Paired assistance and poverty alleviation: Experience and evidence from China.

This paper used the micro panel data from 2016 to 2019 of 2031 registered poor households in B Town, W County, Lu'an City of Anhui Province in China to analyze the diversified patterns and poverty alleviation effect of paired assistance based on the PSM-DID model. The empirical results show that paired assistance provided by social forces can significantly contribute to the poverty alleviation of poor households, promoting the poverty alleviation rate by 7.8%, which can be concluded through sample matching and control of relevant variables. Furthermore, based on the subsample of poor households with social assistance, we found that external social assistance subject to paired assistance can significantly improve the poverty alleviation rate of poor households by 14.26%, mainly hung on their economic base and strength of poverty alleviation.

Reducing Intergenerational Poverty-An Essential Driver of Health.

This Viewpoint discusses a report from the National Academies of Science, Engineering, and Medicine on how to address intergenerational poverty.

Impacts of poverty eradication on carbon neutrality in China.

China is facing challenges to tackle the threat of climate change while reducing social inequality. Poverty eradication requires improvement in the living conditions of low-income households, which leads in turn to higher carbon footprints and may undermine the efforts of climate change mitigation. Previous studies have assessed the climate impacts of poverty eradication, but few have quantified how the additional carbon emissions of poverty eradication are shared at the subnational level in China and the impact on China's climate targets. We investigated the recent trend of carbon footprint inequality in China's provinces and estimated the climate burden of different poverty reduction schemes, measured by increased carbon emissions. The results indicate that poverty eradication will not impede the achievement of national climate targets, with an average annual household carbon footprint increase of 0.1%-1.2%. However, the carbon emissions growth in less developed provinces can be 4.0%, five times that in wealthy regions. Less developed regions suffer a greater climate burden because of poverty eradication, which may offset carbon reduction efforts. Therefore, interregional collaboration is needed to coordinate inequality reduction with investments in low-carbon trajectories in all provinces.

Ending extreme poverty has a negligible impact on global greenhouse gas emissions.

Growing consumption is both necessary to end extreme poverty1and one of the main drivers of greenhouse gas emissions2, creating a potential tension between alleviating poverty and limiting global warming. Most poverty reduction has historically occurred because of economic growth3-6, which means that reducing poverty entails increasing not only the consumption of people living in poverty but also the consumption of people with a higher income. Here we estimate the emissions associated with the economic growth needed to alleviate extreme poverty using the international poverty line of US $2.15 per day (ref. 7). Even with historical energy- and carbon-intensity patterns, the global emissions increase associated with alleviating extreme poverty is modest, at 2.37 gigatonnes of carbon dioxide equivalent per year or 4.9% of 2019 global emissions. Lower inequality, higher energy efficiency and decarbonization of energy can ease this tension further: assuming the best historical performance, the emissions for poverty alleviation in 2050 will be reduced by 90%. More ambitious poverty lines require more economic growth in more countries, which leads to notably higher emissions. The challenge to align the development and climate objectives of the world is not in reconciling extreme poverty alleviation with climate objectives but in providing sustainable middle-income standards of living.

A planetary health innovation for disease, food and water challenges in Africa.

Many communities in low- and middle-income countries globally lack sustainable, cost-effective and mutually beneficial solutions for infectious disease, food, water and poverty challenges, despite their inherent interdependence1-7. Here we provide support for the hypothesis that agricultural development and fertilizer use in West Africa increase the burden of the parasitic disease schistosomiasis by fuelling the growth of submerged aquatic vegetation that chokes out water access points and serves as habitat for freshwater snails that transmit Schistosoma parasites to more than 200 million people globally8-10. In a cluster randomized controlled trial (ClinicalTrials.gov: NCT03187366) in which we removed invasive submerged vegetation from water points at 8 of 16 villages (that is, clusters), control sites had 1.46 times higher intestinal Schistosoma infection rates in schoolchildren and lower open water access than removal sites. Vegetation removal did not have any detectable long-term adverse effects on local water quality or freshwater biodiversity. In feeding trials, the removed vegetation was as effective as traditional livestock feed but 41 to 179 times cheaper and converting the vegetation to compost provided private crop production and total (public health plus crop production benefits) benefit-to-cost ratios as high as 4.0 and 8.8, respectively. Thus, the approach yielded an economic incentive-with important public health co-benefits-to maintain cleared waterways and return nutrients captured in aquatic plants back to agriculture with promise of breaking poverty-disease traps. To facilitate targeting and scaling of the intervention, we lay the foundation for using remote sensing technology to detect snail habitats. By offering a rare, profitable, win-win approach to addressing food and water access, poverty alleviation, infectious disease control and environmental sustainability, we hope to inspire the interdisciplinary search for planetary health solutions11 to the many and formidable, co-dependent global grand challenges of the twenty-first century.

