Year Published
- 2008 (3) Apply 2008 filter
- 2009 (3) Apply 2009 filter
- 2010 (6) Apply 2010 filter
- 2011 (5) Apply 2011 filter
- 2012 (0)
- 2013 (5) Apply 2013 filter
- 2014 (2) Apply 2014 filter
- 2015 (6) Apply 2015 filter
- (-) Remove 2016 filter 2016
- 2017 (1) Apply 2017 filter
- 2018 (1) Apply 2018 filter
- 2019 (0)
- 2020 (0)
- 2021 (0)
Research Topics
Populations
- Countries/Governments (1) Apply Countries/Governments filter
- Rural Populations (0)
- Smallholder Farmers (0)
- Women (0)
Types of Research
- Data Analysis (4) Apply Data Analysis filter
- (-) Remove Literature Review filter Literature Review
- Portfolio Review (0)
- Research Brief (1) Apply Research Brief filter
Geography
- East Africa Region and Selected Countries (0)
- Global (1) Apply Global filter
- South Asia Region and Selected Countries (0)
- Southern Africa Region and Selected Countries (0)
- Sub-Saharan Africa (1) Apply Sub-Saharan Africa filter
- West Africa Region and Selected Countries (0)
Dataset
- ASTI (0)
- FAOSTAT (0)
- Farmer First (0)
- LSMS & LSMS-ISA (1) Apply LSMS & LSMS-ISA filter
- Other Datasets (0)
Current search
- (-) Remove 2016 filter 2016
- (-) Remove Information & Mobile Technology filter Information & Mobile Technology
- (-) Remove Literature Review filter Literature Review
- (-) Remove Agricultural Productivity, Yield, & Constraints filter Agricultural Productivity, Yield, & Constraints
In Sub-Saharan Africa, 12% of adults now report having a mobile money account, representing over a quarter of the share of those who have any kind of financial account at all. As mobile money expands, there is interest in how regulatory frameworks develop to support digital financial services (DFS) and also support broader financial inclusion. In theory, protecting consumers from risk, and ensuring that they have the information and understanding required to make informed decisions, may increase their confidence and trust in mobile money systems, leading to higher adoption and usage rates. However, consumer protection regulations may also carry certain trade-offs in terms of cost, usage, and innovation. The challenge, according to proponents of consumer protection, is to develop regulations that promote access and innovation, yet still offer an acceptable level of consumer protection. We review the literature on consumer protection institutions and regulatory documents for DFS (particularly mobile money) in 22 developing countries, and identify examples of specific consumer protection regulations relevant to mobile money in each country.
Household survey data are a key source of information for policy-makers at all levels. In developing countries, household data are commonly used to target interventions and evaluate progress towards development goals. The World Bank’s Living Standards Measurement Study - Integrated Surveys on Agriculture (LSMS-ISA) are a particularly rich source of nationally-representative panel data for six Sub-Saharan African countries: Ethiopia, Malawi, Niger, Nigeria, Tanzania, and Uganda. To help understand how these data are used, EPAR reviewed the existing literature referencing the LSMS-ISA and identified 415 publications, working papers, reports, and presentations with primary research based on LSMS-ISA data. We find that use of the LSMS-ISA has been increasing each year since the first survey waves were made available in 2009, with several universities, multilateral organizations, government offices, and research groups across the globe using the data to answer questions on agricultural productivity, farm management, poverty and welfare, nutrition, and several other topics.
Agricultural productivity growth has been empirically linked to poverty reduction across a range of measures for both staple and export crops. Many public and private organizations have thus made it a priority to increase farm productivity, and have invested billions toward this end.This report compiles measures commonly used to track agricultural productivity and discusses the ways in which they are subject to error, bias, and other data limitations. Though each measure has limitations, choosing the measure(s) most appropriate to the goals of an analysis and understanding the sources of variation allows for more effective and closely targeted investments and policy and program recommendations, particularly when measures suggest different drivers of productivity growth and links to poverty reduction.