ex ante Technology Potential Assessment

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WorkingPaperDraft
Ex-Ante Impact Assessment of Improved
Agricultural Technology Adoption:
Country Case Studies in Senegal, Uganda,
and Namibia
Jawoo Koo (IFPRI; j.koo@cgiar.org)
Kodjo Kondo (CORAF/WECARD; k.kondo@coraf.org)
Moses Odeke (ASARECA; modeke@asareca.org)
Baitsi Podisi (CCARDESA; bpodisi@ccardesa.org)
Ulrike Wood-Sichra (IFPRI; u.wood-sichra@cgiar.org)
Cindy Cox (IFPRI; c.cox@cgiar.org)
Liangzhi You (IFPRI; l.you@cgiar.org)
EXECUTIVE SUMMARY
In partnership with Sub-Regional Organizations in Africa (ASARECA, CORAF/WECARD, and
CCARDESA), IFPRI’s Technology Platform team led an ex-ante impact assessment study on the
potential of scaling-up adoption of selected improved agricultural technologies in three
countries. Combining spatially-explicit technology adoption data collected in the target areas
with their estimated adoption scenarios in a partial-equilibrium, multi-market economic surplus
modeling framework, this study systemically assesses the potential economic impacts on the
country’s investment on the scaling-up of technology adoptions in the suitable areas and their
potential spillover effects. Preliminary analysis results indicated that, even under restricted
assumptions with the low-level adoption scenario, overall economic benefits were found to be
attractive for investments. The overall Net Present Value (NPV) of scaling-up technologies by
2025 was estimated to reach about 250 million USD for NERICA in Senegal, 20 million USD for
the improved small ruminants breeding technology in Namibia, and 5 million USD for QPM in
Uganda. This result indicates the need for additional efforts to scale-up the technologies. Overall
analysis will be further refined with more detailed community-level data to be collected in 2017.
Through the collaborative research process, SROs’ analytical capacity on the use of modeling
tools in the monitoring and evaluation was further strengthened.

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INTRODUCTION
In the bid to achieve the targets of the Malabo Declaration, which includes ambitious food security and
nutrition goals in Africa to be achieved by 2025, there is an urgent need of in-country technical capacity to
contextualize the continent-wide goals at the country-level, analyze the country’s capacity to reach the
targets, prioritize agricultural investment options, and review the national agricultural investment plans
(NAIPs) accordingly. The outcome of self-assessment process with NAIPs will further support the planning of
investment in government programs and projects that will accelerate agriculture transformation towards
Malabo, especially the access to productivity and competitiveness-enhancing technologies from the national,
regional and international systems of agricultural innovation. The outcome will moreover inform monitoring,
evaluation, and iterative learning.
IFPRI’s Technology Platform program provides technical assistance to strategic partners in Africa to improve
agricultural data collection and sharing, increase evidence and information, and create an environment to
enable better strategic investment planning to achieve food security targets and goals at the country and
regional levels. Being implemented as a high-level, Strategic Innovation Platform, in collaboration with
technical capacities at SROs, the program team provides policy and investment decision makers with data
analytics and decision-supporting tools to strengthen their technical capacity for self-assessment, aiming to
enhance the effectiveness of agricultural technology investments.
To strengthen in-region technical self-assessment capacity for better targeting of agricultural technology
investments, IFPRI’s Technology Platform team led an ex-ante impact assessment study on the potential
adoption of selected improved agricultural technologies in three countries: NERICA rice varieties in Senegal
(led by CORAF/WECARD), improved small ruminants breeding technology in Namibia (led by CCARDESA), and
Quality Protein Maize varieties in Uganda (led by ASARECA). Combining spatially-explicit technology adoption
data collected in the target areas with their estimated adoption scenarios in a partial-equilibrium, multi-
market economic surplus modeling framework, this study systemically assesses the potential economic
impacts on the country’s investment on the scaling-up of technology adoptions in the suitable areas and their
potential spillover effects.
TECHNOLOGY PROFILES
NERICA Rice Varieties in Senegal
New Rice for Africa (NERICA) refers to a group of modern rice varieties developed from interspecific crosses
between Africa rice (O. glaberrima) and Asia rice (O. sativa), a technique originated by crop breeders at the
Africa Rice Center (AfricaRice). NERICA varieties combine the best traits of both parents. These include high
yield potential from the Asian parent and the ability to thrive in harsh environments from the African parent.
During the period 2000 – 2006, AfricaRice released the original 18 upland and 60 lowland NERICA rice
varieties. NEARICAs are generated through conventional breeding and are not, therefore, considered
genetically modified organisms, although advances in biotechnology allow breeders to ‘rescue’ offspring from
crosses that are otherwise difficult between two closely related species, nor are they considered ‘hybrids’
where genetic material (yield) erodes rapidly after each generation of seed.
Farmers grow NERICA rice like traditional rice varieties, either in upland or lowland ecologies, although the
growing duration is shorter, and may integrate the technology into existing farming practices, such as in
rotation or intercropped with other varieties and crops. Compared to traditional rice varieties, NERICAs have
greater yield potential and respond strongly to the use of inputs such as fertilizers. As with any rice system,

