Traditional Poverty Research Articles

构建乡城融合一体化多元主体扶贫体系的构想

With the continuous promotion of new urbanization, the multidimensional poverty problem of new urban residents is becoming increasingly prominent. Due to significant differences between the new citizen group and the old citizen group, farmer group, and migrant worker group, traditional poverty alleviation measures applicable to the old citizen, farmer group, and migrant worker group are inefficient when applied to the new citizen group. Therefore, it is necessary to explore new poverty alleviation measures that are suitable for the actual needs of new citizen groups. This measure emphasizes the integration of multiple resources through a flexible urbanization model, fully leveraging the roles of diverse entities such as cities, rural areas, governments, communities, and employers. It aims to build a poverty alleviation system that blocks the poverty of new urban groups through the construction of capacity systems, rights protection mechanisms, public service systems, and cost sharing mechanisms.

Are dynamic tariffs effective in reducing energy poverty? Empirical evidence from US households

Statistics from the United States (US) Energy Information Administration and the US Census Bureau reveal that a growing number of households are threatened by energy poverty. Both argue that energy poverty is becoming more common than traditional poverty. Recently, dynamic pricing programmes have been made possible by the increasing use of smart meters and other devices which enable consumers to play a more active role in electricity systems. This study aims to determine if dynamic pricing programmes can reduce the energy burden on households and diminish the number suffering from energy poverty. Data from the Annual Electric Power Industry Report and the American Community Survey were merged and analysed by state and year to assess the impact of dynamic pricing on energy poverty for 51 US states from 2013 until 2021. The results show that time-of-use and critical-peak-pricing tariffs can reduce the number of households suffering from energy poverty. Conversely, CPP and RTP increase the number of households in energy poverty. These findings indicate that policymakers and retailers need to develop pricing programmes that will encourage consumers to modify their consumption habits and enhance the integration of intermittent renewable energy sources and reduce energy poverty.

Poverty decompositions with counterfactual income and inequality dynamics

AbstractTraditional poverty accounting decomposes changes in a country's poverty headcount ratio into changes in income and inequality. We argue that this approach is unsatisfactory from the perspective of policy analysis because it compares a country in two points of time without taking the country's initial situation, and hence its potential for poverty reduction, into account. We thus suggest comparing traditional poverty decompositions with a counterfactual situation. This counterfactual indicates what a country starting from its initial situation could be expected to achieve in terms of income, inequality, and, hence, poverty developments. We construct those counterfactuals by modeling income and inequality trends characterized by convergence and a “Kuznets” relationship between inequality and development. Parameters in those relationships are estimated using PovcalNet survey data from 144 countries and we construct our counterfactual poverty predictions for 71 developing countries. While there is overall a tight relationship between actual developments and counterfactuals, we identify several cases, where both deviate from each other and discuss the policy implications. We also check for commonalities in differently performing countries and find that those who fell particularly short of expectations often underwent political transition and state fragility.

Does it matter which poverty measure we use to identify those left behind? Investigating poverty mismatch and overlap for Botswana

This study offers the first attempt in Botswana and adds to the limited literature on poverty mismatch and overlaps in Sub-Saharan Africa. Using the 2015/16 Botswana multi-topic household survey data, the study compares the country’s current official monetary poverty measure with an individual-level multidimensional poverty measure. The results show that multidimensional poverty levels are higher than monetary poverty levels. The results also reveal that significant mismatches and overlaps exist, suggesting that individuals experiencing monetary and multidimensional poverty are not the same. However, the mismatch size and overlaps vary across different subgroups of the populations and place of residence. The econometric estimation results show that age, household size, household head’s education status, household head’s employment status, and location (place of residence) influence poverty mismatch and overlap in Botswana. The findings suggest the need to go beyond traditional monetary poverty measure and complement it with multidimensional poverty measure to identify those left behind. The results are critical for policy interventions, especially for monitoring the trends, understanding poverty dynamics, and targeting social assistance programmes.

Research on Innovation and Development of Financial Poverty Alleviation Model Promoted by Fintech

Although the traditional financial poverty alleviation model has provided great convenience and played a great role in China's targeted poverty alleviation to a large extent, the problem of information asymmetry between farmers, the government and financial institutions cannot be effectively solved. solve. Therefore, if new financial technologies such as blockchain, big data, and cloud computing can be flexibly applied to financial poverty alleviation, it will have a great boosting effect on consolidating the achievements of poverty alleviation. This paper mainly analyzes the defects of the traditional financial poverty alleviation model and the development prospects of the financial technology innovative financial poverty alleviation model, and finally summarizes and puts forward relevant suggestions.

