Types of Research
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Studies of improved seed adoption in developing countries almost always draw from household surveys and are premised on the assumption that farmers are able to self-report their use of improved seed varieties. However, recent studies suggest that farmers’ reports of the seed varieties planted, or even whether seed is local or improved, are sometimes inconsistent with the results of DNA fingerprinting of farmers' crops. We use household survey data from Tanzania to test the alignment between farmer-reported and DNA-identified maize seed types planted in fields. In the sample, 70% of maize seed observations are correctly reported as local or improved, while 16% are type I errors (falsely reported as improved) and 14% are type II errors (falsely reported as local). Type I errors are more likely to have been sourced from other farmers, rather than formal channels. An analysis of input use, including seed, fertilizer, and labor allocations, reveals that farmers tend to treat improved maize differently, depending on whether they correctly perceive it as improved. This suggests that errors in farmers' seed type awareness may translate into suboptimal management practices. In econometric analysis, the measured yield benefit of improved seed use is smaller in magnitude with a DNA-derived categorization, as compared with farmer reports. The greatest yield benefit is with correctly identified improved seed. This indicates that investments in farmers' access to information, seed labeling, and seed system oversight are needed to complement investments in seed variety development.
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.
Precise agricultural statistics are necessary to track productivity and design sound agricultural policies. Yet, in settings where intercropping is prevalent, even crop yield can be challenging to measure. In a systematic survey of the literature on crop yield in low-income settings, we find that scholars specify how they estimate the yield denominator in under 10% of cases. Using household survey data from Tanzania, we consider four alternative methods of allocating land area on plots that contain multiple crops, and explore the implications of this measurement decision for analyses of maize and rice yield. We find that 64% of cultivated plots contain more than one crop, and average yield estimates vary with different methods of calculating area planted. This pattern is more pronounced for maize, which is more likely than rice to share a plot with other crops. The choice among area methods influences which of these two staple crops is found to be more calorie-productive per ha, as well as the extent to which fertilizer is expected to be profitable for maize production. Given that construction decisions can influence the results of analysis, we conclude that the literature would benefit from greater clarity regarding how yield is measured across studies.
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 brief, we report on measures of economic growth, poverty and agricultural activity in Ethiopia. For each category of measure, we first describe different measurement approaches and present available time series data on selected indicators. We then use data from the sources listed below to discuss associations within and between these categories between 1994 and 2017.
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.
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.
In Tanzania, agriculture represents approximately 50 percent of GDP, 80 percent of rural employment, and over 50 percent of the foreign exchange earnings. Yet poor soil fertility and resulting low productivity contribute to low economic growth and widespread poverty. Chemical fertilizer has the potential to contribute to crop yield increases. Yet high prices and weaknesses in the fertilizer market keep fertilizer use low. This literature review examines the history of government interventions that have intended to increase access to fertilizers, and reviews current policies, market structure, and challenges that contribute to the present conditions. We find that despite numerous strategies over the last fifty years, from heavy government involvement to liberalization, major weaknesses in Tanzania’s fertilizer market prevent efficient use of fertilizer. High transportation costs, low knowledge level of farmers and agrodealers, unavailability of improved seed, and limited access to credit all contribute to the market’s problems. The government’s current framework, the Tanzania Agriculture Input Partnership (TAIP), acknowledges this interconnectedness by targeting multiple components of the market. This model could help Tanzania tailor solutions relevant to specific road, soil, and market conditions of different areas of the country, contributing to enhanced food security and economic growth.
Governments in Sub-Saharan Africa have often intervened in the fertilizer sector to promote more optimal levels of fertilizer use. Many West African nations, in particular, have inherited a legacy of government involvement, stemming from French colonial policies that encouraged state participation in the agricultural sector. Senegal's colonial past has influenced much of its present economy, from its principal export crop (peanuts) to its major food import (rice). The colonial legacy includes a relatively high degree of urbanization; limited domestic industrial capacity; institutions, policies, and agricultural networks focused on supporting a single export crop; and a history of state intervention into markets. After government intervention in the 1960s and 1970s, followed by a period of liberalization in the 1980s and 1990s, Senegal is again defining its agricultural policy. This literature review examines the state of agriculture in Senegal and the history of Senegalese agricultural policy in order to understand past and current trends in fertilizer usage. We find that Senegal continues to experience a high level of food price fluctuations as it imports increasing amounts of rice to cover its food deficit. Increased use of fertilizer, along with irrigation technology may help improve rice production and increase food security. To achieve this goal, the Government of Senegal (GoS) has embarked on several initiatives, notably the Agro-Silvo-Pastoral Law (LOASP) and the Grande Offensive Agricole pour la Nourriture et l’Abondance (GOANA), employing subsidies to increase fertilizer demand and making food sovereignty a national priority. In the coming years, GoS will need to determine what role the government should play in the agricultural sector, and what level of intervention can be sustained in the long-term.
Nigeria’s experience with fertilizer subsidy programs has been different than that of other countries in Sub-Saharan Africa. Nigeria is one of the only African countries capable of producing fertilizer domestically. But Nigeria is also large and densely populated. This makes national agricultural policy difficult due to logistical problems with implementation and the unique fertilizer needs of the various agro-ecological zones. This research brief discusses the effects of Nigeria’s input subsidy programs on maize production and fertilizer consumption. It focuses on the years 2000 to 2007, but also includes a discussion of Nigeria’s subsidy history from the early 1970s to 2009. Researchers have had difficulty studying Nigeria’s subsidy schemes due to a lack of data. In spite of decades of authoritarian, centralized leadership, Nigeria’s states have significant power to implement their own subsidies. This complicates any evaluation of a program’s effectiveness, in part due to the variety of subsidies at any given time, as well as inconsistent accounting practices.