Identification Of Poverty Research Articles

Factors of Energy Poverty: Evidence from Tibet, China

Energy poverty due to rising energy demand is a matter of global concern. Therefore, examination of the causes of energy poverty and development of effective solutions are urgent concerns. Using survey data on livelihood development in Tibetan farming and pastoral areas in 2019, this study applied logistic and ordinary least squares models to empirically investigate the factors that influence energy poverty in Tibet. We found that energy poverty is (1) unrelated to age, gender, education, marital status, political and village cadre experience, planting, or expenditures related to religious activities; (2) negatively correlated with migrant work, village status, household income, and traffic conditions; (3) positively correlated with employment, area, and breeding; and (4) both positively and negatively affected by family residence altitude. The results offer new insights and empirical evidence for the identification and elimination of energy poverty, improving livelihoods, and promoting rural revitalisation in Tibet.

Identifying Urban Poverty Using High-Resolution Satellite Imagery and Machine Learning Approaches: Implications for Housing Inequality

Enriching Asian perspectives on the rapid identification of urban poverty and its implications for housing inequality, this paper contributes empirical evidence about the utility of image features derived from high-resolution satellite imagery and machine learning approaches for identifying urban poverty in China at the community level. For the case of the Jiangxia District and Huangpi District of Wuhan, image features, including perimeter, line segment detector (LSD), Hough transform, gray-level cooccurrence matrix (GLCM), histogram of oriented gradients (HoG), and local binary patterns (LBP), are calculated, and four machine learning approaches and 25 variables are applied to identify urban poverty and relatively important variables. The results show that image features and machine learning approaches can be used to identify urban poverty with the best model performance with a coefficient of determination, R2, of 0.5341 and 0.5324 for Jiangxia and Huangpi, respectively, although some differences exist among the approaches and study areas. The importance of each variable differs for each approach and study area; however, the relatively important variables are similar. In particular, four variables achieved relatively satisfactory prediction results for all models and presented obvious differences in varying communities with different poverty levels. Housing inequality within low-income neighborhoods, which is a response to gaps in wealth, income, and housing affordability among social groups, is an important manifestation of urban poverty. Policy makers can implement these findings to rapidly identify urban poverty, and the findings have potential applications for addressing housing inequality and proving the rationality of urban planning for building a sustainable society.

Rural Poverty Patterns and Influencing Factors in Yunnan Province, China: Based on County Level Dataset

The identification of poverty at the county level is the precondition for poverty alleviation by formulating accurate strategies that are targeted for a certain area. Yunnan Province has the largest number of poverty counties in China. The vast number of people living under the poverty-line, and the deep degree of poverty across a wide distribution range, pose major challenges. Based on the rural poverty incidence data, this paper describes the rural poverty patterns in Yunnan Province in 2010 and 2015, and then it explores the main factors which influence the incidence and changes in rural poverty at the county level in Yunnan Province using a stepwise regression analysis method. This study found that the rural poverty in counties of Yunnan Province was deeply affected by natural conditions and the geographical environment. In 2010 and 2015, the rural poverty situation in the middle region of Yunnan Province was relatively light, while it was more serious in the northwest, northeast and south regions. The pattern of county poverty is in good agreement with the topography and landforms of Yunnan Province and the poverty-stricken areas. There are strong correlations between the incidence of rural poverty in Yunnan Province with both the annual per capita net income of rural residents and the degree of agricultural mechanization. These factors are related to the living standards and agricultural production necessary for the peasantry to sustain their livelihood. The change in the incidence of rural poverty at the county level in Yunnan Province from 2010 to 2015 is significantly correlated with changes in the value-added of the primary industries and the degree of agricultural mechanization. These correlations indicate that the development of primary industry plays a key role in the process of lifting rural residents in Yunnan Province out of poverty so they can achieve prosperity. Therefore, improving the annual per capita net income of rural residents and the degree of agricultural mechanization for rural areas in Yunnan Province are still the main points for focused efforts. In the current phase of poverty alleviation, Yunnan Province should emphasize increasing rural residents' income and agricultural production and management in order to formulate effective policies and measures for poverty alleviation.

