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Policy-oriented discussions often assume that \"better targeting\" implies larger impacts on poverty or more cost-effective interventions for fighting poverty. The literature on the economics of targeting warns against that assumption, but evidence has been scarce and the lessons from the literature have often been ignored by practitioners. This paper shows that standard measures of targeting performance are uninformative or even deceptive about the impacts on poverty, and cost-effectiveness in reducing poverty, of a large cash transfer program in China. The results suggest that in program design and evaluation, it would be better to focus directly on the program's outcomes for poor people than to rely on prevailing measures of targeting.

Poverty, particularly in developing regions, is a complex, multifaceted issue deeply embedded in various interrelated factors. It extends beyond mere financial insufficiency, encompassing limited access to essential services such as healthcare, education, and overall living standards. This study examines both the unidimensional and multidimensional aspects of rural poverty in Suri Sadar Sub-Division, located in Eastern India. For the unidimensional aspect, this study employs the poverty headcount ratio and the Poverty Gap Index to gauge the incidence and intensity of poverty. In contrast, the multidimensional approach utilized three dimensions and 12 indicators to assess the incidence, severity, and multidimensional poverty index utilizing the Alkire–Foster (AF) methodology. The unidimensional analysis, focusing on income and consumption, highlights significant economic disparities, particularly in the western Community Development Blocks, namely, Khoyrasole, Md. Bazar, and Rajnagar. The highest levels of multidimensional poverty are generally consistent with the unidimensional findings, particularly in the western blocks. These results underscore the need for comprehensive poverty reduction strategies that address both economic and broader aspects of poverty. In areas like the western blocks, where both income-based and multidimensional poverty rates are high, strategies should integrate economic development, improved healthcare access, enhanced educational quality, and living standards improvement. Therefore, this study serves not only as an academic endeavor but also as a vital tool for informed policymaking in poverty alleviation, providing planners, administrative officials, and researchers with essential insights to develop effective, localized, and sustainable poverty reduction strategies.

Longitudinal data modeling is widely carried out using parametric methods. However, when the parametric model is misspecified, the obtained estimator might be severely biased and lead to erroneous conclusions. In this study, we propose a new estimation method for longitudinal data modeling using a mixed estimator in nonparametric regression. The objective of this study was to estimate the nonparametric regression curve for longitudinal data using two combined estimators: truncated spline and local linear. The weighted least square method with a two-stage estimation procedure was used to obtain the regression curve estimation of the proposed model. To account for within-subject correlations in the longitudinal data, a symmetric weight matrix was given in the regression curve estimation. The best model was determined by minimizing the generalized cross-validation value. Furthermore, an application to a longitudinal dataset of the poverty gap index in Bengkulu Province, Indonesia, was conducted to illustrate the performance of the proposed mixed estimator. Compared to the single estimator, the truncated spline and local linear mixed estimator had better performance in longitudinal data modeling based on the GCV value. Additionally, the empirical results of the best model indicated that the proposed model could explain the data variation exceptionally well.

According to a recent World Bank study of remittances, Bangladesh, India, Pakistan and Sri Lanka are all among the top 20 receivers of remittances, with estimated receipts of US3.2 billion, US8.4 billion and U.S 1.5 billion respectively. Migrant Labor Remittances in South Asia identifies and discusses the key issues affecting the remittance industry in South Asia. It examines the development and implementation of policies, processes, and infrastructure to foster a development-oriented transfer of financial resources between migrants in developed economies and their families in the region. Rather than duplicate previous remittances work, this title only focuses on the region’s distinguishing characteristics, namely: A large migrant population of semi-skilled and unskilled workers largely concentrated in the Arabian Gulf countries, particularly Saudi Arabia and the United Arab Emirates.; The presence of dedicated public institutions and government financial incentives aimed at facilitating and providing incentives for temporary migration and remittance inflows; The existence of large state bank branch networks with immense potential for a more effective and efficient remittance financial market.; The widespread usage of trade related informal remittance channels by both legal and illegal migrants. The book is intended for policymakers who legislate and regulate the financial sector, as well as for researchers and providers of remittance services.

As the largest developing country in the world, China’s rural areas face many poverty- related issues. It is imperative to assess poverty dynamics in a timely and effective manner in China’s rural areas. Therefore, we used the poverty gap index to investigate the poverty dynamics in China’s rural areas during 2000–2014 at the national, contiguous poor areas with particular difficulties and county scales. We found that China made significant achievements in poverty alleviation during 2000–2014. At the national scale, the number of impoverished counties decreased by 1428, a reduction of 97.28%. The rural population in impoverished counties decreased by 493.94 million people or 98.76%. Poverty alleviation was closely associated with economic development, especially with industrial development. Among all 15 socioeconomic indicators, the industrial added value had the highest correlation coefficient with the poverty gap index ( r = –0.458, p <0.01). Meanwhile, the inequality of income distribution in the out-of-poverty counties has been aggravated. The urban-rural income gap among the out-of-poverty counties increased by 1.67-fold, and the coefficient of variation in rural per-capita income among the out-of-poverty counties also increased by 9.09%. Thus, we argued that special attention should be paid to reducing income inequality for sustainable development in China’s rural areas.

