Drivers of agricultural productivity in Uganda

Academic Paper, 2021

15 Pages, Grade: 5.00





Data and methods

Household characteristics
Agricultural practices
Land characteristics
Land characteristics vs agricultural productivity



Drivers of agricultural productivity in Uganda

Baguma Brian1


The major objective of this study is to investigate factors that significantly affect agricultural productivity in Uganda. It entirely made use of secondary data from Uganda National Panel Survey (UNPS) for the 2013/2014 round since it is the most recent wave available at the Uganda Bureau of Statistics (UBOS). Given the survey data, non-parametric methods were used in data analysis to answer the research hypotheses. In this research we narrow our focus on drivers of agricultural productivity which are connected to socio-economic characteristics of the household head, the agricultural practices followed by the household as well as the characteristics of the soil cultivated by the household. Research results are based on the answers of 2492 Ugandan households. Results from the model revealed that Ugandan household’s agricultural productivity is highly dependent on the gender and age of the household head. Agricultural productivity of households was found to be significantly higher in the Western than in the Eastern and Northern region. The use of improved seeds and keeping improved breeds of animals found to significantly affect agricultural productivity. Results also revealed that agricultural productivity is dependent of topography, land quality (as reported by respondents), soil type, and the use of extension services.

Keywords: agricultural productivity, Uganda, land use


Agriculture is key to Africa’s future. The continent has the largest proportion of the world’s arable land, with over half of its population employed in the sector, and also agriculture is the largest contributor to total gross domestic product (GDP). Yet, the same continent continues to produce very little food and low value-added products. Productivity has been stagnant since the 1980s (AGRA, 2018). In most developing countries agriculture is the source of food for communities and a means of livelihood for the vulnerable people. Raising agricultural productivity is an important policy goal for concerned governments and development agencies (Kuku, Ajibola, & Saweda, 2011; Amone, 2014).

Most literatures across developing countries document that improving agricultural productivity is the main pathway out of poverty. These literatures conclude that agricultural productivity has a significant and positive impact on household consumption growth (Muyanga, Jayne, and Burke 2013; Dar and Laxmipathi Gowda 2013; F. Darko, A. Palacios-Lopez, T. Kilics, 2018). Results have shown that while agricultural productivity has a positive impact on welfare growth for non-poor households, it also has a negative impact for poor households (Amare et al., 2016).

According to the FAO, Uganda's fertile land has the capability to feed 200 million people (J. Popp, J. Oláh, A. Kiss, Z. Lakner, 2019). Today, 80 percent of Uganda’s land is arable but only 35 percent is being cultivated. Agriculture accounted for about 23.6 percent of GDP in 2016, and 46 percent of export earnings, and the Uganda Bureau of Statistics (UBOS) estimates that about 72 percent of all Uganda’s working population is employed in agriculture. Despite the relatively high GDP growth achieved in Uganda in the last two decades, agriculture and its productivity have not grown consistently (Amone, 2014). In spite of generally favorable agriculture conditions, agricultural productivity remains low and poverty afflicts more than 40 percent of the national population (Walaga et al., 2000).

However, agriculture productivity has been reducing over the last decade mainly due to a number of factors such as: high costs of inputs, poor production techniques, limited extension services, dependency on rain to feed agricultural lands, limited markets, land tenure challenges and lack of technology and innovation. Uganda aspires to transform the agriculture sector from subsistence farming to commercial agriculture (Blind, 2006).

Productivity is a key determinant of agricultural transformation. This means that when productivity is on a rise, farm households gain assets and become confident enough to release household labor to the value-added agricultural activities and non-agricultural productive activities. Higher productivity will then generate surpluses to be used as cheap raw material to support a competitive industrial sector through agro-processing. In addition, the food surpluses lower food prices and the living costs, therefore this increases disposable income of non-food producers and moderates wage increases to enhance the competitiveness among the African countries in labor-intensive manufacturing (A. Abunga, 2016; ACET, 2017).

Thirlwall A.P, (1999) notes that in some cases, there has always been an inappropriate labor to land ratio combined with a lack of appropriate and complementary inputs while in others, it is the structure and organization of agriculture and in for most, it is a combination of both entangled with unfavorable natural factors. He concludes by saying emphasis on policies to raise the level of farm productivity is the most urgent development priority.

The key challenge in these countries is how to increase agricultural productivity to meet food security for the growing population while also reducing poverty among smallholder farmers. This study seeks to study the determinants of agricultural productivity in households of Uganda.

This article adds to the existing literature and notes that however much challenging productivity is in Uganda, Agricultural productivity is dependent on the country’s administrative regions with the Western and Central regions being much more productive than the Northern and the Eastern regions, this is true for both crop and animal productivity.

