Integrated Household Panel Survey, 2010-2019 - Malawi

Abstract
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The 2016 Integrated Household Panel Survey (IHPS) was launched in April 2016 as part of the Malawi Fourth Integrated Household Survey fieldwork operation. The IHPS 2016 targeted 1,989 households that were interviewed in the IHPS 2013 and that could be traced back to half of the 204 enumeration areas that were originally sampled as part of the Third Integrated Household Survey (IHS3) 2010/11. The 2019 IHPS was launched in April 2019 as part of the Malawi Fifth Integrated Household Survey fieldwork operations targeting the 2,508 households that were interviewed in 2016. The panel sample expanded each wave through the tracking of split-off individuals and the new households that they formed. Available as part of this project is the IHPS 2019 data, the IHPS 2016 data as well as the rereleased IHPS 2010 & 2013 data including only the subsample of 102 EAs with updated panel weights. Additionally, the IHPS 2016 was the first survey that received complementary financial and technical support from the Living Standards Measurement Study - Plus (LSMS+) initiative, which has been established with grants from the Umbrella Facility for Gender Equality Trust Fund, the World Bank Trust Fund for Statistical Capacity Building, and the International Fund for Agricultural Development, and is implemented by the World Bank Living Standards Measurement Study (LSMS) team, in collaboration with the World Bank Gender Group and partner national statistical offices. The LSMS+ aims to improve the availability and quality of individual-disaggregated household survey data, and is, at start, a direct response to the World Bank IDA18 commitment to support 6 IDA countries in collecting intra-household, sex-disaggregated household survey data on 1) ownership of and rights to selected physical and financial assets, 2) work and employment, and 3) entrepreneurship - following international best practices in questionnaire design and minimizing the use of proxy respondents while collecting personal information. This dataset is included here.

Geographic coverage
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National coverage

Analysis unit
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Households

Universe
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The IHPS 2016 and 2019 attempted to track all IHPS 2013 households stemming from 102 of the original 204 baseline panel enumeration areas as well as individuals that moved away from the 2013 dwellings between 2013 and 2016 as long as they were neither servants nor guests at the time of the IHPS 2013; were projected to be at least 12 years of age and were known to be residing in mainland Malawi but excluding those in Likoma Island and in institutions, including prisons, police compounds, and army barracks.

Kind of data
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Sample survey data [ssd]

Sampling procedure
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SAMPLING PROCEDURE:

A sub-sample of IHS3 2010 sample enumeration areas (EAs) (i.e. 204 EAs out of 768 EAs) was selected prior to the start of the IHS3 field work with the intention to (i) to track and resurvey these households in 2013 in accordance with the IHS3 fieldwork timeline and as part of the Integrated Household Panel Survey (IHPS 2013) and (ii) visit a total of 3,246 households in these EAs twice to reduce recall associated with different aspects of agricultural data collection. At baseline, the IHPS sample was selected to be representative at the national, regional, urban/rural levels and for each of the following 6 strata: (i) Northern Region - Rural, (ii) Northern Region - Urban, (iii) Central Region - Rural, (iv) Central Region - Urban, (v) Southern Region - Rural, and (vi) Southern Region - Urban. The IHPS 2013 main fieldwork took place during the period of April-October 2013, with residual tracking operations in November-December 2013.

Given budget and resource constraints, for the IHPS 2016 the number of sample EAs in the panel was reduced to 102 out of the 204 EAs. As a result, the domains of analysis are limited to the national, urban and rural areas. Although the results of the IHPS 2016 cannot be tabulated by region, the stratification of the IHPS by region, urban and rural strata was maintained. The IHPS 2019 tracked all individuals 12 years or older from the 2016 households.

Mode of data collection
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Computer Assisted Personal Interview [capi]

Research instrument
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HOUSEHOLD
- Household and Geographic Area Identification and Survey Information (data of interview, enumerator's and supervisors codes, etc.)
- Household Roster
- Education
- Health
- Time Use and Labor
- Housing
- Food Consumption (over past one week)
- Food Security
- Non-food Expenditures - over past one week and one month
- Non-food Expenditures - over past three months
- Non-food Expenditures - over past 12 months
- Durable Goods
- Farm Implements, Machinery, and Structures
- Household Enterprises
- Children Living Elsewhere
- Other Income
- Gifts Given Out
- Social Safety Nets
- Credit
- Subjective Assessment of Well-being
- Shocks and Coping Strategies
- Child Anthropometry
- Deaths in Household

