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Agricultural Productivity in EAC Region (1965-2010)
Trends and Determinants
Joseph Karugia, Stella Massawe, Paul Guthiga and Eric Macharia
October, 2013
Paper presented at the International Symposium and Exhibition on the Agricultural
Development in the EAC Partner States at the 50 Years of Independence
4th to 8th November, 2013
Kampala, Uganda
ii
Table of Contents
1. Introduction .................................................................................................................................... 1
1.1 Overview of Agricultural Sector performance ............................................................................. 1
1.2 Agricultural Productivity; concepts and measurements ......................................................... 2
2. Data and methodology ........................................................................................................................ 4
3. Findings ................................................................................................................................................ 6
3.1 Productivity trends of selected food staples ................................................................................ 6
3.2 Key observations from the results section ................................................................................. 15
4. Determinants of agricultural productivity in the EAC region .......................................................... 19
4.1 Policy reforms ............................................................................................................................. 19
4.2 Investments in research and development ................................................................................. 20
4.3 Political stability ........................................................................................................................... 20
4.4. Weather patterns ....................................................................................................................... 20
4.5 Population dynamics ................................................................................................................... 21
5.0 Conclusions and Policy Implications ............................................................................................... 22
5.1 Conclusions ................................................................................................................................. 22
5.2 Policy implications ....................................................................................................................... 22
6.0 References ....................................................................................................................................... 24
7.0 Annexes .......................................................................................................................................... 27
Annex 1: Agriculture value added as share of GDP (%)................................................................... 27
Annex 2: Trends in crop productivity in East Africa Community countries (1965-2010)............... 28
Annex 3: Number of animals 000' (heads) producing beef and milk................................................ 30
Annex 4: Beef and milk productivity and its growth ........................................................................ 31
Annex 5: Average area harvested (Million ha) per crop .................................................................. 32
Annex 6: Growth of area harvested per crop.................................................................................. 34
1
1. Introduction
1.1 Overview of Agricultural Sector performance
Agriculture is an important economic activity in the East African Community (EAC) region.
It plays a key role in economic growth, poverty reduction, food security and employment.
Agriculture sector provided employment for about 70 percent of rural population in the
EAC region the majority of who are women. The sector is also an important source of
employment to the urban population. Available data on the annual average agriculture value
added shows that during the period 2005-2006 the sector contributed about 28% of the
gross domestic product (GDP) in EAC (see Annex 1). During the same period, the share of
agricultural GDP to the EAC member states stood at: 39 % in Burundi, 26% in Kenya, 35%
in Rwanda, 30% in Tanzania and 25% in Uganda (Annex 1).
Share of agriculture to the total GDP among the EAC member states has been declining
over the past two decades. Similarly, the regional share of agricultural GDP to total GDP
has also declined. During the period 1990-1995, the EAC’s agricultural GDP was about 40 %
declining to about 28% in 2005-2010 (Annex 1). It is however worth noting that decline in
agricultural contribution to the GDP is not an undesirable outcome, as it does not
automatically reflect poor performance of the agriculture sector or its diminished
importance (Benin et al. 2010). Furthermore, the decline is only relative because the
absolute contribution of the agriculture sector has actually increased over time. The decline
in the share of agriculture to the economies of these countries is a result of progress in the
development of other sectors, especially industry and services, which could indicate early
stages of economic transformation (see Timmer, 1988). The faster growth of the industrial
and service sectors of the economy can augment the growth of the agriculture sector by
creating more and stronger forward and backward linkages.
Despite its crucial role, the agriculture sector in the EAC region faces many challenges
among which low productivity ranks high. Various factors contribute to low agriculture
productivity in the EAC region directly or indirectly, examples include: low use of improved
inputs (such as quality seeds, fertilizers, improved animal breeds, better feeds), erratic
climatic conditions (coupled with recurrence of droughts and occasional floods), scarcity
and low quality of feed resources, pests and diseases, low use of modern technologies,
inadequate access to agriculture extension and veterinary services, poor physical
2
infrastructure affecting market access and access to improved inputs, limited access to
credit, marketing constraints and post-harvest losses among others. The average agricultural
productivity in EAC is significantly lower than in other part of the world. While the
information on low productivity is common knowledge, historical trends in performance in
the EAC region has not been comprehensively synthesized to strategically inform regional
agricultural strategies. This study sought to fill in this knowledge gap by analysing the trends
in agricultural productivity performance of selected staple crops since the mid-1960s to
present. The study used available national and international data sources to construct the
trends. An extensive literature review was also undertaken to explain the observed
productivity trends. The study made efforts to provide insights into factors that have led to
productivity gains in various parts of the region using examples from literature. The
information provided by this paper can help identify possible policy actions and options to
address the challenge of low agricultural productivity in EAC.
1.2 Agricultural Productivity; concepts and measurements
Agricultural productivity measures are categorized into partial or total measures. Total factor
productivity (TFP) is a method of calculating agricultural productivity by comparing an index
of agricultural inputs to an index of outputs. It is defined as the ratio of the value of output
to the value of all inputs used (Nyoro and Jayne 1999). TFP trends over time are often used
to assess net gains from technological change (Pingali and Heisey 1999). Although TFP
measures are the most appropriate measures of productivity, they are used less often,
especially in Africa. This is because TFP measures are difficult to construct in the absence of
data on prices and costs of key inputs (Nyoro and Jayne 1999). Partial factor productivity
measures refer to the amount of output per unit of a particular input such as yield (output
per unit of land or output per animal) and labour productivity (output per economically
active person or output per agricultural person-hour). Output and yield growth rates
remain the most commonly used indicators of productivity growth in developing-country
agriculture (Pingali and Heisey 1999; Chilonda et al. 2007). The main weakness of partial
factor productivity indices is that they do not account for all the inputs used in
production/marketing systems. This paper focuses on selected partial factor productivity
(PFP) measures.
3
Land productivity is measured as the ratio of total output harvested per area or value added
per unit of agricultural land. The paper presents an analysis of the status and trends of
productivity of some of the key food staples in the region. We analyse data on staple crops
(maize, dry beans, rice and wheat) and two animal products (beef and milk).
The rest of the paper is organized as follows: section 2 summarises data sources and
methodology for our analysis, Section 3 present findings of our analysis, Section 4 focuses
on discussions on the factors that have contributed to productivity gains in the region, these
chapter forms the basis for our recommendations. Conclusions and policy
recommendations are made in Section 5.
4
2. Data and methodology
Analysis in this paper is based the available national and international data and information
sources. No primary data collection was involved in the preparation of the paper.
Collaborative activities between ReSAKSS and national technical experts involved in
agriculture and rural development M&E facilitated access to national data and information.
The national sources used include agriculture line ministries, national statistical agencies,
ministries of planning and economic development, and ministries of finance and economic
affairs. The following international data sources were used: the International Monetary Fund
(IMF), the United Nations Food and Agriculture Organization database (FAOSTAT) and the
World Bank World Development Indicators.
To supplement information and data collated, a detailed review of literature was conducted
gain insights on the determinants of observed trends in agriculture productivity. A wide
range of published and unpublished literature sources were reviewed. Key references used
were government publications, technical reports by various organisations and research
reports.
Data analyses are presented at national and regional levels. To estimate regional level values,
we adopted a method for regional aggregation used by Benin et al. 2010. Regional values
were estimated using the weighted sum approach; the weighting factor for each country was
the share of that country’s value in the total value of the indicator for all countries in the
region or sub-region. Indicators such as GDP, agriculture GDP, population and land area
were used as the weighting factors depending on the indicator of interest. Details for each
weighting scheme are given in the technical notes in various tables.
To assess performance over time, annual average indicator levels and changes are calculated.
Data are averaged across various periods e.g. 1990–1995, 1995–2000, 2000–2005 and
2005–2010, using overlapping years to smooth the range. Use of multiple years is more
reliable for analysing trends than year-to-year changes that are often fraught with large
variations (Benin et al. 2010). Annual average change for all indicators except those with
possible negative values is the average percentage change from the beginning to the end of
5
years shown by fitting an exponential growth function to the data pints (i.e. LOGEST
function in MS-excel). The calculated growth rate is an average rate that is representative of
the available observations over the entire period and should not be taken to match growth
rate between any two periods and is expressed in percent (%).
6
3. Findings
This section presents results of analysis of productivity trends for selected commodities in
the Eastern African region for the period 1965-2010. Our analysis focused on selected food
staples among the EAC member states. We begin with analysing cereal productivity in
general then move to other individual food commodities. For each food staple, we discuss
two components; status and trends of productivity levels and annual average growth rates
over time.
