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Self-Help Groups (SHGs) in Sub-Saharan Africa can be defined as mutual assistance organizations through which individuals undertake collective action in order to improve their own lives. “Collective action” implies that individuals share their time, labor, money, or other assets with the group. In a recent EPAR data analysis, we use three nationally-representative survey tools to examine various indicators related to the coverage and prevalence of Self-Help Group usage across six Sub-Saharan African countries. EPAR has developed Stata .do files for the construction of a set of self-help group indicators using data from the Living Standards Measurement Study - Integrated Surveys on Agriculture (LSMS-ISA), Financial Inclusion Index (FII), and FinScope.
We compiled a set of summary statistics for the final indicators using data from the following survey instruments:
- Ethiopia Socioeconomic Survey (ESS), Wave 3 (2015-16)
- Kenya FinScope, Wave 4 (2015)
- Kenya FII, Wave 4 (2016)
- Nigeria FII, Wave 4 (2016)
- Rwanda FII, Wave 4 (2016)
- Tanzania National Panel Survey (TNPS), Wave 4 (2014-15)
- Tanzania FinScope, Wave 4 (2017)
- Tanzania FII, Wave 4 (2016)
- Uganda FinScope, Wave 3 (2013)
- Uganda FII, Wave 4 (2016)
The raw survey data files are available for download free of charge from the World Bank LSMS-ISA website, the Financial Sector Deepening Trust website, and the Financial Inclusion Insights website. The .do files process the data and create final data sets at the household (LSMS-ISA) and individual (FII, FinScope) levels with labeled variables, which can be used to estimate summary statistics for the indicators.
All the instruments include nationally-representative samples. All estimates from the LSMS-ISA are household-level cluster-weighted means, while all estimates from FII and FinScope are calculated as individual-level weighted means. The proportions in the Indicators Spreadsheet are therefore estimates of the true proportion of individuals/households in the national population during the year of the survey. EPAR also created a Tableau visualization of these summary statistics, which can be found here.
We have also prepared a document outlining the construction decisions for each indicator across survey instruments and countries. We attempted to follow the same construction approach across instruments, and note any situations where differences in the instruments made this impossible.
The spreadsheet includes estimates of the following indicators created in our code files:
- Proportion of individuals who have access to a mobile phone
- Proportion of individuals who have official identification
- Proportion of individuals who are female
- Proportion of individuals who use mobile money
- Proportion of individuals who have a bank account
- Proportion of individuals who live in a rural area
- Individual Poverty Status
- Two Lowest PPI Quintiles
- Middle PPI Quintile
- Two Highest PPI Quintiles
Coverage & Prevalence
- Proportion of individuals who have interacted with a SHG
- Proportion of individuals who have used an SHG for financial services
- Proportion of individuals who depend most on SHGs for financial advice
- Proportion of individuals who have received financial advice from a SHG
- Proportion of households that have interacted with a SHG
- Proportion of households in communities with at least one SHG
- Proportion of households in communities with access to multiple farmer cooperative groups
- Proportion of households who have used an SHG for financial services
In addition, we produced estimates for 29 indicators related to characteristics of SHG use including indicators related to frequency of SHG use, characteristics of SHG groups, and individual/household trust of SHGs.
Many low- and middle-income countries remain challenged by a financial infrastructure gap, evidenced by very low numbers of bank branches and automated teller machines (ATMs) (e.g., 2.9 branches per 100,000 people in Ethiopia versus 13.5 in India and 32.9 in the United States (U.S.) and 0.5 ATMs per 100,000 people in Ethiopia versus 19.7 in India and 173 in the U.S.) (The World Bank 2015a; 2015b). Furthermore, only an estimated 62 percent of adults globally have a banking account through a formal financial institution, leaving over 2 billion adults unbanked (Demirgüç–Kunt et al., 2015). While conventional banks have struggled to extend their networks into low-income and rural communities, digital financial services (DFS) have the potential to extend financial opportunities to these groups (Radcliffe & Voorhies, 2012). In order to utilize DFS however, users must convert physical cash to electronic money which requires access to cash-in, cash-out (CICO) networks—physical access points including bank branches but also including “branchless banking" access points such as ATMs, point-of-sale (POS) terminals, agents, and cash merchants. As mobile money and branchless banking expand, countries are developing new regulations to govern their operations (Lyman, Ivatury, & Staschen, 2006; Lyman, Pickens, & Porteous, 2008; Ivatury & Mas, 2008), including regulations targeting aspects of the different CICO interfaces.
EPAR's work on CICO networks consists of five components. First, we summarize types of recent mobile money and branchless banking regulations related to CICO networks and review available evidence on the impacts these regulations may have on markets and consumers. In addition to this technical report we developed a short addendum (EPAR 355a) which includes a description of findings on patterns around CICO regulations over time. Another addendum (EPAR 355b) summarizes trends in exclusivity regulations including overall trends, country-specific approaches to exclusivity, and a table showing how available data on DFS adoption from FII and GSMA might relate to changes in exclusivity policies over time. A third addendum (EPAR 355c) explores trends in CICO network expansion with a focus on policies seeking to improve access among more remote or under-served populations. Lastly, we developed a database of CICO regulations, including a regulatory decision options table which outlines the key decisions that countries can make to regulate CICOs and a timeline of when specific regulations related to CICOs were introduced in eight focus countries, Bangladesh, India, Indonesia, Kenya, Nigeria, Pakistan, Tanzania, and Uganda.