Poverty Mapping in the Dian-Gui-Qian Contiguous Extremely Poor Area of Southwest China Based on Multi-Source Geospatial Data

Accurate information on the spatial distribution of poverty is of great significance to the formulation and implementation of the government’s targeted poverty alleviation policy. Traditional poverty mapping is mainly based on household survey data and statistical data, which cannot describe the spatial distribution of poverty well. This paper presents a study of mapping the integrated poverty index (IPI) in the Dian-Gui-Qian contiguous extremely poor area of southwest China. Based on multiple independent spatial variables extracted from NPP/VIIRS nighttime light (NTL) remote sensing data, digital elevation model (DEM), land cover information, open street map, and city accessibility data, eight algorithms were employed and compared to determine the optimal model for IPI estimation. Among these machine learning algorithms, traditional multiple linear regression had the lowest accuracy compared with the other seven machine learning algorithms and XGBoost showed the best performance. Feature selection was performed to reduce overfitting and five variables were finally selected. The final developed XGBoost model achieved an MAE of 0.0454 and an R2 of 0.68. The IPI map derived from the developed XGBoost model characterized the spatial pattern of poverty in the Dian-Gui-Qian contiguous extremely poor area well, which provided a good reference for the poverty alleviation work and public resources allocation in the study area. This study can also serve as a template for poverty mapping in other areas using remote sensing data.

A Clustering Algorithm via Density Perception and Hierarchical Aggregation Based on Urban Multimodal Big Data for Identifying and Analyzing Categories of Poverty-Stricken Households in China

Nowadays, urban multimodal big data are freely available to the public due to the growing number of cities, which plays a critical role in many fields such as transportation, education, medical treatment, and land resource management. The successful completion of poverty-relief work can greatly improve the quality of people’s life and ensure the sustainable development of the society. Poverty is a severe challenge for human society. It is of great significance to apply machine learning to mine different categories of poverty-stricken households and further provide decision support for poverty alleviation. Traditional poverty alleviation methods need to consume a lot of manpower, material resources, and financial resources. Based on the density-based spatial clustering of applications with noise (DBSCAN), this paper designs the hierarchical DBSCAN clustering algorithm to identify and analyze the categories of poverty-stricken households in China. First, the proposed method adjusts the neighborhood radius dynamically for dividing the data space into several initial clusters with different densities. Then, neighbor clusters are identified by the border and inner distances constantly and aggregated recursively to form new clusters. Based on the idea of division and aggregation, the proposed method can recognize clusters of different forms and deal with noises effectively in the data space with imbalanced density distribution. The experiments indicate that the method has the ideal performance of clustering, which identifies the commonness and difference in characteristics of poverty-stricken households reasonably. In terms of the specific indicator “Accuracy,” the accuracy increases by 2.3% compared with other methods.

The Internal Causes and Realistic Directions of China's Relative Poverty Governance in the Post-well-off Era

By the post-well-off era, the policies and governance of traditional poverty alleviation in China can not be confined solely to the relative poverty phenomenon, the targets and priorities of poverty alleviation, and realistic paths must have been changed in order to better promote common prosperity in the process of relative poverty governance. Therefore, in the process of poverty alleviation and governance, it is necessary to prevent the emergence of the difference between returning to poverty and new poverty, formulate a scientific and reasonable relative poverty governance mechanism, and continuously improve people's living standards.

The Affordable Care Act Reduced Income Inequality In The US.

Income inequality estimates based on traditional poverty measures do not capture the effects of health care spending and health insurance. To explore the distributional effects of the Affordable Care Act's (ACA's) expansion of health benefits and the resulting income inequality, this study used alternative income measures that incorporate the value of the ACA's health insurance changes under the law. The study simulated the impact of the ACA on income inequality in 2019 compared with a scenario without the ACA. We found that the ACA reduced income inequality and that the decrease was much larger in states that expanded Medicaid than in states that did not. We also decomposed the effect of the ACA on inequality by race/ethnicity, age, and family educational attainment. The ACA reduced inequality both across groups and within these groups. With efforts to repeal the ACA-specifically, California v. Texas-having shifted from Congress to the courts, it remains important to consider the consequences of fully repealing the ACA, which would likely reverse reduced inequality observed under the law.