3.1 Productivity trends of selected food staples
Productivity trends in cereals1
Historical data from 1965 to 2010 shows that average cereal productivity at EAC region has
been less than 2t/ha over the whole period. Average cereal productivity has ranged from
1t/ha (1965-1970) and 1.5t/ha (from 1990 - 2010). Some fluctuations are observed between
periods (see Figure 1; Annex 2). The regional long term average (1965-2010) cereal
productivity stood at about 1.3t/ha. During the same period, the average cereal
productivity in stood at 1.1t/ha, 1.2t/ha, 1.2t/ha,1.4t/ha and 1.5t/ha, in , and respectively
Rwanda, Burundi, Tanzania, Uganda and Kenya respectively. There was some gradual
increase in cereal productivity in all the EAC countries for the period between 1960 and
late 1980’s. It was then followed by a drop in Burundi, Kenya and Rwanda till mid 2000’s. In
the period 1965-1975, Tanzania cereals productivity was trailing behind the other countries
with 0.7t/ha and 0.8t/ha in periods 1965-1970 and 1970-1975 respectively; this was below
the 1t/ha level which all other four countries had achieved and below the average regional
productivity. Over the period 1965-1970, cereal productivity in Tanzania had been declining
at a rate of 6.6% per annum (see Table 3.1). However, over time Tanzania’s cereal
productivity has been gradually increasing from 0.8t/ha in the period 1970-1975 to a high of
1.5t/ha in 2000-2005, eventually overtaking Rwanda and Burundi who reached a high of
1.35t/ha in 1990-1995 and 1.38t/ha in 2005-5010 respectively.
1 Notes: Cereals include wheat, rice, maize, barley, oats, rye, millet, sorghum, buckwheat and mixed grains. Production data
on cereals relate to crops harvested for dry grain only. Cereal crops harvested for hay or harvested green for food, feed
or silage and those used for grazing are excluded.
7
Cereal productivity in Kenya and Uganda remained highest in the region, with Kenya
reaching a peak of 1.7t/ha over the period between 1985-1990 and 1990-1995. On the
other hand, Uganda had been slowly but consistently increasing its productivity, from 1.1t/ha
in 1965-1970 to most recent statistic standing at 1.7t/ha by 2005-2010.
Source: Computed by the authors using data from FAOSTAT
Figure 1: Cereal productivity (annual average level in t/ha) in the EAC region 1965-2010
Growth rates in cereal yields
Average growth in cereal productivity for the period 1965-2010 has been positive in the
EAC region, albeit at a low pace of about 1% per year (Table 3.1). Fluctuations in cereal
yields are observed over time. Declines in regional level cereal productivity were recorded
in the periods 1975-1980, 1995-2000 and 2000-2005. High declines in the late nineties and
early part of 2000’s could be attributed to droughts that were experienced in various parts
of the region. The fastest growth in cereal production at the regional level occurred in
1970-1975 when EAC registered an annual average growth rate of 5.1 percent. The period
2005-2010 saw the highest growth rate in cereal productivity since 1980’s. The average
annual percentage growth rate of the cereals yield (for the period 1965-2010) in Burundi,
Kenya, Rwanda, Tanzania and Uganda were 0.0%, 0.7%, -0.2%, 1.9% and 1.2% , respectively.
During the most recent period (2005-2010), Kenya and Burundi recorded decline in cereal
productivity, while the other countries registered positive growth rates, with highest annual
8
increase being registered in Rwanda. Post-election violence in Kenya (2007-2008) was
largely responsible for yield decline not only in cereals but also other crops.
Table 3.1: Growth rate (Annual percentage change) in cereal productivity in EAC 1965-2010
1965-
2010
1965-
1970
1970-
1975
1975-
1980
1980-
1985
1985-
1990
1990-
1995
1995-
2000
2000-
2005
2005-
2010
EAC 0.96 1.88 3.19 -1.00 3.06 1.69 2.06 -1.38 -3.50 3.13
Burundi 0.74 2.44 -0.78 -0.24 1.44 3.31 -0.73 -1.85 1.18 -0.08
Kenya 0.55 2.81 1.86 -3.79 2.26 -1.20 2.29 -2.81 3.65 -2.54
Rwanda 0.17 -4.48 -1.80 1.69 -0.18 -3.13 0.99 -8.15 5.00 12.22
Tanzania 1.73 -6.62 10.69 0.82 6.17 3.71 1.56 -1.28 -9.14 4.01
Uganda 1.08 8.87 -0.33 3.86 -3.02 2.51 1.03 3.04 -0.96 6.66
Source: computed by the authors using data from FAOSTAT
Productivity trends in maize
At the global level, maize yields stand at 4.9t/ha with yields increasing at 1.6t/ha per annum.
In comparison, the annual average maize productivity (1965-2010) for EAC and its
respective countries had been far much lower than the global average, at 1.3t/ha and a
growth of 1t/ha per annum for the 45 years period. The highest productivity level from the
five EAC countries was 1.8t/ha (Kenya, for period between 1985-1990) and the lowest being
0.7t/ha (Tanzania, for the period 1965-1970).
9
Source: computed by the authors using data from FAOSTAT
Figure 2 Maize productivity (annual average level in t/ha) in the EAC region 1965-2010
Growth rates in maize productivity
Annual average growth rate in maize production over the 45 years of this analysis (1965-
2010) has been about 1.1 percent (Table 3.2). During the same period annual average
annual growth rate of the maize yield for Burundi, Kenya, Rwanda, Tanzania and Uganda
were 0.0%, 0.7%, -0.2%, 1.9% and 1.2% respectively( see Table 3). The annual average
growth rate in maize yields has been fluctuating highly at both regional and country levels. A
closer look at the regional growth rates for maize yield depicts a generally very fluctuating
pattern. Positive growth rates were recorded in most of the periods. However, some
periodic instance of negative growth rates led to loss of productivity achievements. Decline
in maize productivity were registered in 1975-1980, 1995-2000 and 2000-2005. The period
2000-2005 had the highest rate of decline in maize productivity per annum since 1960’s. As
noted above, most countries in the region were affected by drought during this period. Our
analysis reveals a similar pattern of maize and cereal productivity (see Figure 2 and 3).
Regionally, cereal trends follow almost same pattern as the maize productivity pattern,
which could be due to importance of maize being a major staple and cash crop for
smallholder farmers in the region.
Table 3.2: Growth rate (Annual percentage change) in maize productivity in EAC 1965-2010
1965-
2010
1965-
1970
1970-
1975
1975-
1980
1980-
1985
1985-
1990
1990-
1995
1995-
2000
2000-
2005
2005-
2010
EAC 1.1 0.7 5.1 -1.7 2.1 1.7 3.9 -0.7 -7.1 4.0
Burundi 0.0 3.1 -1.6 -0.5 1.4 2.5 -1.9 -4.3 0.3 -1.4
Kenya 0.7 3.5 3.0 -4.5 4.0 -1.0 2.4 -3.2 3.2 -2.4
Rwanda -0.2 -6.4 -1.7 1.4 0.5 -1.5 5.6 -10.2 3.0 25.6
Tanzania 1.9 -9.6 15.2 1.0 1.1 4.2 5.0 2.1 -17.6 4.7
Uganda 1.2 9.0 -3.4 1.1 -1.1 6.5 2.1 4.3 -3.9 10.8
Source: computed by the authors using data from FAOSTAT
Productivity trends in dry beans
Dry beans have historically been used as an important food staple in the Eastern Africa
region. Productivity of this crop is generally low in EAC, and a stagnating trend has been
observed over time (Figure5). Between 1965 and 2010, bean yield in the region rose
marginally from 0.7 tons per hectare in 1970, to 0.8 tons per hectare by 1995, and dropped
to 0.6 tons per hectare in 2010 (Annex 2). Such levels are far less than what is achieved in
10
other parts of Africa such as Egypt, Libya and Sudan whose yields of dry beans are more
than 2t/ha. This is an indication of the yield gaps in this crop. Bean yield is reportedly high in
Burundi and lowest in Kenya for most of the 45 year period, which was at least 0.9t/ha in
Burundi and as low as 0.4t/ha in Kenya.
Source: computed by the authors using data from FAOSTAT
Figure 3 Bean productivity (annual average level in t/ha) in the EAC region 1965-2010
Growth rate in the productivity of dry beans
Analysis of available data reveals that during the four and a half decade period, the average
annual percentage growth rate of bean yields for Burundi, Kenya, Rwanda, Tanzania and
Uganda were -0.27%, -0.49%, -0.19%, 1.21% and -0.6% respectively (see Figure 2 and annex
2). During the same period, the overall regional yield was declined by -0.33%. Although
some periodic fluctuations are noted, these statistics illustrates a decline in bean
productivity in four of the five member countries apart from Tanzania, hence down-ward
trend at regional level. However, the area harvested gradually increased through the period
with an average annual percentage growth rate of 1%, 1.05%, 1.02%, 1.03% and 1.03%
growth in Burundi, Kenya, Rwanda, Tanzania and Uganda respectively while it grew at 1.03%
regionally. This means that increased production has only been achieved through expansion
in areas under bean rather than increased productivity.
11
During the most recent period of our analysis (2005–2010) EAC recorded some
improvements in the growth rate of beans productivity (Annex 2). Efforts to sustain the
recorded positive gains are necessary because the crop is the main source of protein for the
poor who are increasingly facing challenges in accessing animal protein sources due to
soaring food prices.
