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.

Analysis unit

The study describes (including but not limited to): - Household - Individual - Parcel - Plot - Community

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, and (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.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The UNPS had six questionnaires namely: Household Questionnaire; Woman Questionnaire; Agriculture & Livestock Questionnaire; Fisheries Questionnaire; Community Questionnaire and Market Questionnaire. A module on Biological data collection was also administered in 2019/20. Each of these questionnaires is divided into a number of sections and the number of questions in each section varies accordingly. It should be noted that in 2013/14, 2015/16, 2018/19, and 2019/20, all questionnaires were administered using the CAPI software .

This series measures the prevalence and correlates of drug use in the United States. The surveys are designed to provide quarterly, as well as annual, estimates. Information is provided on the use of illicit drugs, alcohol, and tobacco among members of United States households aged 12 and older. Questions include age at first use as well as lifetime, annual, and past-month usage for the following drug classes: marijuana, cocaine (and crack), hallucinogens, heroin, inhalants, alcohol, tobacco, anabolic steroids, nonmedical use of prescription drugs including psychotherapeutics, and polysubstance use. Respondents were also asked about substance abuse treatment history, illegal activities, problems resulting from use of drugs, perceptions of the risks involved, personal and family income sources and amounts, need for treatment for drug or alcohol use, criminal record, and needle-sharing. Questions on mental health and access to care, which were introduced in the 1994-B questionnaire (see NATIONAL HOUSEHOLD SURVEY ON DRUG ABUSE, 1994), were retained in this administration of the survey. Demographic data include sex, race, age, ethnicity, marital status, motor vehicle use, educational level, job status, income level, veteran status, and past and current household composition. This study has 1 Data Set.

Abstract

The demand for evidence based decision making has reached unprecedented levels today more than ever before. The level of data usage has extended not only to cover basic administrative data but also to include more detailed household level information. Household surveys therefore, have become an invaluable source of information for monitoring outcome and impact indicators of national and international development frameworks.

As a key contributor to the monitoring framework, Uganda Bureau of Statistics (UBOS) has conducted large-scale surveys since 1989. The surveys have had a nationwide coverage with varying core modules and objectives. The 2005/06 round of household surveys was yet another in a series conducted by UBOS. The last household survey was conducted in 2002/03 with a focus on labourforce and informal sector in addition to the standard Socio-economic module. This time round, the survey carries an agriculture module in addition to the Socio-economic module. The surveys primarily collect socio-economic data required for measurement of human development and monitoring social goals with special reference to the measurement of poverty under the Poverty Eradication Action Plan (PEAP) and Millennium Development Goals (MDGs).

The main objective of the survey was to collect high quality and timely data on demographic, social and economic characteristics of the household population for national and international development frameworks.

Specifically, the objectives were to: 1. Provide information on the selected economic characteristics of the population including their economic activity status among others. 2. Design and conduct a country-wide agricultural survey through the household approach and to prepare and provide estimates of area and production of major crops and other characteristics at national and regional levels. 3. Meet special data needs of users for the Ministries of Finance, Planning and Economic Development, Agriculture, Animal Industry and Fisheries, Health, Education and Sports among others, and other collaborating Institutions like Economic Policy Research Centre, together with donors and the NGO community so as to monitor the progress of their activities and interventions. 4. Generate and build social and economic indicators and monitor the progress made towards social and economic development goals of the country; and 5. Consolidate efforts being made in building a permanent national household survey capability at UBOS.

Geographic coverage

National

Analysis unit

• Households
• Individuals
• Communities

Universe

The survey covered a sample of household members in each district.

Kind of data

Sample survey data [ssd]

Sampling procedure

Survey Design A two stage sampling design was used to draw the sample. At the first stage, Enumeration Areas (EAs) were drawn with Probability Proportional to Size (PPS), and at the second stage, households which are the Ultimate Sampling Units, were drawn using Simple Random Sampling (SRS).

The sample of EAs for the UNHS 2005/06 was selected using the Uganda Population and Housing Census Frame for 2002. Initially, a total of 600 Enumeration Areas (EAs) was selected. These EAs were allocated to each region on the basis of the population size of the region. However, in the Northern region, the number of EAs drawn was doubled. The extra EAs were to be held in reserve to allow for EA attrition due to insecurity.

After this sample was drawn, it was realized that the sample size in 10 districts needed to be increased to about 30 EAs in each district to have an adequate sample size for separate analysis. These extra EAs were selected using an inter-penetrating sampling method which led to drawing an extra 153 EAs. Moreover, because a considerable proportion of the population in the North was in Internally Displaced People (IDPs) camps, this was treated as a separate selection stratum and an additional sample of 30 EAs was drawn from the IDPs. Thus, a total of 783 EAs representing both the general household population and displaced population was selected for the UNHS 2005/06.

Sample Size The size required for the sample was determined by taking into consideration several factors, the three most important being: the degree of precision (reliability) desired for the survey estimates, the cost and operational limitations, and the efficiency of the design. The UNHS 2005/06 covered a sample size of about 7,400 households.

