fossil fuel energy and CO2 emission on economic progress in China by using an annual time series data varies from 1975 to 2017. Stationarity amid variables was verified by applying the unit root tests, while non-linear autoregressive distributed lag (NARDL) bounds testing model was used to examine the asymmetric impacts on variables with short- and long-run dynamics. Outcomes revealed that via short-run estimates, the negative shocks of energy usage cause significantly to increase the economic efficiency, but positive shocks of energy utilization display the adverse linkage with the economic progress. Similarly, the negative shocks of GDP per capita growth demonstrate a substantial upsurge in the economic progress, and the positive shocks establish the adverse influence towards economic growth. Further, the outcomes of short-run dynamics also exposed the negative shocks of urbanization significantly affected the economic growth, but positive shocks exposed the adversative influence on economic growth. The outcomes display that fossil fuel energy consumption showed a constructive impact to economic progress, and additionally, the variable CO2 emission also uncovered a positive shocks having significant impact on economic progress. Furthermore, the outcomes of long-run analysis express that energy utilization has negative and positive shocks that expose the adverse influence on economic progress of China. GDP per capita growth exposed the constructive influence on the economic growth in both shocks. The negative and positive shocks of urbanization demonstrate a noteworthy influence on economic growth. The variable fossil fuel energy consumption also exposed an optimistic influence on economic progress, and finally the influence of CO2 emission on economic growth is insignificant as the results exposed. The reducing carbon alteration target aims to be reached for China, and in the next several decades, it will encourage the green energy options in order to decrease carbon dioxide emission to avoid environmental pollution by raising its energy intensity. [ABSTRACT FROM AUTHOR]

The People's Republic of China, which is the starting point of the Covid-19 epidemic, is one of the dominant economies that steer the world economy. This situation appears as a determining factor in the extent of the cycles in the global economy. In this respect, considering the exponential rate of the epidemic, the incidence of the epidemic around the world increases day by day and increases social and economic uncertainties and risks. While the outbreak is producing disruptions in the internal economies of the country's economies and production processes, the increase in the uncertainty over the epidemic poses the risk of a systemic crisis, primarily through activities such as global trade, tourism and transportation. In this study, the scenarios and effectiveness of monetary-fiscal measures and the effectiveness of monetary and fiscal measures regarding the shape and length of the recession on the global economy within the framework of the economic risks arising from the pace of the outbreak. [ABSTRACT FROM AUTHOR]

Since the 1970s, China has begun to implement the developing industrial civilization in the world alienated from its traditional culture and has achieved a rapid development trend as a result of the reforms it has made. As a result of rapid industrialization and distorted urbanization, China has begun to tackle various ecological and social problems that adversely affect the well-being of society both academically and politically. In this context, it has developed the “Ecological Civilization” paradigm since the end of the 20th century. This study aims to explain the concept of ecological civilization and the factors in its emergence, examining the dimensions of ecological civilization and the relationship between sustainable development, evaluation of this paradigm within the scope of sustainable development policies of today's Turkey. [ABSTRACT FROM AUTHOR]

The role of energy cannot be passed over in the process of economic growth and development in any economy. China consumes colossal quantity of energy; thus, the central objectives of this study is to empirically evaluate the linkages among energy use, environment by CO2 emissions, human health by health expenditures, Foreign Direct Investment (FDI) inflows, and real GDP per capita used for economic growth over the period of 1995–2016 for China. The nature of the data directed to employ the Canonical cointegrating regression (CCR) method for unknown parameter estimation. Four equations have estimated namely for FDI, health, environment, and economic growth. The result for China during the period under the study reveals that energy consumption has significant positive impact on FDI, health, environment, and economic growth. The study results suggest that policy makers need to chalk out effective policy for effective utilization of energy so as to encourage permissible economic growth and development in China. [ABSTRACT FROM AUTHOR]

The present study is aimed to explore the relationship between coal consumption, industrial production, and CO emissions in China and India for the period of 1971-2011. The structural break unit root test and cointegrating approach have been applied. The direction of causal relationship between the variables is investigated by applying the VECM Granger causality test. Our results validate the presence of cointegration among the series in both countries. Our results also validate the existence of inverted U-shaped curve between industrial production and CO emissions for India, but for China, it is a U-shaped relationship. Coal consumption adds in CO emissions. The causality analysis reveals that industrial production and coal consumption Granger cause CO emissions in India. In the case of China, the feedback effect exists between coal consumption and CO emissions. Due to the importance of coal in China and India, any reduction in coal consumption will negatively affect their industrial value added as well as economic growth. [ABSTRACT FROM AUTHOR]

Compares the financial characteristics of United States and Japanese electronics firms. U.S. trade deficit with Japan, especially in the electronics industries; Comparison of the profitability and financial leverage of the two countries in different periods; Impact of the devaluation of the Japanese yen against the U.S. dollar on commercial transactions.