Productivity trends in rice
Rice production has been growing over time. Our analysis indicates that the EAC regional
average annual production stood at 1.90 million tons during the period 2005-2010;
increasing from 0.14 million tons during the period 1965-1970. Regional rice yields have
increased by two folds, from 1.1t/ha in 1965-1970 to 2.0t/ha in 2005-2010. Average rice
yields (1965-2010) for the EAC member states have been as follows: Burundi (2.7 t/ha),
Kenya (4t/ha), Rwanda (2.9t/ha), Tanzania (1.5t/ha) and Uganda (1.3t/ha). In the most recent
period of analysis (2005-2010) rice productivity in the EAC member states stood at 3.3t/ha
for Burundi, 2.9t/ha for Kenya, 4.7t/ha for Rwanda, 1.9t/ha for Tanzania and 1.8t/ha for
Uganda.
Source: computed by the authors using data from FAOSTAT
Figure 4 Rice productivity (annual average level in t/ha) in the EAC region 1965-2010
Productivity trends in wheat
The average annual growth rates in wheat productivity for the period starting 1965 to 2010
in the region was 0.77% with 0.71%, 1.09%, 0.54% and 0.41% in Burundi, Kenya, Rwanda and
12
Tanzania respectively (See Annex 2). By year 2000 the rate of increase in wheat
productivity had slowed down after a strong rise from 1965 to the late 1980’s with large
variations of yield among different countries. Noticeably, the regional yield trends are very
similar to Kenya, which may be attributable to the large share of the country in total wheat
production in the region.
Source: Computed by the authors using data from FAOSTAT
Figure 5 Wheat productivity (annual average level in t/ha) in the EAC region 1965-2010
Negative growth was observed in the period between 1990 and 2000 with Burundi, Kenya,
Rwanda, Tanzania, Uganda and the regional figures standing at -2.62%, -5.47%, -11.22%, -
14.85%, -0.59% and -7.68% by year 2000 respectively. As a result of this slow growth,
changes in productivity during the period have only been minimal. However, there were
some improvements in growth of productivity from early 2000’s and by 2010, the yield rates
stood at 0.83t/ha for Burundi, 2.51 t/ha for Kenya, 1.2 t/ha for Rwanda, 1.46 t/ha for
Tanzania, 1.71 t/ha for Uganda and 1.94 t/ha for the region respectively.
Productivity trends in Sorghum
Between 2005 and 2010, sorghum production in EAC is estimated at 1.6 million tonnes with
Tanzania being the leading sorghum producer in the region at an average of 0.7 tonnes. It
was grown on average 1.4 million ha in EAC, accounting for about 14.9% of cereal acreage
and 11% of cereal production.
13
Source: computed by the authors using data from FAOSTAT
Figure 6 Sorghum productivity (annual average level in t/ha) in the EAC region 1965-2010
The growth in productivity varied across the important sorghum growing countries in the EAC
region. Productivity of Sorghum in Rwanda is somewhat stagnant; it is progress was positive in
Burundi and negative in Kenya. Annex 3 and figure 6 indicates that productivity gains were
experienced over the 45 years’ time period in Burundi, Tanzania, Uganda and overall regional with
yield rates at 1.09t/ha, 0.86t/ha, 1.34t/ha and 1.02t/ha respectively. A decrease in productivity was
observed in Kenya and Rwanda whose average yield was 0.9t/ha and 1.1t/ha, and a growth rates of -
1.02% and -0.17% respectively. In terms of annual productivity growth rate, Tanzania experienced
the highest growth rate (1.52%) followed by Burundi (0.78%) and Uganda (0.44%).
Productivity trends in Cassava
Cassava productivity in the EAC region rose from about 5.4t/ha in the 1960s to a high of
10.3t/ha in the mid-1980s. It has since reduced and stagnated at around 8.3t/ha since the
early 2000. Since 1965 through 1995, it is noted that a constant level of productivity existed
in Burundi at around 9t/ha while it marginally declined to 8.4t/ha during 2000-2005 period.
Before 1985, Rwanda was leading in productivity with a high of 12.3t/ha during the early
1980’s, but this drastically decreased to 2.2t/ha in the 1990-1995. In Uganda the yield
increased constantly from 4.3 t/ha in the 1960’s to a high and leading yield of 13.5t/ha by
early 2000’s.
14
Figure 7 Cassava productivity (annual average level in t/ha) in the EAC region 1965-2010
Productivity trends in beef
From the period 1965-1970 to the most recent 2005-2010, average beef productivity in the
region has stagnated at around 130kg/animal and an overall growth rate of 0.1% per annum.
In Burundi, Kenya, Rwanda, Tanzania, and Uganda the average productivity stood at
160kg/animal, 140kg/animal, 100kg/animal, 100kg/animal and 150kg/animal with a growth of
1.35%, 0.06%, 0%, 0.2% and 0% respectively.
Figure 8 Beef productivity (carcass weight (kg/an) in the EAC region 1965-2010
15
Productivity trends in milk
The average milk productivity in EAC region was 340kg/animal during the period 1965-2010.
In the period 2005-2010, the average productivity rose to a high of 410kg/animal. At country
level, variations were observed. Before 1990, milk productivity in Tanzania stagnated at 160
kg per animal. Even though milk yield in Tanzania has improved to 240kg over the period
2005-2010, which is about 50% increase, the country is still trailing behind others in the
region. Rwanda and Kenya competitively lead in productivity, with 580 and 620 kg per
animal respectively, which is more than double the yield in Tanzania. Rwanda milk yields
have almost doubled from 300 in late 1960’s to the recent 580kg/animal and so has the
numbers, while Kenya had increased by 38% from 450 kg/animal.
Figure 2 Milk productivity (kg/an) in the EAC region 1965-2010
3.2 Key observations from the results section
i. Cereal productivity has only been rising at moderate rates since the 1960s;
productivity levels are below what is achieved in other parts of the world.
Declining trends in the productivity of some crops has also been observed.
Cereal yields in EAC have fluctuated below 2 t/ha since the 1960s. Country reports and data
provide further evidence of declining or stagnating productivity, not just for cereals, but also
for other crops. For example, UBOS (2010) indicates that between 2004 and 2009 Uganda
experienced a decline in the yields of beans, cassava, plantain bananas, Irish potatoes and
16
maize. Bekunda (1999) indicates that banana production in Uganda has been declining since
the 1990s. Similarly, statistics from the Kenya’s Ministry of Agriculture and Livestock
indicate that maize yields are declining in Kenya.
ii. Production is growing at a much faster pace compared to productivity
Generally, crop production is growing faster than crop productivity. Long term annual
averages (1965-2010) show that growth rate for production of maize in EAC has been 2.8%
while the productivity growth has lagged behind increasing at only 1% annually. Similar
trends are recorded for the other key staples (see Table 3.3). This suggests that expansion
of crop land is the major driver for the observed increase in production.
Table 3.3: Comparison of growth rates (%) in production versus yields of selected crops in EAC
Burundi Kenya Rwanda Tanzania Uganda Regional
Period Prd
n
Yiel
d
Prd
n
Yiel
d
Prd
n
Yiel
d
Prd
n
Yiel
d
Prd
n
Yiel
d
Prd
n
Yiel
d Cereal
1965-2010 0.00 0.74 1.16 0.55 1.45 0.17 4.11 1.73 1.99 1.08 2.42 0.96
2005-2010 2.15 -0.08 -0.53 -2.54 14.73 12.22 7.71 4.01 10.62 6.66 6.33 3.13
Maize
1965-
2010
0.02 0.01 1.48 0.70 2.05 -0.22 4.20 1.89 3.81 1.17 2.77 1.04
2005-
2010
0.40 -1.36 -0.55 -2.43 38.39 25.59 7.02 4.67 16.75 10.74 6.82 3.98
Beans, Dry
1965-
2010
-0.54 -0.27 4.17 -0.49 1.46 -0.19 4.55 1.21 2.70 -0.60 2.49 -0.33
2005-
2010
-1.37 2.70 -2.19 4.81 8.43 8.52 6.32 2.73 -0.12 -2.61 2.57 2.97
Rice, paddy
1965-
2010
8.87 1.80 1.88 -1.45 12.73 6.00 1.42 8.49 1.36 6.02 1.20
2005-
2010
4.28 -0.79 -1.43 -4.28 4.17 4.35 13.59 2.54 8.13 13.03 12.06 3.08
Wheat
1965-
2010
1.09 0.71 1.69 1.09 9.19 0.54 0.90 0.41 1.72 0.77
2005-
2010
2.23 2.05 1.34 1.83 37.85 15.92 -
10.73
-22.02 5.14 -0.64 2.51 -3.20
Sorghum
1965-
2010
3.63 0.78 -1.96 -1.02 0.09 -0.17 3.52 1.52 0.67 0.44 1.26 0.40
2005-
2010
2.58 0.68 -3.87 -11.28 -5.75 1.29 -0.36 1.33 -3.19 -6.65 -1.83 -2.22
Cassava
1965-
2010
1.46 -0.16 0.05 0.38 2.55 -2.31 0.90 0.13 2.97 2.82 1.68 0.93
2005-
2010
-1.22 2.47 2.72 -4.34 28.23 13.86 -3.01 -3.39 -0.29 -2.05 1.35 -0.50
Source: Computed by the authors using data from FAOSTAT
iii. Massive expansion of crop land occurred in the past 45 years
EAC has experienced massive expansion in area under crop land since 1960s. Millet is the
only crop that registered decline in crop land out of the commodities analysed in this study.