Mode of data collection

Face-to-face [f2f]

Research instrument

Five types of questionnaires were administered, namely; socio-economic survey questionnaire, agriculture questionnaire, community questionnaire, price questionnaire and crop harvest cards. The Socio-economic questionnaire collected information on household characteristics including education and literacy, the overall health status, health seeking behavior of household members, malaria, fever and disability, activity status of household members, wage employment, enterprise activities, transfers and household incomes, housing conditions assets, loans, household expenditure, welfare indicators and household shocks. The Agricultural module covered the household crop farming enterprise particulars with emphasis on land, crop area, inputs, outputs and other allied characteristics. The Community Survey questionnaire collected information about the community (LC1). The information related to community access to facilities, community services and other amenities, economic infrastructure, agriculture and markets, education and health infrastructure and agricultural technologies. The Price questioonaire was administered to provide standard equivalents of non standard units through weighing items sold in markets. It was used to collect the different local prices and the non standard units which in many cases are used in selling various items. A crop card was administered to all sampled households with an agricultural activity. Respondents were requested to record all harvests from own produce.

Cleaning operations

Double entry was done to take care of data entry errors. Interactive data cleaning and secondary editing was done. All these processes were done using CSPro ( Census Survey Processing Data Entry application).

To ensure good quality of data, a system of double entry was used. A manual system of editing questionnaires was set-up in June 2005 and two office editors were recruited to further assess the consistency of the data collected. A computer program (hot-deck scrutiny) for verification and validation was developed and operated during data processing.

Range and consistency checks were included in the data-entry program that was developed in CSPro. More intensive and thorough checks were carried out using MS-ACCESS by the processing team.

Sampling error estimates

The estimates were derived from a scientifically selected sample and analysis of survey data was undertaken at national, regional and rural-urban levels. Sampling Errors (SE) and Coefficients of Variations (CVs) of some of the variables have been presented in Appendices of the Socio-Economic Report and Agricultural Module Reports to show the precision levels.

Geographic coverage

National coverage

Analysis unit

households/individuals

Kind of data

survey

Frequency of data collection

Quarterly

Sampling procedure

Sample size:

The National Household Travel Survey provides information to assist transportation planners and policy makers who need comprehensive data on travel and transportation patterns in the United States

This profile presents information from the 2011 National Household Survey (NHS) for various levels of geography, including provinces and territories, census metropolitan areas/census agglomerations, census divisions, census subdivisions, census tracts and federal electoral districts. NHS data topics include: Immigration and Ethnocultural Diversity; Aboriginal Peoples; Education and Labour; Mobility and Migration; Language of work; Income and Housing.

Abstract

The General Household Survey-Panel (GHS-Panel) is implemented in collaboration with the World Bank Living Standards Measurement Study (LSMS) team as part of the Integrated Surveys on Agriculture (ISA) program. The objectives of the GHS-Panel include the development of an innovative model for collecting agricultural data, interinstitutional collaboration, and comprehensive analysis of welfare indicators and socio-economic characteristics. The GHS-Panel is a nationally representative survey of approximately 5,000 households, which are also representative of the six geopolitical zones. The 2023/24 GHS-Panel is the fifth round of the survey with prior rounds conducted in 2010/11, 2012/13, 2015/16 and 2018/19. The GHS-Panel households were visited twice: during post-planting period (July - September 2023) and during post-harvest period (January - March 2024).

Geographic coverage

National

Analysis unit

• Households • Individuals • Agricultural plots • Communities

Universe

The survey covered all de jure households excluding prisons, hospitals, military barracks, and school dormitories.

Kind of data

Sample survey data [ssd]

Sampling procedure

The original GHS‑Panel sample was fully integrated with the 2010 GHS sample. The GHS sample consisted of 60 Primary Sampling Units (PSUs) or Enumeration Areas (EAs), chosen from each of the 37 states in Nigeria. This resulted in a total of 2,220 EAs nationally. Each EA contributed 10 households to the GHS sample, resulting in a sample size of 22,200 households. Out of these 22,200 households, 5,000 households from 500 EAs were selected for the panel component, and 4,916 households completed their interviews in the first wave.

After nearly a decade of visiting the same households, a partial refresh of the GHS‑Panel sample was implemented in Wave 4 and maintained for Wave 5. The refresh was conducted to maintain the integrity and representativeness of the sample. The refresh EAs were selected from the same sampling frame as the original GHS‑Panel sample in 2010. A listing of households was conducted in the 360 EAs, and 10 households were randomly selected in each EA, resulting in a total refresh sample of approximately 3,600 households.

In addition to these 3,600 refresh households, a subsample of the original 5,000 GHS‑Panel households from 2010 were selected to be included in the new sample. This “long panel” sample of 1,590 households was designed to be nationally representative to enable continued longitudinal analysis for the sample going back to 2010. The long panel sample consisted of 159 EAs systematically selected across Nigeria’s six geopolitical zones.

The combined sample of refresh and long panel EAs in Wave 5 that were eligible for inclusion consisted of 518 EAs based on the EAs selected in Wave 4. The combined sample generally maintains both the national and zonal representativeness of the original GHS‑Panel sample.

Sampling deviation

Although 518 EAs were identified for the post-planting visit, conflict events prevented interviewers from visiting eight EAs in the North West zone of the country. The EAs were located in the states of Zamfara, Katsina, Kebbi and Sokoto. Therefore, the final number of EAs visited both post-planting and post-harvest comprised 157 long panel EAs and 354 refresh EAs. The combined sample is also roughly equally distributed across the six geopolitical zones.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The GHS-Panel Wave 5 consisted of three questionnaires for each of the two visits. The Household Questionnaire was administered to all households in the sample. The Agriculture Questionnaire was administered to all households engaged in agricultural activities such as crop farming, livestock rearing, and other agricultural and related activities. The Community Questionnaire was administered to the community to collect information on the socio-economic indicators of the enumeration areas where the sample households reside.

