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.
Cereals and pulses are important food and cash crops for farmers and rural households in Ethiopia. Despite the economic and food security importance of these crops, data and opinion suggest a yield gap: actual smallholder farm yields do not achieve estimated potential yields for wheat, sorghum, maize, lentils and peas. Furthermore, cereal prices in Ethiopia fall between import and export parity prices, limiting their international trading prospects. Although there are significant wheat imports, these reflect the influx of food aid, rather than competitive trade on the international market. The purpose of this brief is to estimate yield gaps in important Ethiopian crops in order to identify potential areas for productivity gains. We find that wheat, sorghum and maize all exhibit the potential for yield gains to increase domestic food availability. Additionally, all three crops experienced significant spikes in yield in the 2006 season. Further investigation into the climate conditions and policy in place that year may generate potential strategies to increase future yields. Analysis of Ethiopian lentil and pea yields suggest that productivity gains may be possible to increase food availability. Limited access to improved technologies appears to be the main constraint to pulse productivity in Ethiopia. Opportunities to increase lentil and pea yields appear to exist through increasing cultivation of improved varieties.
EPAR’s Poultry Markets in West Africa series provides an overview of poultry market trends across West Africa and compares the opportunities for poultry sector development in Benin, Burkina Faso, Côte d’Ivoire, Ghana, Mali, Niger, Nigeria, Senegal and Sierra Leone. The briefs in this series provide detailed country-specific poultry market analyses. The primary resources for these analyses included many reports prepared in response to the avian influenza epidemic, which may explain some of the emphasis on the importance of biosecurity in the available literature. We find that the West African poultry sector faces high production costs, safety concerns due to lack of sanitary controls, and technical constraints in processing and marketing. In addition to biological issues, the lack of breeders, marketing, and processing technology present technical constraints to poultry sector growth.
This report provides an overview of poultry market trends in Benin as compared to the wider West African region. In Benin, live chickens, hens, poultry meat, and eggs for consumption are subject to the 20 percent Common External Tariff (CET), which facilitates an influx of cheap poultry imports from the European Union (EU). Live turkeys and other poultry, reproducers, and hatching eggs are subject to a 5 percent tariff. In the late 1990s, Benin experienced an influx of cheap poultry products primarily from the EU. By 2002, annual poultry imports reached approximately 24,000 tons, more than the poultry imports of any other country in West Africa. In 2004 and 2005, Benin banned imports of poultry and poultry by-products from countries affected by avian influenza. Current information about the poultry industry in Benin is limited. The primary sources for this analysis are a FAO poultry sector review from 2006, a poultry sector project report from the New Partnership for African Development (NEPAD), and a 2006 assessment by the Benin Ministry of Agriculture, Livestock, and Fishing. We find that the poultry sector plays an important economic, social and cultural role in Benin. Poultry and egg production is a major contributor to the agricultural sector and is an important source of nutrition and income for Beninese households. The poultry sector in Benin has the potential to improve the nutritional wellbeing and income security of a large percentage of the population. Traditional smallholders produce the majority of poultry products domestically; however, current production is limited due to low productivity, poor biosecurity, and lack of inputs. We find that a reduction of foreign imports and greater institutional support for the industry may help domestic producers reach their potential.
This report provides an overview of poultry market trends in Sierra Leone as compared to the wider West African region. Sierra Leone did not adopt the Common External Tariff (CET) until 2005, however 2004 tariff rates were already on par with official CET rates. The tariff for live chickens, hens, poultry meat and eggs for consumption remains at 20 percent, which facilitates an influx of cheap poultry imports from Europe. Live turkeys and eggs for hatching are subject to a 5 percent tariff. There is little public information available regarding poultry production in Sierra Leone. The primary sources for this analysis are Government of Sierra Leone documents responding to the avian influenza epidemic in the West African region. This report provides a brief overview of consumption and consumer preferences, domestic production, trade, the political environment, and opportunities for future poultry development in Sierra Leone. Because of the small amount of information regarding poultry production in Sierra Leone, we find that further information is necessary to understand the scope of opportunity for poultry market development.
This report provides an overview of poultry market trends in Côte d’Ivoire as compared to the wider West African region. Côte d’Ivoire experienced an influx of cheap poultry products between 2000 and 2005, contributing to a significant increase in poultry consumption during those years. In 2005, Côte d’Ivoire banned imports from countries affected by avian influenza and increased taxes on all other imported poultry. The primary sources for this analysis are the FAO-Emergency Centre for Transboundary Animal Diseases (ECTAD) poultry sector review from 2008 and the information provided by the Interprofession Avicole Ivoirienne (IPRAVI) on their website. IPRAVI is the umbrella organization overseeing Côte d’Ivoire’s poultry sector. We find that smallholders produce the majority of poultry in Côte d’Ivoire. Common production practices lead to low productivity, poor bio-security, and limited distribution opportunities. Since the influx of cheap poultry imports between 2000 and 2005 and the import ban of 2005, overall consumption of poultry has declined along with imports, suggesting significant market potential for domestic poultry products. We provide specific areas for interventions to improve poultry productivity, based upon evidence from the African Development Bank and the FAO. Furthermore, we examine analyses from the FAO that suggest there is sufficient infrastructural capacity to expand the poultry sector and increase smallholder productivity.