Year Published
- 2008 (0)
- 2009 (0)
- 2010 (0)
- (-) Remove 2011 filter 2011
- 2012 (1) Apply 2012 filter
- 2013 (0)
- 2014 (1) Apply 2014 filter
- 2015 (0)
- (-) Remove 2016 filter 2016
- (-) Remove 2017 filter 2017
- 2018 (2) Apply 2018 filter
- 2019 (2) Apply 2019 filter
- 2020 (0)
- 2021 (1) Apply 2021 filter
Research Topics
Populations
Types of Research
- Data Analysis (2) Apply Data Analysis filter
- Literature Review (2) Apply Literature Review filter
- Portfolio Review (0)
- Research Brief (0)
Geography
- (-) Remove East Africa Region and Selected Countries filter East Africa Region and Selected Countries
- Global (6) Apply Global filter
- South Asia Region and Selected Countries (9) Apply South Asia Region and Selected Countries filter
- Southern Africa Region and Selected Countries (0)
- Sub-Saharan Africa (9) Apply Sub-Saharan Africa filter
- (-) Remove West Africa Region and Selected Countries filter West Africa Region and Selected Countries
Dataset
- ASTI (0)
- FAOSTAT (0)
- Farmer First (0)
- LSMS & LSMS-ISA (1) Apply LSMS & LSMS-ISA filter
- Other Datasets (2) Apply Other Datasets filter
Current search
- (-) Remove East Africa Region and Selected Countries filter East Africa Region and Selected Countries
- (-) Remove Finance & Investment filter Finance & Investment
- (-) Remove Environment & Climate Change filter Environment & Climate Change
- (-) Remove 2016 filter 2016
- (-) Remove Health filter Health
- (-) Remove 2017 filter 2017
- (-) Remove Global & Regional Public Goods filter Global & Regional Public Goods
- (-) Remove Technology Adoption filter Technology Adoption
- (-) Remove 2011 filter 2011
- (-) Remove West Africa Region and Selected Countries filter West Africa Region and Selected Countries
- (-) Remove Monitoring & Evaluation filter Monitoring & Evaluation
- (-) Remove Poverty filter Poverty
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.
In this report, we analyze the evidence that improved and expanded access to financial services can be a pathway out of poverty in Bangladesh and Tanzania. A brief background review of finance and poverty reduction evidence at the country, household, and individual level emphasizes the importance of a functioning financial system and the need to remove individual and household barriers to capital accumulation. We follow with an in-depth literature review on studies that link poverty reduction in Bangladesh or Tanzania with one or more of five financial intervention categories: remittances; government subsidies; conditional and unconditional cash transfers; credit; and combination programs. The resulting empirical evidence from these sources reveal a high share (61%) of positive reported associations between a financial intervention and outcome measure related to our five chosen financial interventions. The remaining studies found insignificant or mixed associations, but very few (3 out of 56) indicate that access to a financial mechanism was associated with worsened poverty. The heterogeneity of study types and interventions makes it difficult to draw conclusions about the efficacy of one intervention over another, and more research is needed on whether such approaches constitute a durable, long-term exit from poverty.
Common aid allocation formulas incorporate measures of income per capita but not measures of poverty, likely based on the assumption that rising average incomes are associated with reduced poverty. If declining poverty is the outcome of interest, however, the case of Nigeria illustrates that such aid allocation formulas could lead to poorly targeted or inefficient aid disbursements. Using data from the World Bank and the Nigerian National Bureau of Statistics, we find that while the relationship between economic growth and poverty in Nigeria varies depending on the time period studied, overall from 1992-2009 Nigeria’s poverty rate has only declined by 6% despite a 70% increase in per capita gross domestic product (GDP). A review of the literature indicates that income inequality, the prominence of the oil sector, unemployment, corruption, and poor education and health in Nigeria may help to explain the pattern of high ongoing poverty rates in the country even in the presence of economic growth. Our analysis is limited by substantial gaps in the availability of quality data on measures of poverty and economic growth in Nigeria, an issue also raised in the literature we reviewed, but our findings support arguments that economic growth should not be assumed to lead to poverty reduction and that the relationship between these outcomes likely depends on contextual factors.