AGRICULTURE
- Garden Roster (both for rainy season and dry (dimba) season)
- Plot Roster (both for rainy season and dry (dimba) season)
- Garden Details (both for rainy season and dry (dimba) season)
- Plot Details (both for rainy season and dry (dimba) season)
- Coupon Use (rainy season)
- Other Inputs (both for rainy season and dry (dimba) season)
- Crops (both for rainy season and dry (dimba) season)
- Seeds (both for rainy season and dry (dimba) season)
- Sales/ Storage (both for rainy season and dry (dimba) season)
- Tree/ Permanent Crop Production (last 12 months)
- Tree/ Permanent Crop Sales/ Storage (last 12 months)
- Livestock
- Livestock Products
- Access to Extension Services
- Network Roster

FISHERY
- Fisheries Calendar
- Fisheries Labor (last high season and last low season)
- Fisheries Inputs (last high season and last low season)
- Fisheries Output (last high season and last low season)
- Fish Trading (last high season and last low season)

COMMUNITY
- Roster of Informants
- Basic Information
- Economic Activities
- Agriculture
- Changes
- Community Needs, Actions and Achievements
- Communal Resource Management
- Communal Organization

Cleaning operations
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a. Data Entry Platform
To ensure data quality and timely availability of data, the IHPS 2019 was implemented using the World Bank’s Survey Solutions CAPI software. To carry out IHPS 2019, 1 laptop computer and a wireless internet router were assigned to each team supervisor, and each enumerator had an 8–inch GPS-enabled Lenovo tablet computer that the NSO provided. The use of Survey Solutions allowed for the real-time availability of data as the completed data was completed, approved by the Supervisor and synced to the Headquarters server as frequently as possible. While administering the first module of the questionnaire the enumerator(s) also used their tablets to record the GPS coordinates of the dwelling units. Geo-referenced household locations from that tablet complemented the GPS measurements taken by the Garmin eTrex 30 handheld devices and these were linked with publically available geospatial databases to enable the inclusion of a number of geospatial variables - extensive measures of distance (i.e. distance to the nearest market), climatology, soil and terrain, and other environmental factors - in the analysis.

b. Data Management
The IHPS 2019 Survey Solutions CAPI based data entry application was designed to stream-line the data collection process from the field. IHPS 2019 Interviews were mainly collected in “sample” mode (assignments generated from headquarters) and a few in “census” mode (new interviews created by interviewers from a template) for the NSO to have more control over the sample. This hybrid approach was necessary to aid the tracking operations whereby an enumerator could quickly create a tracking assignment considering that they were mostly working in areas with poor network connection and hence could not quickly receive tracking cases from Headquarters. The range and consistency checks built into the application was informed by the LSMS-ISA experience with the IHS3 2010/11, IHPS 2013 and IHPS 2016. Prior programming of the data entry application allowed for a wide variety of range and consistency checks to be conducted and reported and potential issues investigated and corrected before closing the assigned enumeration area. Headquarters (the NSO management) assigned work to the supervisors based on their regions of coverage. The supervisors then made assignments to the enumerators linked to their supervisor account. The work assignments and syncing of completed interviews took place through a Wi-Fi connection to the IHPS 2019 server. Because the data was available in real time it was monitored closely throughout the entire data collection period and upon receipt of the data at headquarters, data was exported to Stata for other consistency checks, data cleaning, and analysis.

c. Data Cleaning
The data cleaning process was done in several stages over the course of fieldwork and through preliminary analysis. The first stage of data cleaning was conducted in the field by the field-based field teams utilizing error messages generated by the Survey Solutions application when a response did not fit the rules for a particular question. For questions that flagged an error, the enumerators were expected to record a comment within the questionnaire to explain to their supervisor the reason for the error and confirming that they double checked the response with the respondent. The supervisors were expected to sync the enumerator tablets as frequently as possible to avoid having many questionnaires on the tablet, and to enable daily checks of questionnaires. Some supervisors preferred to review completed interviews on the tablets so they would review prior to syncing but still record the notes in the supervisor account and reject questionnaires accordingly. The second stage of data cleaning was also done in the field, and this resulted from the additional error reports generated in Stata, which were in turn sent to the field teams via email or DropBox. The field supervisors collected reports for their assignments and in coordination with the enumerators reviewed, investigated, and collected errors. Due to the quick turn-around in error reporting, it was possible to conduct call-backs while the team was still operating in the EA when required. Corrections to the data were entered in the rejected questionnaires and sent back to headquarters.