GHS-Panel Household Questionnaire: The Household Questionnaire provided information on demographics; education; health; labour; childcare; early child development; food and non-food expenditure; household nonfarm enterprises; food security and shocks; safety nets; housing conditions; assets; information and communication technology; economic shocks; and other sources of household income. Household location was geo-referenced in order to be able to later link the GHS-Panel data to other available geographic data sets (forthcoming).

GHS-Panel Agriculture Questionnaire: The Agriculture Questionnaire solicited information on land ownership and use; farm labour; inputs use; GPS land area measurement and coordinates of household plots; agricultural capital; irrigation; crop harvest and utilization; animal holdings and costs; household fishing activities; and digital farming information. Some information is collected at the crop level to allow for detailed analysis for individual crops.

GHS-Panel Community Questionnaire: The Community Questionnaire solicited information on access to infrastructure and transportation; community organizations; resource management; changes in the community; key events; community needs, actions, and achievements; social norms; and local retail price information.

The Household Questionnaire was slightly different for the two visits. Some information was collected only in the post-planting visit, some only in the post-harvest visit, and some in both visits.

The Agriculture Questionnaire collected different information during each visit, but for the same plots and crops.

The Community Questionnaire collected prices during both visits, and different community level information during the two visits.

Cleaning operations

CAPI: Wave five exercise was conducted using Computer Assisted Person Interview (CAPI) techniques. All the questionnaires (household, agriculture, and community questionnaires) were implemented in both the post-planting and post-harvest visits of Wave 5 using the CAPI software, Survey Solutions. The Survey Solutions software was developed and maintained by the Living Standards Measurement Unit within the Development Economics Data Group (DECDG) at the World Bank. Each enumerator was given a tablet which they used to conduct the interviews. Overall, implementation of survey using Survey Solutions CAPI was highly successful, as it allowed for timely availability of the data from completed interviews.

DATA COMMUNICATION SYSTEM: The data communication system used in Wave 5 was highly automated. Each field team was given a mobile modem which allowed for internet connectivity and daily synchronization of their tablets. This ensured that head office in Abuja had access to the data in real-time. Once the interview was completed and uploaded to the server, the data was first reviewed by the Data Editors. The data was also downloaded from the server, and Stata dofile was run on the downloaded data to check for additional errors that were not captured by the Survey Solutions application. An excel error file was generated following the running of the Stata dofile on the raw dataset. Information contained in the excel error files were then communicated back to respective field interviewers for their action. This monitoring activity was done on a daily basis throughout the duration of the survey, both in the post-planting and post-harvest.

DATA CLEANING: The data cleaning process was done in three main stages. The first stage was to ensure proper quality control during the fieldwork. This was achieved in part by incorporating validation and consistency checks into the Survey Solutions application used for the data collection and designed to highlight many of the errors that occurred during the fieldwork.

The second stage cleaning involved the use of Data Editors and Data Assistants (Headquarters in Survey Solutions). As indicated above, once the interview is completed and uploaded to the server, the Data Editors review completed interview for inconsistencies and extreme values. Depending on the outcome, they can either approve or reject the case. If rejected, the case goes back to the respective interviewer’s tablet upon synchronization. Special care was taken to see that the households included in the data matched with the selected sample and where there were differences, these were properly assessed and documented. The agriculture data were also checked to ensure that the plots identified in the main sections merged with the plot information identified in the other sections. Additional errors observed were compiled into error reports that were regularly sent to the teams. These errors were then corrected based on re-visits to the household on the instruction of the supervisor. The data that had gone through this first stage of cleaning was then approved by the Data Editor. After the Data Editor’s approval of the interview on Survey Solutions server, the Headquarters also reviews and depending on the outcome, can either reject or approve.

The third stage of cleaning involved a comprehensive review of the final raw data following the first and second stage cleaning. Every variable was examined individually for (1) consistency with other sections and variables, (2) out of range responses, and (3) outliers. However, special care was taken to avoid making strong assumptions when resolving potential errors. Some minor errors remain in the data where the diagnosis and/or solution were unclear to the data cleaning team.

Response

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 Uganda National Household Survey (UNHS) 2012-2013 was conducted by the Uganda Bureau of Statistics from June 2012 to June 2013. The objectives of the survey included:

1. To provide information required for monitoring the National Development Strategy, of major programs such as NAADS and General Budget Support, and also to provide information to 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 and provide annual information on service delivery and consumption expenditure estimates to monitor poverty and service outcomes in interim years of other national survey efforts, such as the 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- and post-natal care, or assessing the effect of agricultural input subsidies;
4. To provide a framework for policy oriented analysis and capacity building substantiated with the UGDR and support to other research which will feed into the Annual Policy Implementation Review;
5. To facilitate randomized impact evaluations of interventions whose effects cannot currently be readily assessed through the existing system of Uganda National Household Surveys.

The UNHS is scheduled to be carried out annually over a twelve-month period on a nationally representative sample of approximately 3,000 households. The survey was conducted in two visits in order to capture the two cropping seasons of the country. The UNHS interviewed each household twice a year, in visits six months apart.

Geographic coverage

National

Analysis unit

• Household
• Individual

Kind of data

Sample survey data [ssd]

Sampling procedure

The UNHS initial sample was a subset of about 3,220 households, selected from the 7,426 households visited during the UNHS 2005-06. This initial sample has been visited for three consecutive years (2009/10, 20010/11 and 2011/2012) after which, parts of the sample will start to be replaced in Wave IV (2013/2014) by new EAs extracted from the updated sample frames developed by UBOS from the 2012 Census. About 100 have been replaced.

