By successfully reaching historically underserved and vulnerable populations such as women, the poor, and people living in rural communities, Digital Financial Services have contributed to unprecedented growth in financial inclusion in Sub-Saharan Africa during the past decade.
... See More + The adoption and usage of DFS -- and the subsequent financial inclusion that has resulted -- has helped reduce poverty and increase prosperity throughout the region. Still, service providers and development practitioners often lack reliable, detailed, and low-cost poverty data that could help them accurately identify additional communities and individuals who would benefit the most from access to financial services. The lack of data hinders the deployment of services throughout the region and complicates efforts to monitor and evaluate the impact that interventions have on poverty. Relying on traditional household surveys for poverty data is time consuming and expensive. What’s more, by the time the data are collected and analyzed, it is often out of date. But there are alternatives for estimating and mapping poverty with the goal of accelerating and expanding financial inclusion and helping DFS providers target the poorest. Machine learning algorithms can, for example, be trained to predict poverty based on imagery captured by satellites and from call detail records, which document mobile phone usage. For this research study, the IFC Mastercard Foundation Partnership for Financial Inclusion collaborated with the Stanford University Sustainability and Artificial Intelligence Lab to advance existing poverty prediction models to generate poverty estimates at neighborhood-level resolution, which is much more refined than macro-level estimates produced by research to date. Satellite Imagery and call detail records (CDR), validated by ground-truth surveys, were used to develop models that can predict poverty in Ghana and Uganda.
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Afghanistan has been in protracted conflict for almost four decades, with direct implications on progress towards development objectives. This context of recurring episodes of violence and insecurity, economic and political instability, and the consequent displacement of populations within and outside the nation’s borders has important implications on the landscape of data and evidence available for the design, implementation, monitoring and evaluation of interventions and programs, and their timeliness and relevance.
... See More + Afghans represent the world’s largest and most protracted refugee population, with an estimated 3.5 million people currently living abroad as refugees for more than four decades. Given the large disparities in poverty incidence and high levels of inequality within Afghanistan, the knowledge of living standards at more disaggregated geographical levels of districts and nahias could help inform policy design and improve decision making at a sub-province level. Therefore, poverty mapping, which aims at estimating poverty incidence at levels lower than the household survey, was applied in Kabul and Herat provinces. This technical report describes the methodology and data used to produce the Kabul and Herat poverty maps and presents the resulting collection of poverty maps, the first of its kind for Afghanistan. The structure of the report is as follows. Section 2 outlines the poverty mapping methodology, specifically the small area estimation approach, applied in Afghanistan. Section 3 discusses the data sources and the various technical challenges faced with the datasets. Section 4 discusses the modeling phase, including model selection, model parameters, and assumptions. Section 5 presents the poverty maps at a district and nahia level, and section 6 concludes. The Annexes contains supporting data and analysis.
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Outcome is moderately unsatisfactory, Risk to development outcome is significant, Bank performance is moderately unsatisfactory, and Borrower performance is moderately unsatisfactory.
... See More + Lessons from the project include: (i) Adaptability to local needs, retaining beneficiaries in the territory, and integration between different types of interventions are key features in slum upgrading and social housing. (ii) Weakness in social service delivery can jeopardize expected outcomes and sustainability. Flexible designs and adequate sequencing of activities might help ensure results. (iii) It is crucial in slum upgrading projects to guarantee delivery of all outputs in the social activities cycle because even small failures can jeopardize the expected outcomes. (iv) Adoption of multiphase projects or a programmatic long-term approach in slum-upgrading projects might be appropriate when social capital strengthening is considered necessary to achieve long-term results. (v) Appropriate timing in the preparation of slum-upgrading projects is crucial. Studies and diagnostics require sufficient time (though not too long) to avoid frustrating local expectations or hampering integration. (vi) Continuity in project management is a success factor in complex institutional development and social capital–strengthening projects, allowing familiarity with the local context and building mutual trust with the affected communities. (vii) It is important for World Bank project management to ensure that slum-upgrading projects in urban areas are consistent with existing city plans and are integrated seamlessly into World Bank Group sectoral and thematic operations.
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Project Performance Assessment Report 127250 JUN 29, 2018
This note summarizes the key findings from an in-depth analysis of the evolution of poverty and shared prosperity in Morocco. It is the result of a collaboration between the High Commissioner of Planning and the World Bank and provides the background information for the systematic country diagnostic, prepared by the World Bank in consultation with national stakeholders.
... See More + The results of the poverty analysis undertaken highlights four points. First, economic growth has been reflected in increased household expenditures, especially for those in the bottom forty percent of the distribution. Second, there has been a process of convergence in poverty rates across regions, yet spatial disparities are still large. Third, monetary transfers have increased and had a larger impact on poverty reduction, but are still regressive. Last, while poverty decline was accompanied by broader improvement in welfare, perceptions of well-being do not reflect these.
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This note summarizes the key findings from an in-depth analysis of the evolution of poverty and shared prosperity in Morocco. It is the result of a collaboration between the High Commissioner of Planning and the World Bank and provides the background information for the systematic country diagnostic, prepared by the World Bank in consultation with national stakeholders.
... See More + The results of the poverty analysis undertaken highlights four points. First, economic growth has been reflected in increased household expenditures, especially for those in the bottom forty percent of the distribution. Second, there has been a process of convergence in poverty rates across regions, yet spatial disparities are still large. Third, monetary transfers have increased and had a larger impact on poverty reduction, but are still regressive. Last, while poverty decline was accompanied by broader improvement in welfare, perceptions of well-being do not reflect these.
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The objectives of the Bangladesh Programmatic Poverty Analysis (BPPA), in the context of the Systematic Country Diagnostic (SCD) and Country Partnership Framework (CPF) cycle, are the following: (i) to support the Bangladesh Bureau of Statistics (BBS) in the production of higher quality and more timely household survey data; (ii) to build knowledge and evidence on extreme poverty and shared prosperity; (iii) to inform the design and implementation of selected projects included in the CPF; and (iv) to fill selected knowledge gaps identified in the SCD.
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