The data cleaning process was done in several stages over the course of the fieldwork and through preliminary analyses. The first stage was during the interview itself. Because CAPI software was used, as enumerators asked the questions and recorded information, error messages were provided immediately when the information recorded did not match previously defined rules for that variable. For example, if the education level for a 12 year old respondent was given as post graduate. The second stage occurred during the review of the questionnaire by the Field Supervisor. The Survey Solutions software allows errors to remain in the data if the enumerator does not make a correction. The enumerator can write a comment to explain why the data appears to be incorrect. For example, if the previously mentioned 12 year old was, in fact, a genius who had completed graduate studies. The next stage occurred when the data were transferred to headquarters where the NSO staff would again review the data for errors and verify the comments from the enumerators and supervisors regarding anomalies that remain. Additional cleaning was performed after interviews were “Approved” where appropriate to resolve systematic errors and organize data modules for consistency and efficient use. Case by case cleaning was also performed during the preliminary analysis specifically pertaining to out of range and outlier variables. All cleaning activities were conducted led by the NSO, and the World Bank LSMS-ISA team provided technical assistance.

Response rate
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2,508 households from IHPS 2016 were the tracking targets for IHPS 2019 with 12,250 total individuals and 8,995 eligible individuals. By the end of the 2019 tracking operation the panel sample grew to 3,178 households with 14,649 individuals. This represents an entire household shift, or a single person from a household splitting off and forming a new one. These 3,178 households stemmed from 2,368 of the 2016 households representing a household-level attrition rate of 5.6 percent.

At the individual level, the calculation of the attrition rate is as follows. Baseline households contained 12,250 individuals in 2016, of whom 153 died between 2016 and 2019. Out of the remaining 12,097 individuals and irrespective of the tracking rules that were in place, the IHPS 2016 accounted for 10,516 baseline individuals, representing an overall attrition rate of 13 percent at the individual level. If one focuses only the individuals that were tracking-eligible in accordance with the aforementioned tracking rules and that were alive in 2016, the IHPS accounted for 7,737 individuals out of 8,859 tracking-eligible individuals, representing an attrition rate of 13 percent at the individual level.

摘要
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2016年综合家庭面板调查（IHPS）于2016年4月启动，作为马拉维第四次综合家庭调查实地操作的一部分。2016年IHPS针对1,989户家庭，这些家庭在2013年接受了IHPS调查，并且可以追溯到2010/11年第三次综合家庭调查（IHS3）中最初抽样的204个抽样区域的一半。2019年IHPS于2019年4月启动，作为马拉维第五次综合家庭调查实地操作的一部分，目标是对2016年接受的2,508户家庭进行调查。通过追踪分离的个人和他们形成的新家庭，面板样本在每个波次中都在扩大。本项目提供的数据包括IHPS 2019数据、IHPS 2016数据以及重新发布的数据，包括只有102个抽样区域（EA）的子样本，这些区域具有更新的面板权重。此外，IHPS 2016是首次获得生活标准测量研究-加（LSMS+）计划补充财务和技术支持的调查，该计划由性别平等信托基金、世界银行统计能力建设信托基金和国际农业发展基金资助成立，并由世界银行生活标准测量研究（LSMS）团队实施，与世界银行性别小组和合作伙伴国家统计办公室合作。LSMS+旨在提高个体分解的家庭调查数据的可用性和质量，最初是对世界银行IDA18承诺的直接回应，该承诺支持6个IDA国家收集家庭内、性别分解的家庭调查数据，包括1）对选定实物和金融资产的所有权和权利，2）工作和就业，以及3）创业——遵循国际最佳实践在问卷设计中的使用，并尽量减少收集个人信息时使用代答人。本数据集包含于此。

地理覆盖范围
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全国覆盖

分析单位
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家庭

总体
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IHPS 2016年和2019年试图追踪所有2013年IHPS的来自102个原始204个基线面板抽样区域的IHPS 2013家庭，以及2013年至2016年间从2013年住所搬走的人，只要他们在2013年IHPS时既不是仆人也不是客人；预计至少12岁，并且已知他们居住在马拉维大陆，但不包括利科马岛和机构，包括监狱、警察营地和军队营房。

数据类型
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样本调查数据 [ssd]

抽样程序
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抽样程序：

在IHS3 2010抽样区域（EA）（即768个EA中的204个EA）选择子样本之前，IHS3实地工作已经开始，目的是（i）根据IHS3实地工作时间表，在2013年对这些家庭进行追踪和复查，作为综合家庭面板调查（IHPS 2013）的一部分，以及（ii）访问这些EA中的总共3,246个家庭两次，以减少与农业数据收集不同方面的回忆。在基线阶段，IHPS样本被选中在国家、地区、城市/农村层面以及以下6个层面上具有代表性：（i）北部地区 - 农村，（ii）北部地区 - 城市，（iii）中部地区 - 农村，（iv）中部地区 - 城市，（v）南部地区 - 农村，（vi）南部地区 - 城市。IHPS 2013主要实地工作于2013年4月至10月进行，剩余的追踪操作于2013年11月至12月进行。

