Actual value and historical data chart for Uganda Poverty Headcount Ratio At National Poverty Line Percent Of Population

Uganda UG: Poverty Headcount Ratio at National Poverty Lines: % of Population data was reported at 21.400 % in 2016. This records an increase from the previous number of 19.700 % for 2012. Uganda UG: Poverty Headcount Ratio at National Poverty Lines: % of Population data is updated yearly, averaging 32.450 % from Dec 1992 (Median) to 2016, with 8 observations. The data reached an all-time high of 56.400 % in 1992 and a record low of 19.700 % in 2012. Uganda UG: Poverty Headcount Ratio at National Poverty Lines: % of Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Uganda – Table UG.World Bank.WDI: Poverty. National poverty headcount ratio is the percentage of the population living below the national poverty lines. National estimates are based on population-weighted subgroup estimates from household surveys.; ; World Bank, Global Poverty Working Group. Data are compiled from official government sources or are computed by World Bank staff using national (i.e. country–specific) poverty lines.; ; This series only includes estimates that to the best of our knowledge are reasonably comparable over time for a country. Due to differences in estimation methodologies and poverty lines, estimates should not be compared across countries.

Uganda Poverty Headcount Ratio at Societal Poverty Lines: % of Population data was reported at 48.000 % in 2019. This records a decrease from the previous number of 48.600 % for 2016. Uganda Poverty Headcount Ratio at Societal Poverty Lines: % of Population data is updated yearly, averaging 58.000 % from Dec 1989 (Median) to 2019, with 10 observations. The data reached an all-time high of 67.900 % in 1999 and a record low of 46.200 % in 2012. Uganda Poverty Headcount Ratio at Societal Poverty Lines: % of Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Uganda – Table UG.World Bank.WDI: Social: Poverty and Inequality. The poverty headcount ratio at societal poverty line is the percentage of a population living in poverty according to the World Bank's Societal Poverty Line. The Societal Poverty Line is expressed in purchasing power adjusted 2017 U.S. dollars and defined as max($2.15, $1.15 + 0.5*Median). This means that when the national median is sufficiently low, the Societal Poverty line is equivalent to the extreme poverty line, $2.15. For countries with a sufficiently high national median, the Societal Poverty Line grows as countries’ median income grows.;World Bank, Poverty and Inequality Platform. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are mostly from the Luxembourg Income Study database. For more information and methodology, please see http://pip.worldbank.org.;;The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than 2000 household surveys across 169 countries. See the Poverty and Inequality Platform (PIP) for details (www.pip.worldbank.org).

In 2025, over **** million people in Madagascar lived in extreme poverty (less than **** U.S. dollars a day), the highest number within East Africa. However, this accounts for ** percent of the overall population living below the poverty line in the country. Uganda and Malawi followed, with almost **** million and more than **** million people living in destitution, respectively.

In 2025, nearly 11.7 percent of the world population in extreme poverty, with the poverty threshold at 2.15 U.S. dollars a day, lived in Nigeria. Moreover, the Democratic Republic of the Congo accounted for around 11.7 percent of the global population in extreme poverty. Other African nations with a large poor population were Tanzania, Mozambique, and Madagascar. Poverty levels remain high despite the forecast decline Poverty is a widespread issue across Africa. Around 429 million people on the continent were living below the extreme poverty line of 2.15 U.S. dollars a day in 2024. Since the continent had approximately 1.4 billion inhabitants, roughly a third of Africa’s population was in extreme poverty that year. Mozambique, Malawi, Central African Republic, and Niger had Africa’s highest extreme poverty rates based on the 2.15 U.S. dollars per day extreme poverty indicator (updated from 1.90 U.S. dollars in September 2022). Although the levels of poverty on the continent are forecast to decrease in the coming years, Africa will remain the poorest region compared to the rest of the world. Prevalence of poverty and malnutrition across Africa Multiple factors are linked to increased poverty. Regions with critical situations of employment, education, health, nutrition, war, and conflict usually have larger poor populations. Consequently, poverty tends to be more prevalent in least-developed and developing countries worldwide. For similar reasons, rural households also face higher poverty levels. In 2024, the extreme poverty rate in Africa stood at around 45 percent among the rural population, compared to seven percent in urban areas. Together with poverty, malnutrition is also widespread in Africa. Limited access to food leads to low health conditions, increasing the poverty risk. At the same time, poverty can determine inadequate nutrition. Almost 38.3 percent of the global undernourished population lived in Africa in 2022.

