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

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 .

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.

Geographic coverage

National coverage

Analysis unit

households/individuals

Kind of data

survey

Frequency of data collection

Quarterly

Sampling procedure

Sample size:

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 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%

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, and nonmedical use of prescription drugs, including psychotherapeutics. Respondents were also asked about substance abuse treatment history, illegal activities, problems resulting from the use of drugs, 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. In 1996, the section on risk/availability of drugs was reintroduced, and sections on driving behavior and personal behavior were added. 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.

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.

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

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

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

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 objective of the ENIGH is to provide a statistical overview of the behavior of household income and expenditure in terms of its amount, origin and distribution; it also offers information on the occupational and sociodemographic characteristics of the members of the household, as well as the characteristics of the housing infrastructure and household equipment.

From 1984, when INEGI began to carry out the survey, until today, new methodologies have been developed, international recommendations have been issued and good practices have been documented for the generation of information on household income and expenditure through surveys.

During this period, additions have been made to the subject matter of the survey, methodological updates and innovations in the processes, to obtain results that reflect reality, taking into account international recommendations and the information requirements of the different users. When the adoption of recommendations and good practices implied a break in the comparability of results, it was preferred to maintain historical comparability.

As of 2008, INEGI decided to publish the results of the ENIGH, whose variables have been constructed and presented in accordance with the recommendations of the UN, specifically, those issued at the 17th International Conference of Labor Statisticians and in the Report of the Canberra Group. This new construction is also the one used in the database of the Socio-Economic Conditions Module of the ENIGH, which is the source of information for the multidimensional measurement of poverty carried out by the National Council for the Evaluation of Social Development Policy (CONEVAL).

Now, in addition to mentioning and analyzing the international recommendations that were put into practice at the ENIGH 2020, this document also recounts the background of the ENIGH, how it emerged and the significant changes it has undergone since then; the objectives of the survey and the recruitment instruments used are mentioned; likewise, as the main axis, there is the description of income and expenditure, their sources, their correlation and implications, this, as the main indicators of household well-being; another chapter lists the main users of the survey information; and finally, the schemes of the topics, categories and variables used in the ENIGH 2020 are presented. Periodicity: Since 1992 it has been carried out biennially (every two years) with the exception of 2005 when an extraordinary survey was carried out.

Target population: It is made up of the households of nationals or foreigners, who usually reside in private homes within the national territory.

Selection Unit: Private home. The dwellings are chosen through a meticulous statistical process that guarantees that the results obtained from only a part of the population (sample) can be generalized to the total.

Sampling Frame: The sampling frame used is the multipurpose framework of the INEGI, it is constituted with the demographic and cartographic information obtained from the Population Census and Housing 2010. Effective sample size: 105,483 households. Observation unit: The home.

Unit of analysis: The household, the dwelling and the members of the household.

Thematic coverage:

Characteristics of the house. Residents and identification of households in the dwelling. Sociodemographic characteristics of the residents of the dwelling. Home equipment, services. Activity condition and occupational characteristics of household members aged 12 and over. Total current income (monetary and non-monetary) of households. Financial and capital perceptions of households and their members. Current monetary expenditure of households. Financial and capital expenditures of households.

The different concepts of the ENIGH are governed by recommendations agreed upon in international conventions, for example:

The resolutions and reports of the 18 International Conferences on Labour Statistics, of the International Labour Organization (ILO).

The final report and recommendations of the Canberra Group, an expert group on "Household Income Statistics".

Manual of Household Surveys. Department of International Economic and Social Affairs, Bureau of Statistics. United Nations, New York, 1987.

They are also articulated with the System of National Accounts and with the Household Surveys carried out by INEGI.

Sample size: At the national level, including the ten-one, there are 93,186 private homes.

Workload: According to the meticulousness in the recording of information in this project, a load of six interviews in private homes per dozen has been defined for each interviewer. The number of interviews may decrease or increase according to several factors: non-response, recovery from non-response, or additional households.

Geographic coverage

National and at the state level - Urban: localities with 2,500 or more inhabitants - Rural: localities with less than 2,500 inhabitants

Analysis unit

The household, the dwelling and the members of the household.

