Abstract

The main objectives of the 2018/19 NLSS are: i) to provide critical information for production of a wide range of socio-economic and demographic indicators, including for benchmarking and monitoring of SDGs; ii) to monitor progress in population's welfare; iii) to provide statistical evidence and measure the impact on households of current and anticipated government policies. In addition, the 2018/19 NLSS could be utilized to improve other non-survey statistical information, e.g. to determine and calibrate the contribution of final consumption expenditures of households to GDP; to update the weights and determine the basket for the national Consumer Price Index (CPI); to improve the methodology and dissemination of micro-economic and welfare statistics in Nigeria.

The 2018/19 NLSS collected a comprehensive and diverse set of socio-economic and demographic data pertaining to the basic needs and conditions under which households live on a day to day basis. The 2018/19 NLSS questionnaire includes wide-ranging modules, covering demographic indicators, education, health, labour, expenditures on food and non-food goods, non-farm enterprises, household assets and durables, access to safety nets, housing conditions, economic shocks, exposure to crime and farm production indicators.

Geographic coverage

National coverage

Analysis unit

Households

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

SAMPLING PROCEDURE The 2018/19 NLSS sample is designed to provide representative estimates for the 36 states and the Federal Capital Territory (FCT), Abuja. By extension. The sample is also representative at the national and zonal levels. Although the sample is not explicitly stratified by urban and rural areas, it is possible to obtain urban and rural estimates from the NLSS data at the national level. At all stages, the relative proportion of urban and rural EAs as has been maintained. Before designing the sample for the 2018/19 NLSS, the results from the 2009/10 HNLSS were analysed to extract the sampling properties (variance, design effect, etc.) and estimate the required sample size to reach a desired precision for poverty estimates in the 2018/19 NLSS.

EA SELECTION: The sampling frame for the 2018/19 NLSS was based on the national master sample developed by the NBS, referred to as the NISH2 (Nigeria Integrated Survey of Households 2). This master sample was based on the enumeration areas (EAs) defined for the 2006 Nigeria Census Housing and Population conducted by National Population Commission (NPopC). The NISH2 was developed by the NBS to use as a frame for surveys with state-level domains. NISH2 EAs were drawn from another master sample that NBS developed for surveys with LGA-level domains (referred to as the “LGA master sample”). The NISH2 contains 200 EAs per state composed of 20 replicates of 10 sample EAs for each state, selected systematically from the full LGA master sample. Since the 2018/19 NLSS required domains at the state-level, the NISH2 served as the sampling frame for the survey. Since the NISH2 is composed of state-level replicates of 10 sample EAs, a total of 6 replicates were selected from the NISH2 for each state to provide a total sample of 60 EAs per state. The 6 replicates selected for the 2018/19 NLSS in each state were selected using random systematic sampling. This sampling procedure provides a similar distribution of the sample EAs within each state as if one systematic sample of 60 EAs had been selected directly from the census frame of EAs.

A fresh listing of households was conducted in the EAs selected for the 2018/19 NLSS. Throughout the course of the listing, 139 of the selected EAs (or about 6%) were not able to be listed by the field teams. The primary reason the teams were not able to conduct the listing in these EAs was due to security issues in the country. The fieldwork period of the 2018/19 NLSS saw events related to the insurgency in the north east of the country, clashes between farmers and herdsman, and roving groups of bandits. These events made it impossible for the interviewers to visit the EAs in the villages and areas affected by these conflict events. In addition to security issues, some EAs had been demolished or abandoned since the 2006 census was conducted. In order to not compromise the sample size and thus the statistical power of the estimates, it was decided to replace these 139 EAs. Additional EAs from the same state and sector were randomly selected from the remaining NISH2 EAs to replace each EA that could not be listed by the field teams. This necessary exclusion of conflict affected areas implies that the sample is representative of areas of Nigeria that were accessible during the 2018/19 NLSS fieldwork period. The sample will not reflect conditions in areas that were undergoing conflict at that time. This compromise was necessary to ensure the safety of interviewers.

HOUSEHOLD SELECTION: Following the listing, the 10 households to be interviewed were selected from the listed households. These households were selected systemically after sorting by the order in which the households were listed. This systematic sampling helped to ensure that the selected households were well dispersed across the EA and thereby limit the potential for clustering of the selected households within an EA. Occasionally, interviewers would encounter selected households that were not able to be interviewed (e.g. due to migration, refusal, etc.). In order to preserve the sample size and statistical power, households that could not be interviewed were replaced with an additional randomly selected household from the EA. Replacement households had to be requested by the field teams on a case-by-case basis and the replacement household was sent by the CAPI managers from NBS headquarters. Interviewers were required to submit a record for each household that was replaced, and justification given for their replacement. These replaced households are included in the disseminated data. However, replacements were relatively rare with only 2% of sampled households not able to be interviewed and replaced.

Sampling deviation

Although a sample was initially drawn for Borno state, the ongoing insurgency in the state presented severe challenges in conducting the survey there. The situation in the state made it impossible for the field teams to reach large areas of the state without compromising their safety. Given this limitation it was clear that a representative sample for Borno was not possible. However, it was decided to proceed with conducting the survey in areas that the teams could access in order to collect some information on the parts of the state that were accessible.

The limited area that field staff could safely operate in in Borno necessitated an alternative sample selection process from the other states. The EA selection occurred in several stages. Initially, an attempt was made to limit the frame to selected LGAs that were considered accessible. However, after selection of the EAs from the identified LGAs, it was reported by the NBS listing teams that a large share of the selected EAs were not safe for them to visit. Therefore, an alternative approach was adopted that would better ensure the safety of the field team but compromise further the representativeness of the sample. First, the list of 788 EAs in the LGA master sample for Borno were reviewed by NBS staff in Borno and the EAs they deemed accessible were identified. The team identified 359 EAs (46%) that were accessible. These 359 EAs served as the frame for the Borno sample and 60 EAs were randomly selected from this frame. However, throughout the course of the NLSS fieldwork, additional insurgency related events occurred which resulted in 7 of the 60 EAs being inaccessible when they were to be visited. Unlike for the main sample, these EAs were not replaced. Therefore, 53 EAs were ultimately covered from the Borno sample. The listing and household selection process that followed was the same as for the rest of the states.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Two sets of questionnaires – household and community – were used to collect information in the NLSS2018/19. The Household Questionnaire was administered to all households in the sample. 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.

Household Questionnaire: The Household Questionnaire provides information on demographics; education; health; labour; food and non-food expenditure; household nonfarm income-generating activities; food security and shocks; safety nets; housing conditions; assets; information and communication technology; agriculture and land tenure; and other sources of household income.

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

Cleaning operations

CAPI: The 2018/19 NLSS was conducted using the Survey Solutions Computer Assisted Person Interview (CAPI) platform. The Survey Solutions software was developed and maintained by the Development Economics Data Group (DECDG) at the World Bank. Each interviewer and supervisor was given a tablet which they used to

Abstract

Tanzania Mainland through the National Bureau of Statistics (NBS) has been conducting the household budget surveys (HBSs) since 1969 to collect data on consumption, expenditure and the poverty situation in the country. The first round of scientific HBSs that represented urban and rural areas was conducted in 1991. Since then NBS has successfully completed five rounds of scientific HBS including the 2017- 18 HBS. The HBS data series is the major sources of information for estimation of poverty and its associated characteristics. It provides empirical evidence for users to understand the income (using the consumption expenditure as proxy to income) dimension of poverty.