The area harvested for cereals in the EAC region has significantly grown over time. Between
1965 and 2010, the regional area harvested increased by 97% from an average of 4.8 million
ha in 1965-1970 to 9.6 million ha in 2005-2010 (See Annex 5 and figure 12). Area under dry
beans has increased by three folds compared to the figures for 1960s, while areas under
17
maize and rice production have more than doubled. Smaller increases in acreage were
recorded for sorghum, cassava and wheat. Annex 6 provides country specific examples on
the trends of expansion of area under crop production in the EAC member states. Although
area expansion might be feasible where land is available, this option is not sustainable in the
long run. Currently, land scarcity prevents expansion of area under cultivation in areas with
high population density (especially the high potential areas of Kenya, Rwanda, Burundi,
Malawi and Tanzania). Farm size per household has been declining over time among the
rural communities living in the high potential areas of these countries. In such situations,
farmers are compelled to shift from extensive to semi-intensive or intensive crop and
livestock production strategies. Increase in yields remains the only option for sustainably
increasing food production so as to ensure adequate food supply, especially among the
households that rely heavily on subsistence agriculture.
Source: computed by the authors using data from FAOSTAT
Figure 12: Changes in area under crop land in the EAC region-1965-1970 compared to 2005-
2010
18
iv. Increase in the cattle population is the major driver of growth in the
production of milk and beef
Beef and milk production have been increasing over the past 20 years. Milk production grew
steadily in East Africa in the 1980s and 1990s as the numbers of the milk producing animals
increased (Figure 13). Some gains in beef and milk productivity have been recorded as well;
however, the rates of growth have been rather slow. Milk productivity growth has been
especially slow, suggesting that most of the observed increase in milk production is driven
by growth in number of animals rather than productivity per animal.
Source: computed by the authors using data from FAOSTAT
Figure 3 Cow milk producing animals (000) heads
19
4. Determinants of agricultural productivity in the EAC region
Determinants of productivity were assessed through review of existing literature and
synthesis of available information. It is important to note at the outset that there are
relatively few studies that have analysed the determinants of agricultural productivity gain
not just in EAC region but Sub-Saharan Africa in general (Block, 1995;Yu and Nin-Pratt,
2011). Some of the studies on productivity have mainly focused on understanding whether
productivity changes are due to technological change or due to efficiency gains. The findings
have been somewhat mixed; some studies have found productivity gains have been due to
efficiency gains (Nin-Pratt and You, 2008) while others found technology progress to be the
main driver of productivity gain (Alene, 2010). In the subsequent section we discuss the
main drivers of agricultural productivity changes.
4.1 Policy reforms
In the 1960-1970s governments in the region followed policies that resulted in overvalued
exchange rates, prolonged budget deficits, protectionist trade policies and government
monopolies in marketing (Yu and Nin-Pratt, 2011). The net impacts of these policies
included were; reduced competition, an implicitly heavy taxation of agricultural exports and
ultimately depressed productivity. Policy reforms are cited as one of the drivers of
productivity gains experienced in agriculture sector in Africa. In particular, the macro-
economic and sectoral reforms undertaken in the 1980s and early 1990s account for major
gains in total factor productivity in the past two decades (Block, 1995; Nin-Pratt and Yu,
2008; Alene, 2010). These policy reforms substantially improved the economic environment
for agriculture through improvements in better policies on pricing policies, trade, exchange
rates, institutions and markets. As noted by Block (1995) and Block (1993), the depreciation
of the real exchange rate was essential in shifting prices in favour of agricultural products
that are considered more tradable than non-agricultural products. Increasing farm
profitability through better prices of agricultural products leads to more adoption of
improved technologies that further drive agricultural productivity. According to the World
Bank (2008), the net taxation for agriculture was more than halved between the period
1980-1984 and 2000-2004.
20
While the policy reforms have gone a long way to change the earlier anti-agriculture
tendencies and biases, some policy barriers still persist to-date. Substantial domestic
distortions that impose a large tax burden to the poor farmers are prevalent (Anderson and
Masters (2008). In particular trade restrictions is a top policy instrument of agricultural
intervention even among EAC member countries.
4.2 Investments in research and development
Investment in agricultural research is a key determinant of agricultural productivity. Some
studies have found it to explain a significant part of productivity gains that have been
experienced in Sub-Saharan Africa since the mid-1980s. For instance Block (1995) found that
the estimated coefficient on lagged expenditure per hectare for research explained up to
one-third of the rate of agricultural growth form 1983-1988 in Sub-Saharan Africa.
Investments in R&D are essential for bringing about the much needed technical change to
drive agricultural productivity upwards. As noted by Block (1995), the development and
extension of hybrid maize in Kenya and Zimbabwe are one of the notable success stories of
African agricultural research. Readorn et al (1996) in their study on determinants of farm
productivity in Africa based on four case study also found plant breeding programs as being
an important driver of productivity gain. Alene (2010) shows that agricultural R&D is socially
profitable with a return of 33 percent per year on investments.
4.3 Political stability
Stable and predictable political environment and working institutions play an essential role in
supporting growth in agricultural productivity. A study by Fulginiti et al (2004), on the
impact of institutions in agricultural productivity (1960-1999) showed that period of political
conflicts and wars were associated with significant reduction in productivity. Conversely
countries that had higher levels of political rights and civil liberties achieved significantly
increases in productivity.
4.4. Weather patterns
Weather patterns are an important predictor of agricultural productivity trends in the EAC
region and other regions in Africa. Rainfall in particular is one of the binding constraints to
agricultural productivity in Africa. This is not surprising given the heavy reliance on rain for
agricultural production. Period of drought are associated with significant drops in levels of
productivity and vice versa. Several studies on productivity point out the role of weather in
determining productivity (see Alene, 2010; Block, 1995; Odhiambo, Nyangito and Nzuma,
2004). According to Alene (2010), the elasticity of agricultural productivity with respect to
21
rainfall was 0.17, meaning that a 10% increase in annual rainfall raises productivity by an
average of 1.7% per year. The study showed that improvements in the amount of rainfall
contributed significantly to the improvements in agricultural productivity after the mid-
1980s. Weather is by and large an exogenous variable that is not within the control of the
country but mitigation measures are available to ameliorate its effects.
4.5 Population dynamics
Declining land-labor ratios have been an important driver of agricultural productivity in line
with the Boserup and Hayami & Ruttan induce innovation hypothesis. Several studies have
reported results that support this hypothesis for instance Odhiambo, Nyangito and Nzuma
(2004), in their analysis of agricultural productivity growth in Kenya showed that labour
contributed to about 48% of agricultural productivity growth during the period between
1965 and 2001. Lusigi and Thirtle (1997), showed that population pressure on land seem to
explain faster growth in agricultural productivity among countries in Sub-Saharan Africa.
According to the study, countries that achieved the highest average productivity growth
were those with more labour pressure on land. In fact, the study by Lusigi and Thirtle found
that 75% of the countries with high population pressure on land experienced more technical
progress relative to change in efficiency. The explanation for this observation is that land
abundance reduces incentives to adopt high yielding technologies.
22
5.0 Conclusions and Policy Implications
5.1 Conclusions
This paper examined trends and pattern of agricultural productivity in the EAC region at
country and regional levels. Our findings indicate that productivity is generally low,
compared to what has achieved at other parts of the world. Crop yields in EAC are highly
variable, in most cases corresponding to climatic conditions due to the associated
dependence on rain fed agriculture. The EAC region has experienced growth in agricultural
production in the past two decades. There has been an increase in the production of most
crops which has mainly resulted from area expansion rather than increase in productivity
per unit of land. Similar trends have been observed in the livestock sector where recent
increases in outputs have been associated with increases in animal herd sizes rather than
productivity per animal. Increasing the area of land under production or animal herd sizes is
only feasible in the short term and where land is available; this strategy is not be feasible in
most parts of the region, especially in areas of high population density.
In the long run, sustained growth in the agriculture sector can only be achieved through
increasing productivity. Efficient use of available resources will increasingly become
important as countries begin to face resource constraints. This means that gains in
productivity must inevitably arise from efficiency gains and not merely technological
progress.
There is huge potential to increase productivity within the region, evident from the huge
yield gaps that still exist today. Some limited interventions aimed at increasing agricultural
productivity have been implemented in the region in the form of programs or projects, and
have resulted to yields that are significantly higher than national averages. Furthermore,
yields achieved at research stations indicate huge yield gaps. There is a need for up scaling of
effective productivity interventions so as to bring about higher effects at country and
regional levels.