The sample frame used was the 2012 cartographic list of eumenaration areas.The survey used a two stage sampling design: - At the first stage, 750 enumeration areas (EA) were selected - At the second stage, 10 households were randomly selected in each EA (7,500)

Mode of data collection

Face-to-face [f2f]

Research instrument

To suit its multiple objectives, the UNPS was comprised of a set of survey instruments. These were the following questionnaires: 1) Socio-Economic Questionaire: Core and rotating modules 2) Labour Module Questionnaire 3) Price (Market) Questionnaire 4) Community / Facility Questionnaires for schools, health facilities and other facilities (potentially conducted on a rotating basis and not in every year of the UNHS)

Response rate

95%

Abstract

The main objective of the Uganda National Household Survey 2002/03 was to collect high quality and timely data on demographic and socio-economic characteristics of household population for monitoring development performance of the country.

Specifically, the survey aimed at: (a) Providing information on the economic characteristics of the population and its economic activity status i.e. the employment, unemployment and underemployment. (b) Generating data for calculating gross output, value added, and other economic indicators required for National Accounts purposes. (c) Integrating household socio-economic and community level surveys in the overall survey programme so as to provide an integrated data set. This will provide an understanding of the mechanisms and effects of various government programmes and policy measures on a comparative basis over time; (d) Meeting special data needs of users for the Ministries of Health; Education; Gender, Labour and Social Development and other collaborating Institutions, together with donors and the NGO community so as to monitor the progress of their activities and interventions (e) Generating and building social and economic indicators for monitoring the progress made towards social and economic development goals of the country

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

The survey included the following modules: · Socio-economic module · Labour force module · Informal sector · Community survey

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

• Individual
• Household
• Community

Universe

The survey covered all resident population.

Kind of data

Sample survey data [ssd]

Sampling procedure

The UNHS sample was drawn through a stratified two-stage sampling design. The Enumeration Area (EA) was used as the first stage sampling unit and the household as the second stage-sampling unit. The sampling frame used for selection of first stage units (fsus) was the list of EAs with the number of households based on the cartographic work of the 2002 Population and Housing Census. A total of 972 EAs (565 in rural and 407 in urban areas) were covered. In order to select the second stage units, which are the households, a listing exercise using listing schedules was done in all selected EAs.

The sample size was determined by taking into consideration several factors, the three most important being: the degree of precision (reliability) desired for the survey estimates, the cost and operational limitations, and the efficiency of the design. UNHS 2002/03 covered a sample of 9,711 households.

Note: Details of the sampling design are given in Appendix III of the socio-economic survey report.

Mode of data collection

Face-to-face [f2f]

Research instrument

Nine types of questionnaires were used during the survey namely; Household Listing questionnaire, the Socio-Economic questionnaire, the Labourforce questionnaire, the Community questionnaire, Forestry Enterprise questionnaire, Trade and Services Enterprise questionnaire, Manufacturing, Mining and Quarrying Enterprise questionnaire, Livestock Enterprise questionnaire and Hotel Enterprise questionnaire. The last five questionnaires were administered to small-scale establishments and household enterprises. These were developed in consultation with various stakeholders. The household listing questionnaire was used to list all houses and households in the selected Enumeration Areas (EAs). Finally, the community questionnaire was administered at community level (Local Council level I).

Cleaning operations

A manual system of editing questionnaires was set up and a set of scrutiny notes to guide in manual checking was developed. In addition, range and consistency checks were included in the data-entry program. More intensive and thorough checks were carried out using MS-ACCESS by the processing team. Besides the editing done before data entry, the validation checks inbuilt in the program and double data entry, additional in-depth data cleaning on sections relevant for basic poverty analysis was done. For instance, individual level files were linked together to ensure that the same individual code reported in different sections of the questionnaire and in other modules corresponded to the same individual. Data cleaning on the other sections was also done. Any inconsistencies, data entry errors etc found were corrected after checking the original questionnaires.

Response rate

The response rate for the Uganda National Household Survey 2002/2003 was approximately 97%. A total of 9711 households were interviewed out of the 10,000 households initially targeted. A total of 289 households could not be interviewed mainly due to insecurity.

Sampling error estimates

There are two types of errors possible in any estimate based on a sample survey – sampling and non-sampling errors.

Non-sampling errors can be attributed to many sources which include: definitional difficulties, differences in the interpretation of questions by the interviewers, inability or unwillingness to provide correct responses on part of the respondents, mistakes in coding or recording the data, et cetera. Nonsampling errors would also occur in a complete census.

On the other hand, sampling errors occur because observations are made only on a sample, and not the entire population. Thus the accuracy of survey results is determined by the joint effects of the sampling and nonsampling errors.

For a given indicator, the sampling error is usually measured by the standard error. The standard error of a survey estimate is a measure of the variation among the estimates from all possible samples, and is a measure of the precision with which an estimate from a particular sample approximates the results from all possible samples. The accuracy of a survey result de pends on both the sampling and nonsampling error measured by the standard error and the bias; and other types of nonsampling errors not measured by the standard error.

The standard errors of the rates presented in this appendix were computed using the SASÓ PROC SURVEYMEANS procedure. This procedure does not assume that the data was taken from a simple random sample, but rather from a more complex design. The SurveyMeans Procedure takes into account the effect of clustering and stratifying in the calculation of the variances and standard errors, using the Taylor expansion method to estimate these sampling errors.