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considerations of land selection and preparation, cropping calendar, planting depth and density, weed
management, and best-practices in soil fertility and pest control are all vital to optimize yields and depend on
local conditions and practices. Research has suggested that a positive effect of NERICA can only be realized
when its adoption is combined with good soil fertility management practices, such as through the use of
appropriate crop rotations. NERICA varieties planted in poorer soils that are limited in essential nutrients may
require the application of (expensive) chemical fertilizers to substantially boost yields over traditional rice
varieties. Varieties may not always be well suitable for farmers’ needs, cultural or ceremonial preferences,
and conditions. Moreover, ineffective NERICA dissemination programs, such as shortages of NERICA seeds
and ineffective extension services, constrain its adoption.
NERICA is targeted to smallholder farmers who depend on rice for food security in the rice-growing regions of
SSA. Many of these growers are women. NERICAs rely on a process of dissemination at the supply side of the
value chain. Seed may be supplied by rice farmers as part of a community-based seed production system in
cooperation with certain NGOs and government extension. NERICAs may also rely on other inputs at the
supply side, such as chemical fertilizers. Like all rice varieties, NERICA rice requires proper post-harvest
handling to avoid losses and functioning markets in cases where production surpasses consumption needs of
the farm household. Farmers may decide to adopt the technology where rice cultivation is suitable and
consumption patterns are high. A large portion of these famers are women. Major NERICA uptake has been
promoted through participatory variety selection in which farmers select varieties based on their
preferences. However, farmers who do not have access to NERICA seed and effective extension services,
chemical fertilizers, or knowledge of good soil fertility practices are less likely to adopt NERICA varieties. As a
result, research suggests they are missing such benefits as increases in per capita income and better food
security.
NERICA rice varieties have been adopted in many countries along the rice belt of West and Central Africa and
in East Africa. The first NERICA varieties were introduced to sub-Saharan Africa in 1996 and varietal testing in
Senegal began in 2006. The original 18 NERICA varieties were adapted to upland rice ecology in SSA where
smallholder farmers lack the means to irrigate or apply chemical fertilizers. Later, 60 lowland NERICA
varieties (NERICA-L) were developed and introduced to farmers, adapted for both rain-fed and irrigated
lowlands ecologies. In Senegal, approximately 90,000 hectares are under rice cultivation, with most in
lowland ecologies. Rice production in Senegal focuses on irrigated fields in the Senegal River Valley near the
Mauritanian border. In the south, however, rice farmers have relied on rainfed agriculture and traditional
paddies. NERICA adoption gives farmers in the south access to high yielding varieties and broadens the vast
upland fields to intensified rice production without investing in irrigation infrastructure. In 2010 USAID
launched a project introducing NERICA varieties to farmers in the southern region of Senegal.
NERICA is suitable for rainfed upland and lowland ecologies where rice cultivation is suitable but low-yielding
varieties are constraining food security goals. In Senegal, farmers in the southern region outside the Senegal
River Valley would likely benefit most from NERICA adoption. In 2005, the national rice varietal release
committee in Senegal officially released ‘Sahel’ varieties for use by irrigated rice farmers in the Senegal River
Valley. They have been widely adopted by farmers in the region. The technology is a good fit for the
intensification of rice, and is particularly valuable for broadening production potential in rainfed upland
ecologies, as well as the south region of Senegal. NERICAs provide smallholder farmers in the rice growing
regions of SSA access to high-yielding rice varieties that outperform or supplement traditional and culturally-
important rice varieties. NERICAs can yield four times the amount of rice per hectare compared to traditional
varieties and have a shorter growth cycle. Several varieties possess early vigor during the vegetative growth

