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Key Takeaways
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A survey of poverty indicators surfaced 139 candidates, of which 36 were ultimately selected for inclusion in the study based on indicator construction, use, and timeliness.
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The selected 36 poverty indicators relied primarily on 26 data sources, mainly household surveys and administrative government data.
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Most indicators relied on household survey data and used multidimensional indices to comprehensively measure poverty, aside from poverty line and poverty gap measures which relied exclusively on income and consumption.
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Indicators or indicator components were typically based on quantitative estimates of income or consumption, although an increasing number of measurements are instead classifying households according to deprivation of assets, food, or access to services and basic infrastructure.
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Overall, critics find that an emphasis on poverty line measurements has led to an incomplete understanding of poverty’s prevalence and trends over the last several decades (UN Special Rapporteur, 2020).
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No single indicator dominates on considerations of reliability, dimensions, depth or intensity, comparability, etc., but rather each measure involves tradeoffs.
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If the goal is to increase the utility of commonly used indicators, including those considering multiple dimensions of poverty, then investments focused on expanding the coverage, frequency, or scope of nationally representative household surveys is a necessary first step.
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Making cross-country comparisons using any poverty indicator runs the risk of using a common metric based on different data sources and collected in different years that may not fully reflect a household’s welfare. Indices which include multiple subcomponents may be more holistic, but even less reliable as the number of components requiring data increases.
Suggested citation:
Landscape Review of Poverty Measures. EPAR Technical Report #424 (2022). Evans School of Public Policy & Governance, University of Washington. Retrieved <Day Month Year> from https://epar.evans.uw.edu/research
This document is an initial scoping of the theory and evidence linking digital services to women’s rural-to-urban migration. The document contains (1) a survey of the literature on digital financial services to discern how often this body of literature considers gender-disaggregated impacts on migration, (2) a detailed review of 13 hypotheses regarding the effects of digital services on women’s migration to cities, and (3) an illustrative overview of rural-urban migration patterns and digital technology usage in two East African countries (Ethiopia and Tanzania).
In this report we analyze three waves nationally-representative household survey data from Kenya, Uganda, Tanzania, Nigeria, Pakistan, Bangladesh, India, and Indonesia to explore sociodemographic and economic factors associated with mobile money adoption, awareness, and use across countries and over time. Our findings indicate that to realize the potential of digital financial services to reach currently unbanked populations and increase financial inclusion, particular attention needs to be paid to barriers faced by women in accessing mobile money. While policies and interventions to promote education, employment, phone ownership, and having a bank account may broadly help to increase mobile money adoption and use, potentially bringing in currently unbanked populations, specific policies targeting women may be needed to close current gender gaps.
Cash transfer programs are interventions that directly provide cash to target specific populations with the aim of reducing poverty and supporting a variety of development outcomes. Low- and middle-income countries have increasingly adopted cash transfer programs as central elements of their poverty reduction and social protection strategies. Bastagli et al. (2016) report that around 130 low- and middle-income countries have at least one UCT program, and 63 countries have at least one CCT program (up from 27 countries in 2008). Through a comprehensive review of literature, this report primarily considers the evidence of the long-term impacts of cash transfer programs in low- and lower middle-income countries. A review of 54 reviews that aggregate and summarize findings from multiple studies of cash transfer programs reveals largely positive evidence on long-term outcomes related to general health, reproductive health, nutrition, labor markets, poverty, and gender and intra-household dynamics, though findings vary by context and in many cases overall conclusions on the long-term impacts of cash transfers are mixed. In addition, evidence on long-term impacts for many outcome measures is limited, and few studies explicitly aim to measure long-term impacts distinctly from immediate or short-term impacts of cash transfers.
A “new wave” of digital credit products has entered the digital financial services (DFS) market in recent years. These products differ from traditional credit by offering loans to borrowers that can be applied for, approved, and disbursed remotely (often without any brick-and-mortar infrastructure), automatically (generally minimizing or eliminating person-to-person interaction), and instantly (often in less than 72 hours). Digital credit also increasingly considers creditworthiness by using alternative (nontraditional) data—ranging from mobile phone activity to utility payments and social media data—potentially allowing for loans to populations previously unable to access bank credit. Two EPAR reports review the characteristics of digital credit offerings in India, Kenya, Nigeria, Tanzania, and Uganda, and regulations specific to digital credit in Africa and Asia.