Uganda made enormous strides in improving household welfare between 1992/93 and 2002/03. Domestic policy brought about consistent, strong, broad-based growth reduced poverty by nearly 50 percent and increase household welfare, despite a decline in world prices for Uganda's key exports. Earnings rose and job growth was strong in the private sector. Mobility was high, allowing Ugandans at all levels of income to take advantage of opportunities, economic growth provided. Services to the poor also improved. Uganda's success early on in achieving virtually the highest net primary school enrollment ratios among low income countries in Africa for poor and vulnerable children, has reduced poverty in the early years of the decade and promises to pay solid dividends in the future. Challenges remain, however. Increases in income inequality and high fertility rates muted the effect of growth on poverty, and the negative impact of these trends on the poverty rate has increased. Poverty reduction was lowest among agricultural households, where the poor were concentrated. Uganda's health indicators remained unacceptably high and showed little improvement over the decade. Meeting these needs requires a continuation of successful policies combined with new approaches in areas such as smallholder agriculture, expansion of infrastructure to improve the environment for private sector growth, and ensuring that high quality health services are accessible to the rural poor, especially for women with unmet needs in family planning and maternal and child health services.

Uganda UG: Poverty Headcount Ratio at National Poverty Lines: Urban: % of Urban Population data was reported at 9.600 % in 2012. This records an increase from the previous number of 9.100 % for 2009. Uganda UG: Poverty Headcount Ratio at National Poverty Lines: Urban: % of Urban Population data is updated yearly, averaging 13.700 % from Dec 1992 (Median) to 2012, with 7 observations. The data reached an all-time high of 28.800 % in 1992 and a record low of 9.100 % in 2009. Uganda UG: Poverty Headcount Ratio at National Poverty Lines: Urban: % of Urban Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Uganda – Table UG.World Bank.WDI: Poverty. Urban poverty headcount ratio is the percentage of the urban population living below the national poverty lines.; ; World Bank, Global Poverty Working Group. Data are compiled from official government sources or are computed by World Bank staff using national (i.e. country–specific) poverty lines.; ; This series only includes estimates that to the best of our knowledge are reasonably comparable over time for a country. Due to differences in estimation methodologies and poverty lines, estimates should not be compared across countries.

The share of Uganda’s population that lives below the poverty line has fluctuated over the last seven years, greatly influenced by shocks that have tested the resilience of the people. The COVID-19 pandemic pushed both urban and rural residents into poverty. Inequality, which reflects the extent to which different population groups benefit from Gross Domestic Product (GDP) growth, and affects the transmission of growth into poverty reduction, remained largely unchanged over this period and may even have worsened in urban areas. The findings of this report show that previously identified patterns and drivers of Uganda’s poverty changes persisted well into 2020 – shaped by low productivity and high vulnerability. Identified inequality of economic opportunities and unequal accumulation of the human capital could hold back structural change in employment. Accelerating poverty reduction in such a setting requires a two-pronged strategy. While at the macroeconomic level, policies addressing growth fundamentals are important for reducing poverty, from a microeconomic perspective, the report’s analysis shows that two strategies will be crucial. The first strategy is to lift the productivity and incomes of poor households in both rural and urban areas. While tackling agricultural productivity and job creation are at the top of the agenda here, making mobile phone services more widely accessible and affordable is a potential opportunity. The second strategy is to strengthen people’s resilience to shocks, particularly in rural areas. To have an impact, policies in both these areas will have to address the inequality in opportunities analyzed in the report. This document provides an overview of key report findings and identifies priority actions.

Historical dataset showing Uganda poverty rate by year from 1989 to 2019.

Uganda UG: Poverty Headcount Ratio at National Poverty Lines: Rural: % of Rural Population data was reported at 22.400 % in 2012. This records a decrease from the previous number of 27.200 % for 2009. Uganda UG: Poverty Headcount Ratio at National Poverty Lines: Rural: % of Rural Population data is updated yearly, averaging 37.400 % from Dec 1992 (Median) to 2012, with 7 observations. The data reached an all-time high of 60.300 % in 1992 and a record low of 22.400 % in 2012. Uganda UG: Poverty Headcount Ratio at National Poverty Lines: Rural: % of Rural Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Uganda – Table UG.World Bank: Poverty. Rural poverty headcount ratio is the percentage of the rural population living below the national poverty lines.; ; World Bank, Global Poverty Working Group. Data are compiled from official government sources or are computed by World Bank staff using national (i.e. country–specific) poverty lines.; ; This series only includes estimates that to the best of our knowledge are reasonably comparable over time for a country. Due to differences in estimation methodologies and poverty lines, estimates should not be compared across countries.

