Consumption Structure Research Articles

Energy Price Distortions and Urban Carbon Emission Efficiency: Evidence from China’s Energy-Intensive Sectors

With a primary focus of achieving carbon neutrality, the energy-intensive industrial sectors (EIIs) contribute to more than half of China’s carbon dioxide (CO2) emissions. During the process of China’s rapid economic development, distorted energy prices gradually became the main obstacle to energy conservation and emission reductions in the EIIs. Therefore, this study focused on determining the mechanisms affecting the energy price distortions of carbon emission efficiency (CEE) in China’s EIIs. Based on a stochastic frontier analysis, the changing trend of CEE in China’s EIIs was evaluated. The channels impacting the energy price distortions of CEE were further analyzed by a mediating effect and moderated mediating effect model. The main contributions and findings include the following: energy price distortions have a significant negative impact on CEE by suppressing technological innovations and hindering the restructuring of energy consumption; governmental environmental regulatory policies mitigate their suppressing effect on technological innovations and reduce the preventing effect by improving the energy consumption structure. The results suggest that market-based price reforms and moderate environmental regulation by the government could help to improve CEE in China’s EIIs. These findings are of great significance for promoting the sustainable development of the energy-intensive industrial sectors and achieving carbon neutrality.

The Promoting Effect of Green Bonds on Reducing Carbon Emission Intensity Through Energy Structure Transition

Climate change poses a significant threat to the sustainable development of all countries. The transition to low-carbon energy sources is a crucial strategy for reducing carbon emissions and mitigating climate change. We investigate the mediating role of clean energy consumption (EC) and fossil energy supply (ES) on the promoting of carbon emission intensity per unit of GDP (CO2/GDP) reduction by green bonds (GBs). We develop a mediating model to analyze how GB influences CO2/GDP reduction through EC and ES, utilizing panel data from 13 prefecture-level cities in Jiangsu province spanning the years 2007 to 2021. Additionally, we assess the model’s reliability through endogeneity and robustness tests. We find that GBs contribute to reducing CO2/GDP by facilitating the structural transition of energy supply and consumption. Furthermore, the development of GBs enhance the consumption of clean energy and plays a direct role in advancing the transition in structure of both energy supply and energy consumption. Notably, we observe heterogeneity in the effectiveness of GBs on CO2/GDP reduction across different regions. Therefore, it is imperative for the government to actively promote the development of GBs to achieve sustainable economic growth. Furthermore, both financial and energy policies should be tailored to align with the specific energy structures of various regions.

A study on the impact of high-speed rail on the consumption structure of urban and rural residents in China.

Consumption is crucial to individual well-being and national economic development. This study investigates whether high-speed rail (HSR) influences consumption expenditure (CE) and consumption structure (CS) of urban and rural Chinese citizens. Using panel data from 2003 to 2019 and econometric models, this study finds that: (1) HSR significantly increases CE for both urban and rural residents, promotes CS upgrades in rural areas, but inhibits CS upgrades in urban areas. These results remain robust after extensive testing. (2) HSR's impact on urban consumption is relatively focused and singular, whereas its effect on rural consumption is dispersed and extensive. Additionally, the impact of HSR on consumption exhibited significant delays and regional characteristics. (3) Mediation analysis reveals that HSR significantly enhances urban and rural CE and facilitates rural CS upgrades through market, price, and income effects. However, it also triggers housing price increases, impeding urban CS upgrades. This study provides important references for the government to optimize transportation infrastructure investments, promote balanced economic development between urban and rural areas, and enhance residents' well-being.

The Impact of Changes in China's Population Structure on Consumption Patterns

Consumer spending is the key engine driving economic growth in China. However, in recent years, the overall consumption pattern in China has been affected by domestic epidemics, leading to an increase in unemployment rates among residents and a decrease in consumer willingness. As a result, the annual changes in final consumption expenditure have tended to stabilize, with almost no upward trend. Consequently, numerous studies have emerged based on the current consumption situation in China, providing recommendations to promote consumption. This paper, using data from the World Bank and China's National Statistical Yearbook, conducts research on the impact of demographic changes on consumption structure and proposes relevant suggestions to boost consumption in China. Researching the development of China's population structure reveals several notable trends. These include a decrease in the working-age population accompanied by a significant aging trend, improvements in population quality due to enhanced human capital, and a noticeable trend towards urbanization and increased population mobility. Therefore, this paper provides a series of recommendations, encourages national policies and corporate innovations that promote consumption, and offers solutions to potential issues arising from changes in population structure.