Objectives of the Survey: The main objective of the 2017-18 HBS was to obtain current information on poverty estimation and its associated characteristics and to assess the progress made in improving the living standards of the people. The result will be used for monitoring the implementation of national, regional and global commitments such as Tanzania Development Vision 2025, national Second Five Year Development Plan (FYDP-II 2016/17 2020/21), East Africa Community Vision 2050 (EAC 2050), Africa Development Agenda 2063 (ADA 2063) and Global Agenda 2030 on Sustainable Development Goals (2030 SDGs). Specifically, the 2017-18 HBS aimed at: - Providing series of data for assessing poverty and changes in the households' living standards over time; and for monitoring and evaluation of the impacts of socio-economic policies and programs on the welfare of people; - Providing baseline data for compiling household accounts such as the Private Final Consumption Expenditure (PFCE) component of the demand side of Gross Domestic Product (GDP) as recommended in the System of National Accounts (SNA); and - Rebasing of GDP and Consumer Price Indices (CPI).

Geographic coverage

• National coverage for Tanzania Mainland
• Rural and urban areas
• Regions: Dodoma, Arusha, Kilimanjaro, Tanga, Morogoro, Pwani, Dar es Salaam, Lindi, Mtwara, Ruvuma, Iringa, Mbeya, Singida, Tabora, Rukwa, Kigoma, Shinyanga, Kagera, Mwanza, Mara, Manyara, Njombe, Katavi, Simiyu, Geita, and Songwe.

Analysis unit

• Individuals
• Households
• Communities

Universe

The survey covered all members residing in private households in Tanzania Mainland.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample for the 2017-18 HBS covered the population residing in private households in Tanzania Mainland. A representative probability sample of 9,552 households was selected. This sample was designed to allow separate estimates for each of the 26 regions of the Tanzania Mainland, also urban and rural areas separately at the national level.

The 2017-18 HBS adopted a two-stage cluster sample design. The first stage involved selection of enumeration areas (primary sampling units - PSUs) from the 2012 Population and Housing Census (2012 PHC) Frame. A total of 796 PSUs (69 from Dar es Salaam, 167 from Other Urban Areas and 560 from Rural Areas) was selected. The NBS carried out listing exercise in which households residing in selected PSUs were freshly listed to update the 2012 PHC list before selecting households.

The second stage of sampling involved systematic sampling of households from the updated PSUs list. A sample of 12 households was selected from each selected PSU. All household members regardless of their age, who were usual members of the selected households and all visitors who were present in the household on the night before the survey interview, were eligible for the survey.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The 2017-18 HBS was implemented using six electronic questionnaires (Forms I - V and VII) and a paper questionnaire (Form VI). The information collected was the following: - Form I: Demographics; parents' survivorship; birth delivery and breast feeding; citizenship and migration; education; literacy; health; disability; insurances, individual asset ownership and identification documents; labour market indicators; non-farm household businesses; and individual non-wage income; - Form II: Dwellings; utility; water and sanitation; transport and communications; tourism; investments; banking; and households’ recall expenditures; children and adult mortality. The form also contained the TASAF and food security modules; - Form III: Crops, livestock and food security; - Form IV: Time use (5+ years Household members); - Form V: Household diary for recording daily household consumption and expenditure over a 14-days period; - Form VI: Individual diary for recording daily consumption and expenditure for each household member age five years or more; and - Form VII: Access to community services (selected communities).

The questionnaires are in English, and provided as external resources.

Response rate

Out of 9,552 selected households, 9,465 households participated in the survey yielding a response rate of 99 percent.

Abstract

The SHDS is a national sample survey designed to provide information on population, birth spacing, reproductive health, nutrition, maternal and child health, child survival, HIV/AIDS and sexually transmitted infections (STIs), in Somalia.. The main objective of the SHDS was to provide evidence on the health and demographic characteristics of the Somali population that will guide the development of programmes and formulation of effective policies. This information would also help monitor and evaluate national, sub-national and sector development plans, including the Sustainable Development Goals (SDGs), both by the government and development partners. The target population for SHDS was the women between 15 and 49 years of age, and the children less than the age of 5 years

Geographic coverage

The SHDS 2020 was a nationally representative household survey.

Analysis unit

The unit analysis of this survey are households, women aged 15-49 and children aged 0-5

Universe

This sample survey covered Women aged 15-49 and Children aged 0-5 years.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample Design The sample for the SHDS was designed to provide estimates of key indicators for the country as a whole, for each of the eighteen pre-war geographical regions, which are the country's first-level administrative divisions, as well as separately for urban, rural and nomadic areas. With the exception of Banadir region, which is considered fully urban, each region was stratified into urban, rural and nomadic areas, yielding a total of 55 sampling strata. All three strata of Lower Shabelle and Middle Juba regions, as well as the rural and nomadic strata of Bay region, were completely excluded from the survey due to security reasons. A final total of 47 sampling strata formed the sampling frame. Through the use of up-to-date, high-resolution satellite imagery, as well as on-the-ground knowledge of staff from the respective ministries of planning, all dwelling structures were digitized in urban and rural areas. Enumeration Areas (EAs) were formed onscreen through a spatial count of dwelling structures in a Geographic Information System (GIS) software. Thereafter, a sample ground verification of the digitized structures was carried out for large urban and rural areas and necessary adjustments made to the frame.

Each EA created had a minimum of 50 and a maximum of 149 dwelling structures. A total of 10,525 EAs were digitized: 7,488 in urban areas and 3,037 in rural areas. However, because of security and accessibility constraints, not all digitized areas were included in the final sampling frame-9,136 EAs (7,308 in urban and 1,828 in rural) formed the final frame. The nomadic frame comprised an updated list of temporary nomadic settlements (TNS) obtained from the nomadic link workers who are tied to these settlements. A total of 2,521 TNS formed the SHDS nomadic sampling frame. The SHDS followed a three-stage stratified cluster sample design in urban and rural strata with a probability proportional to size, for the sampling of Primary Sampling Units (PSU) and Secondary Sampling Units (SSU) (respectively at the first and second stage), and systematic sampling of households at the third stage. For the nomadic stratum, a two-stage stratified cluster sample design was applied with a probability proportional to size for sampling of PSUs at the first stage and systematic sampling of households at the second stage. To ensure that the survey precision is comparable across regions, PSUs were allocated equally to all regions with slight adjustments in two regions. Within each stratum, a sample of 35 EAs was selected independently, with probability proportional to the number of digitized dwelling structures. In this first stage, a total of 1,433 EAs were allocated (to urban - 770 EAs, rural - 488 EAs, and nomadic - 175 EAs) representing about 16 percent of the total frame of EAs. In the urban and rural selected EAs, all households were listed and information on births and deaths was recorded through the maternal mortality questionnaire. The data collected in this first phase was cleaned and a summary of households listed per EA formed the sampling frames for the second phase. In the second stage, 10 EAs were sampled out of the possible 35 that were listed, using probability proportional to the number of households. All households in each of these 10 EAs were serialized based on their location in the EA and 30 of these households sampled for the survey. The serialization was done to ensure distribution of the households interviewed for the survey in the EA sampled. A total of 220 EAs and 150 EAs were allocated to urban and rural strata respectively, while in the third stage, an average of 30 households were selected from the listed households in every EA to yield a total of 16,360 households from 538 EAs covered (220 EAs in urban, 147 EAs in rural and 171 EAs in nomadic) out of the sampled 545 EAs. In nomadic areas, a sample of 10 EAs (in this case TNS) were selected from each nomadic stratum, with probability proportional to the number of estimated households. A complete listing of households was carried out in the selected TNS followed by the selection of 30 households for the main survey interview. In those TNS with less than 30 households, all households were interviewed for the main survey. All eligible ever-married women aged 12 to 49 and never-married women aged 15 to 49 were interviewed in the selected households, while the household questionnaire was administered to all households selected. The maternal mortality questionnaire was administered to all households in each sampled TNS.

