Research Topics

EPAR Technical Report #363
Publication Date: 02/10/2019
Type: Data Analysis
Abstract

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.

EPAR TECHNICAL REPORT #362
Publication Date: 01/16/2019
Type: Data Analysis
Abstract

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:
    • Ethiopia Socioeconomic Survey (ESS), Wave 3 (2015-16)
  • Kenya:
    • Kenya FinScope, Wave 4 (2015)
    • Kenya FII, Wave 4 (2016)
  • Nigeria
    • Nigeria FII, Wave 4 (2016)
  • Rwanda:
    • Rwanda FII, Wave 4 (2016)
  • Tanzania:
    • Tanzania National Panel Survey (TNPS), Wave 4 (2014-15)
    • Tanzania FinScope, Wave 4 (2017)
    • Tanzania FII, Wave 4 (2016)
  • Uganda:
    • 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:

Sub-Populations

  • 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

Characteristics
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.

EPAR Research Brief #167
Publication Date: 10/07/2011
Type: Data Analysis
Abstract

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.

EPAR Technical Report #163
Publication Date: 10/03/2011
Type: Data Analysis
Abstract

This is "Section F" 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 soil characteristics and soil management, of input use by crop and gender at the plot and household levels, and of improved variety seeds and water management.

EPAR Technical Report #161
Publication Date: 10/01/2011
Type: Data Analysis
Abstract

This is "Section D" 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 basic farm characteristics, land and labor productivity, crop sales, yield measures, intercropping, and pre- and post-harvest losses, including comparisons by gender of household head and by zone.

EPAR Research Brief #137
Publication Date: 03/30/2011
Type: Research Brief
Abstract

This brief presents selected material from the Fourth African Agricultural Markets Program (AAMP) policy symposium, Agricultural Risks Management in Africa: Taking Stock of What Has and Hasn’t Worked, organized by the Alliance for Commodity Trade in Eastern and Southern Africa and the Common Market for Eastern and Southern Africa that took place in Lilongwe, Malawi, September 6-10, 2010.  We draw almost exclusively from Rashid and Jayne’s summary, “Risk Management in African Agriculture: A review of experiences.”  This article summarizes across the background papers, with major findings grouped into three broad categories: cross cutting, government-led policies, and modern instruments.

EPAR Technical Report #133
Publication Date: 03/07/2011
Type: Literature Review
Abstract

This report provides a summary of Tanzania’s agriculture sector, crop production, agricultural productivity and yield levels, risks, and policies and reforms. This review uses resources found on the University of Washington Libraries system and Google Scholar, as well as the websites of the Government of Tanzania, FAO, and World Bank. We find that Tanzanian agriculture workers comprise 80% of the population and farm a wide variety of crops, ranging from staple crops such as maize, cassava, and rice, to export crops such as coffee, cotton, tobacco, tea, and sugar. Smallholder farmers face increasing risks from climate change, pests, diseases, and land degradation, among others. While they have some resources available, such as farmer groups and limited access to ICTs, they lack important resources such as credit and inputs. We find that Tanzania’s land tenure and agriculture policies may further complicate the lives of smallholders through increased taxes and administrative processes. Through the Agricultural Sector Development Programme (ASDP) reform, however, the Government of Tanzania hopes to empower farmers and improve service delivery.  

EPAR Research Brief #50
Publication Date: 12/29/2009
Type: Research Brief
Abstract

EPAR’s Political Economy of Fertilizer Policy series provides a history of government intervention in the fertilizer markets of eight Sub-Saharan African countries: Côte d’Ivoire, Ghana, Kenya, Malawi, Mozambique, Nigeria, Senegal, and Tanzania. The briefs focus on details of present and past voucher programs, input subsidies, tariffs in the fertilizer sector, and the political context of these policies. The briefs illustrate these policies’ effect on key domestic crops and focus on the strengths and weaknesses of current market structure. Fertilizer policy in SSA has been extremely dynamic over the last fifty years, swinging from enormous levels of intervention in the 1960s and 70s to liberalization of markets of the 1980s and 1990s. More recently, intervention has become more moderate, focusing on “market smart” subsidies and support. This executive summary highlights key findings and common themes from the series.

EPAR Research Brief #52
Publication Date: 11/09/2009
Type: Literature Review
Abstract

Ecological farming and conventional farming are two approaches to producing food. The term “ecological farming” describes a range of agricultural systems that seek to provide food and environmental and social benefits by using natural processes and local resources rather than off-farm, purchased inputs (commonly referred to as “external inputs”). Recent debate about the merits of ecological farming over conventional methods has centered on each system’s ability to increase production in the context of numerous and varied biophysical and social constraints. A review of the literature suggests that ecological farming can offer some benefits to smallholder farmers, but that specific approaches must be tailored to local climate and soil conditions and availability of labor, training, and organic inputs.

EPAR Research Brief #78
Publication Date: 11/06/2009
Type: Literature Review
Abstract

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.