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Household Surveys performed in four villages selected from Oromia, Amhara and Southern Nations, Nationalities, and Peoples’ Region (SNNPR) following from the ‘Ethiopian Rural Household Survey’ (ERHS) conducted in 2004.It contains detailed data on household consumption and expenditures, assets, income, agricultural activities, land allocation, demographic characteristics, and other variables. From September 2011 to January 2012 another survey of 221 households was conducted in three major regions of central and southern Ethiopia. At the time of this latest survey effort the most recent ERHS survey data available was from 2004. The selection of respondents, determination of sample size, and apportionment of the sample were based on a proportional sampling technique.In addition to addressing important questions from the ERHS survey data, the field survey was designed to generate detailed information on household biomass energy production and consumption practices; as well as farming activities; labour and land allocation; economic and demographic characteristics; and expenditures on food, non-food items, and energy. The 2011 survey effort collected detailed household biomass energy use data. The measurement of household biomass energy use was obtained in traditional units and later converted into kilograms. The conversion factors for each of the biomass were collected from the closest urban centre of each of the study areas. Information obtained on household biomass energy use was collected for a time period of one week before the survey was conducted. It was then aggregated into annual figures, although household biomass energy use may vary seasonally. Quality/Lineage: The data was collected by qualified enumerators who had participated in previous ERHS survey. In addition to myself I recruited assistant supervisor to check the accuracy and quality of data on daily basis and followup interview process closely. Before the survey commenced a pilot survey was conducted in each of the study areas to identify the different types of energy households are using and other critical variables of interest for the research. This information was used to revise and improve questionnaire. Moreover, a one day in-depth training was given to enumerators and assistant supervisor to enrich their deeper understanding of each the question in the survey and to further improve questionnaire from their earlier experiences in those villages. Purpose: Over 90% of Ethiopian rural population rely on biomass energy. However, biomass energy utilization is linked to household livelihood as in rural households produce and consume biomass energy simultaneously with other (on and off-farm)activities. With the rampant rate of deforestation that Ethiopia is facing it is important to investigate the effect of deforestation or fuelwood scarcity which is assumed affect household welfare through influence on wage and price. In light of this, the survey effort collected information on household use of biomass energy sources, expenditure and labour allocation choices and amount of labour time used for each activities.This helped me to investigate the effect of fuelwood scarcity on household welfare from three aspects: labour allocation decision, energy expenditure and fuel choice and biomass energy consumption behavior to better understand the related linkage of household production and utilization of biomass with livelihoods or food security. This dataset was first published on the institutional Repository "Zentrum für Entwicklungsforschung: ZEF Data Portal" with ID={c08e08aa-3055-4651-801b-0383610c1987}.

Although the United Nations’ Sustainable Development Goals (SDGs) advocate, through SDG 4 and SDG 10, equitable quality education and the reduction of inequalities within and between countries, respectively, few studies have examined how inequalities in regional sustainability influence higher education. Therefore, this study aims to examine the relationship between regional sustainability and higher education in China using fixed-effects panel modelling. A systematic force framework showing how regional sustainability drives higher education was constructed from economic, social, and environmental perspectives, and the endogeneity in the process of how regional sustainability affects higher education was explored by introducing one-year lagged values as instrumental variables. Our results show that regional sustainability has a significant impact on higher educational attainment in China, with differing effects in the eastern, central, and western regions, respectively. In central China, economic sustainability plays a significant positive role in higher educational attainment; in the western region, economic and social sustainability have stronger positive effects, while environmental sustainability has significantly negative effects. In terms of policy implications, our findings can be used to support regional development policies to promote regional higher education.

This dataset contains the underlying data for the following publication: Li, R., Perdana, S., Vielle, M. (2021), Potential integration of Chinese and European emissions trading market: welfare distribution analysis, Mitigation and Adaptation Strategies for Global Change, 26:22 https://doi.org/10.1007/s11027-021-09960-7.

We researched China's climate and sustainable development goal with relevant and susceptible instruments capable of inducing and mitigating carbon emissions. Amidst the contributor to the global carbon emissions, China is caught in between mitigating its carbon emission and aiming towards placing its national contribution of emissions to the acceptable levels of 1.5 °C and below 2 °C. Following the intricacies surrounding China's sustainable development as it contains its economic and environmental performance, we adopt China's data of 1980 and 2018 with different scientific approaches (nonlinear autoregressive distributed lag (NARDL), dynamic ordinary least square test, and bootstrap Granger causality) with different instruments (such as economic growth, financial development, renewable energy, and innovation policies) to research China's sustainable development. For clear exposition and insight into our findings with policies attached, we draw a conclusion from the outcomes of the mentioned approaches. From NARDL and dynamic ordinary least squares (DOLS), we find that economic growth through economic activities is statistically significant in determining the trend (increase) of carbon emissions in China in both periods (short run and long run). However, other selected instruments (financial, renewable, and innovation policies) tend towards controlling and moderating the carbon emissions in China. Thus, China has good prospects to mitigate its carbon emissions if considered tailoring its policies towards favorable instruments. From bootstrap Granger causality, we find similar inferential results that support previous findings thereby confirming the positive implication of the selected instruments to China's sustainable development. Hence, the nexus that is established among the selected instruments clearly show the importance of technological innovation and renewable energy in mitigating carbon emissions.