Mode of data collection

Face-to-face [f2f]

Response rate

A total of 16,360 households were selected for the sample, of which 15,870 were occupied. Of the occupied households, 15,826 were successfully interviewed, yielding a response rate of 99.7 percent. The SHDS 2020 interviewed 16,486 women-11,876 ever-married women and 4,610 never-married women.

Sampling error estimates

Sampling errors are important data quality parameters which give measure of the precision of the survey estimates. They aid in determining the statistical reliability of survey estimates. The estimates from a sample survey are affected by two types of errors: non-sampling errors and sampling errors. Non-sampling errors are the results of mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the Somaliland Health and Demographic Survey ( SHDS 2020) to minimise this type of error, non-sampling errors are impossible to avoid and difficult to evaluate statistically. Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the SHDS 2020 is only one of many samples that could have been selected from the same population, using the same design and sample size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability among all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results. Sampling error is usually measured in terms of the standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall. For example, for any given statistic calculated from a sample survey, the value of that statistic will fall within a range of plus or minus two times the standard error of that statistic in 95% of all possible samples of identical size and design. If the sample of respondents had been selected by simple random sampling, it would have been possible to use straightforward formulas for calculating sampling errors. However, the SHDS 2020 sample was the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulas. The variance approximation procedure that account for the complex sample design used R program was estimated sampling errors in SHDS which is Taylor series linearization. The non-linear estimates are approximated by linear ones for estimating variance. The linear approximation is derived by taking the first-order Tylor series approximation. Standard variance estimation methods for linear statistics are then used to estimate the variance of the linearized estimator. The Taylor linearisation method treats any linear statistic such as a percentage or mean as a ratio estimate, r = y/x, where y represents the total sample value for variable y and x represents the total number of cases in the group or subgroup under consideration

Data appraisal

• Household age distribution
• Age distribution of eligible and interviewed women
• Pregnancy- related mortality trends Note: See detailed data quality tables in APPENDIX C of the report.

Abstract

To facilitate the use of data collected through the high-frequency phone surveys on COVID-19, the Living Standards Measurement Study (LSMS) team has created the harmonized datafiles using two household surveys: 1) the country’ latest face-to-face survey which has become the sample frame for the phone survey, and 2) the country’s high-frequency phone survey on COVID-19.

The LSMS team has extracted and harmonized variables from these surveys, based on the harmonized definitions and ensuring the same variable names. These variables include demography as well as housing, household consumption expenditure, food security, and agriculture. Inevitably, many of the original variables are collected using questions that are asked differently. The harmonized datafiles include the best available variables with harmonized definitions.

Two harmonized datafiles are prepared for each survey. The two datafiles are: 1. HH: This datafile contains household-level variables. The information include basic household characterizes, housing, water and sanitation, asset ownership, consumption expenditure, consumption quintile, food security, livestock ownership. It also contains information on agricultural activities such as crop cultivation, use of organic and inorganic fertilizer, hired labor, use of tractor and crop sales.
2. IND: This datafile contains individual-level variables. It includes basic characteristics of individuals such as age, sex, marital status, disability status, literacy, education and work.

Geographic coverage

National coverage

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

See “Nigeria - General Household Survey, Panel 2018-2019, Wave 4” and “Nigeria - COVID-19 National Longitudinal Phone Survey 2020” available in the Microdata Library for details.

Mode of data collection

Computer Assisted Personal Interview [capi]

Cleaning operations

Nigeria General Household Survey, Panel (GHS-Panel) 2018-2019 and Nigeria COVID-19 National Longitudinal Phone Survey (COVID-19 NLPS) 2020 data were harmonized following the harmonization guidelines (see “Harmonized Datafiles and Variables for High-Frequency Phone Surveys on COVID-19” for more details).

The high-frequency phone survey on COVID-19 has multiple rounds of data collection. When variables are extracted from multiple rounds of the survey, the originating round of the survey is noted with “_rX” in the variable name, where X represents the number of the round. For example, a variable with “_r3” presents that the variable was extracted from Round 3 of the high-frequency phone survey. Round 0 refers to the country’s latest face-to-face survey which has become the sample frame for the high-frequency phone surveys on COVID-19. When the variables are without “_rX”, they were extracted from Round 0.

Response rate

See “Nigeria - General Household Survey, Panel 2018-2019, Wave 4” and “Nigeria - COVID-19 National Longitudinal Phone Survey 2020” available in the Microdata Library for details.

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 Geneal Household Survey is a brainchild of the National Bureau of Statistics (NBS) and is often referred to as Regular survey carried out on quarterly basis by the NBS over the years. In recent times, starting from 2004 to be precise, there is a collaborative effort between the NBS and the CBN in 2004 and 2005 and in 2006 the collaboration incorporated Nigerian Communications commission (NCC). The main reason of for conducting the survey was to enable the collaborating agencies fulfil their mandate in the production of current and credible statistics, to monitor and evaluate the status of the economy and the various government programmes such as the National Economic Empowerment and Development Strategy (NEEDS) and the Millennium Development Goals (MDGs).
The collaborative survey also assured the elimination of conflicts in data generated by the different agencies and ensured a reliable, authentic national statistics for the country.

Geographic coverage

National

Analysis unit

Household

Universe

Household

Kind of data

Sample survey data [ssd]

Response rate

On National basis, 85.98 percent response rate was acheived at EA level while 85.96 percent was acheived at housing units level.

Sampling error estimates

No sampling error estimate

Data appraisal

QUALITY CONTROL AND RETRIEVAL OF RECORD
Quality Control measures were carried out during the survey, essentially to ensure quality of data. There were three levels of supervision involving the supervisors at the first level, CBN staff, NBS State Officers and Zonal Controllers at second level and finally the NBS/NCC Headquarter staff constituting the third level supervision. Field monitoring and quality check exercises were also carried out during the period of data collection as part of the quality control measures.

Abstract

The EESs are conducted by the National Bureau of Statistics (NBS), as mandated by Statistics Act 2015 and its 2018 and 2019 Amendments, which empowers NBS to collect, compile and disseminate official statistics in the country. The summary is presented for the six main topical areas namely: -Employment Profile; Wage Rates Profile; Cash Earnings Profile; Annual Wage Bill Profile; Newly Recruited Workers; and Job Vacancies

Geographic coverage

Tanzania Mainland Regional level

Analysis unit

Formal establishment

Universe

The survey covers all formal establishment with employees in both public and private sectors. establishment are divided in three main which are all public sector establishment, all registrated private establishmnent employ at least 50 persons and a sample of registrated of private establishments whose number of employees are from 5-49 persons.

Kind of data

Sample survey data [ssd]

Sampling procedure

The 2017Employment and Earnings Survey is an establishment- based survey which covered a total of 10,896establishments from a frame of 52,429establishments. The frame consisted ofall public establishments and formal private establishments employing 5 persons or above

The survey covered all public -sector establishments and private sector establishments with at least 50 employees. Furthermore, the survey covered a sample of private establishments employing 5 to 49 persons. The sampling for this group involved stratifying establishments into those with 5 to 9 employees and those with 10 to 49 employees. Establishments in these strata were further stratified on the basis of their economic activities and ultimately a single stage sampling technique was used to derive representative establishments from each activity using the probability proportion to size (PPS).