Identification and analysis spatial areas of urban poverty in Shahrekord neighborhoods, Iran

One of the most important topics in development economics texts is the issue of poverty, measuring and reducing it and poverty alleviation. The first step in planning to fight poverty and reducing inequality is to have a proper understanding of the poverty situation. According to this issue, the purpose of this study is identifying and analyzing urban poverty as well as its spatial distribution in the neighborhoods of Shahrekord and to formulate and present suggestions and solutions appropriate to the approach of organizing human societies in order to address its unhealthy conditions. The present article has taken a cognitive and exploratory approach in terms of purpose and is considered evaluative-comparative in terms of method that after explaining the concept of urban poverty with the help of quantitative and qualitative data (statistical block 2016, Upstream plans, land use maps, etc.) of 40 indicators in the form of four main economic, social, cultural and physical variables has been classified using TOPSIS and AHP methods and has identified and distributed the spatial distribution of urban poverty in Shahrekord neighborhoods with ARC GIS software. Urban poverty was addressed in Shahrekord neighborhoods and a map of poverty distribution was drawn. The results show that Koreh, Borveh Pahneh, Darb Darreh, Ashtaftak and Mahdieh neighborhoods were identified as poor and targets for planning.

Energy Poverty and Protection of Vulnerable Consumers. Overview of the EU Funding Programs FP7 and H2020 and Future Trends in Horizon Europe

Energy poverty—involving a combination of factors, such as low household incomes, high energy prices, and low levels of residential energy efficiency—is identified as a complex and increasing issue affecting people’s physical health, well-being, and social inclusion. Even though a shared identification of energy poverty is not yet agreed, this phenomenon has been recognized as an EU priority. Several EU legislative documents address the topic, trying to outline its boundaries and provide a framework for mitigative actions. At the same time, different research and demonstration projects have been funded to experiment and evaluate innovative approaches, strategies, and solutions and to promote good practices at national, regional, and local levels. This review paper presents some results of the “ZOOM” project (“Energy zoning for urban systems. Models and relations for the built environment”, funded by University of Bologna in the framework of Alma Idea 2017–ongoing), proposing a critical overview of the EU projects directly or indirectly connected to energy poverty—funded under the 7th Framework Program (FP7) and under Horizon 2020 Program (H2020). The aim of such a review is to highlight the main objectives, trends, and related topics of ongoing and concluded projects addressing energy poverty, in order to identify gaps and open issues and to understand the possible orientation and placement of this subject in the future EU research and innovation framework project, Horizon Europe.

Poverty reduction in Mexico? case study for Quintana Roo 2010-2016

This paper evaluates the status of poverty in Quintana Roo, Mexico for the period 2010- 2016. The research question that supports this paper is whether the decrease in extreme poverty and poverty that the federal government of Enrique Peña Nieto asserted as real is actually an improvement in living and income conditions, or if said decrease takes place at based solely on the criteria with which poverty is defined and measured. To this end, cabinet work was carried out in two parts: The first was a review and analysis of the Guidelines and Criteria for the Definition, Identification and Measurement of Poverty that appear in the Official Gazette of the Federation; and the second in the analysis of the data on deprivation and income that the National Council for the Evaluation of Social Development Policy (CONEVAL) and the National Institute of Statistics, Geography and Informatics (INEGI) offer for 2010 2015 and 2010, 2012 , 2014 and 2016, respectively. Among the most important results, it can be mentioned that, in effect, the average shortfalls of the househo in Quintana Roo decreased, however, the income in 2016 remained in conditions similar to those of 2010, that is, the reduction of extreme poverty can be attribute only to state intervention through the creation of infrastructure and not the effectiveness of its economic policies.

Identification of poverty based on nighttime light remote sensing data: A case study on contiguous special poverty-stricken areas in Liupan Mountains

Identification of poverty based on nighttime light remote sensing data: A case study on contiguous special poverty-stricken areas in Liupan Mountains

Federalism, development and the changing political dynamics in Ethiopia

In the last two and half decades, Ethiopia has undertaken remarkable political and economic changes at the center of which is the transformation of the country from a highly homogenizing and centrist rule to a federal system that aims to manage the country’s complex, politically mobilized ethnonational diversity. Ethiopia continues to register impressive economic performance but at the same time is facing political instability. This article seeks to explain two major paradoxes: Why has the federal system, with its promise of self-rule that ensures autonomous self-government and representation in federal institutions, not been able to ensure political stability, and how does one explain the emerging protests and uncertainties? Two factors explain the puzzle. The idea that development is centrally designed and managed along with the identification of poverty as an existential threat against which all resources have to be mobilized means that development takes an overriding priority thus compromising self-rule. While federalism and the developmental state are two major pillars of the EPRDF-led government, they have not been aligned well, as the latter became an overriding ideology.The outcome as witnessed in the latest protests is new mobilization and conflict unleashed by growing ethnonationalism. The vanguard party that has monopolized political power and overshadowed the institutions also sidelined the political opposition while emboldening hardliners leading to political instability.