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phase which may help compete against weeds. A number of them are resistant to drought and African pests
and diseases, such as rice blast, rice stemborers and termites. NERICAs also have higher protein content and
amino acid balance than most imported rice varieties. In places like West Africa where NERICAs have been
widely adopted, research suggests lessening dependency on rice imports and greater food security among
rice growing households. In Senegal rice is a staple crop and it requires more water than other traditional
grains such as millet and sorghum. Because of this, most rice production focuses on the irrigated fields in the
Senegal River Valley near the Mauritanian border. In the south, farmers have relied on rain for irrigation or
planted rice in lowlands similar to irrigated paddy. NERICA adoption in the south of Senegal increases
production potential and rice diversity in the region, particularity in upland ecologies.
Some stakeholders worry that NERICAs will cause the displacement of traditional rice varieties, thereby
annihilating a rich pool of traditional, cultural, and time-tested genetic resources. Additionally, farmers may
not realize the full potential of NERICA rice if best practices and good soil management are not adopted
alongside. According to USAID, NERICA rice gives farmers in the south of Senegal “a chance to sharply
increase their traditional lowland yields. More importantly, NERICA opens the vast upland fields to high-
yielding rice production without investing in irrigation infrastructure.”
Improved breeding of small ruminants in Namibia
The rearing of small ruminants (i.e. sheep and goats) is an important agricultural activity in Namibia in the
westend and southern parts of the country which are drier compared to the north region (Joint Presidential
Committee, 2008). Namibia is a surplus producer of mutton and lamb and has been exporting live sheep and
mutton mainly to South Africa and goat production is more favoured in the Northern communal areas of
Namibia. Despite the under-explored opportunity, the sheep and goat subsector is hampered by low
productivity. The most important traits contributing to economic production of livestock under Namibia’s
tough ranching conditions are: pre-weaning growth rate, post-weaning growth rate, feed conversion ratio
(efficiency of feed use), carcass composition and quality, reproductive ability and a low mortality rate. Higher
production can be addressed by increasing the lambing percentage, lowering the mortality rate and
increasing the actual weight produced by farming with the appropriate breeds and through good production
practices.
The important traits of smallstock (fertility, meat conformation, breed characteristics) can be improved
through adopting improved breeding practices by selecting and keeping the best lambs/kids from the best
ewes and using animals of genetic quality as parents and disposing animals with undesirable performance.
Besides the Dorper sheep breed and its crosses, there are indigenous breeds of sheep and goats which have
potential to contribute to local meat production with improved management and selective breeding.
Superior performance of small ruminant flocks or populations over time can arise from genetic improvement
through the use of genetically superior animals coupled with improved health management and feeding
conditions. This improvement therefore entails the use of a suite of breeding technologies, innovations and
management practices (TIMPs). The improvement is gradual and takes place over time to bring about
production efficiency but this requires: i) tailoring the interventions for a given production system based on
the relative importance of the different constraints in the system; (ii) definition of the selected breeding
objectives with the involvement of farmers. (iii) using accurate methods of identifying superior genotypes
and; (iv) having practical mechanisms of allowing the superior genetic material to be used to disseminate the
superior qualities within the national flocks.

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The main limitations of a wider application of selective breeding in small ruminants especially in communal
areas is the difficulties in keeping animal records required for objective genetic assessment of animals. The
control of the mating of animals is a challenge because animals easily mix in the grazing areas. The
implementation of breed improvements through employment of selection requires community cooperation
and technical support. The easier route is often to effect improvement through crossbreeding via the use of
suitable exotic sires. However, indiscriminate cross breeding can erode the well adapted genotypes from
unplanned crossbreeding where the use of indigenous breeds improved through selection could have been a
better alternative. The indigenous breeds have also not been well characterized to be harnessed in
meaningful strategic breeding programmes. Nonetheless, even the most crude selection processes can add
value to the genetic improvement of the national flocks.
Livestock breeders and geneticists use selection or cross breeding to produce genetically superior animals, to
meet defined needs. The Government Agencies typically work in collaboration with national breeder
associations to promote sustainability of small ruminant breeding programs. Genetically superior and hardy
breeds help farmers adapt to climate change from the rearing of breeds that can cope with the hot and dry
conditions while attaining superior meat yields compared to the unimproved genotypes. International and
government-involved efforts have invested in national breeding programs to improve the genetic quality of
the national flock. Goats are predominantly located in the northern communal areas of Namibia where most
of the livestock are found. About 60% of goats in Namibia belong to indigenous breeds variously called North
Western, North Central, Caprivi or Kavango breeds and are owned mainly by smallholder farmers.
Commercial farmers who keep their animals in fenced ranches have a better means of controlling their
breeding interventions. During the last 30 years, considerable progress has been made globally in sheep and
goat embryo technologies, especially in the fields of estrous synchronization, superovulation and in vitro
embryo production. However, the costs and inefficiencies of the system restricts its use to special situations.
While their applications are widespread in cattle, ARTs are almost restricted to estrous synchronization and
artificial insemination in small ruminants such as sheep and goats. Thereby making their likely use by small
holder farmers in Namibia very limited and not cost-effective.
The main limitations of a wider application of ARTs in small ruminants are the naturally occurring anestrous
period, the variability of response to super-ovulatory treatments, the fertilization failure and the need of
surgery for collection and transfer of gametes and embryos. Nonetheless, Artificial Insemination helps
prevent the spread of infectious or contagious diseases and rapidly increases gains in genetic development
and production. ARTs also enable breeding between animals in different geographic locations. Genetically
improved goats can help farmers adapt to climate change by availing improved livestock that have a higher
rate of productivity and are more resistant to drought compared to the unselected local breeds. The genetic
improvement of livestock offers advantages of increased adaptability and resilience to specific environmental
conditions, superior performance in terms of health and vigor, and better quality nutritious food products (in
short, more food per goat and per unit of land). The genetic improvement of goats is a worthwhile
investment using traditional livestock improvement approaches which require less investment than the use
of ARTs especially for communal farmers who are usually resources-constrained. Traditional selective
breeding interventions have a higher chance of success because of their simplicity and excellent cost/benefit,
especially where proven sires are used.
Compared to Multiple Ovulation Embryo Transfer, (MOET), estrous synchronization and artificial
insemination are the most commonly used assisted reproductive technologies (ARTs) used worldwide
because of their simplicity and excellent cost/benefit, especially when proven sires are used. Considerable