Mode of data collection

Face-to-face [f2f]

Research instrument

Establishment based questionairre was development in english and was translated in swahili language

Cleaning operations

Data editing took place at a number of stages throughout the processing, including: a) Office editing and coding b) During data entry c) Structural checking of SPSS data files

Response rate

81.4

Sampling error estimates

Estimates from a sample survey are affected by two types of errors: 1) non-sampling errors and 2) sampling errors. Non-sampling errors are the results of mistakes made in the implementation of data collection and data processing. Numerous efforts were made during implementation of the EES 2017 to minimize this type of error, however, non-sampling errors are impossible to avoid and difficult to evaluate statistically.

Abstract

NASC is an exercise designed to fill the existing data gap in the agricultural landscape in Nigeria. It is a comprehensive enumeration of all agricultural activities in the country, including crop production, fisheries, forestry, and livestock activities. The implementation of NASC was done in two phases, the first being the Listing Phase, and the second is the Sample Survey Phase. Under the first phase, enumerators visited all the selected Enumeration Areas (EAs) across the Local Government Areas (LGAs) and listed all the farming households in the selected enumeration areas and collected the required information. The scope of information collected under this phase includes demographic details of the holders, type of agricultural activity (crop production, fishery, poultry, or livestock), the type of produce or product (for example: rice, maize, sorghum, chicken, or cow), and the details of the contact persons. The listing exercise was conducted concurrently with the administration of a Community Questionnaire, to gather information about the general views of the communities on the agricultural and non-agricultural activities through focus group discussions.

The main objective of the listing exercise is to collect information on agricultural activities at household level in order to provide a comprehensive frame for agricultural surveys. The main objective of the community questionnaire is to obtain information about the perceptions of the community members on the agricultural and non-agricultural activities in the community.

Additional objectives of the overall NASC program include the following: · To provide data to help the government at different levels in formulating policies on agriculture aimed at attaining food security and poverty alleviation · To provide data for the proposed Gross Domestic Product (GDP) rebasing

Geographic coverage

Communities (in Enumerated Areas).

Analysis unit

Community

Universe

The population units are communities encompassing the designated enumeration areas, where household listing was performed.

Kind of data

Census/enumeration data [cen]

Sampling procedure

Focus group interviews were performed in communities overlapping with in the EAs selected for the extended listing operation. Accordingly, a focus group discussion in a total of 26,555 communities were undertaken to administer the community level questionnaire. It is important to note here that the results from the community survey are unweighted results and all the tables produced from the community level data are only from the 26,555 communities interviewed.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The NASC community listing questionnaire served as a meticulously designed instrument administered within every community selected to gather comprehensive data. It encompassed various aspects such as agricultural activities in the community, infrastructures, disaster, etc. The questionnaire was structured into the following sections:

• Identification of the community • Respondent Characteristics (Name, Sex, age) • Agricultural Activities in the Community • Disasters and Shocks • Community Infrastructure and Transportation • Community Organizations • Community Resources Management • Land Prices and Credit • Community Key Events • Labour

Cleaning operations

Data processing of the NASC household listing survey included checking for inconsistencies, incompleteness, and outliers. Data editing and cleaning was carried out electronically using the Stata software package. In some cases where data inconsistencies were found a call back to the household was carried out. A pre-analysis tabulation plan was developed and the final tables for publication were created using the Stata software package.

Abstract

The broad objective of the Employment and Earnings Survey was to obtain comprehensive data on the annual status of Employment and Earnings as well as data on the socio-economic characteristics of the Labour Market.

Kind of data

Sample survey data [ssd]

Sampling procedure

(a) The Selection of Establishments The Employment and Earnings Survey of 2001 used the existing Central Register of Establishments (CRE) frame. The selection of establishments from the CRE frame falls under the following groups: - (i) All establishments of public sectors found in the CRE frame of 2001 were taken. (ii) All establishments of private sector with at least 50 employees found in the CRE frame of 2001 were taken. (iii) The selection of establishments of private sector employing persons in the range of 5 to 49 was based on a sample.

(b) The Sample Design (i) A sample of 10 percent of establishments was selected in the employment size group of 5 to 9 employees. (ii) A sample of 33 percent of establishments was selected in the employment size group of 10 to 49 employees.

(c ) Sample Selection A random sampling method was used to select the number of establishments to be enumerated according to the sample size in each employment group.

During the enumeration process enumerators were instructed to include in the survey, all new establishments in the public sector and those employing at least 50 persons in the private sectors that will be identified in the field but were not included in the provided list of establishments prepared for the survey.

Mode of data collection

Face-to-face [f2f]

Response rate

73.2

Kind of data

Sample survey data [ssd]

Mode of data collection

Face-to-face [f2f]

Geographic coverage

National coverage

Analysis unit

household

Kind of data

Census/enumeration data [cen]

Mode of data collection

Face-to-face [f2f]

Research instrument

A short questionnaire for all dwellings and a long questionnaire for a sample of the population. There was a separate "collective questionnaire" for group living arrangements.

Cleaning operations

There was a team of personnel for manually editing with emphasis on identification on each questionaire, District identification validity checked were done by the program written by ODA computer consultant. Data files were shipped over Microlan 2 to PWS micro computer for further checking, the check include records with invalidity district identification codes, records containing any characters other than blanks and digits, record type was neither '1'(Population records) or '2'(household records), records with duplicate identification numbers and out of sequence records.

CONsistency and CORrection software (CONCOR) was used during editing with minimum imputations.

Abstract

This report presents the findings of 2000-2001 Tanzania Household Budget Survey(HBS).It focuses on poverty- monitoring indicators and offers a set of baseline mesurements for the future.Data on key poverty indicators are presented for each region. Trends over the 1990s are also assessed by comparison with the 1991/92 HBS.

The HBS collected information on a range of individual and household characteristics. These included;

*household members, education,economic activities, and health status *household expenditure, consumption and income *ownership of consumer goods and assets *housing structure and materials *household access to services and facilities, and *food security

Geographic coverage

NATIONAL COVERAGE

Analysis unit

Individuals and households,

Universe

The survey covered all de jure household members

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample of households interviewed in the 2000/2001 HBS was selected in two stage.In the first stage 1,161 small areas called Primary Sampling Units (PSUs) were selected throughout the country.In the second stage. 24 households were initialy selected in each PSU.

The sampled households are located in the National Master Sample (NMS) of PSUs. The NMS is a generalised set of area units that can be used as PSUs for conducting various household surveys. It is a fixed sample of rural and urban clusters, which among other things, make possible the performance of a continuous survey programme as well as ad hoc sample surveys. the NMS has four modules, A,A+B,A+B+C and A+B+C+D, which can provide urban and rural estimates at National, Zonal, Regional and District levels respectively.

The HBS 2000/01 used Module A+B+C of the NMS comprising 621 urban EAS and 540 rural villages drawn from each of the 20 regions of Mainland Tanzania. In the second stage,24 households were selected using systematic random sampling(SRS) from stratified lists of households complied from each of the sampled PSUs. These lists were stratified into high, middle and low socio-economic groups based on socio-economic data collected during the listing exercise. The stratification and selection of households was conducted in the NBS head office and interviewers were supplied with a list of pre-selected households for interview,

RURAL frame.The initial rural NMS frame was based on the 1978 Population Census and later updated with information from the 1988 Population Census.At the beginning, a ward or group of wards was used as Primary Sampling Unit (PSU), but later a village was used insted. The rural frame of the NMS was divided into :normal: large town surroundings; and Low density; strata. In total.150 strata were created and 2 to 8 PSUs (villages) were selected from each stratum to come up with the samp;e of villages that can provide estimates for each region of Mainland Tanzania (Module A+B+C).These villages were selected using the probability proportional to size (PPS) selection procedure. The PSUs (villages) for Module A of the rural NMS are automatically included in the regional sample.