Research on the economic development pattern of Chinese counties based on electricity consumption

With the implementation of the Policy of “Targeted Poverty Alleviation” in 2013, China has been in the critical stage to fight against poverty and the county economy has entered into a new stage of development which presents new evolutionary characteristics. However, traditional poverty county assessments are mostly based on the economic census, which not only costs a lot of manpower and material resources, but also shows the feature of hysteresis and scarcity. In this paper, county-level electricity consumption data is adopted to explore the characteristics of China's county-level economy development based on BIRCH clustering since electricity consumption data can be more sensitive and objective in reflecting regional economic development and residents' income level. The results show that four kinds of county-level economic development patterns can be categorized in China with different industrial structures. Then the potential problems with different development patterns are explored and suitable policy suggestions for each pattern is proposed separately. It can be found that electricity consumption should be a useful auxiliary tool for economic development assessment and monitoring for China and other similar developing countries.

How Poor Are the Poor? Looking beyond the Binary Measure of Income Poverty

This paper contributes to the literature by analysing how poor the income poor are in European countries. Using data from the European Union Statistics on Income and Living Conditions, I go beyond average estimates of the intensity of poverty and analyse the distribution of individual-level poverty gaps in each country of interest. As a next step, I identify which personal and household characteristics predict how far away incomes of the poor fall from the poverty line. The results indicate that, in most European countries, half of the poor have income shortfalls not exceeding 30% of the poverty line whereas only a few percent of the poor have income deficits of 80% and more. The results also suggest that traditional poverty correlates (e.g. age, gender, educational background) are not always significantly associated with the size of normalised poverty gaps at the individual level, or the nature of these associations differs as compared to when the same characteristics are linked to the probability of being poor.

Multi-dimensional well-being associated with economic dependence on ecosystem services in deltaic social-ecological systems of Bangladesh

While the benefits humans gain from ecosystem functions and processes are critical in natural resource-dependent societies with persistent poverty, ecosystem services as a pathway out of poverty remain an elusive goal, contingent on the ecosystem and mediated by social processes. Here, we investigate three emerging dimensions of the ecosystem service-poverty relationship: economic contribution of provisioning ecosystem services to the household livelihood mix, social-ecological systems producing different bundles of ecosystem services and material wealth versus reported life satisfaction. We analyse these relationships in Bangladesh, using data from a bespoke 1586-household survey, stratified by seven social-ecological systems in the delta coastal region. We create poverty lines to ensure comparability with traditional poverty measures that overlook environmental factors and subjective measurements of well-being. We find that any contribution of ecosystem service-based income to the livelihood mix decreases the likelihood of the incidence of poverty, and of individuals reporting dissatisfaction. We find no relationship between the incidence of material poverty and the specific social-ecological systems, from agriculture to fishery-dominated systems. However, the probability of the household head being dissatisfied was significantly associated with social-ecological system. Individuals living in areas dominated by export-oriented shrimp aquaculture reported lower levels of life satisfaction as an element of their perceived well-being. These results highlight the need for social policy on poverty that accounts for the diversity of outcomes across social-ecological systems, including subjective as well as material dimensions of well-being. National poverty reduction that degrades ecosystem services can have negative implications for the subjective well-being of local populations.

“Nothing About Us Without Us”: Reading Protests against Oppressive Knowledge Production as Guidelines for Solidarity Research

Drawing from my analysis of sex worker and homeless protests as well as my experience doing ethnographic research with people experiencing homelessness and people in the sex trade, I put forth recommendations for ethical, policy-relevant research with groups of people who experience routine, normalized violence, and who are frequently silenced and misrepresented by academics and policy makers. This article analyzes protests against what activists identify as oppressive knowledge production by “outsiders” who are not sex workers or homeless. Protest events against research “about us without us” occurred between 2012 and 2015, and targeted academic researchers and policymakers. I draw lessons from marginalized groups’ protests against knowledge production by outsider “experts” to present three problems with traditional poverty research: pathologization, paternalism, and extractive exotification. I use my observations of protests and service provision to develop guidelines for solidarity research, a knowledge production practice that prioritizes the needs and perspectives of marginalized communities.

No Longer Trapped? Promoting Entrepreneurship Through Cash Transfers to Ultra‐Poor Women in Northern Kenya

AbstractWe examine the short‐to‐medium‐run impacts of the Rural Entrepreneur Access Program, a poverty graduation program that promotes entrepreneurship among ultra‐poor women in arid and semi‐arid northern Kenya, a context prone to poverty traps. The program relies on cash transfers (rather than asset transfers) in addition to business skills training, business mentoring, and savings. Participation in each of the program's three rounds was randomly determined through a public lottery. In the short‐to‐medium‐run, we find that the program has a positive and significant impact on income, savings, and asset accumulation, similar to more traditional poverty graduation programs that rely on asset transfers.