Estimating the economic and social impact of conditional cash transfers from the Prospera Program in Mexico.

This research analyses the Prospera program's impact on poverty and income distribution through a computable general equilibrium model. It concludes that transfers to households have a positive impact on the Mexican economy but hide the real problem-the low wage share-that, in the long term, prevents poverty from worsening but does not reduce the population in poverty or inequality. In a scenario without transfers, neither the population in poverty nor the Gini Index decreases significantly. The results obtained lead to an understanding of some of the causes of the high rates of poverty and inequality in Mexico, which in turn have been perpetuated since the economic crisis of 1995. This allows the design of public policies in line with the structural needs of the economy, which combat the problem from the root that generates it, in order to contribute to the reduction of inequality in accordance with the UN Sustainable Development Goal 10.

Chairman's Communist Party of China member status and targeted poverty alleviation: Evidence from China.

Based on the data of Chinese listed private companies from 2016 to 2020, this paper investigates the influence of the Chairman's member status of Communist Party of China (CPC) on targeted poverty alleviation. The research results demonstrate that the Chairman's CPC member status of private companies significantly increases the companies' willingness and the amounts of investment in poverty alleviation. The construction of the CPC organization can strengthen the role of the chairman's Communist Party of China member status in promoting targeted poverty alleviation. The conclusions are still valid through robustness tests, such as substituting dependent variables, adjusting the sample range, and PSM-paired samples. In addition, the Impact Threshold for a Confounding Variable is used to deal with endogenous problems.

The effects of cash transfers on adult and child mortality in low- and middle-income countries.

Poverty is an important social determinant of health that is associated with increased risk of death1-5. Cash transfer programmes provide non-contributory monetary transfers to individuals or households, with or without behavioural conditions such as children's school attendance6,7. Over recent decades, cash transfer programmes have emerged as central components of poverty reduction strategies of many governments in low- and middle-income countries6,7. The effects of these programmes on adult and child mortality rates remains an important gap in the literature, however, with existing evidence limited to a few specific conditional cash transfer programmes, primarily in Latin America8-14. Here we evaluated the effects of large-scale, government-led cash transfer programmes on all-cause adult and child mortality using individual-level longitudinal mortality datasets from many low- and middle-income countries. We found that cash transfer programmes were associated with significant reductions in mortality among children under five years of age and women. Secondary heterogeneity analyses suggested similar effects for conditional and unconditional programmes, and larger effects for programmes that covered a larger share of the population and provided larger transfer amounts, and in countries with lower health expenditures, lower baseline life expectancy, and higher perceived regulatory quality. Our findings support the use of anti-poverty programmes such as cash transfers, which many countries have introduced or expanded during the COVID-19 pandemic, to improve population health.

Research on the long tail mechanism of digital finance alleviating the relative poverty of rural households.