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progress has been made in sheep and goat embryo technologies, especially in the fields of estrous
synchronization, superovulation and in vitro embryo production. However, the costs and inefficiencies of the
system might restrict its use to special situations. While their applications are widespread in cattle, ARTs are
almost restricted to estrous synchronization and artificial insemination in small ruminants such as sheep and
goats. While the future of adoption of improved breeding practices by smallholder famers in Namibia may be
limited by access to infrastructure and extension support, goat improvement is a clear opportunity for
investment, since 1) smallholder famers own majority of goats and rely on local, indigenous breeds; 2) goats
are important for rural food security; 3) climate change is expected to increasingly become an important
abiotic stress to the current breeds in Namibia.
Quality Protein Maize varieties in Uganda
Quality protein maize (QPM) is the first biofortified crop ever developed by plant breeders. Biofortified crops,
bred for improved nutritional quality, can alleviate nutritional deficiencies if they are produced and
consumed in sufficient quantities. QPM was developed in the 1990s by the International Maize and Wheat
Improvement Center (CIMMYT) to help reduce human malnutrition in areas where protein deficiency is
prevalent and where maize is the major protein source in the diet. Normal maize lacks quality dietary protein
necessary for a balanced diet. Varieties of QPM have higher nutritional content by producing higher amounts
of two essential amino acids. QPM has superior agronomic traits and generally yields more grain compared to
most modern varieties of tropical maize.
QPM essentially looks and performs like normal maize and is produced using traditional breeding techniques.
Open-pollinated varieties (OPVs) and hybrid QPM have been released in at least 17 countries throughout SSA
across different agroecological zones. Farmers can save seed from OPVs without yield consequences,
although contamination can occur if cross pollination occurs with non-QPM plants. The Obatanpa variety has
been released in numerous countries of Africa, including Uganda where ‘Nalongo’ (the mother of twins,
named for the twin benefits of yield and nutrition) is among the most popular maize varieties. QPM is visually
indistinguishable from normal maize. There is no way of assuring superior nutritional quality and as such, it
does not bring market premiums. Moreover, cross-pollination with conventional maize can quickly dilute the
QPM trait. These qualities have often deterred seed companies from marketing QPM altogether. Farmer
evaluation for agronomic performance is important for QPM adoption since nutritional benefits are virtually
invisible; as such, QPM may be a harder sell to a vast community of maize growers without visually attractive
characteristic’s that farmers prefer over other maize varieties.
Maize growers in SSA use QPM particularity where maize is a staple crop. Many maize farmers are women
who work in the fields and cook with the harvested grain. The seed dissemination process includes farmers,
processors, and consumers for QPM seed, grain and products. QPM has potential health benefits for young
children, pregnant and breastfeeding women, and the elderly, particularly in areas where maize consumption
is high. QPM has also been used in school feeding programs where QPM is promoted because of its nutritive
value. Research has suggested that farmers in project communities who participated in extension activities,
familiarity with QPM was high although understanding of nutritional value was lower. Factors that
significantly influenced adoption were farmers’ participation in extension activities, farmers’ agronomic and
post-harvest evaluation of QPM compared to conventional maize, and to a lesser extent their understanding
of the nutritional benefits. QPM is only intended for populations where maize is a staple crop, consumed in
large quantities, and where legumes and meat are inadequately available leading to dietary protein
deficiencies. QPM adoption is low where promotional activities have not penetrated and access to extension
services (and seed) are poor. In non-adoption maize growing communities where QPM could improve protein

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intake, populations are potentially failing to benefit from better nutritional outcomes, including incidences in
childhood stunting.
QPM varieties have been widely promoted throughout SSA in at least 17 countries for improving human
nutrition where maize is the staple food crop. Particular focus has been in the maize basket of Central and
Eastern Africa. QPM is grown is Ghana, Nigeria, and throughout Central and Eastern Africa, mainly for
household consumption and some animal feed. QPM was first released to maize growers in Uganda in 2000.
Ugandan farmers can plant QPM in most areas except in the most arid parts in the Northeast. QPM maize is
more likely to be adopted when farmers participate in extension services and evaluate agronomic
performance during variety selection, particularly in areas where there has been a substantial effort to
promote QPM and make quality seed available. Evaluation for agronomic performance has been found to be
more important than knowledge of nutritional benefits, although both are important considerations for
farmer adoption. QPM varieties are not adapted to extreme environments in Uganda where maize
production is constrained, such as the Karamoja region in the northeast. Moreover, QPM is not well suited
for regions in which populations do not rely on maize for caloric intake and food security. Benefits from QPM
investment are realized when the human population depends on maize dependent for the bulk of their
calories and lack supplementary proteins in their diets. The technology is similar to other single innovations
that promote improved varieties of maize. QPM is trickier, however, since nutritional benefits are harder to
sell compared to visually compelling agronomic traits that motivate farmer preference. This is why aggressive
promotional systems are necessary for QPM knowledge dissemination and uptake. Agronomic performance
and farmer participatory selection are also critical factors for large scale QPM adoption. If consumed in
enough quantities, QPM is a good technology for improving nutrition and health in countries where maize is
a staple crop. However, heavy investment in promotional activities, including farmer participatory varietal
selection, alongside adequate extension services and seed availability, are important factors for scaling.
Normal maize lacks lysine and tryptophan, two essential amino acids important for growth and health.
Overdependence on maize can lead to deficiency diseases where the body receives adequate calories but not
enough protein for healthy function. Chronic protein malnutrition is potentially life-threatening, found most
often in regions experiencing famine. Varieties of QPM produce at least double amounts of lysine and
tryptophan and potentially offer maize-based communities who suffer from lack of quality dietary protein
better nutrition. If care is not practiced while handing QPM seeds and fields, genetic material can quickly
erode, typically translating into lower yields. Since the QPM trait is not visible, without genetic testing
farmers have no way of knowing the nutritional quality of seed. Moreover, without market premiums for
QPM grain, national interest and investments in the technology, as well as farmer incentives, are more
challenging to garner. In one example, a meta-analysis of past studies from populations in which maize is the
major staple food crop, showed QPM benefits of increases in the rate of growth in weight and height in
infants and young children with mild to moderate undernutrition. QPM is an appropriate technology for
countries like Uganda where maize is a staple crop and consumed in large quantities, assuming meat and
legumes are not widely available to supplement dietary protein. Like normal maize varieties, QPM can be
grown in most areas of Uganda. Consideration of farmer preference and farmer participation in varietal
selection, robust seed dissemination systems, and QPM promotional and educational activities are critical for
scaling QPM. Improving dietary protein quality in vulnerable populations could greatly benefit human lives. A
meta-analysis of existing studies suggests a positive effect of QPM on growth of young children with mild to
moderate undernutrition from populations in which maize is a significant part of the diet. Nevertheless, well-
designed and statistically robust community-based assessments in target populations would help to fill a
major knowledge gap.