URBAN frame: The urban frame for the NMS was the sample used for 1988 Population Census detailed questionnaire. For each district in a region, a list of the urban EAs was compiled and a specific number of EAs was selected from this frame using the systematic random sampling(SRS) procedure to produce the regional urban sample.

Sampling deviation

The final sample analysed for the 2000/01 HBS consisted of 22,178 households, a large sample for any household budget survey. Three PSUs were lost entirely from the sample. Households were included in the analysis if they had at least one record in both the roster and the monthly diary. The weights were calculated for this group of household.

Field supervisors were supplied with a list of twelve :replacement: households drawn as a separate sample at the same time as the main household sample, to be used if a sampled household could not be interviewed for the duration of the survey. The 2000/01 HBS sample had a high level of replacement of households that were not interviewed-around12 per cent.

A total of 4,823 households were analysed for the 1991/92 sample. Losses were higher; levels of replacement were lower (Table A1.2). In both surveys, households that were part of the initial selectionons constitute around 85 per cent of the sample analysed.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaires contain information related to;Household Particulars, Household Facilities, Household Assets, Household Income, Distance to socio-Economic Facilities, Purchase of Durable items and other Services,Food security;

Cleaning operations

A number of data consistency cheks were undertaken early in the fieldwork to assess quality and to assist in the development of the data processing system.These identified a large number of problems in the data coming in from the field, which reflected in part the ambitious size of the survey.The errors identified included consumption unit miscoding,miscoding of transactions, out of range unit prices and problems in the identifier variables. As a consequence, automatic consistency cheking programmes were strengthened and a data editing team was created. where possible,errors were corrected at the data processing centre and the field teams were notified of the problems. This resolved a large number of problems.

Response rate

The 2000/01 HBS inteviewed 98 per cent of the (revised) intended sample size. It did so by relatively frequent use of replacement households, selected from a list provided by the head office. Almost 12 per cent of households included in the final analysis were replacements. The 1991/92 HBS Suffered higher levels of losses but used smaller proportion of replacements.The use of replacements is not usually considered good practice in sampling, since it runs the risk of estimates being biased by replacement with non comparable households.However,it was considered necessary because of the large sample size and demanding character of the data collection process.

Sampling error estimates

Table A1.4 shows standard errors and confidence intervals around a number of estimates, calculated in STATA. It also presents the results of statistical tests for a significant difference between the 2000/01 and 1991/92 estimates, for the total population and each of the three areas. While STATA allows the specification of sample design in the calculation of sampling errors, identifying the srata and PSUs used, it is not possible to specify fully the complexity of the design of the HBS 2000/01. The standard errors, confidence intervals and tests are therefore approximate.

Abstract

The National Bureau of Statistics (NBS) was established with the Statistics Act of 2007 and the merger of the Federal Office of Statistics (FOS) and the National Data Bank (NDB). Nigeria has a Federal System of government with 36 States and a Federal Capital Territory and 774 Local Government Areas. Each Federal Ministry, Department and Agency has a Director of Statistics. Each state has a Director of Statistics and a Head of statistics Unit at the Local Government level. These and the Statistical Institutes constitute Nigeria's National Statistical System (NSS) which is coordinated by the NBS. The Nigeria National Data Archive was established to: Promote best practice and international standards for the documentation of microdata amongst data producers in the country Provide equitable access to microdata in the interest of all citizens Ensure the long term preservation of microdata and the related metadata, and their continued viability and usability The Data Archive holds NBS datasets from 1999 to the current year.

Analysis unit

Households, individuals, and establishments

Kind of data

Administrative records and survey data

Abstract

Between February and March 2016, the World Bank, in collaboration with Somali statistical authorities conducted the first wave of the Somali High Frequency Survey to monitor welfare and perceptions of citizens in all accessible areas of 9 regions within Somalia’s pre-war borders including Somaliland which self-declared independence in 1991. The survey interviewed 2,882 urban households, 822 rural and 413 households in Internally Displaced People (IDP) settlements. The sample was drawn randomly based on a multi-level clustered design. This dataset contains information on economic conditions, education, employment, access to services, security and perceptions. It also includes comprehensive information on assets and consumption, to allow estimation of poverty based on the Rapid Consumption methodology as detailed in Pape and Mistiaen (2014).

Geographic coverage

The following pre-war regions: Awdal, Banadir, Bari, Mudug, Nugaal, Sanaag, Sool, Togdheer and Woqooyi Galbeed (Somaliland self-declared independence in 1991).

Analysis unit

Household

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample employs a stratified two-staged clustered design with the Primary Sampling Unit (PSU) being the enumeration area. Within each enumeration area, 12 households were selected for interviews.

Two different listing approaches were used. In 2 strata with more volatile security as well as for IDP camps, a multi-stage cluster design was employed (micro-listing). Each selected enumeration area was divided into multiple segments and each segment was further divided into blocks. Within each enumeration area, one segment was randomly selected and within the segment 12 blocks were chosen. In each block, all structures were listed before selecting randomly one structure. Within the selected structure, all households were listed and one household randomly selected for interview. In strata less volatile (14 strata), the complete enumeration area was listed before 12 households were randomly selected for interviews (full-listing).

Sampling deviation

EAs were replaced if security rendered field work unfeasible. Replacements were approved by the project manager. Replacement of households were approved by the supervisor after a total of three unsuccessful visits of the household.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Questionnaire Modules - Household Roster (110 questions) - Household Characteristics (38 questions) - Consumption - Food (30 questions per item) - Non-Food (14 questions per item) - Livestock (39 questions per item) - Durables (16 questions per item) - Perception (24 questions) - Food Security* (24 questions) - Income and Remittances* (14 questions) - Household Enterprise* (172 questions) - Shocks* (15 questions)

Abstract

The programme for the World Census of Agriculture 2000 is the eighth in the series for promoting a global approach to agricultural census taking. The first and second programmes were sponsored by the International Institute for Agriculture (IITA) in 1930 and 1940. Subsequent ones up to 1990 were promoted by the Food and Agriculture Organization of the United Nations(FAO). FAO recommends that each country should conduct at least one agricultural census in each census programme decade and its programme for the World Census of Agriculture 2000 for instance corresponds to agricultural census to be undertaken during the decade 1996 to 2005. Many countries do not have sufficient resources for conducting an agricultural census. It therefore became an acceptable practice since 1960 to conduct agricultural census on sample basis for those countries lacking the resources required for a complete enumeration.

In Nigeria's case, a combination of complete enumeration and sample enumeration is adopted whereby the rural (peasant) holdings are covered on sample basis while the modern holdings are covered on complete enumeration. The project named “National Agricultural Sample Census” derives from this practice. Nigeria through the National Agricultural Sample Census (NASC) participated in the 1970's, 1980's, 1990's programmes of the World Census of Agriculture. Nigeria failed to conduct the Agricultural Census in 2003/2004 because of lack of funding. The NBS regular annual agriculture surveys since 1996 had been epileptic and many years of backlog of data set are still unprocessed. The baseline agricultural data is yet to be updated while the annual regular surveys suffered set back. There is an urgent need by the governments (Federal, State, LGA), sector agencies, FAO and other International Organizations to come together to undertake the agricultural census exercise which is long overdue. The conduct of 2006/2008 National Agricultural Sample Census Survey is now on course with the pilot exercise carried out in the third quarter of 2007.

The National Agricultural Sample Census (NASC) 2006/08 is imperative to the strengthening of the weak agricultural data in Nigeria. The project is phased into three sub-projects for ease of implementation; the Pilot Survey, Modern Agricultural Holding and the Main Census. It commenced in the third quarter of 2006 and to terminate in the first quarter of 2008. The pilot survey was implemented collaboratively by National Bureau of Statistics.