Understanding Changes in Poverty brings together different methods to decompose the contributions to poverty reduction. A simple approach quantifies the contribution of changes in demographics, employment, earnings, public transfers, and remittances to poverty reduction. A more complex approach quantifies the contributions to poverty reduction from changes in individual and household characteristics, including changes in the sectoral, occupational, and educational structure of the workforce, as well as changes in the returns to individual and household characteristics. Understanding Changes in Poverty implements these approaches and finds that labor income growththat is, growth in income per worker rather than an increase in the number of employed workerswas the largest contributor to moderate poverty reduction in 21 countries experiencing substantial reductions in poverty over the past decade. Changes in demographics, public transfers, and remittances helped, but made relatively smaller contributions to poverty reduction. Further decompositions in three countries find that labor income grew mainly because of higher returns to human capital endowments, signaling increases in productivity, higher relative price of labor, or both. Understanding Changes in Poverty will be of particular relevance to development practitioners interested in better understanding distributional changes over time. The methods and tools presented in this book can also be applied to better understand changes in inequality or any other distributional change.

'Handbook on Poverty + Inequality' was originally designed to support training courses in poverty analysis and inequality. The 'Handbook' begins with an explanatory text that includes numerous examples, multiple-choice questions to ensure active learning, and extensive practical exercises that use Stata statistical software. The 'Handbook' will help researchers and evaluators in charge of preparing background materials for Poverty Reducation Strategy Papers (PRSPs) and those responsible for monitoring and evaluating poverty reduction programs and policies. The World Bank Institute has used the 'Handbook' in training workshops in countries from Bangladesh, India, and Pakistan, to Cambodia, Indonesia, the Philippines, and Thailand, to Malawi and Tanzania, as well as in university courses on poverty and in distance education courses with participants from Asian and African countries. The 'Handbook' has also been used in an online asynchronous course with more than 200 participants worldwide. Using the feedback from these courses, the authors have created a clearly-written text that balances rigor with practicality. The 'Handbook' is designed to be accessible to people with a university-level background in science or the social sciences. It is an invaluable tool for policy analysts, researchers, college students, and government officials working on policy issues related to poverty and inequality.

This report's objective is to develop the evidence base for policy making in relation to poverty reduction. It produces a diagnosis of the broad nature of the poverty problem and its trends in India, focusing on both consumption poverty and human development outcomes. It also includes attention in greater depth to three pathways important to inclusive growth and poverty reduction harnessing the potential of urban growth to stimulate rural-based poverty reduction, rural diversification away from agriculture, and tackling social exclusion. This report shows that urban growth, which has increasingly outpaced growth in rural areas, has helped to reduce poverty for urban residents directly. In addition, evidence appears of a much stronger link from urban economic growth to rural poverty reduction. Stronger links with rural poverty are due to a more integrated economy. Urban areas are a demand hub for rural producers, as well as a source of employment for the rural labor force. They are aiding the transformation of the rural economy out of agriculture. In urban areas, it is small and medium-size towns, rather than large cities, that appear to demonstrate the strongest urban-rural growth links. Urban growth also stimulates rural-urban migration. But although some increase in such migration has occurred over time, migration levels in India remain relatively low compared to other countries.

The story of Mozambique is one of successful transformation. Since 1994, when it faced a decimated infrastructure, a weak economy, and fragile institutions, it has sustained high economic growth and has made tangible reductions in poverty. Its recovery from civil conflict and extreme poverty make it a showcase for other nations embarking on similar transitions. Still, more than half of the population lives in poverty. Gaps persist between city dwellers and farmers, men and women, rich and poor. And although growth continues, there is concern that Mozambique's drive to reduce poverty may lose momentum as happens in many countries recovering from conflict. If the successes of the past are to be extended into the future, policy makers must take stock of what has worked and what has not as they develop new ways of improving the living standards of all Mozambicans. 'Beating the Odds: Sustaining Inclusion in Mozambique's Growing Economy' focuses on changes in poverty and household community welfare from 1997 through 2003. It uses monetary, human, and social indicators in combination with quantitative and qualitative approaches to understand poverty trends within the country and the dynamics that shaped them. Intended to support the development and implementation of pro-poor policies, its integration of poverty, gender, and social analysis will be of particular interest to policy makers, development practitioners, academics, and researchers.