The sampling errors are computed for selected variables considered to be of interest, but can be computed for all variables in the dataset. The sampling errors are presented for the country as a whole, for women and men where relevant, and for rural and urban areas and for each of the four regions: Central, East, West and North. For each variable the type of statistic (mean, sum, rate) are given as well as the standard error, the 95% confidence limits, and the coefficient of variation.

Generally the standard errors of most national estimates are small and within acceptable limits, but there is wider variability for the estimates of the subpopulations. For example for the Net Attendance Ration (NER), the standard error for the whole country is 6.5 percent, while for urban and rural areas it is 7.6 and 7.3 percent respectively. For more details about the estimates of sampling error can be found in Appendix IV of "UNHS 2002/2003 Report on the Socio-Economic Survey"

The National Household Survey on Drug Abuse (NHSDA) series measures the prevalence and correlates of drug use in the United States. The surveys are designed to provide quarterly, as well as annual, estimates. Information is provided on the use of illicit drugs, alcohol, and tobacco among members of United States households aged 12 and older. Questions include age at first use as well as lifetime, annual, and past-month usage for the following drug classes: marijuana, cocaine (and crack), hallucinogens, heroin, inhalants, alcohol, tobacco, and nonmedical use of prescription drugs, including psychotherapeutics. Respondents were also asked about personal and family income sources and amounts, substance abuse treatment history, illegal activities, problems resulting from the use of drugs, need for treatment for drug or alcohol use, criminal record, and needle-sharing. Questions on mental health and access to care, which were introduced in the 1994-B questionnaire (see NATIONAL HOUSEHOLD SURVEY ON DRUG ABUSE, 1994), were retained in this administration of the survey. Also retained was the section on risk/availability of drugs that was reintroduced in 1996, and sections on driving behavior and personal behavior were added (see NATIONAL HOUSEHOLD SURVEY ON DRUG ABUSE, 1996). The 1997 questionnaire (NATIONAL HOUSEHOLD SURVEY ON DRUG ABUSE, 1997) introduced new items that the 1998 NHSDA continued on cigar smoking, people who were present when respondents used marijuana or cocaine for the first time (if applicable), reasons for using these two drugs the first time, reasons for using these two drugs in the past year, reasons for discontinuing use of these two drugs (for lifetime but not past-year users), and reasons respondents never used these two drugs. Both the 1997 and 1998 NHSDAs had a series of questions that were asked only of respondents aged 12 to 17. These items covered a variety of topics that may be associated with substance use and related behaviors, such as exposure to substance abuse prevention and education programs, gang involvement, relationship with parents, and substance use by friends. Demographic data include sex, race, age, ethnicity, marital status, educational level, job status, income level, veteran status, and current household composition. This study has 1 Data Set.

Geographic coverage

The survey covers all the Counties in Kenya based on the following levels National, Urban, Rural and County

Analysis unit

Households Indviduals within Households

Kind of data

Sample survey data [ssd]

Mode of data collection

Face-to-face [f2f]

The National Household Survey (NHS) tracks progress in personal disaster preparedness through investigation of the American public's preparedness actions, attitudes, and motivations. FEMA administers the survey in English and Spanish via landline and mobile telephone to a random sampling of approximately 5,000 adult respondents. The survey includes a nationally representative sample as well as hazard-specific oversamples which may include earthquake, flood, wildfire, hurricane, winter storm, extreme heat, tornado, and urban event. FEMA delays publishing the data until approximately the release of the summary results for the subsequent NHS iteration. For example, FEMA published the 2017 data package at approximately the same time as the publication of the 2018 NHS Summary.Each zip file may include an analysis summary, the survey instrument, raw weighted and unweighted data, aggregated data analysis, and a codebook with weighting overviews.Raw Data: Datasets may include unedited raw data. As such, users should plan to clean the data as needed prior to analysis.Citation: Users should cite the date the data was accessed or retrieved from fema.gov. In addition, users must clearly state that "FEMA and the Federal Government cannot vouch for the data or analyses derived from these data after the data have been retrieved from the Agency's website.”

Abstract

Panel data possess several advantages over conventional cross-sectional and time-series data, including their power to isolate the effects of specific actions, treatments, and general policies often at the core of large-scale econometric development studies. While the concept of panel data alone provides the capacity for modeling the complexities of human behavior, the notion of universal panel data – in which time- and situation-driven variances leading to variations in tools, and thus results, are mitigated – can further enhance exploitation of the richness of panel information.

The Basic Information Document (BID) provides a brief overview of the Nigerian General Household Survey (GHS) but focuses primarily on the theoretical development and application of panel data, as well as key elements of the universal panel survey instrument and datasets generated by the four rounds of the GHS. As the BID does not describe in detail the background, development, or use of the GHS itself, the wave-specific GHS BIDs should supplement the information provided here.

The Nigeria Universal Panel Data (NUPD) consists of both survey instruments and datasets from the two survey visits of the GHS - Post-Planting (PP) and Post-Harvest (PH) - meticulously aligned and engineered with the aim of facilitating the use of and improving access to the wealth of panel data offered by the GHS. The NUPD provides a consistent and straightforward means of conducting user-driven analyses using convenient, standardized tools.

The design of the NUPD combines the four completed Waves of the GHS Household Post-Planting and Post-Harvest Surveys – Wave 1 (2010/11), Wave 2 (2012/13), Wave 3 (2015/16), and Wave 4 (2018/19) – into pooled, module-specific survey instruments and datasets. The panel survey instruments offer the ease of comparability over time, with modifications and variances easily identifiable as well as those aspects of the questionnaire which have remained identical and offer consistent information. By providing all module-specific data over time within compact, pooled datasets, panel datasets eliminate the need for user-generated merges between rounds and present data in a clear, logical format, increasing both the usability and comprehension of complex data.