Uganda Proportion of Population Pushed Below the 60% Median Consumption Poverty Line By Out-of-Pocket Health Expenditure: % data was reported at 2.620 % in 2016. This records an increase from the previous number of 2.050 % for 2012. Uganda Proportion of Population Pushed Below the 60% Median Consumption Poverty Line By Out-of-Pocket Health Expenditure: % data is updated yearly, averaging 2.050 % from Dec 1996 (Median) to 2016, with 7 observations. The data reached an all-time high of 2.620 % in 2016 and a record low of 1.620 % in 2002. Uganda Proportion of Population Pushed Below the 60% Median Consumption Poverty Line By Out-of-Pocket Health Expenditure: % data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Uganda – Table UG.World Bank.WDI: Social: Poverty and Inequality. This indicator shows the fraction of a country’s population experiencing out-of-pocket health impoverishing expenditures, defined as expenditures without which the household they live in would have been above the 60% median consumption but because of the expenditures is below the poverty line. Out-of-pocket health expenditure is defined as any spending incurred by a household when any member uses a health good or service to receive any type of care (preventive, curative, rehabilitative, long-term or palliative care); provided by any type of provider; for any type of disease, illness or health condition; in any type of setting (outpatient, inpatient, at home).;Global Health Observatory. Geneva: World Health Organization; 2023. (https://www.who.int/data/gho/data/themes/topics/financial-protection);Weighted average;This indicator is related to Sustainable Development Goal 3.8.2 [https://unstats.un.org/sdgs/metadata/].

Uganda UG: Poverty Gap at National Poverty Lines: % data was reported at 5.200 % in 2012. This records a decrease from the previous number of 6.800 % for 2009. Uganda UG: Poverty Gap at National Poverty Lines: % data is updated yearly, averaging 10.000 % from Dec 1992 (Median) to 2012, with 7 observations. The data reached an all-time high of 20.900 % in 1992 and a record low of 5.200 % in 2012. Uganda UG: Poverty Gap at National Poverty Lines: % data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Uganda – Table UG.World Bank.WDI: Poverty. Poverty gap at national poverty lines is the mean shortfall from the poverty lines (counting the nonpoor as having zero shortfall) as a percentage of the poverty lines. This measure reflects the depth of poverty as well as its incidence.; ; World Bank, Global Poverty Working Group. Data are compiled from official government sources or are computed by World Bank staff using national (i.e. country–specific) poverty lines.; ; This series only includes estimates that to the best of our knowledge are reasonably comparable over time for a country. Due to differences in estimation methodologies and poverty lines, estimates should not be compared across countries.

Abstract

The Uganda National Household Survey 2002/03 was the eighth in a series of household surveys that started in 1988. The UNHS 2002/2003 collected information on the economic characteristics of the population and its activity status at the household level. The main objective of the survey was to collect high quality and timely data on population and socio-economic characteristics of households for monitoring development performance. The UNHS 2002/2003 focused on four modules namely the Socio-economic, Labour force, the Informal Sector, and Community modules. The survey covered 55 districts of Uganda, with some parts of Gulu and Kitgum districts not fully covered due to insecurity. Pader District was not covered at all. Indicators on population characteristics, labourforce participation rates, education, health, household expenditure and poverty among others have been presented at national, regional and rural-urban levels. The UNHS 2002/03 survey findings estimate the population of Uganda at around 25 million. The average household size is estimated at 5 persons per household. Like in the previous surveys, a large proportion of the population is below 15 years of age, with the majority of household members being children of the household head, which trend has been the same over years. The Poverty Monitoring and Evaluation Strategy targets 98 percent primary school enrollment by the year 2003. The results of the survey reveal that in spite of efforts made so far, Net Primary Enrollment for children aged 6-12 is below the target at 86 percent. This is partly caused by the fact that some children enroll late for primary school. The results also show that many children continue to attend primary school after the official age of 12. For example, more than half of all children aged 13-18 years attend primary school. In addition, households report that the monetary costs related to schooling deter participation to a certain extent. The results show that the percentage enrolled increases with increased household wealth. There are consistent differences in educational attainment and in literacy, and these differences are consistent across regions, both by sex and income bracket. The northern region consistently emerges worse-off in almost every education indicator. About twenty eight percent of the country’s population fell sick in the 30 days preceding the survey with malaria/fever reported as the major cause of ill health. Of those who fell sick, many practiced self-treatment while others preferred to go to private clinics. Usage of mosquito nets remains low with only 11 percent of the population using them. Awareness of HIV/AIDS is almost universal. However it is not matched by knowledge of specific ways to avoid HIV/AIDS. The condom however is most mentioned as the specific method one can use to avoid HIV/AIDS. The radio is reported to be the main medium through which people acquire information on HIV/AIDS. Most of the housing and household conditions have improved especially the housing structure i.e. wall, roof and floor. Households are still dependent on “tadoba” for lighting and worse still, the majority of the households depend on wood as fuel for cooking. The 2002/03 survey has shown an increase in Per-household and Per-capita expenditure. Foods, Beverages and Tobacco still dominate the household budget share, despite a drop of 8 percent observed over the same period. However, these changes have not been high enough to over turn the observed increases in poverty levels. The percentage of the population living below the poverty line rose from 34 percent to 38 percent. This rise is statistically significant. The main finding is that, despite some very modest economic growth, poverty increased. This is in contrast to trends in the 1990s, where growth was stronger and appeared to be broadly shared. There has been a general downward trend in the welfare indicators between 1999/00 and 2002/03 periods. Ownership of clothes declined between the 1999/00 and 2002/03 periods while ownership of bicycles and radios has improved over the same period. One in every 5 children aged 0 – 5 years, in the eastern and northern regions does without breakfast. About 36 percent of the households in Uganda own non-crop enterprises. The major enterprises being in the manufacturing and trade and services broad industries. These two categories employ 1.8 million persons while livestock, poultry, bee-keeping, and fishing industry employs another 0.5 million persons. Most household based enterprises are sole proprietorship, and similarly there are mainly started by owners. Nearly 90 percent of the persons aged 10 years and above were usually active during the 12 months prior to the survey. About 60 percent of these were own account workers followed by unpaid family workers (26 percent). The distribution of usually active persons by Industry show that the agricultural sector is still dominant accounting for 68 percent of the employed persons . Considering the last seven days, a higher proportion of persons aged 10 years and above were own account workers (54 percent). The Northern and Eastern Regions recorded the highest proportion of persons employed in agriculture. It is noted that most of the urban dwellers are employed in the sales and service sector. Occupational categories of household members show that 2 in every 3 persons were engaged in agriculture, only 4 percent were involved in Market Oriented Agriculture Production. A higher proportion of women than men was recorded for those who were engaged in domestic duties. Those who did not participate in economic activities during the last 7 days, stated being ill as the dominant reason. Among reasons for not being usually active during the last 12 months, attending school featured as the prominent reason followed by attending to domestic duties. Nearly 25 percent of the employed population were engaged in secondary activities and the service workers were more likely to engage in secondary activities than any other occupational category. The current labourforce participation rate is 67 percent. Participation levels by selected background characteristics show that persons without education had higher participation levels than those with primary education. The findings further show that rural women had higher participation rates than their urban counterparts. Twenty percent of the persons in paid employment earn at most shillings 20,000. Of those persons earning more than shillings 60,000, 63 percent were men while only 37 percent were women. Of the currently economically active persons, 3 percent are unemployed. Youth unemployment (5.3 percent) rate was higher than the national rate (3.2 percent). Central region had unemployment rate higher than other regions. Sixty five percent of the unemployed had attempted to look for work. This was mainly through friends and relatives. Most of the unemployed depended on relatives or spouses for survival with females depending more on spouses. The underemployment rate is highest among youth but steadily declines among those aged 50 years and over. The national underemployment rate stood at 15 percent. The survey results show that the underemployed are mainly in the agricultural sector. The underemployed were willing to do any job to earn more money. Findings show that although one in every five working children is an orphan, three out of every four children were non-orphans. Children whose parent survival status is not known are more likely to work. Children who were not attending school engaged in paid employment than those attending school. Furthermore, those who engaged in paid domestic services were more likely to work for more hours in a day than those engaged in other activities.