Spatio-temporal variations of energy carbon emissions in Xinjiang based on DMSP-OLS and NPP-VIIRS nighttime light remote sensing data.

With the rapid economic development of Xinjiang Uygur Autonomous Region (Xinjiang), energy consumption became the primary source of carbon emissions. The growth trend in energy consumption and coal-dominated energy structure are unlikely to change significantly in the short term, meaning that carbon emissions are expected to continue rising. To clarify the changes in energy-related carbon emissions in Xinjiang over the past 15 years, this paper integrates DMSP/OLS and NPP/VIIRS data to generate long-term nighttime light remote sensing data from 2005 to 2020. The data is used to analyze the distribution characteristics of carbon emissions, spatial autocorrelation, frequency of changes, and the standard deviation ellipse. The results show that: (1) From 2005 to 2020, the total carbon emissions in Xinjiang continued to grow, with noticeable urban additions although the growth rate fluctuated. In spatial distribution, non-carbon emission areas were mainly located in the northwest; low-carbon emission areas mostly small and medium-sized towns; and high-carbon emission areas were concentrated around the provincial capital and urban agglomerations. (2) There were significant regional differences in carbon emissions, with clear spatial clustering of energy consumption. The clustering stabilized, showing distinct "high-high" and "low-low" patterns. (3) Carbon emissions in central urban areas remained stable, while higher frequencies of change were seen in the peripheral areas of provincial capitals and key cities. The center of carbon emissions shifted towards southeast but later showed a trend of moving northwest. (4) Temporal and spatial variations in carbon emissions were closely linked to energy consumption intensity, population size, and economic growth. These findings provided a basis for formulating differentiated carbon emission targets and strategies, optimizing energy structures, and promoting industrial transformation to achieve low-carbon economic development in Xinjiang.

Regional energy consumption policy practice to promote low-carbon economy

IntroductionEnergy is the fundamental driving force for world economic and social development. However, the growth of carbon dioxide emissions and increasing environmental challenges are becoming increasingly problematic, limiting the pace of economic development.MethodsTo optimize the energy consumption structure and promote the development of low-carbon economy, this study took Shaanxi Province as an example to analyze the impact of low-carbon economy policy variables on the energy consumption structure dominated by coal. The purpose of this study is to examine the influence of policy variables on the evolution of energy consumption structure by constructing a system dynamics model. In addition, this study will explore policy optimization issues.ResultsThe error of simulation results was within ±10%. The consumption of non-fossil energy increased from 2,196,400 tons of standard coal in 2009 to 22.578 million tons in 2030, which is in line with the development trend. Under these four policy combinations, the share of coal will fall to 57.8 percent by 2030. In addition, the share of non-fossil energy sources will increase to 21 percent and the share of natural gas will reach 16 percent.DiscussionThe policy suggestions put forward in this paper are of great significance to the optimization of energy structure led by coal. The model constructed can be effectively applied to practical policy simulation and adjustment, and can provide reference for the development of low-carbon economic policies in other regions.

Urban housing prices and consumption structure upgrading: Different relationships in urban and rural China

The dynamics of housing prices can play a pivotal role in shaping household behavior. Motivated by the limited research on the impact of housing prices on consumption structure upgrading in China, this paper presents a series of analyses that deploy panel data from 276 Chinese cities between 2005 and 2019 to scrutinize this impact. Firstly, fixed effect models were used to investigate the relationship between urban housing price and the consumption structure upgrading, and it was found that urban housing price has an inverted U-shaped effect on the consumption structure upgrading of Chinese urban residents, while it has an inhibitory effect on the consumption structure upgrading of Chinese rural residents. Then, we conducted multiple robustness tests, all of which corroborated the benchmark results’ reliability. Finally, deeper than existing research, the mechanism of the impact of urban housing prices on the consumption structure upgrading was further explored and it was found that increasing urban housing prices can affect consumption structure upgrading by affecting residents’ marginal propensity to consume in development and enjoyment. Our findings provide key alternatives for China’s government to promote residents’ consumption structure upgrading.

