General Household Survey, Panel 2018-2019, Wave 4 - Nigeria

Abstract
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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
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National

Analysis unit
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- Households
- Individuals
- Agricultural plots
- Communities

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

Kind of data
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Sample survey data [ssd]

Sampling procedure
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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
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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
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Computer Assisted Personal Interview [capi]

Research instrument
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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
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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 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.

摘要
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本《综合农业调查》（ISA）项目下的《一般家庭调查-面板》（GHS-Panel）由世界银行生活水平测量研究（LSMS）团队与我国合作实施。GHS-Panel的目标包括开发收集农业数据的创新模型、加强机构间合作，以及全面分析福利指标和社会经济特征。GHS-Panel是国家层面的代表性调查，涉及约5,000户家庭，这些家庭也代表了六个地理政治区。2018/19年是该调查的第四轮，之前已进行的调查分别于2010/11、2012/13和2015/16年进行。GHS-Panel家庭接受过两次访问：第一次在2018年7月至9月的种植季节之后（种植后），第二次在2019年1月至2月的收获季节之后（收获后）。
地理覆盖范围
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全国
分析单元
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- 家庭
- 个人
- 农业地块
- 社区
总体
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本调查涵盖了所有合法家庭，不包括监狱、医院、军事营房和学校宿舍。
数据类型
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样本调查数据 [ssd]
抽样程序
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原始GHS-Panel样本为5,000户家庭，分布于500个抽样单位（EAs），旨在在全国层面和地区层面都具有代表性。GHS-Panel的完整抽样信息详见2010/2011年《GHS-Panel基本信息文档》。然而，经过近十年的同一家庭访问后，在第四波中实施了GHS-Panel样本的部分更新。
对于样本的部分更新，随机选取了一套新的360个EAs，每个地区60个EAs。更新EAs来自与2010年原始GHS-Panel样本相同的抽样框架（“主框架”）。在360个EAs中进行了所有家庭的登记，并在每个EAs中随机选取了10户家庭，从而形成了约3,600户的总更新样本。
除了这3,600户更新家庭外，还从2010年的原始5,000户GHS-Panel家庭中选取了一部分作为新样本的一部分。这个“长期面板”样本旨在具有全国代表性，以便能够对追溯到2010年的样本进行持续纵向分析。长期面板样本由6个地理政治区系统选出的159个EAs组成。系统的选择确保了EAs在6个地区（包括城市和农村地区）的分布与原始GHS-Panel样本成比例。访谈员试图对原居住在159个EAs中并在2016年之前成功接受访问的家庭进行访谈。这包括2010年已从原地点搬离的家庭。总的来说，访谈员试图从原始面板样本中访谈了1,507户家庭。