Geographic coverage

The Uganda National Household Survey 2002/03 was conducted in all districts except Pader. Some parts of Kitgum and Gulu districts were also not covered due to insecurity.

Analysis unit

The following are the units of analysis; - Individual - Household - Community

Universe

The survey covered all resident population.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling design was chosen to fit the purpose of the survey. Stratified two stage sampling was adopted, but with a few refinements such as over-sampling of urban areas, and possibly of some rural areas with concentrated informal sector activity. The sampling frame for selection of first stage units (FSUs) was the list of EAs with the number of households based on cartographic work for the 2002 Population and Housing Census. For selection of the second stage units, which were the households, listing exercise through listing schedules was done in selected EAs. Each district was a stratum and was divided into rural and urban sub-strata. The urban area was further sub-divided into district town and other urban areas. This deep stratification enabled a better spread and representation of the sample, thereby increasing the efficiency of the estimates. Additionally, the continuity over rounds was maintained to enable pooling of results over rounds, if ever considered necessary. The total number of about 1,000 FSUs was firstly allocated between urban and rural in the proportion of 40:60. Thereafter, the urban and rural sample was generally allocated between the strata in proportion to the number of households with certain adjustments. The allocated sample was selected with probability proportional to number of households. A suitable plan for sub-stratification and selection of households at the listing stage, was introduced to ensure adequate representation of households with at least one unemployed person and an informal sector enterprise activity. The households were

Abstract

The National Panel Survey (UNPS) was carried out to collect high quality data on key outcome indicators such as poverty, service delivery, employment and to monitor government's development programs like the National Development Plan (NDP) on an annual basis. The 2010/11 survey collected information on socio-economic characteristics at household, individual and community levels.The NPS 2010/11 was comprised of six modules: the Socio-Economic, Woman, Agriculture, Fisheries, Community and Market Price modules. The survey covered 3,200 households that were scientifically selected and followed for re-interview in 2009/10 and 2010/11. The objectives of the survey were:

1) To provide information required for monitoring the NDP and other development objectives like the JAF, MDGs as well as specific programs such as the National Agricultural Advisory Services (NAADS) among others. 2) To provide high quality nationally representative information on income dynamics at the household level as well as annual consumption expenditure estimates to monitor poverty in years between Uganda National Household Surveys (UNHS). 3) To supply regular data on agriculture in order to characterize and monitor the performance of the agricultural sector.