Geographic coverage

National

Analysis unit

• Households
• Individuals

Universe

The survey covered all de jure households excluding prisons, hospitals, military barracks, and school dormitories.

Kind of data

Sample survey data [ssd]

Sampling procedure

Please see the GHS BIDs for each round for detailed descriptions of the sample design used in each round and their respective implementation efforts as this is a compilation of datasets from all previous waves.

Mode of data collection

Face-to-face [f2f]

Research instrument

The larger GHS-Panel project consists of three questionnaires (Household Questionnaire, Agriculture Questionnaire, Community Questionnaire) for each of the two visits (Post-Planting and Post-Harvest). The GHS-NUPD only consists of the Household Questionnaire.

GHS-Panel Household Questionnaire: The Household Questionnaire provides information on demographics; education; health (including anthropometric measurement for children); labor; food and non-food expenditure; household nonfarm income-generating activities; food security and shocks; safety nets; housing conditions; assets; information and communication technology; and other sources of household income.

The Household Questionnaire is slightly different for the two visits. Some information was collected only in the post-planting visit, some only in the post-harvest visit, and some in both visits.

Cleaning operations

Please see the GHS BIDs for each round for detailed descriptions of data editing and additional data processing efforts as this is a compilation of datasets from all previous waves.

Abstract

The General Household Survey-Panel (GHS-Panel) is implemented in collaboration with the World Bank Living Standards Measurement Study (LSMS) team as part of the Integrated Surveys on Agriculture (ISA) program. The objectives of the GHS-Panel include the development of an innovative model for collecting agricultural data, interinstitutional collaboration, and comprehensive analysis of welfare indicators and socio-economic characteristics. The GHS-Panel is a nationally representative survey of approximately 5,000 households, which are also representative of the six geopolitical zones. The 2018/19 is the fourth round of the survey with prior rounds conducted in 2010/11, 2012/13, and 2015/16. GHS-Panel households were visited twice: first after the planting season (post-planting) between July and September 2018 and second after the harvest season (post-harvest) between January and February 2019.

Geographic coverage

National

Analysis unit

• Households
• Individuals
• Agricultural plots
• Communities

Universe

The survey covered all de jure households excluding prisons, hospitals, military barracks, and school dormitories.

Kind of data

Sample survey data [ssd]

Sampling procedure

The original GHS-Panel sample of 5,000 households across 500 enumeration areas (EAs) and was designed to be representative at the national level as well as at the zonal level. The complete sampling information for the GHS-Panel is described in the Basic Information Document for GHS-Panel 2010/2011. However, after a nearly a decade of visiting the same households, a partial refresh of the GHS-Panel sample was implemented in Wave 4.

For the partial refresh of the sample, a new set of 360 EAs were randomly selected which consisted of 60 EAs per zone. The refresh EAs were selected from the same sampling frame as the original GHS-Panel sample in 2010 (the “master frame”). A listing of all households was conducted in the 360 EAs and 10 households were randomly selected in each EA, resulting in a total refresh sample of approximated 3,600 households.

In addition to these 3,600 refresh households, a subsample of the original 5,000 GHS-Panel households from 2010 were selected to be included in the new sample. This “long panel” sample was designed to be nationally representative to enable continued longitudinal analysis for the sample going back to 2010. The long panel sample consisted of 159 EAs systematically selected across the 6 geopolitical Zones. The systematic selection ensured that the distribution of EAs across the 6 Zones (and urban and rural areas within) is proportional to the original GHS-Panel sample. Interviewers attempted to interview all households that originally resided in the 159 EAs and were successfully interviewed in the previous visit in 2016. This includes households that had moved away from their original location in 2010. In all, interviewers attempted to interview 1,507 households from the original panel sample.

The combined sample of refresh and long panel EAs consisted of 519 EAs. The total number of households that were successfully interviewed in both visits was 4,976.

Sampling deviation

While the combined sample generally maintains both national and Zonal representativeness of the original GHS-Panel sample, the security situation in the North East of Nigeria prevented full coverage of the Zone. Due to security concerns, rural areas of Borno state were fully excluded from the refresh sample and some inaccessible urban areas were also excluded. Security concerns also prevented interviewers from visiting some communities in other parts of the country where conflict events were occurring. Refresh EAs that could not be accessed were replaced with another randomly selected EA in the Zone so as not to compromise the sample size. As a result, the combined sample is representative of areas of Nigeria that were accessible during 2018/19. The sample will not reflect conditions in areas that were undergoing conflict during that period. This compromise was necessary to ensure the safety of interviewers.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The GHS-Panel Wave 4 consists of three questionnaires for each of the two visits. The Household Questionnaire was administered to all households in the sample. The Agriculture Questionnaire was administered to all households engaged in agricultural activities such as crop farming, livestock rearing and other agricultural and related activities. The Community Questionnaire was administered to the community to collect information on the socio-economic indicators of the enumeration areas where the sample households reside.

GHS-Panel Household Questionnaire: The Household Questionnaire provides information on demographics; education; health (including anthropometric measurement for children); labor; food and non-food expenditure; household nonfarm income-generating activities; food security and shocks; safety nets; housing conditions; assets; information and communication technology; and other sources of household income. Household location is geo-referenced in order to be able to later link the GHS-Panel data to other available geographic data sets.