5.2 Policy implications
Based on the existing synthesis undertaken in this study the following issues have policy
implications for agricultural productivity in the EAC region:-
23
In order for productivity gains from policy reforms to be fully realized, the reform
agenda must be sustained and all remaining barriers especially trade restriction
among member states should be eliminated.
Investments in agricultural research and development (R&D) must be increased and
sustained in the EAC member states if higher levels of agricultural productivity have
to be achieved and sustained. R&D offer and opportunity to achieve yet unexploited
technical change to drive productivity towards the unachieved potential. In the short
run, the public sector must continue to play significant role in funding agricultural
research.
The high dependence on rain-fed agriculture leaves the agriculture sector in the EAC
region vulnerable to vagaries of weather. There is therefore need to invest in
irrigated agriculture. Investment in effective and efficient early warning systems
would also help to dampen the effects of extreme weather events.
It is worth noting that none of the above measures can work in isolation. To improve
chances that productivity-enhancing interventions will be effective, several interventions
need to be implemented together in a way that they complement each other for maximum
benefits towards enhancing agriculture productivity.
24
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27
7.0 Annexes
Annex 1: Agriculture value added as share of GDP (%)
Notes: Blank cells indicate missing values. Regional aggregate values are calculated as weighted summations. The weights
are computed using country’s GDP as a share of regional GDP.
Avg is an abbreviated form of average; this word has been used in all tables in this report.
Source: Authors’ calculation based on data from World Bank (2011).
Country
/Region
1990 -
2010
Annual
Avg
1990 -
2010
Annual
Avg
point
change
1990 -
1995
Annual
Avg
Level
1990 -
1995
Annual
Avg
point
change
1995 -
2000
Annual
Avg
Level
1995-
2000
Annual
Avg
point
change
2000-
2005
Annual
Avg
Level
2000-
2005
Annual
Avg
point
change
2005 -
2010
Annual
Avg Level
2005
- 2010
Annual
Avg
point
change
EAC 34.0 -0.7 40.4 0.2 37.2 -1.7 30.8 -0.6 27.8 -0.6
Burundi 45.8 -1.0 51.9 -1.5 48.4 -0.4 44.6 -0.3 38.6 -1.9
Kenya 29.3 -0.2 30.4 0.3 31.5 0.2 29.5 -1.0 26.2 -0.4
Rwanda 38.2 0.0 37.6 2.3 43.6 -1.4 37.3 0.2 35.2 -1.2
Tanzania 37.5 -0.9 47.1 0.2 40.6 -2.7 32.7 -0.3 29.8 -0.7
Uganda 36.2 -1.6 51.9 -1.4 41.1 -4.0 26.6 -0.5 24.6 -0.5
28
Annex 2: Trends in crop productivity in East Africa Community countries (1965-2010)
Crop Country 1965-2010 1965-1970 1970-1975 1975-1980 1980-1985 1985-1990 1990-1995 1995-2000 2000-2005 2005-2010
(t/ha)i %ii (t/ha) % (t/ha) % (t/ha) % (t/ha) % (t/ha) % (t/ha) % (t/ha) % (t/ha) % (t/ha) %
Cereals
Burundi 1.19 0.74 1.03 2.44 1.07 -0.78 1.12 -0.24 1.10 1.44 1.25 3.31 1.35 -0.73 1.33 -1.85 1.31 1.18 1.33 -0.08
Kenya 1.49 0.55 1.23 2.81 1.32 1.86 1.41 -3.79 1.57 2.26 1.69 -1.20 1.68 2.29 1.49 -2.81 1.59 3.65 1.57 -2.54
Rwanda 1.14 0.17 1.11 -4.48 1.05 -1.80 1.12 1.69 1.16 -0.18 1.19 -3.13 1.15 0.99 1.03 -8.15 0.98 5.00 1.38 12.22
Tanzania 1.15 1.73 0.68 -6.62 0.78 10.69 1.04 0.82 1.23 6.17 1.33 3.71 1.32 1.56 1.47 -1.28 1.46 -9.14 1.33 4.01
Uganda 1.36 1.08 1.06 8.87 1.21 -0.33 1.35 3.86 1.42 -3.02 1.42 2.51 1.51 1.03 1.45 3.04 1.58 -0.96 1.70 6.66
Regional 1.29 0.96 0.99 1.88 1.09 3.19 1.22 -1.00 1.35 3.06 1.44 1.69 1.45 2.06 1.45 -1.38 1.46 -3.50 1.46 3.13
Maize
Burundi 1.14 0.01 1.07 3.08 1.12 -1.61 1.16 -0.36 1.13 1.48 1.29 2.41 1.35 -1.77 1.20 -4.34 1.08 0.35 1.03 -1.36
Kenya 1.53 0.70 1.18 3.56 1.29 2.89 1.44 -4.51 1.63 3.98 1.81 -1.01 1.78 2.42 1.57 -3.22 1.64 3.20 1.60 -2.43
Rwanda 1.16 -0.22 1.18 -6.35 1.05 -1.60 1.11 1.24 1.21 0.57 1.31 -1.41 1.33 5.45 0.93 -10.21 0.80 3.10 1.31 25.59
Tanzania 1.25 1.89 0.67 -9.61 0.78 15.15 1.22 1.02 1.33 1.19 1.37 4.21 1.42 4.98 1.80 2.06 1.81 -17.53 1.30 4.67
Uganda 1.39 1.17 1.08 8.91 1.27 -3.27 1.32 1.17 1.24 -1.13 1.27 6.50 1.51 2.09 1.52 4.28 1.69 -3.91 1.80 10.74
Regional 1.36 1.04 0.98 0.84 1.09 5.14 1.32 -1.76 1.43 2.10 1.52 1.75 1.56 3.94 1.60 -0.79 1.59 -7.12 1.46 3.98
Beans, Dry
Burundi 1.00 -0.27 1.03 -0.58 1.01 -0.51 1.02 -0.39 0.99 -0.58 1.04 2.97 1.12 -4.36 1.01 -3.44 0.90 -2.60 0.89 2.70
Kenya 0.53 -0.49 0.50 2.77 0.54 0.60 0.57 -0.36 0.59 1.74 0.67 4.91 0.65 -10.51 0.40 1.44 0.42 -3.03 0.48 4.81
Rwanda 0.77 -0.19 0.82 3.97 0.82 -4.96 0.78 -2.46 0.79 4.21 0.82 -3.31 0.74 -1.63 0.65 -1.62 0.66 -1.34 0.88 8.52
Tanzania 0.63 1.21 0.52 1.47 0.52 -0.48 0.52 0.12 0.56 5.54 0.71 3.24 0.76 0.79 0.79 0.58 0.74 -2.64 0.75 2.73
Uganda 0.67 -0.60 0.70 -9.47 0.61 2.02 0.74 -3.94 0.73 4.69 0.77 1.49 0.73 -3.87 0.53 4.41 0.64 -2.49 0.51 -2.61
Regional 0.69 -0.33 0.73 -1.20 0.69 -0.91 0.71 -2.72 0.70 3.07 0.78 1.74 0.76 -4.61 0.62 0.11 0.63 -2.39 0.63 2.97
Rice, paddy
Burundi 2.73 1.80 1.72 -4.63 1.84 9.79 2.19 2.58 2.82 13.31 3.33 -2.19 3.18 -1.53 3.00 2.93 3.23 1.76 3.34 -0.79
Kenya 4.00 -1.45 5.35 -4.24 4.96 1.05 5.16 -6.22 3.75 -5.18 3.26 4.67 3.84 5.23 4.09 -0.32 3.68 1.61 2.85 -4.28
Rwanda 2.92
2.12
2.48 5.18 2.69 4.88 2.94 -11.55 2.03 -1.24 2.52 16.28 2.74 -10.07 3.50 9.64 4.72 4.35
Tanzania 1.51 1.42 1.00 -6.70 1.36 9.75 1.27 -2.95 1.28 13.11 1.87 0.13 1.67 -1.53 1.58 4.42 1.82 -3.49 1.92 2.54
Uganda 1.30 1.36 1.09 -17.20 0.86 2.41 1.17 8.65 1.32 -2.29 1.31 2.51 1.38 0.54 1.41 1.19 1.47 -1.26 1.75 13.03
Regional 1.60 1.20 1.14 -6.35 1.46 7.98 1.38 -1.99 1.40 10.82 1.92 0.14 1.75 -1.50 1.66 3.76 1.87 -2.63 1.98 3.08
Wheat
Burundi 0.74 0.71 0.66 -3.47 0.60 0.91 0.70 -0.52 0.65 -1.79 0.83 2.90 0.75 1.42 0.78 -2.62 0.80 1.03 0.83 2.05
Kenya 1.79 1.09 1.50 4.87 1.54 -1.23 1.68 5.65 1.96 -5.51 1.69 -2.98 1.86 4.10 1.81 -5.47 2.16 8.40 2.51 1.83
Rwanda 0.92 0.54 0.84 1.52 0.85 -2.39 0.78 -3.92 0.85 5.59 1.06 3.89 1.17 -1.95 0.87 -11.22 0.75 6.16 1.20 15.92
29
Crop Country 1965-2010 1965-1970 1970-1975 1975-1980 1980-1985 1985-1990 1990-1995 1995-2000 2000-2005 2005-2010