Data and methods

The study will use a nationally representative data from Uganda National Panel Survey (UNPS) for the 2013/2014 round. The UNPS is a yearly multi-topic panel household survey that commenced in 2009/2010 to inform policymaking through descriptive reports.

The Uganda National Panel Survey structure comprises of the following topics: Households, Women, Agriculture, Community or Facility. However, for this study focus is placed on the household identification, land holdings, labor inputs, crops grown, types of seeds used, agricultural production, livestock owned, inputs, livestock production, extension services, farm implements and machinery.

The unit of observation in UNPS varies across different sections. Since our unit of analysis is the household, we had to aggregate most of the data to the household level. Animal productivity was calculated by first aggregating for meat productivity, milk productivity, poultry productivity, egg productivity and small animals’ productivity; each of these was changed into z score and then summed up the z scores to create animal productivity. Standardization of the different productivity sub-measures was necessary in order to the equal recognition of the sub-measures in the productivity measurement. After standardization, the sub-measures have been put to the same scale, while their relative importance did not change. Crop productivity was calculated by taking the monetary value of the output divided by the total land cultivated in acres. Due to the difference in calculation methodologies, animal and crop productivity were standardized by generating z scores to ensure that they were on the same scale before aggregation. All the aggregations were done by household unique identifier. Agricultural productivity was calculated by first calculating animal and crop productivity separately and then the mean to get agricultural productivity.

For land characteristics, the size of each of the land plots under a given category was obtained by summing up the sizes of the plots per household and its proportion of the total household land size ascertained by dividing the total land size under a given land characteristic by the total land size owned by the household.

Data were checked for outliers, inconsistencies and missing values where possible some of the records were eliminated to avoid inconsistencies in the results.

Table 1: Demographics of respondents

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Table 1 above represents the demographic characteristics of the household’s heads that participated in the survey and as can be observed, majority of the households are in rural areas, headed by males and who studied up to primary level. The households were evenly distributed across the 4 different regions of Uganda which is per the sampling design used.

Table 2: Agricultural practices used by respondents

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It can be seen that there is generally low uptake for some of the best practices that would boost agricultural productivity. The results reveal that less than 10% of the surveyed households; use fertilizers whether organic or inorganic, try out soil erosion control measures at their farms, keep improved breeds of cattle. Close to 20% of the households’ access extension services majority of which use government extension (NAADS) while a considerable proportion (40%) are able to provide drinking water to their animals more than twice a day.

Table 5: Characteristics of respondent’s land

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*Due to missing responses, the data is based on fewer acres

From the table, its observed that the biggest part of the land used is sandy loam that is either flat or gently sloping, biggest proportion of which is rated to be good in quality and therefore fit for agriculture.


Household characteristics

In the following section we will show information mainly on the household heads, and show the results of the bivariate analysis, which studies the factors of agricultural productivity.

Agriculture has a lot of gender related issues that need to be overcome if Uganda's productivity is to improve through agricultural transformation. There is a need to ensure that women equally benefit from the opportunities brought about by the transformation. (ACET, 2017). According to FAO (2011), Women produce over 90 percent of Uganda’s total food output, but they still lack the resources necessary to effectively produce crops on a sustainable scale. Women lack agricultural resources and opportunities needed to make the most productive use of their time and having indulged in farming and entrepreneurship, they still face tremendous challenges than the men in accessing agricultural resources, markets and services (Ann McKenna & Ann, 2014).

Table 7: Difference between agricultural productivity by the gender of the household head

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Table 7 shows, that there is significant difference in animal, crop and agricultural productivity between male and female headed households. Male headed households have higher productivity compared to female headed households because they have access to resources such as land enabling them to do productive work as opposed to females. Women often face an excessive work burden and that much of their labor remains unskilled, unpaid and unrecognized. The female headed households often get paid less than the male due to that they are less skilled, lack access to productive assets such as land and also makes it difficult to access subsidies or even be visible in agrarian communities. Women still have less connections to influential networks and markets. This 'gender gap' hinders the female households’ productivity and decreases their contribution to the agricultural sector and to the achievement of wider objectives for economic and social growth. Closing the gender gap in agriculture through addressing and recognizing that both men and women have equal rights to land and resources would ensure that both can maintain their livelihoods. Equal consideration of male and female household farmers would unlock the opportunity to maximize incomes, increase productivity and income earning potential.

Agricultural practices

Agriculture in Uganda is constantly declining due to the poor agricultural practice methods among the farmers. The primary components of the green revolution package for raising agricultural productivity are improved seed varieties, fertilizers, irrigation and access to water, and farmers’ knowledge of improved management practices (ACET, 2017).