GHS-Panel Agriculture Questionnaire: The Agriculture Questionnaire solicits information on land ownership and use; farm labor; inputs use; GPS land area measurement and coordinates of household plots; agricultural capital; irrigation; crop harvest and utilization; animal holdings and costs; and household fishing activities. Some information is collected at the crop level to allow for detailed analysis for individual crops.

GHS-Panel Community Questionnaire: The Community Questionnaire solicits information on access to infrastructure; community organizations; resource management; changes in the community; key events; community needs, actions and achievements; and local retail price information.

The Household Questionnaire is slightly different for the two visits. Some information was collected only in the post-planting visit, some only in the post-harvest visit, and some in both visits.

The Agriculture Questionnaire collects different information during each visit, but for the same plots and crops.

Cleaning operations

CAPI: For the first time in GHS-Panel, the Wave four exercise was conducted using Computer Assisted Person Interview (CAPI) techniques. All the questionnaires, household, agriculture and community questionnaires were implemented in both the post-planting and post-harvest visits of Wave 4 using the CAPI software, Survey Solutions. The Survey Solutions software was developed and maintained by the Survey Unit within the Development Economics Data Group (DECDG) at the World Bank. Each enumerator was given tablets which they used to conduct the interviews. Overall, implementation of survey using Survey Solutions CAPI was highly successful, as it allowed for timely availability of the data from completed interviews.

DATA COMMUNICATION SYSTEM: The data communication system used in Wave 4 was highly automated. Each field team was given a mobile modem allow for internet connectivity and daily synchronization of their tablet. This ensured that head office in Abuja has access to the data in real-time. Once the interview is completed and uploaded to the server, the data is first reviewed by the Data Editors. The data is also downloaded from the server, and Stata dofile was run on the downloaded data to check for additional errors that were not captured by the Survey Solutions application. An excel error file is generated following the running of the Stata dofile on the raw dataset. Information contained in the excel error files are communicated back to respective field interviewers for action by the interviewers. This action is done on a daily basis throughout the duration of the survey, both in the post-planting and post-harvest.

DATA CLEANING: The data cleaning process was done in three main stages. The first stage was to ensure proper quality control during the fieldwork. This was achieved in part by incorporating validation and consistency checks into the Survey Solutions application used for the data collection and designed to highlight many of the errors that occurred during the fieldwork.

The second stage cleaning involved the use of Data Editors and Data Assistants (Headquarters in Survey Solutions). As indicated above, once the interview is completed and uploaded to the server, the Data Editors review completed interview for inconsistencies and extreme values. Depending on the outcome, they can either approve or reject the case. If rejected, the case goes back to the respective interviewer’s tablet upon synchronization. Special care was taken to see that the households included in the data matched with the selected sample and where there were differences, these were properly assessed and documented. The agriculture data were also checked to ensure that the plots identified in the main sections merged with the plot information identified in the other sections. Additional errors observed were compiled into error reports that were regularly sent to the teams. These errors were then corrected based on re-visits to the household on the instruction of the supervisor. The data that had gone through this first stage of cleaning was then approved by the Data Editor. After the Data Editor’s approval of the interview on Survey Solutions server, the Headquarters also reviews and depending on the outcome, can either reject or approve.

The third stage of cleaning involved a comprehensive review of the final raw data following

Abstract

The Uganda 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 UNPS 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

• Household
• Individual
• Communities

Kind of data

Sample survey data [ssd]

Sampling procedure

The 2010/11 UNPS survey maintained the 2009/10 UNPS 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 UNPS 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 [f2f]

Research instrument

To suit its multiple objectives, the UNPS was comprised of a set of survey instruments. These were the following questionnaires: 1. Agriculture Questionnaire (administered to the subset of UNPS households engaged in agricultural activities) 2. Household Questionnaire 3. Community Questionnaire

Response rate

84%

Conducted by the Federal Highway Administration (FHWA), the National Household Travel Survey (NHTS) is the authoritative source on the travel behavior of the American public. It is the only source of national data that allows one to analyze trends in personal and household travel. It includes daily non-commercial travel by all modes, including characteristics of the people traveling, their household, and their vehicles. The NHTS has been conducted in 1983, 1990, 1995, 2001, 2009, and 2017.

The 2011 NHS survey is typically expressed as count data. The IHDA will express the survey results in percentages. This is done by dividing specific counts by the total, for each survey roup. For some questions, the survey is already expressed as a percent (ex. Participation Rate).

Abstract

The National Household Travel Survey (NHTS) 2020 is the third round of the survey series designed to assess domestic transport and tourism travel patterns of South African households as well as their attitudes about transport. The NHTS collects data on general household characteristics, travel patterns of households, and attitudes about transport.

Geographic coverage

National coverage

Analysis unit

Households and individuals

Universe

The target population of the survey consists of all private households in all nine provinces of South Africa and residents in workers' hostels. The survey does not cover other collective living quarters such as students' hostels, old-age homes, hospitals, prisons and military barracks.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample design for the NHTS was based on a master sample (MS) that used a two-stage, stratified design with probability-proportional-to-size (PPS) sampling of PSUs from within strata, and systematic sampling of dwelling units (DUs) from the sampled primary sampling units (PSUs). A self-weighting design at provincial level was used and MS stratification was divided into two levels, primary and secondary stratification. Primary stratification was defined by metropolitan and non-metropolitan geographic area type. During secondary stratification, the Census 2001 data were summarized at PSU level. The following variables were used for secondary stratification, household size, education, occupancy status, gender, industry and income.

