Multidimensional Assessment and Alleviation of Global Energy Poverty Aligned With UN SDG 7

There are increasing concerns that energy poverty across nations is weakening the global efforts toward achieving Sustainable Development Goals (SDGs). A systematic assessment of energy poverty is, therefore, essential to track the spatiotemporal pattern of SDG 7 and monitor the global efforts in alleviating energy poverty. This article develops the first Multidimensional Energy Poverty Assessment Index (MEAI), incorporating energy availability, affordability, and efficiency applicable to quantify the spatiotemporal dynamics of energy poverty development at global, regional, and national scales. Our analyses indicate that the overall MEAI and indices in all dimensions decreased from 2001 to 2016 at a global level with energy affordability experiencing the highest decline. The MEAI at the national level declines within the same period, showing significant regional heterogeneity in terms of the sub-index. Energy efficiency in developed and less-developed regions is characterized by high carbon emissions and low energy modernization, respectively. The energy availability indices are lower in developed nations and in nations with abundant energy resources. Overall, our results highlight a sudden increase in MEAI for Central America in 2014 and a gradual decline in MEAI for East Asia during 2014–2016. A call for regional actions is critically needed to solve energy poverty from different facets.

Evaluation and Analysis of Poverty-Stricken Counties under the Framework of the UN Sustainable Development Goals: A Case Study of Hunan Province, China

Eliminating all forms of poverty in the world is the first United Nations Sustainable Development Goal (SDG). Developing a scientific and feasible method for monitoring and evaluating local poverty is important for the implementation of the SDG agenda. Based on the 2030 United Nations SDGs, in this paper, a quantitative evaluation model is built and applied to all poverty-stricken counties in Hunan Province. First, based on the SDG global index framework and local index system of China, a local SDG index system for poverty-related goals is designed, and the weights of the indexes are derived using an entropy method. The scores obtained for counties and districts with data available are then taken as the true value for the poverty assessment. Second, using National Polar-orbiting Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) nighttime light images and land use and digital elevation model data, six factors, including socioeconomic, land cover, terrain and traffic factors, are extracted. Third, we then construct multiple linear evaluation models of poverty targets defined by the SDGs and machine learning evaluation models, including regression trees, support vector machines, Gaussian process regressions and ensemble trees. Last, combined with statistical data of poverty-stricken counties in Hunan Province, model validation and accuracy evaluation are carried out. The results show that the R2 and relative error of the localized, multiple linear evaluation model, including all six factors, are 0.76 and 19.12%, respectively. The poverty-stricken counties in Hunan Province were spatially aggregated and distributed mainly in the southeastern and northwestern regions. The proposed method for regional poverty assessment based on multisource geographic data provides an effective poverty monitoring reference scheme for the implementation of the poverty eradication goals in the 2030 agenda.

Water poverty assessment based on the random forest algorithm: application to Gansu, Northwest China

This study proposes a random forest algorithm to evaluate water poverty. It shows how the machine learning technique can be used to classify the degree of water poverty into five levels: very severe, severe, moderate, mild, and very mild. The strengths of the proposed random forest method include a high classification accuracy, good operational efficiency, and the ability to handle high-dimensional datasets. The success of the proposed method is empirically illustrated through a case study in Gansu, Northwest China. The analysis shows that from 2000 to 2017, the severity of water poverty in the study area declined. In 2000, most municipalities were classified as level 1 (very severe) or level 2 (severe). In 2017, level 1 water poverty disappeared, with most municipalities classified in as level 3 (moderate) and level 4 (mild). Spatially, there is a significant difference between the water poverty levels of the western, central, and eastern parts of Gansu, and the eastern part is affected by serious water poverty problems.

A Systematic Literature Review of Indices for Energy Poverty Assessment: A Household Perspective

Both developed and developing countries face energy poverty issues today. The growing interest over the last few years at the scientific level demonstrates the importance of the problem. It was a practice for many years to measure energy poverty by calculating the economic single indicators. In recent years, this practice was increasingly criticized and new, more comprehensive indices were developed. Review and analysis of indices developed can help scholars to dig deep into the specific aspects of the problem. The paper aims to review the indices for energy poverty assessment from households’ perspectives and to provide the main insights into the indicators selection process by providing the set of indicators for sustainable energy poverty assessment. The literature search and analysis follows the SALSA (Search, Appraisal, Synthesis and Analysis) and the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodologies. The literature search was carried out in the Web of Science (WoS) Core Collection database. The search covered the period 1994–2020. Thirty-four developed indexes for energy poverty were identified for assessment. In order to measure the most important dimensions and to reflect the modern concept of the energy poverty, the paper proposes a set of indicators for sustainable energy poverty assessment.

Covid-19 and Poverty Assessment in Nigeria – The Vulnerability Approach

The aim of the study was to abstract from the vulnerability theory to predict the likelihood of more people in Nigeria falling into the poverty trap as a result of the Covid-19 pandemic. The study used a parametric technique to obtain estimates of the mean and variance of one-period ahead log-consumption. In doing this, the study hypothesized that estimating household consumption function is important in making inferences about the future and in assessing the vulnerability of household to shocks. The simulation analysis shows that of the 82 percent of the households that are vulnerable to poverty, only about 13 percent are in transitory poverty while the rest are in structural poverty. The implication of this finding is that poverty situation in Nigeria is widespread, entrenched and inter-generational. The current coronavirus pandemic has merely worsened the poverty situation and is not the fundamental cause of poverty in Nigeria. The study recommended among others, that anti-poverty intervention measures of the government, going forward, must be forward-looking and aim largely to increase the productive capacity of the populace instead of merely aiming to alleviate their current state of poverty.

Poverty Assessment for Reorienting Poverty Alleviation Programmes in the Forest Fringe Area of Madhya Pradesh, India

The present study attempts to assess poverty using two commonly used indices namely Progress out of Poverty Index (PPI) and Progress out of Deprivation Index (PDI or DI) of 325 households, spread in twenty-nine villages of Hoshangabad and Mandla districts of Madhya Pradesh, India. The analysis of PPI and PDI scores showed that the poverty of a household/community decreases as their level of the economy, occupation and education improve, irrespective of their social class to which the household/community belongs. With this finding, it is recommended that prioritisation of the beneficiaries of programmes and policies related to poverty eradication in the forest fringe villages should not be based on caste or social class, but on household’s occupation, economy and education.

Poverty assessment in Russia: dependence on the measurement methodology

Poverty reduction is one of the main objectives of the state policy in the Russian Federation. In the decree of the President of the Russian Federation No. 474 of 21.07.2020 «On the national goals of the Russian Federation for the period up to 2030,» a target is determined - reducing the poverty level by half by 2030. To measure poverty in the Russian Federation until 2021, the absolute concept was used. Within the framework of this concept, it is planned to create a minimum standard on the basis of which the level of poverty was determined. In the Russian Federation, a consumer basket is adopted as a standard, on the basis of which the cost of living is calculated. The cost of living is the threshold for poverty. Since 2021, the methodology for measuring poverty has changed, the calculation is based on the relative concept, the median method is used to measure poverty. A number of countries also use the multidimensional poverty concept with a set of indicators to measure poverty. The article provides a comparative analysis of methodological approaches for poverty assessment. The article proves that the level of poverty depends on the methodological approach underlying its measurement. The author believes that only a multidimensional approach to measuring poverty will contribute to the development of effective public policies to overcome poverty.