Enormous inter-country inequality of embodied carbon emissions and its driving forces in South America

South America is a crucial developing region under significant pressure to reduce emissions and achieve carbon neutrality. This study fills a vital gap by comprehensively analysing the continent’s carbon emissions from both production and consumption perspectives. Utilizing the most up-to-date global Multi-Regional Input-Output (MRIO) models, we examine the emissions embodied in the internal and external trade of nine major South American countries, tracing the emission flows from their origins to final consumers and analyzing the socio-economic drivers behind these patterns. Our analysis reveals that regions bearing heavier burdens of energy-intensive production often face exacerbated economic disparities. Trade-related emissions are embodied in heavy industry and transportation, and the share of emissions attributable to developing countries is continuously climbing. Brazil is the sole net-exporter of emissions, while Colombia has become a significant net importer. Energy intensity offsets the increase in carbon emissions caused by per capita consumption, especially in Brazil. Meanwhile, Colombia experiences an increase in emissions due to its energy structure, whereas a general trend towards decreasing emissions is noted elsewhere. The impact of the industrial chain is mainly domestic and extends forward along the supply chain. Interestingly, the consumption structure reduces emissions in Argentina and Bolivia, but increases them in other countries. Key emission mitigation initiatives include Brazil enhancing its leadership in bioenergy, Chile intensifying the development of green industrial chains for high-emission sectors, and Uruguay advancing its wind energy projects to increase clean energy exports, etc. These measures could facilitate targeted and effective decarbonization while promoting equitable and sustainable economic development across South America.

Exploring carbon footprints and carbon intensities of Indonesian provinces in a domestic and global context

Within Indonesia, the structure of consumption and production differs significantly across provinces. This implies that carbon footprints and intensities between provinces are also diverse. This paper calculates historical consumption- and production-based carbon emissions at the provincial level using a multi-scale input-output (IO) database for 2010, in which an environmentally extended multi-regional IO (EE MRIO) table for 34 Indonesian provinces is integrated in the global EE MRIO EXIOBASE with data for 43 countries and 5 rest of the world regions. Emissions from consumption are detailed by product and their points of origin, while emissions from production are detailed by industry and their destinations. Our results show the heterogeneity of Greenhouse Gas (GHG) emissions under both sides. The Java region is a net importer of carbon emission, while Sumatra and Kalimantan are net exporters. In the global context, the Asia Pacific region plays important role in national GHG emissions. Services product contributed 57.1% of national consumption-based GHG emissions, followed by manufacture (30.6%), and agriculture (12.3%). On the national level, 63.5% of national GHG emissions are related to household consumption. There is a high disparity across provinces in Indonesia in carbon footprints. Provincial average per capita carbon footprints vary from 2 t CO2e/capita in East Nusa Tenggara to 13.84 t CO2e/capita in East Kalimantan. Carbon intensity also varies from 0.83 kt CO2e/M Euro in Jakarta to 2.37 kt CO2e/M Euro in North Kalimantan. Agriculture and food products dominate household carbon footprints, while construction leads in government carbon footprints. Utilities and transportation services play important roles on national carbon intensities. We further correlated the Human Development Index (HDI) with per capita carbon footprints and expenditure, and find that provinces with similar GHG emissions and expenditure per capita income as Java, tend to have a lower HDI. Understanding development status and province-level characteristics is important for selecting policy strategies.