Universe

The survey is aimed at households in the national territory.

Kind of data

Probabilistic household survey

Sampling procedure

The design of the subsample for ENIGH-2020 is characterized by being probabilistic; Consequently, the results obtained from the survey are generalized to the entire population of the study domain, in turn it is two-stage, stratified and by clusters, where the ultimate unit of selection is the dwelling and the unit of observation is the household.

The ENIGH-2020 subsample was selected from the 2012 INEGI master sample, this master sample was designed and selected from the 2012 Master Sampling Framework (Marco Maestro de Muestreo (MMM)) which was made up of housing clusters called Primary Sampling Units (PSUs), built from the cartographic and demographic information obtained from the 2010 Population and Housing Census. The master sample allows the selection of subsamples for all housing surveys carried out by INEGI; Its design is probabilistic, stratified, single-stage and by clusters, since it is in them that the dwellings that make up the subsamples of the different surveys were selected in a second stage. The design of the MMM was built as follows:

Formation of the primary sampling units (PSUs) First, the set of PSUs that will cover the national territory is built. The primary sampling units are made up of groups of dwellings with differentiated characteristics depending on the area to which they belong, as specified below:

In high urban areas The minimum size of a PSU is 80 inhabited dwellings and the maximum is 160. They can be made up of: · A block · The union of two or more contiguous blocks of the same AGEB. · The union of two or more contiguous blocks of different AGEBs in the same locality. · The union of two or more contiguous blocks of different localities, which belong to the same size of locality.

In urban complement The minimum size of a PSU is 160 inhabited homes and the maximum is 300. They can be made up of: · A block · The union of two or more contiguous blocks of the same AGEB · The union of two or more contiguous blocks of different AGEBs in the same locality. · The union of two or more contiguous blocks of different AGEBs and localities, but of the same municipality.

In rural areas The minimum size of a PSU is 160 inhabited homes and the maximum is 300. They can be made up of: · An AGEB. · Part of an AGEB. · The union of two or more adjoining AGEBs in the same municipality. · The union of an AGEB with a part of another adjoining AGEB in the same municipality.

In this way, each PSU was classified into a single geographical and a sociodemographic stratum. As a result, a total of 683 strata were obtained throughout the country.

The sample size for the ENIGH 2020 was calculated at the Entity level with urban and rural scope considering the variables and non-response rates mentioned above.

At the Entity level with an urban area, in the case of the variable Quarterly Average Current Income, there is a variation between 31 554.58 and 91 003.53, with a variance that is the between 609 706 543.70 and 570 110 356 234.59, and a design effect that fluctuates between 1.09 and 4.24.

At the Entity level with a rural environment, the variable Quarterly Average Current Income varies between 14 115.33 and 44 778.03, with a variance that ranges between 156 406 519.01 and 12 108 216 477.28, and a design effect that fluctuates between 1.00 and 9.43. Annex C presents the sample sizes for urban and rural entity areas.

Integrating the sample sizes at the national level, there is a sample size of 87,826 households, which guarantees an error of 4,485% at the national level for the variable quarterly average current income.

Due to the openness to go out into the field to conduct face-to-face interviews in the selected inhabited homes during the time of the COVID-19 pandemic, there were indications of having a greater refusal of households to accept the interviews, it was decided to take precautionary measures to increase the non-response rate to an additional 20%, due to these adjustments, the resulting sample was 105,483 households nationwide.

Sampling deviation

The ENIGH 2020, were raised in a national sample of 105,483 selected homes.

The sample allows information to be obtained at the national level, with a breakdown for localities of 2,500 and more inhabitants and localities of less than 2,500 inhabitants.

Mode of data collection

Face-to-face [f2f]

Research instrument

Six collection instruments will be used for the collection of information in each household, four of which concentrate

Geographic coverage

National coverage

Analysis unit

households/individuals

Kind of data

survey

Frequency of data collection

Quarterly

Sampling procedure

Sample size:

Abstract

The Household Income and Expenditure Survey (NHIES) 2009 was a survey collecting data on income, consumption and expenditure patterns of households, in accordance with methodological principles of statistical enquiries, which were linked to demographic and socio-economic characteristics of households. A Household Income and expenditure Survey was the sole source of information on expenditure, consumption and income patterns of households, which was used to calculate poverty and income distribution indicators. It also served as a statistical infrastructure for the compilation of the national basket of goods used to measure changes in price levels. It was also used for updating the national accounts.