Mapping poverty using mobile phone and satellite data.

Poverty is one of the most important determinants of adverse health outcomes globally, a major cause of societal instability and one of the largest causes of lost human potential. Traditional approaches to measuring and targeting poverty rely heavily on census data, which in most low- and middle-income countries (LMICs) are unavailable or out-of-date. Alternate measures are needed to complement and update estimates between censuses. This study demonstrates how public and private data sources that are commonly available for LMICs can be used to provide novel insight into the spatial distribution of poverty. We evaluate the relative value of modelling three traditional poverty measures using aggregate data from mobile operators and widely available geospatial data. Taken together, models combining these data sources provide the best predictive power (highest r2 = 0.78) and lowest error, but generally models employing mobile data only yield comparable results, offering the potential to measure poverty more frequently and at finer granularity. Stratifying models into urban and rural areas highlights the advantage of using mobile data in urban areas and different data in different contexts. The findings indicate the possibility to estimate and continually monitor poverty rates at high spatial resolution in countries with limited capacity to support traditional methods of data collection.

Traditional Knowledge, Intellectual Properties, Development and Poverty Reduction in Africa

Africans are still reliant on traditional knowledge systems for survival. This knowledge system thrives due to the fact that foreign concepts are not easily understood by Africans. There is also the belief that traditional knowledge is more effective in catering for their needs and suitable for their environment. Development through sustainable means is urgently required in Africa and this can be achieved by nurturing and transforming cultural values, traditional knowledge and practices. Thus Africa should take into consideration the development of traditional knowledge systems as important aspects of economic development and the reduction of poverty in their societies. This paper explores the relationship between traditional knowledge, intellectual properties and development in Africa.

How Does Early Deprivation Relate to Later-Life Outcomes? A Longitudinal Analysis

Measures of material deprivation are increasingly used as alternatives to traditional poverty indicators. While there exists extensive literature focusing on the impact that growing up in a (financially) poor household has on future success, little is known about how material deprivation relates to long-run outcomes. This study uses longitudinal data from the 1970 British Cohort Study to assess the relationship between material deprivation and outcomes in adult life. We control for an extensive set of observable characteristics, and further employ value-added analysis and generalized sensitivity analysis to assess the nature of this relationship. We find that deprivation relates to a diverse set of outcome variables, but the magnitude of the conditional relationships are generally small. Immaterial indicators of family quality show relatively stronger ties to future outcomes, especially with respect to non-cognitive skills.

Blind spots of traditional poverty measurement: the case of migrants

The aim of this paper is to examine two blind-spots of poverty measurement with application to the study of migrant poverty. The first regards the definition of income (in particular the consideration of non-cash income components in the definition of income) and the second regards the methodological treatment of a migrant group with very particular characteristics (those working as domestic workers). Both issues have eluded the attention of many applied researchers and practitioners. The microdata of the 2009 Cyprus Family Expenditure Survey are used to illustrate the importance of the points made above as well as to put forth potential solutions.

Poverty Scorecards: Lessons from a Microlender in Bosnia‐Herzegovina

AbstractHow poor are participants in development projects? This article analyzes how well a simple scorecard identifies poor clients at a microlender in Bosnia‐Herzegovina. The scorecard effectively ranks clients by the likelihood that they are poor by an absolute, expenditure‐based standard. The score tracks poverty more closely than loan size, microfinance's traditional poverty indicator. Overall, poverty scorecards are a simple, inexpensive way for microlenders—or any other development entity—to target the poor, track changes in poverty over time, manage poverty outreach, and report on clients' absolute poverty.

Reflections on the development of psychology in Ethiopia and future directions

The introduction and development of psychology in Ethiopia has been mainly limited to Addis Ababa University in the capital city, and also to educational and school psychology which was highly influenced by the field of education at this pioneering university. Similarly, mental health services have been principally developed at the Amanuel Mental Hospital in Addis Ababa that has existed since the 1950s. However, the expansion of higher learning institutions on one hand, and the apparent growing prevalence of mental illness on the other, seem to have contributed to the development of both mental health training and services in other regional cities and towns. Although the influence of the education-oriented psychological training of the Addis Ababa University is still present, clinical psychology education and services are now being started in other universities. One of these is the master's programme in clinical psychology opened for the first time in the University of Gondar. This article sheds light on the development of psychology in Ethiopia and addresses some of the issues raised about the factors that have influenced its development such as traditional beliefs, poverty and comparisons between mental health in lower middle-income countries and higher middle-income countries (). The paper also proposes future directions for the education, research, infrastructure and services of clinical psychology and mental health in Ethiopia.