Continued use of organic fertilizers results in increased organic soil matter, decreased erosion, enhanced penetration and aeration of water, increased biological activity of the soil as the materials decompose in the soil, and increased yields after the year of application (residual effects). And also, with the exception of green manures, if organic fertilizers are combined with nitrogen-based mineral fertilizers or other nitrogen-rich organic materials, there is a significant crop response (F. Mtambanengwe, P.Kosina, 2007).

Table 12: Difference between agricultural productivity by fertilizer use

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From Table 12, it can be observed that there is significant difference in crop and agricultural productivity of farmers who make use of fertilizers and those who do not, the results are significant at 5% level of significance. Fertilizers improve soils fertility and boost agricultural productivity. Fertilizers replenish essential nutrients after each harvest, naturally occurring such as nitrogen, phosphorus, and potassium that are also found to a lesser extent in manure and compost. Fertilizers enable farmers to grow more on their land and provide food and nutrition for all. Using fertilizers responsibly, efficiently, and sustainably helps to maintain soil fertility, increase food production, improve farmers’ livelihoods and safeguard natural habitats.

The aim of agricultural extension or advisory services is to support farmers by conducting research and development, by promoting the scaling-up of effective developments, by providing educational, technical and financial services and by empowering them through farmers' organizations to protect their own interests. The Ugandan government turned its public extension system into an innovative public-private partnership organization in 2001 in an effort to improve the quality and efficiency of rural service delivery. Farmers' demand for services under the National Agricultural Advisory Services (NAADS) program is met by independent agents working on a short-term contract basis (Dr Lorenz Bachmann, David Kersting 2017). For example, various organizational performance problems and evolving institutional mandates have hindered the efficiency and efficacy of the public extension system in the NAADS. These concerns include insufficient extension staff, corruption, insufficient central government support, a limited number of private-public partnerships, and a continued top-down linear emphasis on extension (Mildred Barungi, 2016).

Table 13: Access to Extension and agricultural productivity

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Despite Uganda’s well-intended interventions in extension reforms, the numerous public extension programs remain untouched by a large number of smallholder farmers and other disadvantaged groups, and the private sector still plays a limited role. It can be observed that there is significant difference in crop and agricultural productivity of farmers who use of extension services and those who do not, the results are significant at 5% level of significance. However, the results reveal that extension use does not influence animal productivity (p > 0.05). The dissemination of agricultural information is known to lead improved production, higher prices and higher incomes, but weak infrastructure, high rates of illiteracy and too few extension agents are making it more difficult in Uganda. The challenges facing the agricultural sector are on the rise because farmers need to be taught and enriched with climate change-related information, market ties, awareness and adoption of modern agricultural technology, links between farmers and the market, and how to use farm inputs.

The most likely cause of soil erosion in Uganda is forest clearing on mountain slopes for agricultural purposes. In highland areas, agriculture and natural factors such as ample tropical rainfall and a steep topography increase soil erosion rates (Karamage et al., 2017). NEMA, (2010); Barungi M, Edriss A, Mugisha (2013) also agrees that Uganda's highlands have been recognized as one of the main hotspots where land degradation is rampant owing to soil erosion, especially in the eastern region. In these highlands, soil erosion affects 60 to 90 percent of the land, but successful technologies such as contours, terraces, trenches, agroforestry, and grass planting along contours and terraces can easily regulate soil erosion

Table 14: Soil Erosion control and agricultural productivity

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Results in the table reveal that there is significant difference in crop productivity of farmers who made some effort to control soil erosion and those who didn’t (p < 0.05). However, results reveal that soil erosion control doesn’t affect animal productivity as well as agricultural productivity as whole (p > 0.05). Soil erosion mainly affects crops since it washes away nutrients that would have otherwise been used by crops to flourish. This is why there are differences in crop productivity as opposed to animal productivity between farmers who use fertilizers and those that do not.

Table 15: Type of seeds planted and agricultural productivity

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Resource-constrained smallholders are the majority of farmers in Uganda. Their decision to implement drought-tolerant seeds will therefore be impacted by the economic risks perceived. The seeds used by farmers of the local varieties are those that they have saved from previous harvests and can cost them nothing.

Results in the table reveal that there is a significant difference in crop and animal productivity for farmers who used improved crop seeds and those who didn’t (p < 0.05). However, results reveal that use of improved crop seeds doesn’t affect agricultural productivity as whole (p > 0.05). Improved seeds are more productive than the indigenous seeds which is why there is productivity difference between farmers who use improved seeds and those that don’t.