The geography of poverty: Review and research prospects

Geography of poverty (GOP) or poverty geography is a branch of human geography, which studies the geographical patterns, distribution characteristics, areal types and evolution mechanism of poverty and the relationship with geographical environment as well as antipoverty measures. Based on the systematical analysis on the significance of GOP research, this study firstly put forward the impoverished areal system (IAS), and then elaborated the main contents, research progresses and existing problems in GOP research, and finally proposed the possible key areas in the future. Results show that the IAS is an open system with structure and function and has its life-cycle law, which is composed of natural endowments, location conditions, human capital and geographical capital within a certain geographical area. The subsystem of human, land and industry is the core of the IAS. Poverty geography studies both regional (place) poverty and individual (people) poverty. Regional poverty is an external manifestation of the coupling maladjustment of human, land and industry elements in a particular area. There are 5W + H (What, Where, Why, When, Who and How) models in GOP research. Key areas of future GOP research include: 1) IAS's life cycle evolution law; 2) regional multidimensional poverty measurement; 3) geographical identification of poverty and its areal type; 4) dynamic simulation of impoverished and its mechanism; 5) poverty mapping; 6) antipoverty measure; and 7) poverty reduction effectiveness evaluation. Facing the UN's goal of eradicating poverty by 2030, poverty geography research in the new period should focus on the complexity, spatial heterogeneity and mechanism of poverty, and designs anti-poverty paths and models suitable for different countries. To adapt to the trend of globalization and informationization, poverty geographers should make use of modern technologies such as data platform, cloud computing, remote sensing and artificial intelligence to focus on the spatio-temporal pattern of poverty and its driving mechanism as well as antipoverty path, and to solve the global poverty problem and promote the internationalization, basification and engineering of geography.

Federalism and Development: The Ethiopian Dilemma

Key to Ethiopia’s remarkable political and economic changes is its transformation from highly homogenising and centrist rule to a federal system aiming at managing its complex diversity. The post-1991 dispensation has ended years of civil war, and served as a foundation for the impressive economic performance. Lately the country has continued to face wide-spread protests. How does one explain the paradox between an impressive economic performance versus growing political instability? Development is centrally designed and managed along with the identification of poverty as an existential threat against which all resources must be mobilised. This means that development takes overriding priority and a central role, compromising the constitutional autonomy of the states. The outcome as witnessed in the protests is new mobilisation and conflict unleashed by growing ethno-nationalism. The absolute dominance of a single vanguard party that monopolised power has also overshadowed institutions and sidelined political opposition while emboldening hardliners.

Spatial Identification of Multi-dimensional Poverty in Rural China: A Perspective of Nighttime-Light Remote Sensing Data

Poverty has emerged as one of the chronic dilemmas facing the development of human society during the twenty first century. Accurately identifying regions of poverty could lead to more effective poverty-alleviation programs. This study used a new type of remote-sensing data, NPP-VIIRS, to locate poverty-stricken areas based on nighttime light, taking Chongqing Municipality as a sample, and constructed a multidimensional poverty index (MPI) system, guided by a well-known and widely used conceptual framework of sustainable livelihood. A regression model was constructed and results were correlated with those using the average nighttime light index. The model was then tested on Shaanxi Province, and average relative error of the estimated MPI was only 11.12%. These results showed that multidimensional poverty had a high spatial concentration effect at the regional scale. We then applied the index nationwide, at the county scale, analyzing 2852 counties, which we divided into seven classifications, based on the MPI: extremely low, low, relatively low, medium, relatively high, high, and extremely high. Eight hundred forty-eight counties in 26 provinces were identified as multidimensionally poor. Among these, 254 were absolutely poor counties and 543 were relatively poor counties; 195 of these are not on the list of poverty-stricken counties as identified by income levels alone. By improving the accuracy of targeting, this method of identifying multidimensional poverty areas could help the Chinese government improve the effectiveness of poverty reduction strategies, and it could also be used as a reference for other countries or regions that seek to target poor areas that suffer multidimensional deprivation.