Geographic coverage

National coverage

Analysis unit

Households

Kind of data

Sample survey data [ssd]

Sampling procedure

The 2010/11 NPS survey maintained the 2009/10 NPS sample design where all the households that were sampled for Wave I (2009/10) were tracked and re-interviewed in Wave II (2010/11). Out of the 7,400 households interviewed during the UNHS 2005/06, 3,200 households were selected for the NPS and the same sample was maintained in both 2009/10 and 2010/11 Panel surveys. During data collection, the population of persons interviewed in Wave II was slightly higher than that of Wave I due to the following reasons: 1. About 20 households that had initially been missed in Wave I were found and successfully interviewed in Wave II. 2. Changes in household composition contributed to the increase in the number of persons that were added to the panel. Most importantly, if a household member split-off from his/her original household (e.g. children leaving home to set up their own household,or a couple separates), all the new households were included/ joined the panel. Inclusion of split-offs was the main way in which panel surveys, maintain sample representativeness over the years. The new households formed are known as Split-off households while the individuals are termed as Movers.

Mode of data collection

Face-to-face paper [f2f]

Response rate

The response rate for the survey is 84%.

Uganda UG: Poverty Gap at National Poverty Lines: Urban: % data was reported at 2.500 % in 2012. This records an increase from the previous number of 1.800 % for 2009. Uganda UG: Poverty Gap at National Poverty Lines: Urban: % data is updated yearly, averaging 3.500 % from Dec 1992 (Median) to 2012, with 7 observations. The data reached an all-time high of 8.700 % in 1992 and a record low of 1.800 % in 2009. Uganda UG: Poverty Gap at National Poverty Lines: Urban: % data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Uganda – Table UG.World Bank: Poverty. Urban poverty gap at national poverty lines is the urban population's mean shortfall from the poverty lines (counting the nonpoor as having zero shortfall) as a percentage of the poverty lines. This measure reflects the depth of poverty as well as its incidence.; ; World Bank, Global Poverty Working Group. Data are compiled from official government sources or are computed by World Bank staff using national (i.e. country–specific) poverty lines.; ; This series only includes estimates that to the best of our knowledge are reasonably comparable over time for a country. Due to differences in estimation methodologies and poverty lines, estimates should not be compared across countries.

Abstract

The UNPS aims at producing annual estimates in key policy areas; and providing a platform for experimenting with and assessing national policies and programs. Explicitly, the objectives of the UNPS include:

1. To provide information required for monitoring the National Development Strategy, of major programs such as National Agricultural Advisory Services (NAADS) and General Budget Support, and also to provide information for the compilation of the National Accounts (e.g. agricultural production);
2. To provide high quality nationally representative information on income dynamics at the household level as well as information on service delivery and consumption expenditure estimates annually; to monitor poverty and service outcomes in interim years of other national survey efforts, such as the Uganda National Household Survey (UNHS), Uganda Demographic and Health Survey (UDHS) and National Service Delivery Surveys (NSDS);
3. To provide a framework for low-cost experimentation with different policy interventions to e.g. reduce teacher absenteeism, improve ante-natal and post-natal care, and assess the effect of subsidies on agricultural inputs among others;
4. To provide a framework for policy oriented analysis and capacity building substantiated with the UGDR and support to other research which feed into the Annual Policy Implementation Review; and 5. To facilitate randomized impact evaluations of interventions whose effects cannot currently be readily assessed through the existing system of national household surveys.

Geographic coverage

National coverage

Analysis unit

Households, Individuals, Plots of land, Communities

Kind of data

Sample survey data [ssd]

Sampling procedure

The UNPS is carried out over a twelve-month period (a "wave") on a nationally representative sample of households, for the purpose of accommodating the seasonality associated with the composition of and expenditures on consumption. The survey is conducted in two visits in order to better capture agricultural outcomes associated with the two cropping seasons of the country. The UNPS therefore interviews each household twice in a year, in visits approximately six months apart. In 2009/10, the UNPS set out to track and interview 3,123 households that were distributed over 322 Enumeration Areas (EAs), selected out of 783 EAs that had been visited during the Uganda National Household Survey (UNHS) in 2005/06.

The distribution of the EAs covered by the 2009/10 UNPS was such that it included all 34 EAs in Kampala District, and 72 EAs (58 rural and 14 urban) in each of the other regions i.e. Central excluding Kampala, Eastern, Western and Northern which make up the strata. Within each stratum, the EAs were selected with equal probability with implicit stratification by urban/rural and district (in this order). However, the probabilities of selection for the rural portions of ten districts that had been oversampled by the UNHS 2005/06 were adjusted accordingly. Since most IDP (Internally Displaced People) camps in the Northern region are currently unoccupied, the EAs that constituted IDP camps were not part of the UNPS sample. This allocation allows for reliable estimates at the national, rural-urban and regional levels i.e. at level of strata representativeness which includes: (i) Kampala City (ii) Other Urban Areas (iii) Central Rural (iv) Eastern Rural (v) Western Rural (vi) Northern Rural.