This paper examines the environmental Kuznets curve (EKC) theory, augmenting the role of oil resources and energy consumption in carbon dioxide (CO2) emissions using the annual data of 11 African oil-producing countries from 1980 to 2014. We apply advanced panel cointegration and panel autoregressive distributive lag (ARDL) techniques coupled with Granger non-causality analysis to account for cross-sectional dependence and heterogeneity. The results of the augmented mean group (AMG) reveal that oil resources abundance degrades the environmental quality in Angola while abating CO2 emissions in Algeria, Gabon, Morocco, and Nigeria. Contrarily, energy consumption escalates pollution in the Congo Democratic Republic (COD), Côte d’Ivoire (CIV), Gabon, Morocco, and Tunisia. Our findings support the EKC hypothesis only in Cameroon, CIV, and Nigeria while exhibiting a U-shaped curve in Algeria and Morocco. Causality analysis unveils that oil resources Granger cause energy consumption, suggesting the balance between renewable and non-renewable energy sources. The current study has important policy implications for promoting green technology, economic diversification, service sector, and green investments.

The study investigates the nexus of CO2 emissions, tourism, fossil fuels, and GDP growth using China’s data from 1970 to 2019. The research applied the upset U-molded EKC and the ARDL -models to calculate the time series stationarity variables. The results showed that in the initial enlargement phases, a sophisticated GDP adversely impacts CO2 emissions, then a higher GDP positively influences CO2 emissions. The development of tourism, use of fossil fuels (coal and oil), and population growth show an important influence on CO2 emissions but the use of gas and electricity has little effect on CO2 emissions. In contrast, foreign direct investment besides population development had little effect on increasing CO2 emissions. Retreating foreign direct investment, strengthening the use of sustainable electricity, and improving transportation for explorers, especially the green tourism business, are excellent ways to reduce environmental degradation in China.

Abstract Reasonable assessment of the environmental benefits of integrating forest products into global value chains (GVCs) is important to promote sustainable development. Based on the forest product sector data for 41 countries from 2002 to 2014, this paper explores the impact of GVC participation on carbon embodied in exports using the 2008 financial crisis, a quasi-natural experiment of negative global value chain shocks. We found that deepening backward participation in forest product value chains led to more substantial increases in carbon emissions than did forward participation. Countries with large decreases in GVC participation reduced more carbon embodied in forest product exports after the financial crisis (relative to countries with small decreases) through a larger reduction in the scale of forest product exports, and a decrease in the growth rate of capital-intensive products as a result of the relative decline in capital investment. They increased the embodied carbon of exports through a decrease in the growth rate of skilled personnel. Strengthening the technology effect of GVCs with the guidance of skilled forestry personnel is a key way to decrease exported embodied carbon.

As absolute poverty in China, measured by the current standard, is being eliminated, the focus of future poverty reduction projects will necessarily shift to addressing relative poverty. Contiguous poverty areas have been identified in Hebei province around Beijing and Tianjin (HABT), and this is not conducive to the coordinated development of the Beijing-Tianjin-Hebei region. The dynamic identification of relative poverty at the county level within the region must be the basis for formulating scientific strategies for poverty reduction. Night light (NTL) data can reveal socio-economic information and reflect human activities, and has a wide range of other applications for evaluating and identifying poverty. For this reason, NPP/VIIRS (Visible Infrared Imaging Radiometer Suite equipped on the Suomi National Polar orbiting Partnership satellite) NTL data from 2012 to 2020 were corrected, and NTL data for HABT were obtained. A multidimensional relative poverty index (MRPI) that assesses being “free from worries over food and clothing and having access to compulsory education, basic medical services, and safe housing” using social statistical data was created with the analytic hierarchy process and entropy weight method. A panel regression model with fixed effects was established for MRPI and corrected NPP/VIIRS NTL data. The R2 of fitting was 0.6578 and confirmed a strong correlation between MRPI and corrected NPP/VIIRS NTL data. Based on this, the MRPI estimation model was constructed based on the MRPI and corrected NPP/VIIRS NTL data, and passed the accuracy test. Finally, using the national list of poverty counties, it was verified that, at the county scale, the corrected NPP/VIIRS NTL data could effectively identify areas of relative poverty. This study lays the foundation for the use of NPP/VIIRS NTL data in the identification of areas of relative poverty. It provides a feasible method and data reference for analyzing relative poverty at a smaller scale. The dynamic identification of areas of relative poverty can also provide a basis for formulating scientific poverty reduction strategies.

Developing a low-carbon economy is the only way for countries to achieve sustainable development. Carbon emission reduction policies and low-carbon technology (LCT) innovation play key roles in developing low-carbon economy. Under government reward and punishment regulations, based on the bilateral matching and evolutionary theories, this paper constructs an evolution model consisting of a manufacturer investing LCT and a supplier offering LCT to analyze multi-phase LCT investment strategies. Firstly, the profit optimization model of a green supply chain is constructed from the perspectives of centralized-matching (CM), decentralized-matching (DM), and mismatching (MM), and the spatial information internal evolution law of multi-phase LCT investment is described by the Markov chain. Then, a bilateral matching algorithm is proposed to solve the equilibrium solutions, and the evolution process of the three modes is analyzed by numerical simulation. Finally, based on the product green degree, we analyze the impact of subsidies and taxes on investment-production decisions. Analytical results show that the matching mechanism proposed in this paper can help supply chain firms to obtain stable matching and has a significant effect on the realization of "triple wins" of society, economy, and environment. The investment utility of CM is higher than that of DM and MM. Manufacturers are inclined to adopt LCT, and the investment level tends to be stable over time. Government reward and punishment regulations are helpful to motivate supply chain firms to invest in LCT, and the synergistic effect of subsidies and taxes is better than that of a single policy.