Incorporating embodied carbon transfer and sequestration service flows into regional carbon neutrality assessment in China

Reliable and effective carbon neutrality assessments are crucial prerequisites for implementing various low-carbon policies and achieving carbon neutrality goals. Although the impact of embodied carbon transfer and carbon sequestration service flows on regional carbon neutrality is becoming increasingly significant, these factors are not effectively incorporated into current carbon neutrality assessments. Based on a thorough review of the literature and theoretical analysis, this study attempts to construct a regional carbon neutrality assessment framework that incorporates embodied carbon transfer and carbon sequestration service flows. This framework is then applied to assess carbon neutrality and its influencing factors in China's provinces. Our findings reveal that carbon emissions and sequestration capacities have increased across Chinese provinces, with the highest emissions in North and East China, and the highest sequestration in Southwest China. Economically developed provinces like Beijing, Zhejiang, and Jiangsu transfer substantial embodied carbon to provinces such as Inner Mongolia, Shanxi, and Hebei, while Guangxi, Sichuan, Yunnan, and Qinghai are major providers of carbon sequestration services. Carbon neutrality levels in Chinese provinces show a ring-shaped distribution, increasing from the inner to outer rings. Higher levels are found in Southwest and Northwest provinces (e.g., Yunnan, Qinghai, Guangxi), and lower levels in North and East provinces (e.g., Shanxi, Beijing, Zhejiang). Factors like urbanization rate, population density, per capita GDP, and energy consumption structure negatively impact carbon neutrality levels, whereas ecological land area and annual precipitation have positive impacts. In summary, incorporating embodied carbon transfer and carbon sequestration service flows into the regional carbon neutrality assessment framework facilitates a more comprehensive analysis of regional carbon neutrality levels and their influencing factors. This approach broadens the theoretical and methodological scope of regional carbon neutrality assessments and provides scientific references for the implementation of low-carbon policies and the advancement of carbon neutrality goals.

Impact of urban-rural resident basic medical insurance on consumption quality of middle-aged and older adult residents: evidence from rural China.

In the context of the Chinese government's advocacy for "Internal Circulation", ongoing reforms in medical insurance policies raise critical questions about whether the basic medical insurance system can stimulate resident consumption and enhance its quality. Based on five waves of panel data from the China Health and Retirement Longitudinal Survey (CHARLS), this paper analyzes the impact of medical insurance on the consumption scale and structure of middle-aged and older adult rural residents by using the time-varying difference-in-differences (time-varying DID) method. The findings indicate that the Urban-Rural Resident Basic Medical Insurance (URRBMI) effectively stimulates the consumption scale of rural middle-aged and older adult individuals, particularly enhancing non-food consumption, development-oriented spending, and hedonic consumption. This, in turn, optimizes the consumption structure and improves overall consumption quality. Notably, URRBMI significantly enhances the consumption scale and structure among rural middle-aged and older adult women, unmarried individuals, and residents in western China. These results suggest that URRBMI plays a crucial role in alleviating consumption inequality within rural areas and across different regions, providing a theoretical foundation for policy-making.

How does ICT development in resource-exhausted cities promote the urban green transformation efficiency? Evidence from China

The contradiction between resource depletion and economic growth in resource-exhausted cities is becoming prominent. The role of ICT has been reflected in many policies to promote sustainable urban development. It is necessary to clarify the mechanism of ICT for urban green transformation efficiency (UGTE) in resource-exhausted cities. In this research, 39 resource-exhausted cities in China were selected as the research samples, and panel data were collected for 20 years to assess their ICT development level and their UGTE. The panel regression model, PVAR model, heterogeneity test, and moderating effect test were used to analyze the relationship between the two. The main findings are as follows: (1) ICT has a facilitating effect on UGTE in resource-exhausted cities, with a regression coefficient of 0.170⁎⁎⁎. (2) The improvement of ICT significantly promotes the UGTE in these cities, and the promotional effect reaches a peak after a lag of 6 periods; the original UGTE also has a negative impact on the future ICT development level, and the negative impact reaches a peak after a lag of 6 periods. (3) The promotional effect of ICT on UGTE in resource-exhausted cities consists of being strongest in the eastern region (0.477⁎⁎⁎), then in the central region (0.233⁎⁎⁎), weaker in the western region (0.167⁎⁎), and weakest in the northeastern region (0.080*). (4) The improvement of energy structure, green innovation structure, and urban-rural consumption structure strengthens the promotional effect of ICT on UGTE in resource-exhausted cities. Finally, targeted policy recommendations were proposed.