In the UNPS 2010/11, the concept of Clusters instead of EAs was introduced. A cluster represents a group of households that are within a particular geographical area up to parish level. This was done due to split-off households that fell outside the selected EAs but could still be reached and interviewed if they still resided within the same parish as the selected EA. Consequently, in each subsequent survey wave, a subset of individuals was selected for tracking. The UNPS is part of the long term Census and Household Survey Program hence questionnaires and the timing of data collection are coordinated with the current surveys and census implemented by UBOS.

SAMPLE REFRESH

Starting with the UNPS 2013/14 (Wave 4) fieldwork, one third of the initial UNPS sample was refreshed with the intention to balance the advantages and shortcomings of panel surveys. Each new household will be visited for three consecutive waves, while baseline households will have a longer history of five or six years, given the start time of the sample refresh. This same sample was used for the UNPS 2015/16 (Wave 5) Once a steady state is reached, each household will be visited for three consecutive years, and at any given time one third of the households will be new, one third will be visited for the second time, and one third for the third (and last) time. The total sample will never be too different from a representative cross-section of the country, yet two-thirds of it will be a panel with a background of a year or two. New households were identified using the updated sample frames developed by the UBOS in 2013 as part of the preparations for the 2014 Uganda Population and Housing Census.

Sampling deviation

Of the 17,495 individuals from wave 4 that were to be interviewed in the UNPS 2015/16, 16,748 (96%) were found and interviewed while 747 (4%) had attrited (dropped out). In addition, 2,498 individuals joined or re-joined the panel during the UNPS 2015/16. In total 3300 households were covered in the UNPS 2015/16.

Mode of data collection

Computer Assisted Personal Interview [capi]

Cleaning operations

The 2015/16 round of UNPS used a computerized system of data collection whereby field staff directly captured information using Ultra Mobile Personal Computers (UMPCs) during data collection. The UMPCs were loaded with a data entry application with in-built range and consistency checks to ensure good quality data. Field Team Leaders run checks on the data while still in the field thereafter electronically transmitting it to UBOS Headquarters for verification. Every team was facilitated with an internet modem, a generator and extra UMPC batteries to ensure uninterrupted power supply and internet connectivity while in the field.

Response rate

96 percent

Abstract

The 2016/17 Uganda National Household Survey (UNHS) is the sixth in a series of national household surveys that Uganda Bureau of Statistics (UBOS) has undertaken. The survey collected information on socio-economic characteristics at both household and community levels. The main objective of the survey was to collect high quality data on demographic and socio-economic characteristics of households for monitoring Uganda’s development performance of key indicators in the various sectors. The 2016/17 UNHS comprises four (4) modules. Those are the Socio-Economic, Labour Force, Community, and Market price modules. The main findings are based on the four modules and include trends of several indicators on Education, Health, Household Expenditure and Poverty, Food security, Income and loans, Information and Communication Technology, Vulnerable Groups, Community Characteristics and Non-crop household enterprises, presented at national, rural-urban, regional and sub-regional levels. The survey collected much more information besides what has been included in the main findings. Therefore, UBOS calls upon all stakeholders to utilize the wealth of data collected and availed over the years to undertake in-depth empirical analysis so as to better inform future policy debate.

Geographic coverage

National coverage

Analysis unit

The UNHS 2016/17 had the following units of analysis: individuals, housheholds, and communities.

Universe

The survey covered all de jure household members (usual residents), all currently employed and unemployed persons aged 5 years and above, resident in the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

The 2016/17 UNHS sample was designed to allow for generation of separate estimates at the national level, for urban and rural areas and for the 15 sub-regions of Uganda. At the time of the survey there were only 112 districts. This number later increased to 122 districts. A two-stage stratified sampling design was used. At the first stage, Enumeration Areas (EAs) were grouped by districts of similar socio-economic characteristics and by rural-urban location. The EAs were then drawn using Probability Proportional to Size (PPS). At the second stage, households which are the ultimate sampling units were drawn using Systematic Random Sampling. A total of 1,750 EAs were selected from the 2014 National Population and Housing Census (NPHC) list of EAs which constituted the Sampling Frame. The EAs were then grouped into 15 sub-regions, taking into consideration the standard errors required for estimation of poverty indicators at sub-regions and the rural-urban domains. In addition to the sub-regions, the other sub-groups that were considered during the analysis of the 2016/17 UNHS include the Peace and Recovery Development Plan (PRDP) districts and Hard-to-reach areas such as the mountainous areas. The survey targeted to interview 10 households per EA, implying a total sample of 17,540 households. Prior to the main survey data collection, all the sampled EAs were updated by listing all the households within their boundaries.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The UNHS 2016/17 adminstered four questionnaires including: Socio-Economic, Labour Force, Market Prices, and Community. All questionnaires and modules are provided as external resources in this documentation.