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MATERIALS AND METHODS
Representing Productivity Change in an Economic Framework
An economic approach to evaluating productivity change begins with the basic, commodity market model of
research benefits depicted in Figure 1: S0 represents the supply function before a research-induced technical
change, and D0 represents the demand function. The initial price and quantity are P0 and Q0. Suppose research
generates yield increasing or input saving technologies. These effects can be expressed as a per unit reduction
in production costs, K, that are modeled as a parallel shift down in the supply function to S1. This research-
induced supply shift leads to an increase in production and consumption to Q1 (ΔQ = Q1 - Q0), and the market
price falls to P1 (by ΔP = P0 - P1). Consumers are better off because R&D enables them to consume more of the
commodity at a lower price.
Figure 1 The basic supply-and-demand model of research benefits
Although they receive a lower price per unit, producers who adopt the new technology are better off, too,
because their unit costs have fallen by an amount, K per unit, that is more than the fall in price. The
consumer surplus measure of the consumer benefit is equal to area P0abP1, i.e. rectangle P0aeP1 (= PQ 0 )
plus triangle abe. The producer surplus measure of the producer gain is equal to area P1bcd in Figure 1, i.e.
rectangle P1ecd(=  PKQ 0 ) plus triangle bce. Total benefits are obtained as the sum of producer and
consumer benefits. As an approximation, the cost-saving per unit multiplied by the initial quantity, KQ0, is
often used. Thus the size of the market, as indexed by the initial quantity Q0, as well as the size of the
improved productivity savings in the per unit cost of production, K, are critical factors in estimating the
economic benefits from productivity change. Better estimates of K mean better estimates of the benefits
from technical change, and a better basis on which to allocate scarce investment resources (into research
and extension for example).
Price
P0
F
P1
Quantity/Year
S0
S1
D
0 Q0 Q1
a
b
c
I1
I0
d
K
Figure 1: The Basic Supply-and-Demand Model of Research Benefits

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Figure 1 is the basic static model for research evaluation. However, evaluations of the economic effects of
technical change involve procedures to account for the timing of streams of benefits and costs, since there
may be lengthy lag times between the initial investment in technology research, the regulatory approval
process in this case, the eventual adoption of research results, and the flow of research benefits. Figure 2
represents schematically the timing of flows of benefits and costs from a successful investment in developing
a new technology.1
The vertical axis represents the flow of benefits and costs in a particular year and the
horizontal axis represents years after the commencement of the R&D investment.
Figure 2: Time Profiles of Research Costs and Benefits
Initially, R&D projects involve expenditure without benefits so that, during the research lag and regulatory
process period, only R&D costs (negative benefits) are considered. After the initial research lag there may be
a further delay, a development lag of several years, involving field trials for testing, certification and approval
of the new technology or new variety. For biotechnology, there are usually long periods of regulatory
approval process. Even when a commercial product is available, there are further lags before the maximum
adoption of the new technology is achieved. The adoption lag may involve several years. Eventually, as
shown in Figure 2, the annual flow of net benefits from the adoption of the new technology becomes positive
(at least, for a profitable investment this is true). For biotechnology, seed is a regular cost even after the
technology is adopted. In most cases the flow of benefits will eventually decline as the new technology is
progressively abandoned when it becomes obsolete (e.g., as newer and better technologies evolve) or
depreciates (e.g., as pests evolve), or becomes uneconomic for some other reason. A complete evaluation of
a particular research investment must therefore take account of the dynamic relationships between
investments in research that lead (after some lags) to a stream of future benefits as shown in Figure 2.
The DREAM Approach
In their text on the principles and practices of research evaluation, Alston, Norton and Pardey (1995)
presented a model – DREAM (Dynamic Research Evaluation for Management) – for operationalizing the
concepts outlined in the preceding section. The DREAM approach is based upon the economic surplus
method, and was developed assuming the following conditions:
1 Many new technologies are not successful in the sense that they are never developed for commercial use or adopted in the
field. The figure refers to a new technology that is successful, and adopted.
($ per year)
5 10 15 20 25
Years
Annual Costs
( $ per year)
Regulatory process
Research Benefits
Gross Annual
Benefits
0 30
–
Research Costs
R&D Lag
Regulation Approval
Adoption Process