The main objective of the NHIES 2009-2010 was to comprehensively describe the levels of living of Namibians using actual patterns of consumption and income, as well as a range of other socio-economic indicators based on collected data. This survey was designed to inform policy making at the international, national and regional levels within the context of the Fourth National Development Plan, in support of monitoring and evaluation of Vision 2030 and the Millennium Development Goals (MDG's). The NHIES was designed to provide policy decision making with reliable estimates at regional levels as well as to meet rural - urban disaggregation requirements.

Geographic coverage

National

Analysis unit

• Individuals
• Households

Universe

Every week of the four weeks period of a survey round all persons in the household were asked if they spent at least 4 nights of the week in the household. Any person who spent at least 4 nights in the household was taken as having spent the whole week in the household. To qualify as a household member a person must have stayed in the household for at least two weeks out of four weeks.

Kind of data

Sample survey data [ssd]

Sampling procedure

The targeted population of NHIES 2009-2010 was the private households of Namibia. The population living in institutions, such as hospitals, hostels, police barracks and prisons were not covered in the survey. However, private households residing within institutional settings were covered. The sample design for the survey was a stratified two-stage probability sample, where the first stage units were geographical areas designated as the Primary Sampling Units (PSUs) and the second stage units were the households. The PSUs were based on the 2001 Census EAs and the list of PSUs serves as the national sample frame. The urban part of the sample frame was updated to include the changes that take place due to rural to urban migration and the new developments in housing. The sample frame is stratified first by region followed by urban and rural areas within region. In urban areas, further stratification is carried out by level of living which is based on geographic location and housing characteristics. The first stage units were selected from the sampling frame of PSUs and the second stage units were selected from a current list of households within each selected PSU, which was compiled just before the interviews.

PSUs were selected using probability proportional to size sampling coupled with the systematic sampling procedure where the size measure was the number of households within the PSU in the 2001 Population and Housing Census (PHC). The households were selected from the current list of households using systematic sampling procedure.

The sample size was designed to achieve reliable estimates at the region level and for urban and rural areas within each region. However, the actual sample sizes in urban or rural areas within some of the regions may not satisfy the expected precision levels for certain characteristics. The final sample consists of 10 660 households in 533 PSUs. The selected PSUs were randomly allocated to the 13 survey rounds.

Sampling deviation

All the expected sample of 533 PSUs was covered. However, a number of originally selected PSUs had to be substituted by new ones due to the following reasons.

Urban areas: Movement of people for resettlement in informal settlement areas from one place to another caused a selected PSU to be empty of households.

Rural areas: In addition to Caprivi region (where one constituency is generally flooded every year) Ohangwena and Oshana regions were badly affected from an unusual flood situation. Although this situation was generally addressed by interchanging the PSUs between survey rounds still some PSUs were under water close to the end of the survey period.

There were five empty PSUs in the urban areas of Hardap (1), Karas (3) and Omaheke (1) regions. Since these PSUs were found in the low strata within the urban areas of the relevant regions the substituting PSUs were selected from the same strata. The PSUs under water were also five in rural areas of Caprivi (1), Ohangwena (2) and Oshana (2) regions. Wherever possible the substituting PSUs were selected from the same constituency where the original PSU was selected. If not, the selection was carried out from the rural stratum of the particular region.

One sampled PSU in urban area of Khomas region (Windhoek city) had grown so large that it had to be split into 7 PSUs. This was incorporated into the geographical information system (GIS) and one PSU out of the seven was selected for the survey. In one PSU in Erongo region only fourteen households were listed and one in Omusati region listed only eleven households. All these households were interviewed and no additional selection was done to cover for the loss in sample.