(t/ha)i %ii (t/ha) % (t/ha) % (t/ha) % (t/ha) % (t/ha) % (t/ha) % (t/ha) % (t/ha) % (t/ha) %
Tanzania 1.43 0.41 1.08 -1.04 1.21 13.00 1.47 2.68 1.57 1.95 1.75 1.26 1.52 -8.23 1.20 -14.85 2.04 31.77 1.46 -22.02
Uganda 1.94
2.16
2.11 3.53 2.12 -4.28 2.05 -1.51 2.01 3.06 1.83 -1.43 1.79 -0.59 1.70 -0.87 1.71 -0.64
Regional 1.60 0.77 1.36 3.68 1.39 2.47 1.56 3.96 1.75 -3.27 1.64 -1.41 1.70 1.36 1.55 -7.68 1.92 11.64 1.94 -3.20
Millet
Burundi 1.03 0.59 0.92 -0.79 0.90 0.40 0.95 1.01 1.00 0.00 1.04 1.99 1.15 3.78 1.25 -5.59 1.08 0.67 1.08 0.57
Kenya 1.02 -3.23 1.76 -1.38 1.71 -1.06 1.49 -6.49 0.75 -6.14 0.70 -5.60 0.61 1.96 0.48 4.65 0.52 2.79 0.64 -2.41
Rwanda 0.68 1.19 0.57 0.55 0.65 -5.34 0.57 -2.24 0.57 -0.19 0.46 -15.87 0.67 34.89 0.80 -2.27 0.80 -0.43 0.96 11.69
Tanzania 0.86 0.40 0.66 0.55 0.67 1.90 0.89 -1.86 1.17 11.02 1.00 -0.41 0.92 1.30 0.99 -4.52 0.75 -5.81 0.82 2.66
Uganda 1.35 1.18 1.04 8.30 1.17 2.23 1.33 4.79 1.45 -3.63 1.52 1.13 1.53 0.64 1.43 1.93 1.53 2.81 1.73 3.95
Regional 1.13 0.45 1.01 5.34 1.09 1.58 1.14 -1.62 1.22 3.52 1.20 0.57 1.20 1.16 1.17 -0.21 1.12 0.55 1.28 3.27
Sorghum
Burundi 1.09 0.78 1.00 -0.29 0.98 0.33 0.98 0.40 1.00 0.00 1.01 1.92 1.14 1.51 1.26 -2.13 1.26 0.93 1.28 0.68
Kenya 0.90 -1.02 1.09 -0.82 1.09 -0.64 1.01 -3.12 0.73 -9.96 0.88 2.92 0.86 -6.82 0.69 3.94 0.83 5.19 0.80 -11.28
Rwanda 1.10 -0.17 1.11 -4.55 1.06 -1.88 1.14 1.70 1.14 -0.83 1.14 -4.06 1.04 -2.70 1.07 -7.76 0.99 3.12 1.11 1.29
Tanzania 0.86 1.52 0.55 -5.36 0.54 2.85 0.66 9.12 1.08 13.17 1.04 0.83 1.03 -2.21 1.00 -8.88 0.86 -0.01 1.03 1.33
Uganda 1.34 0.44 1.08 10.52 1.29 -1.39 1.44 5.69 1.64 -4.02 1.50 -0.42 1.50 0.12 1.33 1.48 1.45 1.76 1.35 -6.65
Regional 1.02 0.40 0.91 1.56 0.96 -1.30 0.93 1.62 1.11 4.51 1.12 1.00 1.12 -1.57 1.06 -4.89 1.03 2.07 1.09 -2.22
Cassava
Burundi 8.92 -0.16 9.07 -0.04 9.02 0.14 9.14 0.02 9.12 -0.06 8.94 -1.06 8.96 -0.98 8.71 1.38 8.41 -4.16 8.60 2.47
Kenya 8.71 0.38 7.89 0.44 8.03 0.16 7.90 -0.51 8.78 1.24 9.96 -0.72 10.01 -2.54 9.23 -5.60 8.36 7.38 9.46 -4.34
Rwanda 8.12 -2.31 10.50 -0.34 12.18 0.78 12.32 1.53 11.46 -3.45 6.79 -27.30 2.22 -4.09 3.28 15.29 6.75 -0.39 8.24 13.86
Tanzania 8.00 0.13 5.24 -1.75 5.33 7.00 10.47 7.81 11.43 -0.99 10.87 0.89 11.16 -5.01 8.48 -8.28 6.06 -5.42 6.02 -3.39
Uganda 7.98 2.82 4.25 5.04 5.12 -1.00 5.15 1.72 8.54 1.27 8.75 -0.07 7.72 -4.86 9.08 16.53 13.46 2.19 13.06 -2.05
Regional 7.84 0.93 5.39 0.15 5.59 3.08 8.11 6.33 10.25 0.22 9.79 -1.56 9.08 -3.83 8.32 0.13 8.30 -2.03 8.26 -0.50
Source: Authors calculation based on FAOSTAT | © FAO Statistics Division 2013 | 20 June 2013
Notes: blank cells indicate missing values. Regional aggregate values are calculated as weighted summations. The weights are computed using countries area harvested (ha) as a share of regional area
harvested.
Annual average level (t/ha) – this applies to all columns with (t/ha) in this table
1 Annual average percentage change – this applies to all columns with (%) in this table
1 Annual average level (t/ha) – this applies to all columns with (t/ha) in this table
1 Annual average percentage change – this applies to all columns with (%) in this table
30
Annex 3: Number of animals 000' (heads) producing beef and milk
Country
Annual average level of number of animals 000' Percentage change in number of animals (t/ha)
1965-
2010
1965-
1970
1970-
1975
1975-
1980
1980-
1985
1985-
1990
1990-
1995
1995-
2000
2000-
2005
2005-
2010
1965-
2010
1965-
1970
1970-
1975
1975-
1980
1980-
1985
1985-
1990
1990-
1995
1995-
2000
2000-
2005
2005-
2010
Cattle meat producing animals/slaughtered (Head)
Burundi 61 63 78 90 76 82 50 33 39 48 -1.7 6.6 2.8 3.0 -2.8 -1.9 -11.2 2.3 5.1 -5.5
Kenya 1652 816 998 1303 1522 1719 1861 2108 2170 2975 3.0 4.0 2.4 10.2 3.2 3.3 1.1 0.6 8.8 3.2
Rwanda 135 59 73 107 129 132 119 138 203 308 3.5 3.6 9.1 3.0 2.6 0.1 -7.2 12.0 6.9 8.7
Tanzania 1652 981 1099 1250 1400 1742 1998 2042 2400 2618 2.6 4.4 2.7 1.6 4.8 4.0 3.3 1.3 2.8 1.4
Uganda 572 426 511 578 580 474 570 609 714 821 1.3 3.7 2.6 2.2 1.0 0.5 1.1 2.6 3.6 2.5
Regional 4071 2346 2759 3328 3707 4149 4599 4929 5526 6771 2.5 4.1 2.8 5.0 3.3 3.0 1.7 1.5 5.4 2.6
Cow milk, whole, fresh - milk animals (head)
Burundi 93 104 131 139 95 94 93 69 49 73 -1.9 5.7 3.8 -1.9 -5.5 0.9 -3.7 -5.8 -5.2 28.0
Kenya 3418 1727 1967 2073 2501 4125 4422 4523 4904 5970 3.3 1.5 0.7 1.3 9.9 8.5 -1.3 0.8 7.0 -3.4
Rwanda 146 77 87 100 133 146 156 192 234 262 3.2 8.3 -1.9 7.2 1.7 -1.2 1.6 8.7 2.5 3.1
Tanzania 3094 1914 2004 2154 2504 2903 3175 3400 4423 6348 2.9 5.7 -1.8 2.4 2.6 2.5 1.3 1.2 10.6 4.5
Uganda 1326 620 750 920 973 1069 1290 1383 2240 3158 3.7 4.1 3.1 5.6 1.2 3.8 1.0 2.6 17.8 3.0
Regional 8077 4442 4938 5385 6206 8338 9136 9567 11849 15812 3.1 3.9 0.0 2.5 5.1 5.4 -0.1 1.3 10.0 1.3
31
Annex 4: Beef and milk productivity and its growth
Country
Annual average level (kg/animal Annual percentage average change
1965-
2010
1965-
1970
1970-
1975
1975-
1980
1980-
1985
1985-
1990
1990-
1995
1995-
2000
2000-
2005
2005-
2010
1965-
2010
1965-
1970
1970-
1975
1975-
1980
1980-
1985
1985-
1990
1990-
1995
1995-
2000
2000-
2005
2005-
2010
Cattle meat yield/carcass weight (kg/animal)
Burundi 160 130 130 130 130 140 170 200 220 200 1.4 0.0 0.0 0.0 0.0 3.9 0.0 10.0 -5.3 0.0
Kenya 140 140 140 130 120 130 130 120 150 150 0.1 0.1 -1.8 -1.9 -1.5 -0.2 0.1 1.4 -0.2 0.1
Rwanda 100 100 100 100 100 100 100 100 100 100 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Tanzania 100 100 100 100 100 100 110 110 110 110 0.2 -0.9 -3.3 0.9 0.7 0.0 0.7 0.4 -0.1 0.0
Uganda 150 150 150 150 150 150 150 150 150 150 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Regional 120 130 120 120 120 120 120 120 130 130 0.1 -0.3 -1.9 -0.2 -0.6 -0.2 0.2 0.7 0.2 0.1
Cow milk, whole, fresh yield (kg/animal)
Burundi 350 350 350 350 350 350 350 350 350 350 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 -0.2
Kenya 490 450 450 460 460 490 470 460 550 620 0.7 0.7 0.6 0.0 0.1 2.1 -1.4 2.6 -2.9 10.2
Rwanda 460 300 290 420 510 560 540 500 500 580 1.6 0.0 -3.1 16.0 -0.6 2.2 -2.6 -2.0 -1.1 2.7