This study examines the influence of digital finance and renewable energy technology innovation (RETI) on green growth using Chinese regional data from 2007 to 2019. It applies Method of Moments Quantile Regression (MMQR) to integrate asymmetric green growth patterns in China's prefecture-level regions. Moreover, the generalized method of moment (GMM) is used to address possible endogeneity between model variables. The results of MMQR reveal that digital finance stimulates green growth at middle to higher quantiles (4th to 6th), and central and eastern regions fall within these quantiles. In contrast, western regions have an insignificant impact as prescribed by lower quantiles (1st to 3rd). Similarly, RETI failed to increase the growth across lower to middle (1st to 6th) quantiles in western and central regions. However, the extremely high quantiles indicate a significantly positive connection, demonstrating that RETI contributes to green growth primarily in eastern regions. Moreover, the outcomes stated that government intervention significantly enhances green growth throughout quantiles. The results from GMM endorse a similar outcome, indicating that the marginal contribution of digital green finance towards green growth is more substantial in the eastern sub-sample, followed by central and western regions, respectively. Likewise, green growth is more responsive to changes in RETI in eastern and western regions. These results suggest that digital finance and RETI are imperative to ensure regional green growth; however, their marginal contribution should be improved in western and eastern regions. • MMQR and GMM were applied using Chinese regional data. • Regional green growth is heterogeneous. • Digital green finance and renewable energy technologies stimulate green growth. • Eastern and central regions show a higher response in green growth than others. [ABSTRACT FROM AUTHOR]

The current era faces the devastating threats of global warming than what is evident in the pre-industrial age. Efforts toward resolving these environmental issues have heightened the calls for pro-green policy measures in which renewable energy and green finance stand out. Consequently, this study examines the impact of renewable energy, green finance, technological innovation, and economic complexity on sustainable development captured by sustainable economic growth and carbon neutrality in China. The empirical model endogenizes the role of natural resource dependence and human capital. The analysis is based on annual time series data from 1996 to 2018 estimated using autoregressive distributed lag (ARDL) model. The empirical results reveal that renewable energy (RE) and technological innovations (TECIN) are fundamental factors whose engagement is not negligible if the other indicators must provide desirable and consistent growth and environmental effects that support sustainable development. In particular, the essential roles of green finance on sustainable development are empirically confirmed for China. Interestingly, the robustness analyses conducted provided substantial backings for the main results. Practical policy implications leading to the sustenance of green finance, renewable energy, and technological innovation for driving sustainable development in the Chinese economy are formulated based on empirical results. • Policies signify greenhouse gas emissions reduction motivated this research. • Autoregressive distributed lag (ARDL) model employed for the period of 1996–2018. • Renewable energy & technological innovations are vital for sustainable development. • The impacts of the other regressors are inconsistent on the outcome variables. • The robustness analyses conducted provided substantial backings for the main results. [ABSTRACT FROM AUTHOR]

The aim of this research is to examine the link between CO 2 emissions, hydroelectricity consumption, urbanisation and real GDP in China and India during the period of 1965–2013. The long-run cointegration is investigated by the autoregressive distributed lag (ARDL) bounds testing approach, which is augmented with structural breaks. We employ the ARDL cointegration test to establish long run relationship in the variables. Furthermore, we use the ARDL to show that real GDP and urbanisation have long-run positive impact on emission, while hydroelectricity consumption exerts long-run negative impact on emission in both countries. The results support the existence of environmental Kuznets curve (EKC) hypothesis in China and India. Besides, the paper assesses the causal link between the variables by using Granger causality procedures and the results show that there is long-run bidirectional relationship between the variables in both countries. [ABSTRACT FROM AUTHOR]