Mode of data collection

Face-to-face [f2f]

Research instrument

The instruments for data collection were as in the previous survey the questionnaires and manuals. Form I questionnaire collected demographic and socio-economic information of household members, such as: sex, age, education, employment status among others. It also collected information on household possessions like animals, land, housing, household goods, utilities, household income and expenditure, etc.

Form II or the Daily Record Book is a diary for recording daily household transactions. A book was administered to each sample household each week for four consecutive weeks (survey round). Households were asked to record transactions, item by item, for all expenditures and receipts, including incomes and gifts received or given out. Own produce items were also recorded. Prices of items from different outlets were also collected in both rural and urban areas. The price collection was needed to supplement information from areas where price collection for consumer price indices (CPI) does not currently take place.

Cleaning operations

The data capturing process was undertaken in the following ways: Form 1 was scanned, interpreted and verified using the “Scan”, “Interpret” & “Verify” modules of the Eyes & Hands software respectively. Some basic checks were carried out to ensure that each PSU was valid and every household was unique. Invalid characters were removed. The scanned and verified data was converted into text files using the “Transfer” module of the Eyes & Hands. Finally, the data was transferred to a SQL database for further processing, using the “TranScan” application. The Daily Record Books (DRB or form 2) were manually entered after the scanned data had been transferred to the SQL database. The reason was to ensure that all DRBs were linked to the correct Form 1, i.e. each household's Form 1 was linked to the corresponding Daily Record Book. In total, 10 645 questionnaires (Form 1), comprising around 500 questions each, were scanned and close to one million transactions from the Form 2 (DRBs) were manually captured.

Response rate

Household response rate: Total number of responding households and non-responding households and the reason for non-response are shown below. Non-contacts and incomplete forms, which were rejected due to a lot of missing data in the questionnaire, at 3.4 and 4.0 percent, respectively, formed the largest part of non-response. At the regional level Erongo, Khomas, and Kunene reported the lowest response rate and Caprivi and Kavango the highest.

Data appraisal

To be able to compare with the previous survey in 2003/2004 and to follow up the development of the country, methodology and definitions were kept the same. Comparisons between the surveys can be found in the different chapters in this report. Experiences from the previous survey gave valuable input to this one and the data collection was improved to avoid earlier experienced errors. Also, some additional questions in the questionnaire helped to confirm the accuracy of reported data. During the data cleaning process it turned out, that some households had difficulty to separate their household consumption from their business consumption when recording their daily transactions in DRB. This was in particular applicable for the guest farms, the number of which has shown a big increase during the past five years. All households with extreme high consumption were examined manually and business transactions were recorded and separated from private consumption.

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 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).

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 group. For some questions, the survey is already expressed as a percent (ex. Participation Rate).

Abstract

The National Household Travel Survey (NHTS) is the first round of the NHTS series which is designed to assess domestic transport and tourism travel patterns in the country. The NHTS collects data on general household characteristics, travel patterns of households, household transport and attitudes about transport.

Geographic coverage

The survey has 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

Sampling procedure

The National Department of Transport (NDOT) identified 342 national Transport Analysis (TA) zones in consultation with provincial transport departments. From these TA zones, a sample of 50 000 households had to be interviewed in order to collect information about travel patterns and habits. Stats SA overlaid the analysis zones with the Census 2001 Enumerator Areas (EAs) to facilitate the sampling.

The sample design is outlined in the steps which follow: • The 342 TA zones were overlaid with the Census 2001 Enumeration Areas. Each of the analysis zones will be treated as a reporting domain. Where possible, the zones were further stratified by geography type such as urban formal, urban informal, rural formal and tribal. Each zone was allocated a number of EA's proportional to its size using the enumerated "dwelling unit count" on the Stats SA books as a measure of size. • The number of EAs allocated to each TA zone was determined using the number of dwelling units in the EAs as a measure of size. The power allocation method was used to determine the number of primary sampling units (PSUs) to be allocated per zone. • Each PSU number consist of 12 digits, the first 8 representing the EA number and the last 4 the number of the PSU. Ten dwellings had to be enumerated in each of the 5 000 PSUs to arrive at the required sample of 50 000 households. This worked out to an average of 13.3 EAs per zone, based on 10 dwelling units per EA, assuming an equal allocation of EAs to the zone. • Additional EAs were pooled where the selection criterion of a minimum number of 80 dwelling units per EA was not met, such as in farming areas in the Northern Cape. In this case, the extra EA was taken from the same township, suburb and area as the original EA. • Once the dwelling units in each PSU were verified and the dwelling unit total was established, a sample of 10 dwelling units was selected from each PSU. Systematic sampling of EAs was used in all cases and equal probability systematic sampling was used to select the dwelling units that were enumerated in each of the EAs that was drawn. This allows for approximate selfweighting of the selected planning units within each of the zones. • In each household, one person, aged 15 years or older was selected for an interview about their attitudes to transport services. Kish's grid for selection of individuals aged 15 years and older, was used to determine who would be required to complete the attitudinal section of the questionnaire.