Tanzania 180 160 160 160 160 160 170 190 220 240 1.0 0.0 0.0 0.0 0.0 1.2 1.3 3.2 3.0 -0.6
Uganda 350 350 350 350 350 350 350 350 350 350 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Regional 340 310 310 320 320 360 350 350 390 410 0.7 -0.4 0.9 0.2 1.2 2.6 -1.2 2.2 -1.6 3.8
32
Annex 5: Average area harvested (Million ha) per crop
Annual average level (Million ha)
Country
1965-
2010
1965-
1970
1970-
1975
1975-
1980
1980-
1985
1985-
1990
1990-
1995
1995-
2000
2000-
2005
2005-
2010
Cereals
Burundi 0.195 0.154 0.155 0.176 0.208 0.224 0.208 0.202 0.208 0.221
Kenya 1.853 1.640 1.762 1.933 1.571 1.823 1.795 1.895 2.006 2.251
Rwanda 0.240 0.174 0.197 0.224 0.261 0.244 0.197 0.194 0.315 0.356
Tanzania 2.928 1.661 1.809 2.574 2.529 3.003 2.917 2.898 3.776 4.962
Uganda 1.248 1.218 1.271 1.121 0.812 0.942 1.183 1.336 1.479 1.763
Regional 6.464 4.848 5.193 6.028 5.381 6.236 6.300 6.525 7.784 9.552
Maize
Burundi 0.119 0.111 0.114 0.122 0.130 0.130 0.119 0.115 0.114 0.117
Kenya 1.441 1.226 1.333 1.467 1.229 1.416 1.397 1.496 1.588 1.811
Rwanda 0.079 0.044 0.056 0.069 0.079 0.079 0.068 0.070 0.104 0.140
Tanzania 1.665 1.016 1.033 1.283 1.367 1.778 1.630 1.429 2.221 3.046
Uganda 0.489 0.298 0.362 0.402 0.289 0.349 0.483 0.601 0.700 0.880
Regional 3.792 2.694 2.899 3.343 3.093 3.751 3.696 3.711 4.727 5.994
Millet
Burundi 0.010 0.009 0.010 0.010 0.011 0.012 0.012 0.009 0.009 0.010
Kenya 0.086 0.075 0.077 0.080 0.056 0.092 0.094 0.088 0.105 0.103
Rwanda 0.004 0.003 0.004 0.005 0.003 0.002 0.002 0.003 0.005 0.005
Tanzania 0.272 0.199 0.204 0.352 0.325 0.287 0.258 0.251 0.274 0.296
Uganda 0.442 0.626 0.571 0.435 0.314 0.348 0.394 0.392 0.400 0.444
Regional 0.814 0.911 0.865 0.882 0.708 0.741 0.760 0.744 0.793 0.858
Rice, paddy
Burundi 0.010 0.002 0.003 0.004 0.004 0.010 0.012 0.016 0.019 0.022
Kenya 0.011 0.004 0.007 0.008 0.011 0.014 0.012 0.012 0.013 0.019
33
Rwanda 0.005 0.000 0.001 0.001 0.002 0.004 0.005 0.003 0.008 0.015
Tanzania 0.368 0.117 0.159 0.246 0.259 0.329 0.360 0.466 0.554 0.789
Uganda 0.043 0.007 0.017 0.018 0.014 0.023 0.050 0.063 0.085 0.106
Regional 0.437 0.129 0.187 0.277 0.292 0.380 0.438 0.559 0.679 0.950
Sorghum
Burundi 0.046 0.022 0.020 0.033 0.053 0.063 0.055 0.052 0.055 0.063
Kenya 0.158 0.196 0.204 0.209 0.136 0.135 0.121 0.131 0.133 0.157
Rwanda 0.144 0.125 0.133 0.145 0.175 0.151 0.115 0.112 0.181 0.159
Tanzania 0.557 0.291 0.347 0.640 0.524 0.558 0.610 0.662 0.661 0.727
Uganda 0.269 0.286 0.317 0.260 0.190 0.217 0.253 0.275 0.286 0.322
Regional 1.173 0.920 1.022 1.286 1.078 1.124 1.153 1.230 1.316 1.428
Wheat
Burundi 0.010 0.011 0.008 0.007 0.011 0.011 0.012 0.011 0.010 0.010
Kenya 0.132 0.126 0.114 0.113 0.113 0.147 0.147 0.144 0.145 0.139
Rwanda 0.010 0.001 0.002 0.004 0.003 0.007 0.007 0.006 0.016 0.036
Tanzania 0.053 0.039 0.065 0.051 0.050 0.048 0.049 0.067 0.042 0.068
Uganda 0.006 0.002 0.004 0.006 0.005 0.004 0.005 0.006 0.008 0.011
Regional 0.210 0.178 0.193 0.181 0.182 0.217 0.220 0.233 0.221 0.265
Beans, dry
Burundi 0.266 0.251 0.271 0.285 0.286 0.290 0.284 0.257 0.250 0.230
Kenya 0.531 0.123 0.218 0.352 0.452 0.552 0.621 0.745 0.881 0.861
Rwanda 0.249 0.152 0.169 0.220 0.288 0.300 0.198 0.244 0.337 0.338
Tanzania 0.506 0.225 0.268 0.402 0.476 0.391 0.512 0.621 0.741 0.922
Uganda 0.506 0.219 0.369 0.337 0.334 0.421 0.544 0.643 0.769 0.883
Regional 2.058 0.969 1.295 1.595 1.835 1.953 2.160 2.510 2.979 3.235
Cassava
Burundi 0.058 0.043 0.042 0.044 0.050 0.063 0.063 0.068 0.084 0.070
Kenya 0.062 0.062 0.067 0.077 0.063 0.058 0.050 0.059 0.062 0.058
34
Rwanda 0.078 0.023 0.030 0.038 0.048 0.071 0.124 0.090 0.128 0.147
Tanzania 0.693 0.655 0.740 0.508 0.600 0.691 0.636 0.675 0.810 0.912
Uganda 0.385 0.316 0.501 0.467 0.336 0.362 0.364 0.357 0.398 0.396
Regional 1.277 1.099 1.380 1.135 1.097 1.245 1.236 1.247 1.482 1.582
Annex 6: Growth of area harvested per crop
Annual average change ha
Country
1965-
2010
1965-
1970
1970-
1975
1975-
1980
1980-
1985
1985-
1990
1990-
1995
1995-
2000
2000-
2005
2005-
2010
Cereals,Total + (Total)
Burundi 1.01 1.00 1.00 1.05 1.01 1.00 0.97 1.00 1.01 1.02
Kenya 1.01 1.03 1.04 0.98 0.99 1.00 1.01 1.00 1.01 1.02
Rwanda 1.01 1.06 1.01 1.02 1.04 0.99 0.83 1.16 1.04 1.02
Tanzania 1.02 1.03 1.02 1.07 0.98 0.99 0.99 0.97 1.19 1.04
Uganda 1.01 1.02 1.01 0.88 1.03 1.06 1.05 1.01 1.03 1.04
Regional 1.01 1.03 1.02 1.00 0.99 1.01 1.00 0.99 1.10 1.03
Maize
Burundi 1.00 1.01 1.01 1.01 1.00 0.99 0.98 0.99 1.00 1.02
Kenya 1.01 1.03 1.05 0.97 1.00 1.00 1.02 1.01 1.01 1.02
Rwanda 1.02 1.10 1.04 1.03 1.04 1.03 0.84 1.10 1.04 1.10
Tanzania 1.02 1.00 1.02 1.04 1.02 1.01 0.94 0.93 1.34 1.02
Uganda 1.03 1.02 1.09 0.87 1.04 1.08 1.08 1.02 1.05 1.05
Regional 1.02 1.02 1.04 0.99 1.01 1.01 0.99 0.98 1.14 1.03
Millet
Burundi 1.00 1.03 0.99 0.99 1.04 1.00 0.96 0.96 0.98 1.06
Kenya 1.01 1.00 1.01 1.00 0.87 1.12 0.99 1.00 1.00 0.96
Rwanda 1.01 0.96 1.05 0.95 0.78 1.36 0.71 1.46 0.99 1.03
35
Tanzania 1.01 1.04 0.99 1.20 0.93 0.90 1.03 1.01 1.05 1.06
Uganda 0.99 1.03 0.95 0.89 1.02 1.05 1.01 0.99 1.02 1.02
Regional 1.00 1.03 0.97 1.01 0.96 1.00 1.01 1.00 1.03 1.03
Rice, paddy
Burundi 1.07 1.28 0.98 1.05 1.02 1.20 0.96 1.08 1.03 1.05
Kenya 1.03 1.19 1.02 1.09 1.09 0.98 0.96 1.03 1.01 1.03
Rwanda 1.09 1.05 1.15 1.14 0.63 1.43 1.28 1.00
Tanzania 1.05 1.16 1.04 1.03 0.98 1.10 1.00 0.99 1.12 1.11
Uganda 1.07 1.30 0.97 0.88 1.07 1.21 1.07 1.06 1.07 0.96
Regional 1.05 1.17 1.04 1.02 0.99 1.11 1.00 1.01 1.11 1.09
Sorghum
Burundi 1.03 0.98 0.99 1.23 1.01 1.00 0.96 1.00 1.01 1.02
Kenya 0.99 1.04 1.01 1.00 1.02 0.95 1.03 0.99 0.99 1.08
Rwanda 1.00 1.06 1.00 1.02 1.04 0.94 0.84 1.20 1.02 0.93
Tanzania 1.02 1.07 1.06 1.10 0.91 0.92 1.10 1.01 0.99 0.98
Uganda 1.00 0.99 1.01 0.87 1.04 1.05 1.02 1.01 1.01 1.04
Regional 1.01 1.03 1.02 1.03 0.96 0.96 1.04 1.02 1.00 1.00
Wheat
Burundi 1.00 0.92 0.98 0.98 1.08 0.99 0.98 0.95 1.02 1.00
Kenya 1.01 1.05 0.95 0.99 1.05 1.03 0.99 0.96 1.04 1.00
Rwanda 1.09 1.38 1.20 1.03 1.18 1.14 0.80 1.07 1.22 1.19
Tanzania 1.00 1.11 0.93 1.05 0.95 1.07 1.00 1.05 0.87 1.14
Uganda 1.06 1.00 0.91 0.91 1.14 1.07 1.05 1.06
Regional 1.01 1.06 0.95 1.01 1.02 1.03 0.99 0.99 1.01 1.06