基于DMSP-OLS数据和可持续生计的中国农村多维贫困空间识别

基于DMSP-OLS数据和可持续生计的中国农村多维贫困空间识别

Who are they, what do they talk about and who listens to the poor?

The right to a dignified life for all requires overcoming the challenges imposed on the most vulnerable groups, and poverty is one of the oldest and most devastating phenomena. Listening to them is essential to create remediating opportunities. This study aims to identify characteristics of this listening in the context of health promotion and the Sustainable Development Goals - SDGs, an international effort to support the fight against poverty, among others. In an integrative review of literature, conducted through the search terms of Poverty, Right to the City, Equity Policy and Identification of Poverty, 86 studies that listened to vulnerable groups, such as women, children, adolescents, adults, the elderly, families and drug users, all poor and low-skilled workers were analyzed. Each strategy shown was related to one or more SDGs. The recurrent strategies in the studies analyzed were increased social protection and spaces to listen to vulnerable groups, as well as public policies that enabled the fight against poverty. Equity must be thought of in the context of comprehensive and universalizing rights policies, overcoming fragmented and focal policies that fail to address the structural causes of poverty and human exploitation.

Fuzzy Chronic Poverty: A Proposed Response to Measurement Error for Intertemporal Poverty Measurement

A number of chronic poverty measures are now empirically applied to quantify the prevalence and intensity of chronic poverty, vis‐à‐vis transient experiences, using panel data. Welfare trajectories over time are assessed in order to identify the chronically poor and distinguish them from the non‐poor, or the transiently poor, and assess the extent and intensity of intertemporal poverty. We examine the implications of measurement error in the welfare outcome for some popular discontinuous chronic poverty measures, and propose corrections to these measures that seeks to minimize the consequences of measurement error. The approach is based on a novel criterion for the identification of chronic poverty that draws on fuzzy set theory. We illustrate the empirical relevance of the approach with a panel dataset from rural Ethiopia and some simulations.

The Definition and Measurement of Poverty

This chapter analyses the various theoretical and methodological problems causing the lack of consensus on poverty measurement. It deals with the identification of poverty and the aggregation of poverty across individuals. The chapter concentrates on the various methods applied to identify poverty at the household level. It reviews empirical studies in which the composition and size of the population of poor is compared, using different definitions of poverty. It is seen that both in the identification and in the aggregation stage, some welfare judgments are made, either explicitly or implicitly. The chapter discusses the advantages and disadvantages of a number of poverty definitions. It reviews empirical studies in which the composition and size of the population of poor is compared, using different definitions of poverty. Although welfare is theoretically the best basis for a poverty line definition, in practice both the measurement problems and the essentially subjective nature of welfare cause a new set of problems.

How to identify poor immigrants? - An empirical study of the Three Gorges Reservoir in China

This paper aims to study on the precise identification and targeting of immigrant poverty in the TGRR, with a multi-dimensional poverty line as a standard, which has transcended the traditional income poverty line. Then, we figured out the changing trend and the causes of immigrant poverty under the perspective of multidimensional poverty. Based on the dual cutoff method and regression analysis, the study results show that the discrepancy of poverty before and after immigration is significant, but the poverty problem of immigrants in the TGRR is still serious. The current multi-poverty incidence of immigrants is 30.15%, which means that there are still 2.3097 million people under poverty. The major causes of poverty in this region are poverty in assets, poverty in education and poverty in health. The poverty contribution rate of land scarcity has increased from 12.16% to 29.52% with the deterioration of land loss, which has a negative effect on immigrants' livelihood. The results reveal several outstanding poverty problems in this region: the coverage of social security of immigrants is far from ideal; There are still 12.75% of the impoverished immigrants without medical insurance and 11.36% without pension insurance; the percentage of female laborers, the education level of laborers, the percentage of agricultural expenditure and the percentage of medical expenditure have significant correlations with immigrants' poverty in this region. The paper argues that the precise identification and targeting of poverty reduction in China should be undertaken from a multidimensional perspective.