The main objective of the pilot survey was to test the adequacy of the survey instruments, equipments and administration of questionnaires, data processing arrangement and report writing. The pilot survey conducted in July 2007 covered the two NBS survey system-the National Integrated Survey of Households (NISH) and National Integrated Survey of Establishment (NISE). The survey instruments were designed to be applied using the two survey systems while the use of Geographic Positioning System (GPS) was introduced as additional new tool for implementing the project.

The Stakeholders workshop held at Kaduna on 21st-23rd May 2007 was one of the initial bench marks for the take off of the pilot survey. The pilot survey implementation started with the first level training (training of trainers) at the NBS headquarters between 13th - 15th June 2007. The second level training for all levels of field personnels was implemented at headquarters of the twelve (12) concerned states between 2nd - 6th July 2007. The field work of the pilot survey commenced on the 9th July and ended on the 13th of July 07. The IMPS and SPSS were the statistical packages used to develop the data entry programme.

Geographic coverage

State

Analysis unit

Households who are rearing livestock or kept poultry

Universe

Livestock or poultry household

Kind of data

Census/enumeration data [cen]

Sampling procedure

The survey was carried out in 12 states falling under 6 geo-political zones. 2 states were covered in each geo-political zone. 2 local government areas per selected state were studied. 2 Rural enumeration areas per local government area were covered and 3 Livestock/poultry farming housing units were systematically selected and canvassed.

Sampling deviation

No Deviation

Mode of data collection

Face-to-face [f2f]

Research instrument

The NASC livestock and poultry questionnaire was divided into the following sections: - Identification/description of holdings - Funds, employment and earnings/wages - Livestock - Poultry - Fixed assets - Sales - Stock - Subsidy

Cleaning operations

The data processing and analysis plan involved five main stages: training of data processing staff; manual editing and coding; development of data entry programme; data entry and editing and tabulation. Census and Surveys Processing System (CSPro) software were used for data entry, Statistical Package for Social Sciences (SPSS) and CSPro for editing and a combination of SPSS, Statistical Analysis Software (SAS) and EXCEL for table generation. The subject-matter specialists and computer personnel from the NBS and CBN implemented the data processing work. Tabulation Plans were equally developed by these officers for their areas and topics covered in the three-survey system used for the exercise. The data editing is in 2 phases namely manual editing before the data entry were done. This involved using editors at the various zones to manually edit and ensure consistency in the information on the questionnaire. The second editing is the computer editing, this is the cleaning of the already enterd data. The completed questionnaires were collected and edited manually (a) Office editing and coding were done by the editor using visual control of the questionnaire before data entry (b) Cspro was used to design the data entry template provided as external resource (c) Ten operator plus two suppervissor and two progammer were used (d) Ten machines were used for data entry (e) After data entry data entry supervisor runs fequency on each section to see that all the questionnaire were enterd

Response rate

The response rate at EA level was 100 percent, while 99.3 percent was recorded at housing units level.

Sampling error estimates

No computation of sampling error

Data appraisal

The Quality Control measures were carried out during the survey, essentially to ensure quality of data. There were two levels of supervision involving the supervisors at the first level, NBS State Officers and Zonal Controllers at second level and finally the NBS Headquarters staff constituting the second level supervision.

Kind of data

sample survey data[ssd]

Abstract

The Annual Agricultural Sample Survey (AASS) for the year 2022/23 aimed to enhance the understanding of agricultural activities across Tanzania by collecting comprehensive data on various aspects of the agricultural sector. This survey is crucial for policy formulation, development planning, and service delivery, providing reliable data to monitor and evaluate national and international development frameworks.

The 2022/23 survey is particularly significant as it informs the monitoring and evaluation of key agricultural development strategies and frameworks. The collected data will contribute to the Tanzania Development Vision 2025, Zanzibar Development Vision 2020, the Five-Year Development Plan 2021/22–2025/26, the National Strategy for Growth and Reduction of Poverty (NSGRP) known as MKUKUTA, and the Zanzibar Strategy for Growth and Reduction of Poverty (ZSGRP) known as MKUZA. The survey data also supports the evaluation of Sustainable Development Goals (SDGs) and Comprehensive Africa Agriculture Development Programme (CAADP). Key indicators for agricultural performance and poverty monitoring are directly measured from the survey data.

The 2022/23 AASS provides a detailed descriptive analysis and related tables on the main thematic areas. These areas include household members and holder identification, field roster, seasonal plot and crop rosters (Vuli, Masika, and Dry Season), permanent crop production, crop harvest use, seed and seedling acquisition, input use and acquisition (fertilizers and pesticides), livestock inventory and changes, livestock production costs, milk and eggs production, other livestock products, aquaculture production, and labor dynamics. The 2022/23 AASS offers an extensive dataset essential for understanding the current state of agriculture in Tanzania. The insights gained will support the development of policies and interventions aimed at enhancing agricultural productivity, sustainability, and the livelihoods of farming communities. This data is indispensable for stakeholders addressing challenges in the agricultural sector and promoting sustainable agricultural development.

STATISTICAL DISCLOSURE CONTROL (SDC) METHODS HAVE BEEN APPLIED TO THE MICRODATA, TO PROTECT THE CONFIDENTIALITY OF THE INDIVIDUAL DATA COLLECTED. USERS MUST BE AWARE THAT THESE ANONYMIZATION OR SDC METHODS MODIFY THE DATA, INCLUDING SUPPRESSION OF SOME DATA POINTS. THIS AFFECTS THE AGREGATED VALUES DERIVED FROM THE ANONYMIZED MICRODATA, AND MAY HAVE OTHER UNWANTED CONSEQUENCES, SUCH AS SAMPLING ERROR AND BIAS. ADDITIONAL DETAILS ABOUT THE SDC METHODS AND DATA ACESS CONDITIONS ARE PROVIDED IN THE DATA PROCESSING AND DATA ACESS CONDITIONS BELOW.

Geographic coverage

National, Mainland Tanzania and Zanzibar, Regions

Analysis unit

Households for Smallholder Farmers and Farm for Large Scale Farms

Universe

The survey covered agricultural households and large-scale farms.

Agricultural households are those that meet one or more of the following two conditions: a) Have or operate at least 25 square meters of arable land, b) Own or keep at least one head of cattle or five goats/sheep/pigs or fifty chicken/ducks/turkeys during the agriculture year.

Large-scale farms are those farms with at least 20 hectares of cultivated land, or 50 herds of cattle, or 100 goats/sheep/pigs, or 1,000 chickens. In addition to this, they should fulfill all of the following four conditions: i) The greater part of the produce should go to the market, ii) Operation of farm should be continuous, iii) There should be application of machinery / implements on the farm, and iv) There should be at least one permanent employee.

Kind of data

Sample survey data [ssd]

Sampling procedure

The frame used to extract the sample for the Annual Agricultural Sample Survey (AASS-2022/23) in Tanzania was derived from the 2022 Population and Housing Census (PHC-2022) Frame that lists all the Enumeration Areas (EAs/Hamlets) of the country. The AASS 2022/23 used a stratified two-stage sampling design which allows to produce reliable estimates at regional level for both Mainland Tanzania and Zanzibar.

In the first stage, the EAs (primary sampling units) were stratified into 2-3 strata within each region and then selected by using a systematic sampling procedure with probability proportional to size (PPS), where the measure of size is the number of agricultural households in the EA. Before the selection, within each stratum and domain (region), the Enumeration Areas (EAs) were ordered according to the codes of District and Council which reflect the geographical proximity, and then ordered according to the codes of Constituency, Division, Wards, and Village. An implicit stratification was also performed, ordering by Urban/Rural type at Ward level.