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• multiple regions
• producing a homogeneous product
• with linear supply and demand in each region
• with exogenous growth of supply and demand
• with a parallel (technology-induced) supply shift in one or more regions
• with consequent supply shifts in other regions (through the effects of trade and of technology
transfer)
• with a range of market-distorting policies
• with a research lag followed by an adoption curve up to a maximum
• with an eventual decline in adoption
The economic returns to investments in the improved agricultural technologies were estimated using the
dynamic research evaluation for management (DREAM) model (Alston et al., 1995; Wood et al., 2001). The
DREAM approach is based on the economic surplus method where research-induced supply triggers a
process of market-clearing adjustments in one or multiple markets that would affect the flow of final benefits
to producers and consumers (Alston et al., 1995). Linear equations are used to represent supply and demand
in each region with market clearing enforced by a set of quantity identities and price identities. It is a single-
commodity model without explicit representation of cross-commodity substitution effects in production and
consumption, but these aspects are represented implicitly by the elasticities of supply and demand for the
commodity being modeled. Basic region-specific data on quantity produced and consumed, producer and
consumer prices, elasticities of supply and demand, and exogenous growth in supply and demand are needed
to capture pre-adoption economic conditions. DREAM has been developed into a computer software package
(Wood et al., 2001). It has a menu-driven, user-friendly interface that hides the complex computation to
allow users to focus on methodology, data collection, and policy interpretation. Figures 3 and 4 show DREAM
data entry screens for scenario definition and for defining the adoption curve of new technology for a single
region. DREAM provides estimates of changes in production, consumption, trade, food prices, and economic
surplus for producers and consumers, as a consequence of changes in productivity (or price policies).
Figure 3: The DREAM Scenario Definition Screen

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Figure 4: The DREAM Adoption Screen
Baseline Data for DREAM Simulations
We used DREAM to estimate the economic benefits that would be derived from productivity increases for the
three case studies described above. These are NERICA rice varieties adoption in Senegal, improved breeding
of small ruminants in Namibia, and quality protein maize varieties in Uganda. The DREAM analysis takes the
form of a simulation through time as the productivity enhancing measures are disseminated and adopted and
their impacts felt over a larger area. The base period for the simulations varies from 2010 for Uganda and
Namibia, and 2013 for Senegal study, but the base period market values were the annual average values of
production, consumption and prices the 3-year averages around the baseline year, so as to minimize the
effects of short-term variability. Since there are long time lag for the biotechnology research, field trial, and
regulatory process, we take a long simulation period: from base year to 2025. Demand growth over the
simulation period was estimated on the basis of projected national population and national income growth
rates. In the simulation, exogenous production growth is assumed to be equal to demand growth to
maintain constant real price throughout the simulation period. In order to convert benefit streams from the
simulation to a single present value, a real discount rate of 10% was used.
In setting up the regions for DREAM simulations, we take account of the trade situation for each crop. Rice in
Senegal is traded globally. Therefore, the rest of world (ROW) is included to enable the interaction between
Senegal and the world market. For maize in Uganda and small ruminants in Namibia, they are only traded in
regional markets and so the regions, i.e. East Africa and Southern Africa are included. All regions were
represented by their respective total production and consumption and estimated average border prices. The
main source for these data is FAOSTAT (2016) though we consulted various other sources. We made efforts
to collect price elasticities and income elasticities from literature. Table 1 to 3 shows the major input data for
these 3 case studies.

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Region Supply Demand Price(1) Supply
Elasticity
Production
growth
Demand
Elasticity
Demand
Growth
1000 mt 1000 mt $/mt % %
NERICA rice areas 99.59 336.18 0.48 2.53 -0.85 2.53
Other rice areas 393.50 336.18 0.48 2.53 -0.85 2.53
Senegal Consumption 0.00 1,662.45 336.18 0.48 2.53 -0.85 2.53
ROW 723451.7 722282.3 278.66 0.48 2.53 -0.85 2.53
Region K shift R&D
lag
R&D
success
Adoption
lag
Adoption
max
% yrs % yrs %
NERICA rice areas 200 0 100 3 95
Other rice areas 20 0 100 3 30
Senegal Consumption 0 0 100 3 0
ROW 75 0 100 3 40
Table 1: Base data for DREAM simulations: rice in Senegal.
NERICA rice areas: Casamance olda, Sedhiou and Ziguinchor; South Sine Saloum (South Kaffrine and Kaolack). Other rice areas.
Rest of Senegal Rice Producing Regions- ROSRPR. Senegal Consumption = Total Rice Demand in Senegal. ROW = Difference
between demand and other consumption, and use international rice price: 278.66
Region Supply Demand Price
Supply
Elasticity
Production
growth
Demand
Elasticity
Demand
Growth
1000 mt 1000 mt $/mt % %
Central 468.87 483.12 141.67 0.38 3.39 -0.758 3.39
Eastern 885.09 543.51 141.67 0.38 3.39 -0.758 3.39
Northern 605.09 395.82 141.67 0.38 3.39 -0.758 3.39
Western 467.34 559.40 141.67 0.38 3.39 -0.758 3.39
Urban 0.00 177.05 141.67 0.38 3.39 -0.758 3.39
Rest of East Africa 7689.51 7957.00 141.67 0.38 3.39 -0.758 3.39
K shift R&D
lag
R&D
success
Adoption
lag
Adoption
max
% yrs % yrs %
Central 5 8 100 3 85
Eastern 6.5 8 100 3 90
Northern 4.5 8 100 3 80
Western 5 8 100 3 85
Urban 0 0 0 0
Rest of East Africa 0 0 0 0 0
Table 2: Base data for DREAM simulations: maize in Uganda.
Rest Of East Africa include Kenya, Sudan, Tanzania and Rwanda