Recent industrial surge in the Northwestern provinces of China resulted in substantial energy consumption and adverse effect on the environment. Despite being less established, the Northwestern region of China has strategic importance and the use of renewable energy can potentially promote sustainable development in this region. Considering this aspect, this study aims to investigate the impact of renewable energy on environmental pollution in five Northwestern provinces of China during 1995–2014. This study uses the Nonlinear Autoregressive Distributed Lag bounds testing approach with the structural break unit root and other specifications tests. The results indicate that renewable energy positive shock has an adverse impact on the CO 2 emissions of the Northwestern provinces of China. The effect of renewable energy use varies in five provinces, i.e. it is more significant in Gansu, Qinghai and Xinjiang than in Ningxia and Shaanxi. However, reduction in renewable energy consumption leads to higher level of CO 2 emissions and this effect is more significant for Ningxia and Shaanxi in the long run. Furthermore, the positive shockwaves in nonrenewable energy, GDP and transportation are associated with environmental pollution in these provinces both in short run and long run. Nevertheless, the impact of negative shockwaves in nonrenewable energy consumption on environmental pollution is more significant than economic development for all provinces. Our findings suggest that: cutting down fossil fuels use can substantially improve environmental quality in these provinces; depending on the provincial geographies and government strategies, the intensity of positive impact of renewable energy towards CO 2 emissions reduction differs among five provinces. Likewise, renewable energy development has abundant potential to increase the economic and ecological sustainability in the Northwestern provinces of China in the long run. [ABSTRACT FROM AUTHOR]

The economic conditions of rural households have changed because the extensive usage of the Internet technology in rural China. Hence, according to micro-survey data from the China Family Panel Studies (CFPS) in 2014, 2016 and 2018, in this work we use the Probit model to experimentally examine the association between cooking energy usage and Internet technology use in Chinese rural households. Research results showed that Internet technology use can significantly and positively influences the choice of Households' clean cooking energy, and further mechanism analysis reveals that off-farm employment as a partly mediator between the use of the Internet and the clean energy consumed by households. In particular, we further examine the region and age differences in Internet technology use and its household cooking energy consumption consequences. The assessment of the Internet technology used by rural residents' heterogeneity indicates that in the eastern region or the younger and middle-aged group of rural residents can better use the Internet technology to realize the households' cooking energy conversion. Therefore, in the context of global climate change and frequent catastrophic weather occurrences, we suggest that rural households should widely utilize the Internet, greatly expand off-farm employment channels, and accelerate the conversion and upgrading of cooking energy consumption in rural areas. • Impact of Internet use on rural households' fuel consumption in China is examined. • Data from the China Family Panel Studies (CFPS) in 2104, 2016 and 2018 is used in this study. • Probit model and the mediation effect model are applied. • Internet use significantly promotes household clean fuel consumption in rural China • Mechanism analysis reveals that non-agricultural employment plays a partial mediating role. [ABSTRACT FROM AUTHOR]

This study aims to analyze the current situation of farmers' social capital and energy consumption structure in the Qinba mountainous area of southern Shaanxi China. Based on 746 survey data of farmers' social capital and energy consumption it further explores the impact of social capital on farmers' energy consumption structure by using Tobit model and Logit models. Findings of this study reveal that: (1) The energy consumption of farmers in the Qinba mountainous area of southern Shaanxi is diverse and structurally stable. Farmers' energy consumption is mainly based on the electricity, coal, and firewood and farmers' utilization rate of coal, gasoline, and diesel, liquid gas, and solar energy is more than 30%. (2) Findings also reveal that farmers' energy consumption gradually turned to commercialization; cleaning farmers' energy consumption had an obvious tendency, and the power utilization rate was 94.3%. (3) Social capital was significantly positively correlated with commercial energy consumption and new energy consumption, and significantly negatively correlated with non-commercial energy consumption. Improving farmers' social capital, improving energy infrastructure and optimizing energy consumption structure can not only improve farmers' quality of life in rural areas, but also provide reference for reducing carbon dioxide emissions and alleviating global environmental degradation. • This study analyzes the current situation of energy consumption structure. • The results show that energy consumption in the study is diverse and stable. • Social capital has significant correlation with commodity energy consumption. • Social capital has significant negative correlation with non-commodity energy. • Improving farmers' social capital can alleviate global environmental degradation. [ABSTRACT FROM AUTHOR]