Digital finance provides a long-tail mechanism for alleviating relative poverty caused by unequal opportunities and rights. According to the inference of an improved Cobb-Douglas production function and Ramsey-Cass-Koopmans two-stage household consumption model, the long-tail mechanism for digital finance to alleviate the relative poverty of farmers includes productive investment mechanism, credit mechanism, financial asset allocation and entrepreneurial mechanism. An empirical analysis of 11,519 rural households across China based on CHFS2019 data shows that digital finance can significantly and steadily alleviate relative poverty by improving credit availability and promoting household entrepreneurship, while its effect on increasing productive investment opportunities and optimizing financial asset allocation is less certain. Therefore, it is necessary to continue to improve the "blood making" long tail mechanism of digital finance for farmers' credit and innovation and entrepreneurship, and at the same time guide the digital finance to empower the development of rural industries to increase farmers' productive investment opportunities, cultivate endogenous growth momentum, and improve the wealth allocation function of rural digital financial market.

Financial and social efficiency of microcredit programs of partner organizations of Pakistan Poverty Alleviation Fund.

This paper examines the financial and social efficiency of the microcredit programs offered by the Pakistan Poverty Alleviation Fund partner organizations. Panel data concerning variables of interest are collected from Pakistan Microfinance Network, covering a minimum of 14 partner organizations (in 2005) to a maximum of 35 partner organizations (in 2014). The data is analyzed using the Data Envelopment Analysis, assuming both constant and variable returns to scale scenarios and the operational scale of the partner organizations. Trends in average efficiency scores have been analyzed to assess the mission drift of the partner organizations. Results reveal that managerial inefficiency is more pronounced than the sub-optimal production scale in all three scenarios under consideration. Moreover, trends in the efficiency scores indicated a slight mission drift of the microfinance providers. About 77.5% of the partner organizations were financially sustainable over the entire study period. The study recommends providing objective-oriented training, workshops, and seminars for managing microfinance providers.

Ghana's Livelihood Empowerment Against Poverty (1000) Program Seasonally Impacts Birthweight: A Difference-in-Differences Analysis.

Objectives: Low birthweight (LBW) prevalence remains high in African countries and evidence of cash transfer impacts on birthweight, particularly by season of infant birth, is limited. This study examines overall and seasonal cash transfer impacts on LBW in rural Ghana. Methods: Data come from a longitudinal, quasi-experimental impact evaluation of the Livelihood Empowerment Against Poverty (LEAP) 1,000 unconditional cash transfer program for impoverished pregnant or lactating women in rural districts of Northern Ghana. LEAP1000 program impacts on average birthweight and LBW were estimated for a multiply imputed sample of 3,258 and a panel sample of 1,567 infants using differences-in-differences models and triple difference models to assess impacts by season. Results: LEAP1000 decreased LBW prevalence by 3.5 and 4.1 percentage points overall and in the dry season, respectively. LEAP1000 increased average birthweight by 94, 109, and 79 g overall, in the dry season, and in the rainy season, respectively. Conclusion: Our findings of positive LEAP1000 impacts on birthweight across seasons and on LBW in the dry season demonstrate the need to take seasonal vulnerabilities into account when designing and implementing programs for rural populations in Africa.

Sustainable poverty alleviation capacity construction of farmers in poverty-stricken areas under the background of rural revitalization.

Rural revitalization aims to consolidate the achievements of poverty alleviation. Furthermore, enhancing the sustainable poverty alleviation ability of farmers in poverty-stricken areas is a critical concern. Using samples of farmers in four regions of the Yunnan province in China, multidimensional poverty and sustainable poverty alleviation ability indexes were constructed. Furthermore, a multidimensional poverty double boundary method (A-F method) was used to identify multidimensional poverty, and binary logistic function in SPSS was used to perform a regression analysis between multidimensional poverty and sustainable poverty alleviation ability. Results showed that as the poverty dimension increased, poverty incidence rate in the four regions decreased, with middle poverty incidence rate being the highest. Ability poverty was then identified as the major type of poverty in the sample, with the group of poor farmers with a high dimension of poverty being the most affected. Therefore, based on the ability structure of sustainable farmers out of poverty, we analyze the prominent problem of the ability construction of sustainable poverty reduction and propose a path for promoting sustainable poverty reduction ability. Hence, we will effectively link poverty alleviation with rural vitalization.