Beans, dry
Burundi 1.00 1.04 1.00 0.99 0.99 0.96 1.01 0.94 1.03 0.96
Kenya 1.05 1.05 1.14 1.08 1.03 1.03 1.07 1.02 1.03 0.93
Rwanda 1.02 1.04 1.04 1.06 1.06 0.94 0.81 1.08 0.98 1.00
36
Tanzania 1.03 1.04 1.00 1.16 0.97 1.03 1.05 1.03 1.06 1.04
Uganda 1.03 1.13 1.05 0.87 1.08 1.08 1.04 1.03 1.03 1.03
Regional 1.03 1.06 1.04 1.03 1.02 1.01 1.03 1.02 1.03 1.00
Cassava
Burundi 1.02 1.00 1.01 1.00 1.05 1.03 0.98 1.04 1.04 0.96
Kenya 1.00 1.02 1.02 1.03 0.94 1.02 0.98 1.04 0.90 1.07
Rwanda 1.05 1.14 1.01 1.07 1.04 1.18 0.91 1.14 0.99 1.13
Tanzania 1.01 1.03 1.02 0.92 1.12 0.97 1.01 1.06 1.06 1.00
Uganda 1.00 1.09 1.02 0.86 1.02 1.06 0.95 1.04 1.00 1.02
Regional 1.01 1.05 1.02 0.91 1.07 1.01 0.98 1.06 1.03 1.02
i Annual average level (t/ha) – this applies to all columns with (t/ha) in this table ii Annual average percentage change – this applies to all columns with (%) in this table
37
Appendix 7: Indicative achievements of selected productivity enhancing interventions
Project
Examples of Achievements***
Farm Africa
Goat model
Farm-Africa
(2005).
The model has been particularly successful in Kenya; more than 50,000 cross-bred dairy
goats have been produced in the last 10 years
The immediate impacts of the project were both at individual and group level. Individual
farmers have been able to own the assets (dairy goats), obtain milk for home consumption
which resulted in improved nutrition for the family (see Ayele and Peacock, 2003). Income
earned through sales of both milk and animals, and manure is available for crop production
enterprises.
Milk production increased from about 250 ml by indigenous goats to 1 litre by F1s and 2
litres by 75% exotic goats.
Crossbred goats fetch more prices than local ones hence providing farmers with more
income from sale of animals for example Ojango et al, 2010 found that the prices of
breeding goats within the community in the Eastern Highlands of Kenya ranged from $25
for an indigenous goat to US $154 for a crossbred and US $415 for a pure-bred Toggenbu
PUSH-PULL -
ICIPE The technology has been adopted by over 40,000 smallholder farmers in East Africa,
where maize yields have been increased from 1 t/ha to 3.5 t/ha, achieved with minimal
inputs.
This is a low cost technology that simultaneously addresses the major constraints of
cereal-based farming systems such as striga weeds, stemborers and poor soil fertility.
The technology encourages crop-livestock interaction, the technology incorporates
growing of fodder crops such as Nappier grass and desmodium as repellant for striga
Participatory
Irrigation
Development
Programme
(PIDP)
25 400 people benefited from the programme
increased water availability for agriculture and hence increase in productivity – for example
in paddy – from an average of 0.5 to 2 tonnes per hectare
Improved water management systems in the programme areas
Wei Wei
integrated
project
(WWIDP)
Maize and sorghum yields increased from 0.5 t/ha for each crop to 3.5 t/ha and 4 t/ha,
respectively (See Annex 1).
New crops such as green grams, cowpeas and okra were introduced.
The project created employment and income-generation opportunities
Adoption of innovations, not only within the project area but also in areas outside the
project. The community members are expanding land under irrigation on their own
initiative.
Strengthening social capital through increased commercial activities.
Farmers have organized themselves into groups to negotiate for better prices for their
produce.
38
System of
rice
Intensification
(SRI)
Due to investment in irrigation and rehabilitation of the marshland for rice production area
under rice cultivation in Rwanda has increased. The total number of rice farmers has been
increasing.
Increase in rice yields reported, example at country level yields increased from an average
of 3 t/ha in 2002 to 5.2 in 2009. Higher yields have been recorded in some selected sites. In
Kibaza, rice yields increased from 4 t/ha to at least 6 t/ha, for a total production of 135
tonnes. In Rwabutazi, yields rose from 4 t/ha to at least 7 t/ha, for a total production of 401
tonnes in 2008.
Replication of SRI in the marshlands of another project in Rwanda, the Rural Sector Support
Project (RSSP), is ongoing
East Africa
Dairy
Development
Project
(EADD)
EADD beneficiary households earn considerably more income, own more assets, and have
greater household dietary diversity than their non-beneficiary counterparts residing in
catchment areas.
Has developed a number of milk collection hubs, including chilling plants for bulking and
holding milk for pick up by processors in refrigerated milk trucks, satellite coolers have
been installed near villages and this has helped improve milk quality. Time spent on
transportation is reduced, hence reducing the possibilities of milk spoilage.
Artificial insemination is being used to improve local breeds of dairy cows to produce more
milk per day
Farmers have been trained in dairy animal husbandry, business practices, and other subjects
needed to for successful operation of a business to produce, process and market dairy
products.
NERICA
(New Rice
for Africa)-
Uganda
More than 30 districts in Uganda, previously not traditional rice growing districts, have
embraced upland rice production.
There are about 35,000 ha under NERICA4 in Uganda(Diagne, 2010)
Kijima et al (2008) found that the percentage of households that grow NERICA varieties in
Uganda increased from 0.9% in 2002 to 2, 9% in 2003 and reached 16.5% in 2004.
NERICA has had positive effects on productivity, rice yields have increased (Kijima et al,
2006and Kijima et al 2008).
Cassava
Nigeria Before the commencement of the project, the average yield in the project sites was about
11.2. In 2009, when the project ended farmers that participated in the project had achieved
an average yield of 29 tonnes/hectare while those that did not participate (and used non-
CMD resistant varieties) had yields of 12 tonnes/hectare.
*** This is only an indicative list and not an exhaustive list of achievements