A geographic identification of multidimensional poverty in rural China under the framework of sustainable livelihoods analysis

Developing methods of measuring multidimensional poverty and improving the accuracy of poverty identification have been hot topics in international poverty research for decades. They are also key issues for improving the quality and effectiveness of rural poverty reduction programs in China. So far, selection and integration of poverty indicators remains the main difficult for measurement of multidimensional poverty. Guided by the sustainable livelihoods framework developed in the UK by the Department for International Development (DFID), an index system and an integration method for geographical identification of multidimensional poverty were established, and they were further used to carry out a county-level identification of poverty in rural China. Additionally, comparisons were made of the identification results with counties having single-dimension income poverty in rural areas and poor counties designated by the Chinese central government. The results showed that a total of 655 counties, with 141 million rural residents, were identified as multidimensionally poor. They are concentrated and conjointly distributed geographically, and evil natural conditions are their common features. In comparison to the income poor and the designated poor counties, the multidimensionally poor counties were not only worse in single-dimensional and composite scores, but also having multiple disadvantages and deprivations. By identifying the disadvantage and deprived dimensions, the measurement of multidimensional poverty should be very helpful for each county to work out and implement antipoverty programs accordingly, and it would make contribution to improve the sustainability of poverty reduction. Hopefully, this research may also shed light on multidimensional poverty measurement for other developing countries.

STUDI KOMPARASI KEMISKINAN DI INDONESIA: MULTIDIMENSIONAL POVERTY DAN MONETARY POVERTY

Research on poverty has long been done by various methods and approaches. Approach to identifying the poor in general by calculating consumption expenditure or income reveneu. The calculation is then known as monetary poverty. Indonesia also use and implemented that approach. However, some experts believe that monetary poverty approach does not capture the whole cause of poverty because the indicator calculation not enough. Though poverty is a multidimensional phenomenon that involves not only the economic aspects but involves other aspects. Using secondary data from Indonesian family Life survey, this study proposes to calculate the multidimensional poverty index and estimates the poor based on two approaches, multidimensional poverty and monetary poverty. Calculating the poverty by alkire foster method, whereas to estimate multidimensional poverty and Monetary Poverty using logistic regression. The Results for Alkire-Foter calculation method show that identify of poor by multidimensional poverty greater than the monetary poverty. Generally, the standard of living dimension contributes most to the multidimensional poverty index. Standar living dimention was believed to be the dimension that explains the nature of households that are directly related to the everyday household behavior. Meanwhile, estimation of monetary poverty show that variable consumption per capita, the head of the household sector employment, hours of work, household size and household asset ownership affects the identification of poverty. Only education variable is not significant effect on the identification of poverty. Base on those finding, education has two possibilities to affect poverty one significant affect multidimensional poverty, while for monetery hasn't affect.Keywords: Multidimensional poverty, Monetary Poverty, Alkire-Foster Method, Logistic Regression

Poverty Risk in Districts of the Slovak Republic

Poverty in Eastern European countries and the problems that accompany the social malady have become widely discussed topics. We chose Slovakia as an example of aggregated indicator using, but the criteria can also be applied to other countries. The aim of the article is to point to the distinct spatial concentration of poverty in Slovakia, to capture its differentiated level (depth) conditions, and to identify its main traits and carriers. Another aim is to use of an aggregated indicator. An aggregated indicator, a comparatively new method applied by the Eurostat was used for identification of poverty. Data collected by the Regional Database of the Statistical Office of the SR and of the Centre of Labour, Social Matters and Family (UPSVaR) were used in this study. The obtained results showed that poverty is a serious problem for one-third (24) of all Slovak districts, its level and depth are differentiated and it is clearly concentrated in the eastern and southern parts of the country (these territories comprise the six poorest districts of Slovakia). The accumulated statistics also unveiled the conditions, status, and socio-economic situation of poor districts. It was found that poor districts have many common traits and properties which make it possible to identify the characteristics and carriers of poverty in Slovakia. Identification of poor districts and establishment of the level of poverty yield important information in the search for solutions, compilation of programmes, and measures of social and regional policies, which when implemented, would prevent further increase of poverty in affected regions.

The Economics of Poverty Traps and Persistent Poverty: Empirical and Policy Implications

The moral and economic imperatives to intervene in poverty traps motivate the identification of poverty traps and their structural causes so as to inform the design of appropriate policy responses. However, empirical identification remains challenging because of poverty traps’ complexity. After reviewing mechanisms that can generate poverty traps, we focus on one – multiple financial market failures – emphasising its heretofore underappreciated testable implications, including specific behaviours that are rational only in the presence of a poverty trap. We therefore recommend tests for these behaviours rather than more econometrically challenged efforts to directly test for poverty traps in estimated asset dynamics.