Mode of data collection

Face-to-face

Abstract

The National Institute of Statistics and Geography (INEGI) presents two methodological documents in which the main characteristics of the new construction of the ENIGH 2014 are presented, which coincides with the construction of variables of the Socioeconomic Conditions Module of the ENIGH 2014.

The objective of the ENIGH is to provide a statistical overview of the behavior of household income and expenditures in terms of their amount, origin and distribution; it also offers information on the occupational and sociodemographic characteristics of household members, as well as the characteristics of the housing infrastructure and household equipment.

Since 1984, when INEGI began to conduct the survey, new methodologies have been developed, international recommendations have been issued and good practices have been documented for the generation of household income and expenditure information through surveys.

During this period, additions have been made to the subject matter, methodological updates and innovations in the processes to obtain results that reflect reality, taking into account international recommendations and the information requirements of the different users, always ensuring historical comparability.

However, when the adoption of the recommendations and good practices implied a break in the comparability of the results, it was preferred to maintain comparability.

Starting in 2008, INEGI decided to publish the results of the ENIGH, whose variables have been constructed and presented in accordance with UN recommendations, specifically, those issued at the 17th International Conference of Labor Statisticians and in the Canberra Group Report. This new construction, moreover, is the one used in the ENIGH's Socioeconomic Conditions Module database, which is the source of information for the multidimensional poverty measurement conducted by the National Council for the Evaluation of Social Development Policy (CONEVAL). For the 2014 ENIGH, INEGI decided to continue presenting these results in order to give continuity to the results presented in 2008.

This survey additionally provides information on the occupational and socio-demographic characteristics of household members, as well as the characteristics of the housing infrastructure and household equipment.

The ENIGH, with the statistics it generates, contributes to the institutional task of providing the public service of statistical information of national interest.

The results of the ENIGH are used for different purposes, among which the following can be mentioned:

• Generation of weightings for the realization of the National Consumer Price Index.
• Construction of indicators for the study of poverty.
• Conformation of the Household Account of Mexico's System of National Accounts.
• Calculation of statistics on living standards.
• Studies of the behavior of the national economy in the field of household economics and comparisons with other countries.

Geographic coverage

National

• Urban area: localities with 2,500 and more inhabitants.
• Rural area: localities with less than 2,500 inhabitants

States

• Tabasco

Analysis unit

Household, housing and household members

Universe

The survey is aimed at households in the national territory.

Kind of data

Probabilistic household survey

Sampling procedure

Sample design

The sample design for ENIGH-2014 is characterized by being probabilistic. Consequently, the results obtained from the survey are generalized to the entire population. At the same time, the design is two-stage, stratified and by clusters, where the ultimate unit of selection is the dwelling and the unit of observation is the household.

Survey framework

The sample design for ENIGH-2014 is characterized by being probabilistic; consequently, the results obtained from the survey are generalized to the entire population. For the selection of the sample, INEGI's 2012 National Housing Framework was used, constructed from the cartographic and demographic information obtained from the 2010 Population and Housing Census. This frame is actually a master sample from which the samples for all housing surveys conducted by INEGI are selected. Its design is probabilistic, stratified, one-stage and by clusters; the latter are also considered primary sampling units, since it is in them where the dwellings that make up the samples of the different surveys are selected in subsequent stages.