Automated workforce, financial precarities and family consumption: The importance of demand-side policies under the background of automation applications

The continuous innovation of automation technology is expanding its application in the workplace, with wide-ranging implications for the economy and society. However, it is not yet clear how workplace automation changes people’s consumption behavior. This paper conducts an empirical analysis in this regard based on the Chinese General Social Survey. The main results are shown as follows: (1) One standard deviation increase in automation contributes to an average reduction of 7.073 % in family consumption. This finding is validated by conducting several robustness and endogeneity checks using various measures of automation and consumption, instrumental variable approach, placebo analysis, etc. (2) The mechanism is that automation decreases family income and work-related social capital, resulting in a decline in families’ socioeconomic status and increased financial precarities. In addition, financial uncertainties brought about by automation decrease people’s subjective well-being, expectations for future life and risk appetite, thus prompting them to lower consumption as a precautionary measure to prepare for potential risks caused by the technological change. (3) Automation has greater negative effects on hedonic and developmental consumption, which are about three times the impact on non-hedonic and basic living expenses respectively, thus leading to a downgrade in families’ consumption structure. In addition, its effect is more pronounced for families with lower economic status, having no houses and living in urban areas. This study also highlights the importance of demand-side policies in the application of automation technology by finding that better labor protection is needed to mitigate automation’s adverse consequences for family consumption. In the context of automation’s increasingly profound impact on the society, this research has important policy implications.

Research on the prediction and realization path of urban carbon peak along the Yellow River Basin

China and the international community attach great importance to sustainable development goals such as peaking carbon emissions. As an important energy base in China, the Yellow River Basin has significant capacity for reducing carbon emissions and increasing carbon sinks. To accelerate the achievement of carbon peak targets, social and natural development data as well as carbon emission data of 56 cities along the Yellow River Basin from 2000 to 2021 were analyzed. Based on the evaluation indicators of the model, the PSO-XGBoost-RF model was selected from the comparative models to predict the carbon peak of cities in the Yellow River Basin under different paths. Under the current economic and social development, cities along the Yellow River Basin in China are facing huge pressure to reduce emissions. It is expected to achieve a carbon peak in 2033, with a peak of 2,051,320,000 tons, so the target of reaching the peak of carbon emissions before 2030 will not be accomplished. But through comprehensive optimization of the industrial structure and reduction of energy consumption, cities along the Yellow River Basin as a whole may achieve carbon peak by 2026, with a peak of 1,917,132,000 tons.

How does digital finance alleviate fiscal stress? Evidence from China

The impact of digital finance on fiscal stress is an important issue in achieving high-quality financial development. Based on the theoretical analysis of digital finance and fiscal stress, this paper utilizes data from 285 cities in China spanning from 2011 to 2020, empirically tests the impact of digital finance on fiscal stress by employing fixed effect model and spatial Durbin model, and identifies the influence mechanism. The results demonstrate that: (1) The development of digital finance can significantly alleviate fiscal stress, which remains valid after conducting a series of robustness tests. In addition, the impact of digital finance on fiscal stress predominantly originates from the coverage breadth of digital finance. (2) Mechanism analysis reveals that promoting the increase of fiscal revenue and improving the efficiency of fiscal expenditure are crucial mechanisms for digital finance to alleviate fiscal stress. (3) Heterogeneity test indicates that digital finance has a more significant alleviating effect on fiscal stress in central regions and cities with higher levels of economic development. (4) The spatial effect test suggests that digital finance exhibits a significant spatial spillover effect on fiscal stress, and an enhancement in digital finance level in a region will reduce fiscal stress in its neighboring regions. The above findings offer insightful guidance for government to better utilize digital financial tools to manage debt, optimize the structure of fiscal revenue and expenditure, and promote sustainable financial development.