The Ugandan Ministry of Agriculture works to raise incomes, increase agricultural productivity and promote local food protection through training for livestock farmers and access to improved animals. In Uganda, more than 50 percent of households rely for their livelihoods on livestock. Through its latest Lusenke transformation initiative, agricultural officials are hoping to both increase productivity and feed Uganda's rising population more sustainably. The project will also provide livestock farming communities with high-quality livestock breeds and boost their ability to function as reference points and demonstration farms in terms of productive livestock enterprises, animal production and livestock farm management practices.

Table 16: Type of Livestock kept and agricultural productivity

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As can be observed, crop, animal and agricultural productivity are dependent on the type of livestock kept by farmers (p <0.005). Improved animal breeds just like improved seeds boost agricultural productivity.

The rangelands of Uganda are highly degraded. Through overgrazing and charcoal production, nutritious pasture and topsoil have been lost. Rain washes soil down slopes without adequate vegetation cover, filling water bodies such as ponds that provide water for livestock and domestic purposes. The problem is aggravated during the dry season by termites, which consume virtually all useful plant material quickly, including forages on which livestock depend. Without drinking water, livestock in search of watering sites are forced to travel long distances in the dry season. A threat to livestock-based livelihoods is lost pasture, coupled with jeopardized drinking water. In essence, the productivity of livestock water is very low and the soil is not appropriate for alternative livelihood strategies (Mpairwe and Mutetikka 2008).

Table 17: Animal watering frequency and agricultural productivity

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As can be observed, animal productivity is independent of the number of times livestock are watered in a day (p <0.05) but overall agricultural productivity is dependent on the frequency of animal watering (p <0.005). Limiting water consumption decreases animal efficiency faster and more significantly than any other shortage of nutrients (Boyles). Water is approximately 60 to 70 percent of the living weight of an animal and it is more important to consume water than to consume food. All the water they can drink should be given to livestock because animals that do not drink enough water can suffer stress or dehydration, thereby impacting productivity.

Land characteristics

The most dominant soil type in Uganda is ferralitic soil which covers over two thirds of the soils found in the country according to Kamanyire (2000); NEMA (1996). Soil type and topography are key determinants of land use in Uganda.

According to FAO (2004), towards the South of Uganda, the scenery consists of flat-topped hills of undulating plateau and broad intervening valleys containing swamps. Towards the North, the landscape is subdued, consisting of gently laid open plains, hills, mountains and inselbergs. Studies suggest that ferruginous soils are less productive and require careful usage to preserve their poorly developed topsoil, whereas lighter soils unlike heavy soils are more susceptible to leaching.

Land characteristics vs agricultural productivity

Table 18: Land characteristics and agricultural productivity

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ns – not significant, ** significant at 5% level of significance, *** significant at 1% level of significance

Under soil quality, poor soil quality is negatively related to crop productivity an indication that the more poor-quality land a farmer has, the lower the quantity of crops produced keeping other factors constant.

Looking at topography, valleys do not significantly influence agricultural productivity (p > 0.05) whereas gentle and steep slopes are positively related to agricultural productivity, an indication that the more slopping land a farmer has, the higher is his/her agricultural productivity keeping other factors constant. On the other hand, flat lands are negatively related to agricultural productivity meaning that the flatter land a farmer owns, the less will be his/her agricultural productivity keep other factors constant.


The study set out to investigate which factors significantly affect agricultural productivity in Uganda. The study entirely made use of secondary data from Uganda National Panel Survey (UNPS) for the 2013/2014 round.

Because the animal, crop and agricultural productivities were not normally distributed, a quantile regression model was employed to determine these factors.

Results from the model revealed that Uganda’s agricultural productivity is dependent on the gender and age of the household head with female headed households less likely to produce as much as the male headed households (this was significant at 10% level of significance). Households headed by old people are less likely to produce as much agricultural output as those headed by younger individuals keeping other factors constant.

Also, agricultural productivity in Uganda is dependent on the country’s administrative regions with the Western and Central regions much more productive than the Northern and the Eastern regions, this is true for both crop and animal productivity.

Use of improved rather than indigenous seeds for planting improves agricultural productivity and in the same way farmers who keep improved breeds of livestock are more likely to produce more than those who keep local breeds

The use of fertilizers (organic and/or inorganic) seems to have a positive impact on agricultural productivity though this was only significant at 10% level of significance as per the regression model results.

The model results didn’t suggest any relationship between agricultural productivity and use of extension services, topography of the land, land quality as reported by farmers during the survey, soil erosion control and animal watering frequency in a day.


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1 Szent Istvan University, Gödöllő, Hungary

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Drivers of agricultural productivity in Uganda
Szent István University
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Agricultural productivity, land use, Uganda
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Brian Baguma (Author), 2021, Drivers of agricultural productivity in Uganda, Munich, GRIN Verlag,


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