Response rate

Out of the total 17,320 households selected for the 2016/17 UNHS sample, 15,672 households were successfully interviewed, giving a response rate of 91 percent. The response rate was higher in rural areas (93%) compared to urban areas (88%).

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: non-sampling errors and sampling errors. Non-sampling errors usually result from mistakes made during data collection and capture and those include misunderstanding of the questions, either by the respondent or by the interviewer and by capture of wrong entries. Such errors were controlled through rigorous training of the data collectors and through field spot-checks undertaken by the supervisors at the different levels. On the other hand, sampling errors (SE) are evaluated statistically. The 2016/17 UNHS sample is one of the many possible samples that could have been selected from the same population using the same sampling design. Sampling errors are a measure of the variability between all possible samples that would yield different results from the selected sample. Sampling errors are usually measured in terms of the standard error for a particular statistic such as the mean, percentages, etc. The Tables in Appendix III present standard errors and Coefficients of Variations (CVs) for selected indicators at national, rural-urban and sub-regional levels.

Abstract

The overall objective of the UNPS Program is to collect high quality data on key outcome indicators such as poverty, service delivery, governance and employment among others; to monitor Government's development programmes like the NDP and the JAF among others on an annual basis. The specific objectives of the survey are:

• To provide information required for monitoring the NDP and other development objectives like the JAF, MDGs as well as specific programs such as the National Agricultural Advisory Services (NAADS) among others.
• To provide high quality nationally representative information on income dynamics at the household level as well as annual consumption expenditure estimates to monitor poverty in years between the Uganda National Household Surveys (UNHS)
• To supply regular data on agriculture in order to characterize and monitor the performance of the agricultural sector.

Geographic coverage

National

Analysis unit

Households

Kind of data

Sample survey data [ssd]

Sampling procedure

The 2011-2012 UNPS survey maintained the 2010-2011 UNPS sample design whereby all households that were sampled for Wave II (2010/11) were tracked and re-interviewed in Wave III (2011-2012). Out of the 7,400 households interviewed during the UNHS 2005-2006, 3,123 households were selected for the panel surveys. As a result, the same sample was maintained in 2009-2010, 2010-2011 and 2011-2012 round of surveys. During data collection, households or individuals that had permanently left the original households to known locations were tracked and interviewed. The new households formed are known as split-off households whereas the individuals are termed as movers.

Sampling deviation

The drop in the number of households between wave II and wave III can be attributed to sample attrition-that is, households/people dropping out of the sample due to refusal, death, or the inability of the field teams to locate them among others. 32 percent of the UNPS households were not traced in 2011/12 because they had shifted to unknown locations, 25 percent were not known/not found while 12 percent of the households had disintegrated. Regionally, higher proportions of households (48%) that had shifted were registered in the Eastern and Western regions while Kampala (44%) had the highest percentage of households that were not know/not found and the Northern region (18%) had the highest of those households that had disintegrated.

Mode of data collection

Computer Assisted Personal Interview [capi]

Cleaning operations

The 2011-2012 round of UNPS used a computerized system of data collection whereby field staff directly captured information using Ultra Mobile Personal Computers (UMPCs) during data collection. The UMPCs were loaded with a data entry application with in-built range and consistency checks to ensure good quality data. Field Team Leaders run checks on the data while still in the field thereafter electronically transmitting it to UBOS Headquarters for verification. Every team was facilitated with an internet modem, a generator and extra UMPC batteries to ensure uninterrupted power supply and internet connectivity while in the field.

Response rate

75 percent

Abstract

The objectives of the Smallholder Household Survey in Uganda were to: • Generate a clear picture of the smallholder sector at the national level, including household demographics, agricultural profile, and poverty status and market relationships; • Segment smallholder households in Uganda according to the most compelling variables that emerge; • Characterize the demand for financial services in each segment, focusing on customer needs, attitudes and perceptions related to both agricultural and financial services; and, • Detail how the financial needs of each segment are currently met, with both informal and formal services, and where there may be promising opportunities to add value.

Geographic coverage

National coverage

Analysis unit

Households and individual household members

Universe

The universe for the survey consists of smallholder households defined as households with the following criteria: 1) Household with up to 5 hectares OR farmers who have less than 50 heads of cattle, 100 goats/sheep/pigs, or 1,000 chickens; AND 2) Agriculture provides a meaningful contribution to the household livelihood, income, or consumption.

Kind of data

Sample survey data [ssd]

Sampling procedure

The CGAP smallholder household survey in Uganda is a nationally-representative survey with a target sample size of 3,000 smallholder households. The sample was designed to provide reliable survey estimates at the national level and for the following administrative four regions: Central, Eastern, Northern, and Western regions. The Central region includes central metro (i.e., four municipalities surrounding Kampala), the parishes in Kampala with poultry activity but it excludes Kampala city which is entirely urban.