Census enumeration areas (EAs) as delineated for Census 2001 formed the basis of the PSUs. The following additional rules were used: • Where possible, PSU sizes were kept between 100 and 500 dwelling units (DUs); • EAs with fewer than 25 DUs were excluded. • EAs with between 26 and 99 DUs were pooled to form larger PSUs and the criteria used was same settlement type; • Virtual splits were applied to large PSUs: 500 to 999 splits into two; 1000 to 1499 splits into three; and 1500 plus split into four PSUs; and • Informal PSUs were segmented.

A Randomized Probability Proportional to Size (RPPS) systematic sample of PSUs was drawn in each stratum, with the measure of size being the number of households in the PSU. Altogether approximately 3080 PSUs were selected. In each selected PSU a systematic sample of dwelling units was drawn. The number of DUs selected per PSU varies from PSU to PSU and depends on the Inverse Sampling Ratios (ISR) of each PSU.

Mode of data collection

Face-to-face [f2f]

Research instrument

The survey questionnaire consisted of 9 sections: Section 1: General health and functioning, social grants and social relief Section 2: General travel patterns Section 3: Education and education-related travel patterns Section 4: Work-related travel patterns (age 15 years and above) Section 5: Business trips Section 6: Other travel patterns Section 7: General household information Section 8: Household attitudes and perceptions about transport Section 9: Survey officer questions

Abstract

The Uganda Bureau of Statistics (UBOS) has been carrying out an integrated household survey, popularly known as Uganda National Household Survey (UNHS) every other year since the late 1980s. Through the UNHS, Uganda has very rich household time series data covering over 13 years. The data have been the main source of statistical information for monitoring poverty levels, trends and related welfare issues.

The UNHS 2009/10 was undertaken from May 2009 to April 2010 and covered about 6800 households scientifically selected countrywide. The survey was comprehensive and had six modules, namely; Socio-economic, Labor Force, Informal Sector, Community, Price and Qualitative modules.

The main objective of the survey was to collect high quality and timely data on demographic, social and economic characteristics of the household population to inform/monitor international and national development frameworks. The specific objectives of the survey were to: 1. Provide information on selected economic characteristics of the population including their economic activity status among others. 2. Meet data needs of key users such as Ministry of Finance, Planning and Economic Development; Health; Education and Sports, etc.., and other collaborating Institutions like Economic Policy Research Centre (EPRC); the Development Partners as well as the NGO community. 3. Generate and build social and economic indicators and monitor the progress made towards social and economic development goals of the country; and 4. Strengthen efforts being made in building a permanent national household survey capability at UBOS.

Geographic coverage

National

Kind of data

Sample survey data [ssd]

Sampling procedure

Survey Design The UNHS 2009/10 sample was designed to allow reliable estimation of key indicators for the Uganda, rural-urban, and separately for ten sub regions. A two-stage stratified sampling design was used. At the first stage, Enumeration Areas (EAs) were grouped by districts and rural-urban location; then drawn using Probability Proportional to Size (PPS). At the second stage, households which are the Ultimate Sampling Units were drawn using Systematic Sampling.

A total of 712 EAs representing the general household population were selected using the Uganda Population and Housing Census Frame for 2002. These EAs were allocated to the 10 sub-regions with consideration of the rural and urban areas which constituted the main domains of the sample.

Sample Size When determining the required sample size, the degree of precision (reliability) desired for the survey estimates, the cost and operational limitations, and the efficiency of the design were taken into consideration. The UNHS 2009/10 covered a sample size of 6800 households.

Mode of data collection

Face-to-face [f2f]

Research instrument

There are five questionnaires for the UNHS namely: (i) Listing questionnaire (ii) socio-economic Questionnaire (iii) Labour Force survey questionnaire (iv) Informal Sector Questionnaires (v) Community Questionnaire

Note that the informal sector survey questionnaires comprise 5 sets according to activity namely: (1) Livestock, poultry, bee-keeping, and fishing (2) Forestry (3) Mining, quarrying, and manufacturing (4) Hotels, lodges, bars, restaurants and eating places (5) Trade and services

Cleaning operations

A system of double data entry was utilized to ensure good quality data. Questionnaires were manually edited by five office based editors who were recruited to ensure consistency of the data collected. A computer program (hot-deck scrutiny) for verification and validation was developed and operated during data processing. Range and consistency checks were included in the data-entry program. More intensive and thorough checks were also carried out using MS-ACCESS by the data processing team.

Sampling error estimates

Household survey findings are usually estimates based on a sample of households selected using appropriate sample designs. Estimates are affected by two types of errors; sampling and non-sampling errors. Non-Sampling errors result from wrong interpretation of results; mistakes in recording of responses, definitional problems, improper recording of data, etc and are mainly committed during the implementation of the survey.

Sampling errors, on the other hand, arise because observations are based on only one of the many samples that could have been selected from the same population using the same design and expected size. They are a measure of the variability between all possible samples. Sampling errors are usually measured using Standard Errors (SE). SE is the square root of the variance and can be used to calculate confidence intervals for the various estimates. In addition, sometimes it is appropriate to measure the relative errors of some of the variables and the Coefficient of Variation (CV) is one such measure. It is the quotient of the SE divided by the mean of the variable of interest.

The SE and CVs were computed using STATA software and they each take into account the multi-stage nature of the survey design. The results below indicate the SE and CVs computed for the selected variables in the report. The SEs and CVs are presented for national, regional and rural-urban levels.

Note: Detailed sampling error tables are available in the 2009-2010 UNHS final report.