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.
This brief explores how two datasets – The Tanzania National Panel Survey (TZNPS) and the TNS-Research International Farmer Focus (FF) – predict the determinants of inorganic fertilizer use among smallholder farmers in Tanzania by using regression analysis. The (TZNPS) was implemented by the Tanzania National Bureau of Statistics, with support from the World Bank Living Standards Measurement Study – Integrated Surveys on Agriculture (LSMS-ISA) team and includes extensive information on crop productivity and input use. The FF survey was funded by the Bill and Melinda Gates Foundation and implemented by TNS Research International and focuses on the on the behaviors and attitudes of smallholder farmers in Tanzania. The two datasets produce relatively comparable results for the primary predictors of inorganic fertilizer use: agricultural extension and whether or not a household grows cash crops. However, other factors influencing input use produce results that vary in magnitude and direction of the effect across the two datasets. Distinct survey instrument designs make it difficult to test the robustness of the models on input use other than inorganic fertilizer. This brief uses data inorganic fertilizer use, rather than adoption per se. The TZNPS did not ask households how recently they began using a certain product and although the FF survey asked respondents how many new inputs were tried in the past four planting seasons, they did not ask specifically about inorganic fertilizer.
This is "Section B" of a report that presents estimates and summary statistics from the 2008/2009 wave of the Tanzania National Panel Survey (TZNPS), part of the Living Standards Measurement Study – Integrated Surveys on Agriculture (LSMS-ISA). We present our analyses of household characteristics by gender and by administrative zone, considering landholding size, number of crops grown, yields, livestock, input use, and food consumption.
This is "Section C" of a report that presents estimates and summary statistics from the 2008/2009 wave of the Tanzania National Panel Survey (TZNPS), part of the Living Standards Measurement Study – Integrated Surveys on Agriculture (LSMS-ISA). We present our analyses of the basic characteristics of household heads and other household members, as well as our analyses of education for adults, children, and household heads by gender and zone.
In the decades following independence in 1960, Côte d’Ivoire stood out as a shining example of economic growth in Sub-Saharan Africa. GDP increased at an annual average of 8.1 percent from 1960 to 1979, led largely by cocoa and coffee exports. Low export earnings from a fall in world cocoa prices and a heavy public debt burden halted this growth in the 1980s, followed by civil conflict beginning in 1999. Three decades of focus on export crops rather than food crops also left Côte d’Ivoire with a growing food deficit. This literature review examines the state of agriculture in Côte d’Ivoire and the history of government involvement in the agricultural sector. We find that while the country is poised to reemerge from a decade of economic stagnation and civil war after signing the Ouagadougou Political Accord in 2007, the political economy of Côte d’Ivoire is still heavily dependent upon and influenced by the production of cocoa. Cocoa is the top export, and cocoa export taxes provide one of the largest sources of revenue for the Government of Côte d’Ivoire (GoCI). Cocoa is not heavily dependent on fertilizer inputs and growers have increased production by expanding cropland. The small contribution of fertilizer to the production of this essential crop may help explain the GoCI’s low priority on expanding fertilizer production and use. Given that a large part of government revenue comes from the export of cocoa and coffee, the government has chosen to focus resources on crops that increase revenue. Even with the food riots in 2008, the GoCI has not made increasing domestic food production an important focus of agricultural policy.
In Mozambique, the legacies of colonial rule, socialism and civil war continue to constrain economic growth and agricultural production. Eighty percent of Mozambique’s labor force derives its livelihood from agriculture, but the nation remains a net food importer. The majority of all farmland is cultivated by smallholders whose fertilizer usage and crop yields are among the lowest in Africa. While Mozambique has experienced reasonable economic growth since the end of its civil war in 1992, it remains poor by almost any measure. In this literature review, we examine the state of agriculture in Mozambique, the country’s political history and post-war recovery, and the current fertilizer market. We find evidence that smallholder access to fertilizer in Mozambique is limited by lack of information, affordability, access to credit, a poor business environment, and limited infrastructure. The data demonstrate that increased investment in infrastructure is an important step to improve input and output market access for smallholders. The main government intervention currently impacting smallholder fertilizer use is the Agricultural Sector Public Expenditure Program (PROAGRI) initiative, however, more data is necessary to assess the impact of its policies and programs.
Agriculture is the most important sector in the Ghanaian economy. In 2008, it accounted for over 32 percent of GDP and employed over half of the labor force. Economic development in Ghana has historically been dependent on the success of agriculture, particularly the main export crop, cocoa. Despite the sector’s importance, Ghanaian farmers have one of the lowest fertilizer application rates in Sub-Saharan Africa. The combination of a dominant agricultural sector, nutrient-poor soils, low fertilizer use among smallholder farmers, and the absence of locally produced inorganic fertilizers has prompted the government of Ghana (GoG) to intervene in the fertilizer market. This literature review examines the state of agriculture in Ghana, the history of the fertilizer market, and the current market structure. We find that the GoG has been a major actor in the inorganic fertilizer market over the past 50 years, from exercising total control of the domestic supply chain in the 1960s and 1970s to more indirect interventions in later years. In recent years, agricultural growth has averaged 5.5 percent as compared to 5.2 percent growth in the rest of the economy. However, most of this growth has been due to land expansion and favorable weather conditions rather than increased productivity. Increased fertilizer use among smallholder farmers has the potential to contribute to future agricultural growth and continued economic success.