Research Topics

EPAR Technical Report #354
Publication Date: 11/29/2018
Type: Research Brief
Abstract

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.

EPAR Technical Report #355 and EPAR Research Briefs #355A & #355B & #355C
Publication Date: 06/15/2018
Type: Literature Review
Abstract

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.

EPAR Technical Report #310
Publication Date: 11/20/2015
Type: Literature Review
Abstract

Cereal yield variability is influenced by initial conditions such as suitability of the farming system for cereal cultivation, current production quantities and yields, and zone-specific potential yields limited by water availability. However, exogenous factors such as national policies, climate, and international market conditions also impact farm-level yields directly or provide incentives or disincentives for farmers to intensify production. We conduct a selective literature review of policy-related drivers of maize yields in Ethiopia, Kenya, Malawi, Rwanda, Tanzania, and Uganda and pair the findings with FAOSTAT data on yield and productivity. This report presents our cumulative findings along with contextual evidence of the hypothesized drivers behind maize yield trends over the past 20 years for the focus countries.

EPAR Technical Report #303
Publication Date: 08/10/2015
Type: Data Analysis
Abstract

Common estimates of agricultural productivity rely upon crude measures of crop yield, typically defined as the weight harvested of a crop divided by the area harvested. But this common yield measure poorly reflects performance among farm systems combining multiple crops in one area (e.g., intercropping), and also ignores the possibility that farmers might lose crop area between planting and harvest (e.g., partial crop failure). Drawing on detailed plot-level data from Tanzania’s National Panel Survey, our research contrasts measures of smallholder productivity using production per hectare harvested and production per hectare planted.

An initial analysis (Research Brief - Rice Productivity Measurement) looking at rice production finds that yield by area planted differs significantly from yield by area harvested, particularly for smaller farms and female-headed households. OLS regression further reveals different demographic and management-related drivers of variability in yield gains – and thus different implications for policy and development interventions – depending on the yield measurement used. Findings suggest a need to better specify “yield” to more effectively guide agricultural development efforts.

 

EPAR Research Brief #312
Publication Date: 07/30/2015
Type: Literature Review
Abstract

This brief reviews the evidence of realized yield gains by smallholder farmers attributable to the use of high-quality seed and/or improved seed varieties. Our analysis suggests that in most cases, use of improved varieties and/or quality seed is associated with modest yield increases.  In the sample of 395 trials reviewed, positive yield changes accompanied the use of improved variety or quality seed, on average, in 10 out of 12 crops, with rice and cassava as the two exceptions.

EPAR Technical Report #245
Publication Date: 04/10/2015
Type: Data Analysis
Abstract

A farmer’s decision of how much land to dedicate to each crop reflects their farming options at the extensive and intensive margins. The extensive margin represents the total amount of agricultural land area that a farmer has available in a given year (referred to interchangeably as ‘farm size’ or ‘agricultural land’). A farmer increases land use on the extensive margin by planting on new agricultural land. The intensive margin represents area planted of crops as a proportion of total farm size. A farmer increases the intensive margin by increasing output within a fixed area. This analysis examines cropping patterns for households in Tanzania between 2008 and 2010 using data from the Tanzania National Panel Survey (TZNPS).  This brief describes changes in farm size, total area planted, and area planted of select annual crops to highlight the dynamic nature of farmer’s cropping choices for a sample population of 2,246 agricultural households that reported having any agricultural land in 2008 or 2010. Throughout the brief, we present summary statistics at the national level and compare them with household-level data to show how results vary depending on how the sub-population is defined and how average measures can mask household level changes. We analyze these questions in the context of smallholders (defined as households with total agricultural land area as less than two hectares) and farming systems.  

EPAR Research Brief #228
Publication Date: 04/18/2014
Type: Literature Review
Abstract

Cassava (Manihot esculenta Crantz) is a widely-grown staple food in the tropical and subtropical regions of Africa, Asia, and Latin America. In this brief we examine the environmental constraints to, and impacts of, smallholder cassava production systems in Sub-Saharan Africa (SSA) and South Asia (SA), noting where the analysis applies to only one of these regions. We highlight crop-environment interactions at three stages of the cassava value chain: pre-production (e.g., land clearing), production (e.g., soil, water, and input use), and post-production (e.g., crop storage). At each stage we emphasize environmental constraints on production (poor soil quality, water scarcity, crop pests, etc.) and also environmental impacts of crop production (e.g., soil erosion, water depletion and pesticide contamination). We then highlight good practices for overcoming environmental constraints and minimizing environmental impacts in smallholder cassava production systems. Evidence on environmental issues in smallholder cassava production is relatively thin, and unevenly distributed across regions. The literature on cassava in South Asian smallholder systems is limited, reflecting a crop of secondary importance (though it is widely found elsewhere in Asia such as South East Asia), in comparison to cassava in much of SSA. The majority of the research summarized in this brief is from SSA. The last row of Table 1 summarizes good practices currently identified in the literature. However, the appropriate strategy in a given situation will vary widely based on contextual factors, such as local environmental conditions, market access, cultural preferences, production practices and the policy environment.

EPAR Technical Report #254
Publication Date: 03/20/2014
Type: Literature Review
Abstract

This overview introduces a series of EPAR briefs in the Agriculture-Environment Series that examine crop-environment interactions for a range of crops in smallholder food production systems in Sub-Saharan Africa (SSA) and South Asia (SA). The briefs cover the following important food crops in those regions; rice (#208), maize (#218), sorghum/millets (#213), sweet potato/yam (#225), and cassava (#228).

Drawing on the academic literature and the field expertise of crop scientists, these briefs highlight crop-environment interactions at three stages of the crop value chain: pre-production (e.g., land clearing and tilling), production (such as water, nutrient and other input use), and post-production (e.g., waste disposal and crop storage). At each stage we emphasize environmental constraints on crop yields (including poor soils, water scarcity, crop pests) and impacts of crop production on the environment (such as soil erosion, water depletion and pest resistance). We then highlight best practices from the literature and from expert experience for minimizing negative environmental impacts in smallholder crop production systems.

This overview (along with the accompanying detailed crop briefs) seeks to provide a framework for stimulating across-crop discussions and informed debates on the full range of crop-environment interactions in agricultural development initiatives.

A paper based on this research series was published in Food Security in August 2015.

EPAR Research Brief #242
Publication Date: 01/08/2014
Type: Data Analysis
Abstract

The purpose of this analysis is to provide a measure of marketable surplus of maize in Tanzania. We proxy marketable surplus with national-level estimates of total maize sold, presumably the surplus for maize producing and consuming households. We also provide national level estimates of total maize produced and estimate “average prices” for Tanzania which allows this quantity to be expressed as an estimate of the value of marketable surplus. The analysis uses the Tanzanian National Panel Survey (TNPS) LSMS – ISA which is a nationally representative panel survey, for the years 2008/2009 and 2010/2011. A spreadsheet provides our estimates for different subsets of the sample and using different approaches to data cleaning and weighting. The total number of households for Tanzania was estimated with linear extrapolation based on the Tanzanian National Bureau of Statistics for the years 2002 and 2012. The weighted proportions of maize-producing and maize-selling households were multiplied to the national estimate of total households. This estimate of total Tanzanian maize-selling and maize-producing households was then multiplied by the average amount sold and by the average amount produced respectively to obtain national level estimates of total maize sold and total maize produced in 2009 and 2011.