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Region Supply Demand Price Supply
Elasticity
Production
growth
Demand
Elasticity
Demand
Growth
1000 mt 1000 mt $/mt % %
North. Comm. Areas 7.50 0.00 2667 1.97 2.61 -0.6 2.61
Rest Namibia 10.40 0.00 2667 1.97 2.61 -0.6 2.61
Namibia Consumer 7.80 2667 1.97 2.61 -0.6 2.61
Z_ROA_South 199.90 210.00 2690 1.76 2.61 -0.3 2.61
region K shift R&D
lag
R&D
success
Adoption
lag
Adoption
max
% yrs % yrs %
North. Comm. Areas 20 6 80 5 90
Rest Namibia 0 0 0 5 (spill) 50 (spill)
Namibia Consumer 0 0 0
Z_ROA_South 0 0 0 5 (spill) 50 (spill)
Table 3: Base data for DREAM simulations: small ruminants in Namibia. Z_ROA_South is Rest of Southern Africa
RESULTS AND CONCLUSIONS
Benefits of Scaling-up NERICA adoption in Senegal
NERICAs have already been widely adopted by farmers in the rice growing regions of SSA and represent an
arguable example of a success story. They are highly suitable for the intensification of rice, and particularly
valuable for broadening production potential in rainfed upland ecologies, particularity in the south of Senegal
where irrigation waters from the Senegal River do not penetrate. CORAF assessed the potential economic
benefit of scaling-up adoption of NERICA in Casamance and South Sine Saloum regions. Parameterized using
the rice production statistics data in Senegal and field-observed NERICA performance data, the model
quantified the potential economy-wide profitability of NERICA adoption in the regions until 2025. Nine
scenarios of potential adoption and performance levels were developed, based on the stakeholder
consultations and desktop studies (Figure 3). In the preliminary analysis, the model estimated that the overall
Net Present Value (NPV) of scaling-up NERICA in the regions will range from 195 million USD (low adoption,
low performance) to 650 million USD (high adoption, high performance).
Benefits of Scaling-up Improved Breeding Practices in Namibia
Climate change is expected to further exacerbate an already challenging environment where goats are raised
in Namibia. Goat genetic resources in Southern Africa are reputable for their hardiness, prolific breeding,
early attainment of maturity, and low ‘input’ requirements (Msangi, 2014). Furthermore, goat meat contains
less fat and cholesterol than most other types of meat with desirable fatty acids. In addition to provision of
tangible products, goats contribute towards the livelihoods of the poor through risk mitigation and
accumulation of wealth. Therefore, selective breeding and use of adapted breeds/ genotypes is attractive
because of its simplicity and excellent cost/benefit, especially when proven sires are used. This would enable
production of fertile, good-quality animals with the productivity and meat quality required by the markets
such as the export market for goat meat and live animals sold to South Africa. Goats would be a good vehicle

2 0 1 7 - 0 4 - 2 0
14
for generating cash returns to meet food security needs and improve welfare of farming families especially in
the northern communal areas where they are found in larger numbers. CCARDESA assessed the potential
economic benefit of scaling-up adoption of improved breeding interventions in the Northern Region of
Namibia. Parameterized using the small ruminant production statistics data in Namibia and field-observed
breeding performance data, the model quantified the potential economy-wide profitability of adoption
improved breeding in the regions until 2025. Nine scenarios of potential adoption and performance levels
were developed, based on the stakeholder consultations and desktop studies (Figure 4). In the preliminary
analysis, the model estimated that the overall Net Present Value (NPV) of scaling-up improved breeding
practices in the northern region will range from 9 million USD (low adoption, low performance) to 106 million
USD (high adoption, high performance).
Benefits of Scaling-up QPM Adoption in Uganda
QPM has shown superior nutritional benefits over normal maize in highly controlled clinical trials. In
communities where QPM is consumed in typical diets, however, rigorous impact studies are scant. Indeed,
impact assessment of biofortified crop varieties are challenging. ASARECA assessed the potential economic
benefit of scaling-up adoption of QPM in Central Region in Uganda. Parameterized using the maize
production statistics data in Uganda and field-observed QPM performance data, the model quantified the
potential economy-wide profitability of QPM adoption in the regions until 2025. Nine scenarios of potential
adoption and performance levels were developed, based on the stakeholder consultations and desktop
studies (Figure 5). In the preliminary analysis, the model estimated that the overall Net Present Value (NPV)
of scaling-up QPM in the region will range from 2.7 million USD (low adoption, low performance) to 42.2
million USD (high adoption, high performance).
Figure 3 Ex-ante economic benefit of scaling-up adoption of NERICA in Casamance and South Sine Saloum Regions, estimated in
Net Present Value (000USD). K-Shift (%): 100 (low), 200 (medium), 300 (high). Adoption (%): 40 (low), 80 (medium), 95 (high).