In the second stage, a simple random sampling selection was conducted . In hamlets with more than 200 households, twelve (12) agricultural households were drawn from the PHC 2022 list with a simple random sampling without replacement procedure in each sampled hamlet. In hamlets with 200 households or less, a listing exercise was carried out in each sampled hamlet, and twelve (12) agricultural households were selected with a simple random sampling without replacement procedure. A total of 1,352 PSUs were selected from the 2022 Population and Housing Census frame, of which 1,234 PSUs were from Mainland Tanzania and 118 from Zanzibar. A total number of 16,224 agricultural households were sampled (14,808 households from Mainland Tanzania and 1,416 from Zanzibar).

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The 2022/23 Annual Agricultural Survey used two main questionnaires consolidated into a single questionnaire within the CAPIthe CAPI System, Smallholder Farmers and Large-Scale Farms Questionnaire. Smallholder Farmers questionnaire captured information at household level while Large Scale Farms questionnaire captured information at establishment/holding level. These questionnaires were used for data collection that covered core agricultural activities (crops, livestock, and fish farming) in both short and long rainy seasons. The 2022/23 AASS questionnaire covered 23 sections which are:

1. COVER; The cover page included the title of the survey, survey year (2022/23), general instructions for both the interviewers and respondents. It sets the context for the survey and also it shows the survey covers the United Republic of Tanzania.

2. SCREENING: Included preliminary questions designed to determine if the respondent or household is eligible to participate in the survey. It checks for core criteria such as involvement in agricultural activities.

3. START INTERVIEW: The introductory section where basic details about the interview are recorded, such as the date, location, and interviewer’s information. This helped in the identification and tracking of the interview process.

4. HOUSEHOLD MEMBERS AND HOLDER IDENTIFICATION: Collected information about all household members, including age, gender, relationship to the household head, and the identification of the main agricultural holder. This section helped in understanding the demographic composition of the agriculture household.

5. FIELD ROSTER: Provided the details of the various agricultural fields operated by the agriculture household. Information includes the size, location, and identification of each field. This section provided a comprehensive overview of the land resources available to the household.

6. VULI PLOT ROSTER: Focused on plots used during the Vuli season (short rainy season). It includes details on the crops planted, plot sizes, and any specific characteristics of these plots. This helps in assessing seasonal agricultural activities.

7. VULI CROP ROSTER: Provided detailed information on the types of crops grown during the Vuli season, including quantities produced and intended use (e.g., consumption, sale, storage). This section captures the output of short rainy season farming.

8. MASIKA PLOT ROSTER: Similar to Section 4 but focuses on the Masika season (long rainy season). It collects data on plot usage, crop types, and sizes. This helps in understanding the agricultural practices during the primary growing season.

9. MASIKA CROP ROSTER: Provided detailed information on crops grown during the Masika season, including production quantities and uses. This section captures the output from the main agricultural season.

10. PERMANENT CROP PRODUCTION: Focuses on perennial or permanent crops (e.g., fruit trees, tea, coffee). It includes data on the types of permanent crops, area under cultivation, production volumes, and uses. This section tracks long-term agricultural investments.

11. CROP HARVEST USE: In this, provided the details how harvested crops are utilized within the household. Categories included consumption, sale, storage, and other uses. This section helps in understanding food security and market engagement.

12. SEED AND SEEDLINGS ACQUISITION: Collected information on how the agriculture household acquires seeds and seedlings, including sources (e.g., purchased, saved, gifted) and types (local, improved, etc). This section provided insights into input supply chains and planting decisions based on the households, or head.

13. INPUT USE AND ACQUISITION (FERTILIZERS AND PESTICIDES): It provided the details of the use and acquisition of agricultural inputs such as fertilizers and pesticides. It included information on quantities used, sources, and types of inputs. This section assessed the input dependency and agricultural practices.

14. LIVESTOCK IN STOCK AND CHANGE IN STOCK: The questionnaire recorded the

Abstract

The objective of the Nigeria NLPS Phase 2 is to monitor in real-time how the Nigerian households are coping with national and global crises and their effects on the welfare and livelihoods of the households. The households in the Phase 2 are drawn from the sample of households interviewed in GHS-Panel 2018/19 including those interviewed during the Phase 1. This survey has become a flexible tool that contributes to filling critical gaps in information that could be used by the Nigerian government and stakeholders to help design policies to mitigate the negative impacts of the COVID-19 pandemic, the oil prices crises, inflation and global value chain crises, among others. The Nigeria NLPS Phase 2 is designed to accommodate the evolving nature of the crises, including revision of the questionnaire on a bi-monthly basis.

Geographic coverage

National coverage

Analysis unit

• Households
• Individuals

Kind of data

Sample survey data [ssd]

Sampling procedure

BASELINE (ROUND 1): Wave 4 of the GHS-Panel conducted in 2018/19 served as the frame for the Nigeria NLPS surveys. The GHS-Panel sample includes 4,976 households that were interviewed in the post-harvest visit of the fourth wave in January/February 2019. This sample of households is representative nationally as well as across the 6 geopolitical Zones that divide up the country. In every visit of the GHS-Panel, phone numbers are collected from interviewed households for up to 4 household members and 2 reference persons who are in close contact with the household in order to assist in locating and interviewing households who may have moved in subsequent waves of the survey. This comprehensive set of phone numbers as well as the already well-established relationship between NBS and the GHS-Panel households made this an ideal frame from which to conduct the NLPS in Nigeria.

Among the 4,976 households interviewed in the post-harvest visit of the GHS-Panel in 2019, 4,934 (99.2%) provided at least one phone number. Around 90 percent of these households (4,440) provided a phone number for at least one household member while the remaining 10 percent only provided a phone number for a reference person. For the second phase of the NLPS, all 4,440 GHS-Panel households with household member contact details were included in the sample to be contacted. This included the sample of households from the first phase of the NLPS who had household member contact details (2,701 of 3,000). Based on the response rate in the first phase of the NLPS of 65 percent, this was expected to yield an interviewed sample of nearly 2,900 households that is both nationally representative as well as representative of urban and rural areas of the country.

ROUND 2: Interviewers attempted to contact and interview all 2,922 households that were successfully interviewed in the baseline (round 1) of the NLPS Phase 2. The second round of the NLPS Phase 2 also included individual-level data collection on the migration history of household members. For the migration module, information on adult (15 years or older) members of the household was targeted, including respondents that fall into this age range. However, information was not captured for all adult members. In order to limit the burden for respondents and interviewers in cases where the number of adult members is large, a maximum of 6 household members were selected (in addition to the main respondent) to capture information on migration. Therefore, for households with less than 6 adult members, all eligible members were included. However, 93 percent of interviewed households had 6 or less adult members and only 7 percent had more than six. For the 7 percent with more than 6 adult members, 6 members were randomly selected from among the pool of eligible members. The selection was stratified by sex with an equal split of 3 male and 3 females was targeted, depending on the pool of eligible males and females. However, the application of selection as relatively rare.

ROUND 3: Interviewers attempted to contact and interview all 2,811 households that were successfully interviewed in the baseline (round 1) of the NLPS Phase 2, excluding 41 households that refused in Round 2. The third round of the NLPS Phase 2 also included individual-level data collection on employment and job history of household members. For the employment and job history modules, information on adult (15 years or older) members of the household was targeted, including respondents that fall into this age range. However, information was not captured for all adult members. In order to limit the burden for respondents and interviewers in cases where the number of adult members is large, a maximum of 4 household members were selected (in addition to the main respondent) to capture information on employment and job history. Therefore, for households with less than 4 adult members, all eligible members were included.