Sampling Frame

The sampling frame for the smallholder household survey is the list of enumeration areas (EAs) created for the 2014 Uganda National Population and Housing Census. Uganda is divided into 112 districts with each district comprised of counties/municipalities. Each county/municipality consists of sub-counties/town councils with each of them being further divided into parishes/wards and villages/cells.

For the 2014 population census, each village and cell was further divided into EAs. Information on the number of agricultural households at the EA level will be available in December 2015, and thus not on time for the smallholder survey. As a result, the sample allocation of the survey was based on the distribution of households per region and urban and rural according to the 2014 Census.

Sample Allocation and Selection

In order to take non-response into account, the target sample size was increased to 3,158 households assuming a household non-response rate of 5% observed in similar national households. The total sample size was first allocated to the four regions proportionally to their number of households. Within each region, the resulting sample was then distributed to urban and rural areas proportionally to their size.

The sample for the smallholder survey is a stratified multistage sample. Stratification was achieved by separating each region into urban and rural areas. The urban/rural classification is based on the 2014 population census. Therefore, eight strata were created and the sample was selected independently in each stratum. Prior to the sample selection, the sampling frame was sorted by the nine agricultural zones called Zardi (Zonal Agriculture Research Development Institute).

In the first stage, 216 EAs were selected as primary sampling units with probability proportional to size, the size being the number of households in the EAs. A household listing operation was carried out in all selected EAs to identify smallholder households according to the definition used in the survey, and to provide a frame for the selection of smallholder households to be included in the sample.

In the second stage, 15 smallholder households were selected in each EA with equal probability. Due to rounding, this yielded a total of 3,240 smallholder households. In each selected household, a household questionnaire was administered to the head of the household, the spouse or any knowledgeable adult household member to collect information about household characteristics. A multiple respondent questionnaire was administered to all adult members in each selected household to collect information on their agricultural activities, financial behaviors and mobile money usage. In addition, in each selected household only one household member was selected using the Kish grid and was administered the single respondent questionnaire.

The full description of the sample design can be found in the user guide for this data set.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Building on secondary research on the smallholder sector and discussions with stakeholders, the design process for the survey instrument began. This process involved defining the end goal of the research by: • Drawing from existing survey instruments; • Considering the objectives and needs of the project; • Accounting for stakeholder interests and feedback; • Learning from the ongoing financial diaries in country; and, • Building from a series of focus groups conducted early on in the study.

Using this foundation, a framework for the survey instrument was developed to share with stakeholders and capture all the necessary elements of a smallholder household. The framework consisted of five main subject areas: (i) demographics, (ii) household economics, (iii) agricultural practices, (iv) mobile phones, and (v) financial services.

In order to capture the complexity inside smallholder households, the smallholder household survey was divided into three questionnaires: the household questionnaire, the multiple respondent questionnaire and the single respondent questionnaire. In addition to English, the questionnaires were translated into nine local languages: Lugishu, Luganda, Ateso, Lugbara, Runyakole, Lutooro, Ngakaaramojong, Langi, and Acholi.

The household questionnaire collected information on: • Basic household members’ individual characteristics (age, gender, education attainment, schooling status, relationship with the household head) • Whether each household member contributes to the household income or participates in the household’s agricultural activities. This information was later used to identify all household members eligible for the other two questionnaires.
• Household assets and dwelling characteristics

Both the Multiple and Single Respondent questionnaires collected different information on: • Agricultural practices: farm information such as size, crop types, livestock, decision-making, farming associations and markets • Household economics: employment, income, expenses, shocks, borrowing and saving habits, and investments

In addition, the Single respondent questionnaire collected information on: • Mobile phones: attitudes toward phones, usage, access, ownership, desire and importance • Financial services: attitudes towards financial products and services such as banking and mobile money, including ownership, usage, access and importance.

Following the finalization of questionnaires, a script was developed to support data collection on mobile phones. The script was tested and validated before its use in the field.

Cleaning operations

During data collection, InterMedia received a weekly partial SPSS data file from the field which was analyzed for quality control and used to provide timely feedback to field staff while they were still on the ground. The partial data files were also used to check and validate the structure of the data file.

The full data file was also checked for completeness, inconsistencies and errors by InterMedia and corrections were made as necessary and where possible.

Response rate

The user guide includes household and individual response rates for the CGAP smallholder household survey in Uganda.

Sampling error estimates

The sample design for the smallholder household survey was a complex sample design featuring clustering, stratification and unequal probabilities of selection. For key survey estimates, sampling errors taking into account the design features were produced using either the SPSS Complex Sample module or STATA based on the Taylor series approximation method.

In 2024, the unemployment rate in Uganda was 2.94 percent. Between 1991 and 2024, the figure dropped by 0.52 percentage points, though the decline followed an uneven course rather than a steady trajectory.