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Figure 4 Ex-ante economic benefit of scaling-up adoption of breeding TIMPs in Caprivi Region, Namibia, estimated in Net Present
Value (000USD). K-Shift (%): 25 (low), 50 (medium), 100 (high). Adoption (%): 40 (low), 60 (medium), 80 (high).
Figure 5 Ex-ante economic benefit of scaling-up adoption of QPM in Central Region, Uganda, estimated in Net Present Value
(000USD). K-Shift (%): 6 (low), 11 (medium), 22 (high). Adoption (%): 25 (low), 55 (medium), 85 (high).

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REFERENCES
Alston, J., G. Norton, and P.G. Pardey. 1995. “Science Under Scarcity: The Principles and Practice of Research
Evaluation”. CABI, Wallingford, U.K
FAOSTAT. 2016. http://faostat.fao.org/. accessed June 2016
Wood, S., L. You and W. Baitx. 2000. Dynamic Research Evaluation for Management, DREAM 3.5. IFPRI.
Washington. DC. Downloadable from http://www.ifpri.org/dream.htm
References about Small Ruminant Breeding TIMPS
 Joint Presidential Committee (JPC). 2008. Small Stock Management.
 Kosgey, I. S. 2004 .Breeding objectives and breeding strategies for small ruminants in the tropics.
Ph.D. Thesis, Animal Breeding and Genetics Group, Wageningen University, With
 References - With summary in English and Dutch. ISBN: 90-5808-990-8.
 Msangi J. P. 2014. Food security among smallscale agricultural producers in Southern Africa. Weler
Consulting Services. Windhoek, Namibia. (link)
 Musaba, E.C.; Nanyome, L.; Petrus, P. 2009. Analysis and constraints of goats' production in
northern Namibia - A case study in Onesi and Ruacana constituency.
https://inis.iaea.org/search/search.aspx?orig_q=RN:41033566.
 Rumosa Gwaze F, Chimonyo M, Dzama K (2009) Communal goat production in Southern Africa: a
review. Tropical Animal Health and Production, 41, 1157–1168.
 Taljaard P., Alemu Z., A. Jooste and H. Jordaan. 2009. The impact of the Namibian Small Stock
Marketing Scheme on South Africa. National Agricultural Marketing Council (NAMC).
 Van Wyk N. D. 2011. A quantitative analysis of supply response in the Namibian mutton industry.
Downloads/vanwyk_quantitative_2011-1.pdf
 Amiridis GS, Cseh S (2012) Assisted reproductive technologies in the reproductive management of
small ruminants. Animal Reproduction Science, 130, 152–161.
References about NERICA
 Diagne A (2006) Diffusion and adoption of NERICA rice varieties in Côte d’Ivoire. The Developing
Economies, 44, 208–231.
 Kijima Y, Sserunkuuma D, Otsuka K (2006) How revolutionary is the “NERICA revolution”? Evidence
from Uganda. The Developing Economies, 44, 252–267.
 Linares OF (2002) African rice (Oryza glaberrima): History and future potential. Proceedings of the
National Academy of Sciences, 99, 16360–16365.
 Nguezet P, Diagne A (2011) Impact of improved rice technology (NERICA varieties) on income and
poverty among rice farming households in Nigeria: a local average treatment effect (. Quarterly
Journal of International Agriculture, 50, 267.
 Somado EA, Guei RG, Keya SO (2008) NERICA: The new rice for Africa–a compendium. Africa Rice
Center (WARDA), 10-14 pp.

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References about QPM
 Gregory T, Sewando P (2013) Determinants of the probability of adopting of quality protein maize
(QPM) technology in Tanzania: A logistic regression analysis. International Journal of Development
and Sustainability, 2, 729–746.
 Gunaratna NS, De Groote H, Nestel P, Pixley K V., McCabe GP (2010) A meta-analysis of community-
based studies on quality protein maize. Food Policy, 35, 202–210.
 Krivanek AF, De Groote H, Gunaratna NS, Diallo AO, Friesen DK (2007) Breeding and disseminating
quality protein maize (QPM) for Africa. African Journal of Biotechnology, 6, 312–324.
 Mbuya K, Nkongolo KK, Kalonji-Mbuyi A, Kizungu R (2010) Participatory selection and
characterization of quality protein maize (QPM) varieties in Savanna agro-ecological region of DR-
Congo. Journal of Plant Breeding and Crop Science, 2, 325–332.

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