However, 90 percent of interviewed households had 4 or less adult members and only 10 percent had more than four. For the 10 percent with more than 4 adult members, 4 members were randomly selected from among the pool of eligible members. The selection was stratified by sex with an equal split of 2 male and 2 females was targeted, depending on the pool of eligible males and females. The selection of eligible household members in Round 3 was conditional to the selection conducted in Round 2 for the migration module. In that round, up to 6 household members were selected (15 years or older) to answer the migration module. However, the application of selection as relatively rare.

ROUND 4: Interviewers attempted to contact and interview all 2,852 households that were successfully interviewed in the baseline (round 1) of the NLPS Phase 2, excluding 70 households that refused in previous rounds of the survey.

ROUND 5: Interviewers attempted to contact and interview 2,824 households consisting of households that were successfully interviewed in the baseline (round 1) of the NLPS Phase 2 excluding 98 households that refused in previous rounds of the survey.

ROUND 6: Interviewers attempted to contact and interview 2,799 households consisting of households that were successfully interviewed in the baseline (round 1) of the NLPS Phase 2 excluding 123 households that refused in previous rounds of the survey.

ROUND 7: Interviewers attempted to contact and interview 2,784 households consisting of households that were successfully interviewed in the baseline (round 1) of the NLPS Phase 2 excluding 138 households that refused in previous rounds of the survey.

ROUND 8: Interviewers attempted to contact and interview 2,771 households consisting of households that were successfully interviewed in the baseline (round 1) of the NLPS Phase 2 excluding 151 households that refused in previous rounds of the survey.

ROUND 9: Interviewers attempted to contact and interview 2,753 households consisting of households that were successfully interviewed in the baseline (round 1) of the NLPS Phase 2 excluding 169 households that refused in previous rounds of the survey.

ROUND 10: Interviewers attempted to contact and interview 2,743 households consisting of households that were successfully interviewed in the baseline (round 1) of the NLPS Phase 2 excluding 179 households that refused in previous rounds of the survey.

ROUND 11: Interviewers attempted to contact and interview 2,732 households consisting of households that were successfully interviewed in the baseline (round 1) of the NLPS Phase 2 excluding 190 households that refused in previous rounds of the survey.

ROUND 12: Interviewers attempted to contact and interview 2,724 households consisting of households that were successfully interviewed in the baseline (round 1) of the NLPS Phase 2 excluding 198 households that refused in previous rounds of the survey.

ROUND 13: Interviewers attempted to contact and interview 2,714 households consisting of households that were successfully interviewed in the baseline (round 1) of the NLPS Phase 2 excluding 208 households that refused in previous rounds of the survey.

Mode of data collection

Computer Assisted Telephone Interview [cati]

Research instrument

BASELINE (ROUND 1): One questionnaire, the Household Questionnaire, was administered to all households in the sample. The Household Questionnaire provides information on demographics; access to health services; employment and non-farm enterprise; and COVID-19 vaccine.

ROUND 2: One questionnaire, the Household Questionnaire, was administered to all households in the sample. The Household Questionnaire provides information on demographics; migration; employment; and household migrants.

ROUND 3: One questionnaire, the Household Questionnaire, was administered to all households in the sample. The Household Questionnaire provides information on demographics; access to health services; employment; job history; and COVID-19 vaccine.

ROUND 4: One questionnaire, the Household Questionnaire, was administered to all households in the sample. The Household Questionnaire provides information on demographics; access to health services; petrol; employment; credit; and economic sentiments. While the Household Questionnaire was administered to all the sample households, economic sentiments questions were asked to only half of the sample households (randomly selected).

ROUND 5: One questionnaire, the Household Questionnaire, was administered to all households in the sample. The Household Questionnaire provides information on demographics; access to health services; employment; COVID-19 vaccine; economic sentiments; and farmer screening. While the Household Questionnaire was administered to all the sample households,

Abstract

In December 2017, the World Bank, in collaboration with Somali statistical authorities conducted the second wave of the Somali High Frequency Survey to monitor welfare and perceptions of citizens in all accessible areas of 17 regions within Somalia’s pre-war borders including Somaliland which self-declared independence in 1991. The survey interviewed 4,011 urban households, 1,106 rural households, 468 households in Internally Displaced People (IDP) settlements and 507 nomadic households. The sample was drawn randomly based on a multi-level clustered design. This dataset contains information on economic conditions, education, employment, access to services, security, perceptions and details before displacement for displaced households. It also includes comprehensive information on assets and consumption, to allow estimation of poverty based on the Rapid Consumption methodology as detailed in Pape and Mistiaen (2014).

Geographic coverage

The following pre-war regions: Awdal, Bakool, Banadir, Bari, Bay, Galgaduug, Gedo, Hiran, Lower Juba, Mudug, Nugaal, Sanaag, Middle and lower Shabelle, Sool, Togdheer and Woqooyi Galbeed (Somaliland self-declared independence in 1991).

Analysis unit

Household

Kind of data

Sample survey data [ssd]

Sampling procedure

Wave 2 of the SHFS employed a multi-stage stratified random sample, ensuring a sample representative of all subpopulations of interest. Strata were defined along two dimensions - administrative location (pre-war regions and emerging states) and population type (urban areas, rural settlements, IDP settlements, and nomadic population). Households were clustered into enumeration areas (EAs), with 12 interviews was expected for each selected EA. Primary sampling units (PSUs) were generated using a variety of techniques depending on the population type. The primary sampling unit (PSU) in urban as well as rural strata was the enumeration area (EA). For IDP strata, primary sampling units were IDP settlements as defined by UNCHR’s Shelter Cluster. Across all strata, PSUs were selected using a systematic random sampling approach with selection probability proportional to size (PPS). In IDP strata, PPS sampling is applied at the IDP settlement level. In second- and final-stage sample selection, a microlisting approach was used, such that EAs were divided into 12 smaller enumeration blocks, which were selected with equal probability. Every block was selected as 12 interviews per EA were required. A similar second-stage sampling strategy was employed for IDP strata. Each IDP settlement was segmented manually into enumeration blocks. Finally, one household per block was interviewed in all selected blocks within the enumeration area.The household was selected randomly with equal probability in two stages, following the micro-listing protocol. The strategy for sampling nomadic households relied on lists of water points. The list of water points was divided up by stratum at the federated member state level and they served as primary sampling units. Water points were selected in the first stage with equal probability, with 12 interviews to be conducted at each selected water point. The selection of nomadic households to interview relied on a listing process at each water point whose aim was to compile an exhaustive list of all nomadic households at the water point. For more details, see accompanying documents, available under the related materials tab.

Sampling deviation

EAs were replaced if security rendered field work unfeasible. Replacements were approved by the project manager. Replacement of households were approved by the supervisor after a total of three unsuccessful visits of the household.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The household questionnaire is in English. It includes the following modules: - Introduction - Module A: Administrative Information - Module B: Interview Information and Filters - Module C: Household Roster - Module D: Household Characteristics - Module E: Food Consumption - Module F: Non-Food Consumption - Module G: Livestock - Module H: Durable Goods - Module I: Perceptions and Social Services - Module J: Displacement - Module K: Fishing - Module L: Catastrophic Events and Disasters - Module M: Enumerator Conclusions - Appendix A - Enabling Conditions - Appendix B - Validation Conditions and Messages - Appendix C - Instructions - Appendix D - Options - Appendix E - Variables - Appendix F - Option Filters

The household questionnaire is provided under the Related Materials tab.

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