更新和长期面板EAs的合并样本由519个EAs组成。在两次访问中成功访谈的家庭总数为4,976户。
抽样偏差
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虽然合并样本在总体上保持了原始GHS-Panel样本的国家和地区代表性，但尼日利亚东北部的不安全局势阻碍了该地区的全面覆盖。由于安全问题，博尔诺州的农村地区被完全排除在更新样本之外，一些难以到达的城市地区也被排除。安全问题还阻碍了访谈员访问该国其他部分发生冲突的一些社区。无法访问的更新EAs被该地区随机选取的另一个EAs所取代，以避免损害样本量。因此，合并样本代表了2018/19年期间可访问的尼日利亚地区。该样本不会反映当时处于冲突中的地区的状况。这种妥协是为了确保访谈员的安全。
数据收集方式
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计算机辅助个人访谈 [capi]
研究工具
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GHS-Panel第四波包括两次访问的三个问卷。家庭问卷被发放给样本中的所有家庭。农业问卷被发放给所有从事农业活动（如作物种植、畜牧业和其他相关农业活动）的家庭。社区问卷被发放给社区，以收集样本家庭居住的抽样单位的 socioeconomic indicators。
GHS-Panel家庭问卷：家庭问卷提供了关于人口统计、教育、健康（包括儿童的体质测量）；劳动力；食品和非食品支出；家庭非农收入生成活动；粮食安全和冲击；安全网；住房条件；资产；信息和通信技术；以及家庭其他收入来源的信息。家庭位置进行了地理参照，以便能够将GHS-Panel数据与其他可用的地理数据集进行链接。
GHS-Panel农业问卷：农业问卷征求关于土地所有权和使用；农场劳动力；投入使用；GPS土地面积测量和家庭地块的坐标；农业资本；灌溉；作物收获和利用；动物保有和成本；家庭捕鱼活动等信息。一些信息是在作物层面收集的，以便对个别作物进行详细分析。
GHS-Panel社区问卷：社区问卷征求关于基础设施获取；社区组织；资源管理；社区变化；关键事件；社区需求、行动和成就；以及当地零售价格信息。
家庭问卷在两次访问中略有不同。一些信息仅在种植后访问中收集，一些仅在收获后访问中收集，一些在两次访问中都收集。
农业问卷在每次访问中收集不同的信息，但对于相同的地块和作物。
数据清洗
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CAPI：在GHS-Panel中，第四波调查首次采用计算机辅助个人访谈（CAPI）技术。在第四波的种植后和收获后访问中，所有问卷（家庭、农业和社区问卷）都使用CAPI软件Survey Solutions实施。Survey Solutions软件由世界银行经济发展数据组（DECDG）内的调查单位开发并维护。每个调查员都获得了平板电脑，他们使用平板电脑进行访谈。总的来说，使用Survey Solutions CAPI进行调查的实施非常成功，因为它允许及时获取完成的访谈数据。
数据通信系统：第四波使用的数据通信系统高度自动化。每个现场团队都得到了一个移动调制解调器，允许互联网连接和每日平板电脑同步。这确保了阿布贾总部可以实时访问数据。一旦访谈完成并上传到服务器，数据首先由数据编辑员进行审查。数据还从服务器下载，并在下载的数据上运行Stata dofile以检查Survey Solutions应用程序未捕获的额外错误。在运行Stata dofile在原始数据集上后，生成一个excel错误文件。excel错误文件中的信息被传达给相应的现场访谈员，由访谈员采取行动。这项行动在整个调查期间（种植后和收获后）每天进行。
数据清洗：数据清洗过程分为三个主要阶段。第一阶段是在实地工作中确保质量控制。这在一定程度上是通过将验证和一致性检查纳入用于数据收集的Survey Solutions应用程序中实现的，该应用程序旨在突出许多在实地工作中发生的错误。
第二阶段清洗涉及使用数据编辑员和数据助理（总部在Survey Solutions）。如上所述，一旦访谈完成并上传到服务器，数据编辑员会审查完成的访谈，寻找不一致性和极端值。根据结果，他们可以批准或拒绝案例。如果被拒绝，案例将返回到相应的调查员平板电脑上，以便在同步时进行。特别关注确保包含在数据中的家庭与选定的样本相匹配，并且在存在差异的情况下，这些差异被适当评估和记录。农业数据也进行了检查，以确保在主要部分中确定的地块与在其他部分中确定的地块信息相匹配。观察到的其他错误被汇编成错误报告，并定期发送给团队。然后根据监督员的指示对错误进行现场复访进行纠正。经过第一阶段清洗的数据随后由数据编辑员批准。在数据编辑员在Survey Solutions服务器上批准访谈后，总部也会进行审查，并根据结果，可以拒绝或批准。
第三阶段清洗涉及在第一阶段和第二阶段清洗之后对最终原始数据进行全面审查。每个变量都被单独检查，以确保（1）与其他部分和变量的一致性，（2）超出范围的响应，以及（3）异常值。然而，在解决潜在错误时，特别关注避免做出强烈的假设。一些小错误仍然存在于数据中，其中诊断和/或解决方案对于数据清洗团队来说不够明确。