Formation of the primary sampling units (PSU)

The primary sampling units are made up of groups of dwellings with different characteristics depending on the area to which they belong, as specified below:

a) In high urban areas

The minimum size of a PSU is 80 inhabited dwellings and the maximum size is 160:

• A block.
• The union of two or more contiguous blocks from the same AGEB.1
• The union of two or more contiguous blocks of different AGEBs of the same locality.
• The union of two or more contiguous blocks of different localities, belonging to the same size of locality.

b) In urban complement

The minimum size of a PSU is 160 inhabited houses and the maximum is 300. formed by:

• A block.
• The union of two or more contiguous blocks of the same AGEB.
• The union of two or more contiguous blocks of different AGEB of the same locality.
• The union of two or more contiguous blocks of different AGEB and localities, but of the same municipality.

c) In rural areas

The minimum size of a PSU is 160 inhabited dwellings and the maximum size is 300:

• An AGEB.
• Part of an AGEB.
• The union of two or more adjoining AGEB of the same municipality.
• The union of an AGEB with a part of another adjoining AGEB of the same municipality.

Stratification

The political division of the country and the conformation of localities differentiated by size naturally form a first geographic stratification.

In each federative entity, three areas are distinguished (high urban, urban complement and rural), divided in turn into seven zones according to the size of the locality, as indicated below:

High urban 01 - 32 self-represented cities (C.A.) with 100,000 inhabitants or more. 02 - Rest of cities with 100,000 or more inhabitants.

Urban complement 25 - With 50 000 to 99 999 inhabitants. 35 - From 15,000 to 49,999 inhabitants. 45 - From 5 000 to 14 999 inhabitants. 55 - From 2 500 to 4 999 inhabitants.

Rural 60 - Localities with less than 2,500 inhabitants.

This stratification considers the socio-demographic characteristics of the inhabitants of the dwellings, as well as their physical characteristics and equipment, expressed by means of 24 indicators constructed with information from the XII General Population and Housing Census 2000, for which multivariate statistical methods were used.

In a second stage, each PSU was assigned according to its geographic stratum (entity-area-zone).

In a third stage, within each zone and stratum (sociodemographic), some of the PSUs were subjected to a new stratification process with the purpose of having a greater differentiation at that level. For this stratification, indicators differentiated by area were used. The result is a total of 888 substrata at the national level.

Sample Size

For the calculation of the sample size of the ENIGH-2014, the average total current income per household was considered as the reference variable and a nationwide sample of 10 062 households was determined.

Sampling deviation

As a result of the sum of the 21,427 selected households and 359 additional households that were found in these dwellings, the total amounted to 21,786 households.

Mode of data collection

Face-to-face [f2f]

Research instrument

For the collection of information in each household, six collection instruments will be used, four of which concentrate information on the household as a whole.

These are: - Household and housing questionnaire - Household expenditure questionnaires - Daily expenditure booklet - Social programs module

In the other three, individual information is recorded for individuals. Questionnaire for persons 12 years of age or older - Questionnaire for persons under 12 years of age - Questionnaire for household businesses

Cleaning operations

Data capture activities

The capture consisted of transferring the information from the questionnaires that were fully answered to electronic media through IKTAN, in accordance with the procedures established for the capture process of the ENIGH 2014.

On the eighth day of the decade, the Responsible for Capture Validation together with his work team began the capture of the questionnaires collected by each Interviewer, organized by packages of questionnaires of each folio with a complete interview result, following the following established order:

• Package cover (ENIGH-1).
• Household and housing questionnaire.
• Questionnaires for persons under 12 years of age.
• Questionnaires for persons 12 years of age or older.
• Questionnaires for household businesses.
• Questionnaire of household expenses.
• Booklet of daily expenses.

In addition, the IKTAN made it possible to record and know the progress or completion of the workloads.

Validation activities

In parallel to the capture, validation began at the state level, which was carried out in two stages. The first stage consisted of verifying the valid ranges of the folios released for capture, and the second stage consisted of applying the validation criteria in order to purge the files of inconsistencies and omissions before releasing them and sending them to the central office.

Integration and validation of the capture database at central offices

Once the information capture and