Glass-Based Micro-Hotplate With Low Power Consumption and TGV Structure Through Anodic Bonding and Glass Thermal Reflow

Glass-Based Micro-Hotplate With Low Power Consumption and TGV Structure Through Anodic Bonding and Glass Thermal Reflow

Carbon emission prediction in a region of Hainan Province based on improved STIRPAT model.

In 2020, China pledged carbon reduction targets at the United Nations: peaking emissions by 2030 and achieving carbon neutrality by 2060. Research and prediction of regional carbon emissions are crucial for achieving these dual carbon targets across China. This study aims to construct an indicator system for regional carbon emissions and utilize it for forecasting. Analyzing carbon emission data from a specific area in Hainan Province from 2010 to 2020, we established an indicator system. Using the interpretable SHAP model, we assessed indicator importance and trends. Employing an improved STIRPAT model with partial least squares regression to address multicollinearity among influencing factors, we developed a carbon emission prediction model. Based on this, we forecasted carbon emissions from 2021 to 2060 in the specified area under three scenarios: natural, baseline, and ambitious. The results show that the growth of resident population and per capita GDP has the most significant promoting effect on carbon emissions in the region while optimizing industrial structure, energy consumption structure, and reducing energy intensity will inhibit carbon emissions. The prediction results indicate that in the natural scenario, regional carbon emissions will peak in 2035, and achieving carbon neutrality by 2060 is not feasible, while the baseline scenario and ambitious scenario can achieve the dual carbon targets on time or even earlier. The research results of this article provide a reference method for predicting carbon emissions in other regions and a guide for future regional emission reduction.

Transformation of values, consumption and production structure in modern Russia

Transformation of values, consumption and production structure in modern Russia

Evaluating the Impact of Chinese FDI in the Energy Sector on Green GDP Growth: A Spatial Econometric Analysis of MENA Countries

This study analyzes the impact of Chinese foreign direct investment (FDI) in the energy sector on the green GDP (GGDP) growth of seven Middle East and North Africa (MENA) countries based on data from 2009 to 2019. Using panel regression analysis, the study focuses on the effects of FDI, economic development level, population size, energy consumption structure, environmental regulation intensity, government fiscal expenditure, and the KOF Economic Globalization Index on GGDP growth. By comparing fixed-effects and random-effects models and applying the Hausman test to select the most appropriate model, the research indicates that the random-effects model is the most suitable. The results show that FDI, economic development level, and population size have significant positive effects on GGDP, while shifts in energy consumption structure also promote sustainable economic growth. In contrast, environmental regulation intensity and the globalization index have no significant impact on GGDP, suggesting that GGDP growth in MENA countries relies more on internal economic policies and the efficiency of resource allocation.

Effects of Socio-Economic and Demographic Factors on Meat Consumption Pattern in Iran: A Demand System Approach

Meat as one of the most important resources of protein has a special role in human nutrition. Understanding the meat consumption structure of households is essential for planning and policymaking in this regard. In this research, we studied consumption patterns of meat products including chicken, veal, lamb, and fish for households in Iran (Mashhad city) using demand system estimation. The hypothesis of this study is that chicken is a necessary goods and other types of meat are luxury goods. Given the cross-sectional nature of the data and presence of zero expenditure for some households, we used the censored demand model based on a consistent two-step approach. For this purpose, at first, four Probit models were estimated to determine the factors affecting the probability of purchasing each selected meat product. After that, the probability density function (PDF) and the cumulative distribution function (CDF) were calculated for each selected meat product, and the Almost Ideal Demand System (AIDS) considering PDF and CDF was estimated for all types of meat using a non-linear seemingly unrelated regression. Also, the effect of demographic variables on meat consumption pattern was considered in demand system. The results of expenditure elasticities confirmed the hypothesis. The highest own-price elasticity was related to veal. Based on compensated price elasticities, all types of meat were net substitutes for chicken and chicken was also a net complement for all types of meat. On the other hand, the only substitute for lamb and chicken was veal, but with compensating income effect fish also became a substitute for them. So, in the event of an increase of the price of lamb and chicken, we recommend subsidizing the consumers with low purchasing power in order to increase the diversity of consumption of protein products. This can increase the consumption of fish.