由于预算和资源限制，2016年IHPS的面板样本EA数量减少到204个EA中的102个。因此，分析领域仅限于全国、城市和农村地区。尽管IHPS 2016的结果不能按地区编制表格，但IHPS按地区、城市和农村层级的分层得以保持。IHPS 2019追踪了2016年家庭中12岁或以上的所有人。

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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家庭
- 家庭和地理区域标识及调查信息（访谈数据、调查员和监督员代码等）
- 家庭花名册
- 教育
- 健康
- 时间使用和劳动
- 住房
- 食品消费（过去一周）
- 食品安全
- 非食品支出 - 过去一周和一个月
- 非食品支出 - 过去三个月
- 非食品支出 - 过去十二个月
- 耐用消费品
- 农业机械、设备和结构
- 家庭企业
- 在其他地方生活的儿童
- 其他收入
- 赠送礼物
- 社会安全网
- 贷款
- 主观福祉评估
- 冲击和应对策略
- 儿童体格测量
- 家庭中的死亡

农业
- 花园花名册（雨季和干季）
- 耕地花名册（雨季和干季）
- 花园细节（雨季和干季）
- 耕地细节（雨季和干季）
- 优惠券使用（雨季）
- 其他投入（雨季和干季）
- 作物（雨季和干季）
- 种子（雨季和干季）
- 销售/储存（雨季和干季）
- 树木/永久作物生产（过去12个月）
- 树木/永久作物销售/储存（过去12个月）
- 畜牧业
- 畜产品
- 接入扩展服务
- 网络花名册

渔业
- 渔业日历
- 渔业劳动（上次高峰期和上次低谷期）
- 渔业投入（上次高峰期和上次低谷期）
- 渔业产出（上次高峰期和上次低谷期）
- 鱼类贸易（上次高峰期和上次低谷期）

社区
- 咨询者花名册
- 基本信息
- 经济活动
- 农业
- 变化
- 社区需求、行动和成就
- 社区资源管理
- 社区组织

数据清理操作
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a. 数据录入平台
为确保数据质量和数据的及时可用性，2019年IHPS使用世界银行的调查解决方案CAPI软件实施。为了执行2019年IHPS，每个团队监督员分配了1台笔记本电脑和一台无线互联网路由器，每个调查员都有NSO提供的8英寸带GPS功能的联想平板电脑。使用调查解决方案允许在数据完成、经监督员批准并尽可能频繁地同步到总部服务器时实时提供数据。在管理问卷的第一个模块时，调查员还使用他们的平板电脑记录住宅单位的GPS坐标。该平板电脑上的地理参照家庭位置补充了由Garmin eTrex 30便携式设备进行的GPS测量，并将这些测量与公开可用的地理空间数据库相关联，以便在分析中包含大量的地理空间变量——广泛的距离测量（即距离最近市场的距离）、气候学、土壤和地形以及其他环境因素。

b. 数据管理
基于调查解决方案CAPI的数据录入应用程序旨在简化从现场的数据收集过程。2019年IHPS访谈主要在“样本”模式下收集（总部生成的分配），少数在“普查”模式下收集（调查员根据模板创建的新访谈）以使NSO对样本有更多的控制。这种混合方法对于帮助追踪操作是必要的，因为在网络连接较差的地区工作时，调查员可以快速创建追踪分配，因为他们不能快速从总部接收追踪案例。应用程序中内置的范围和一致性检查是根据LSMS-ISA与IHS3 2010/11、IHPS 2013和IHPS 2016的经验制定的。数据录入应用程序的预先编程允许执行广泛的范围和一致性检查，并报告潜在问题，以及在关闭分配的区域之前进行调查和纠正。总部（NSO管理）根据其覆盖区域分配工作给监督员。然后，监督员根据其监督员账户将分配分配给调查员。工作分配和完成访谈的同步通过Wi-Fi连接到IHPS 2019服务器进行。由于数据是实时可用的，因此在整个数据收集期间都进行了密切监控，并且在数据到达总部后，数据被导出到Stata进行其他一致性检查、数据清理和分析。

c. 数据清理
数据清理过程在实地工作和初步分析的过程中分几个阶段进行。第一阶段的数据清理是在现场由基于现场的现场团队进行的，利用调查解决方案应用程序在响应不符合特定问题的规则时生成的错误消息。对于标记错误的提问，调查员应记录问卷中的注释，向其监督员解释错误的原因，并确认他们已与受访者双重检查了响应。监督员应尽可能频繁地同步调查员平板电脑，以避免在平板电脑上有许多问卷，并能够每天检查问卷。一些监督员更喜欢在平板电脑上审查完成的访谈，这样他们就会在同步之前进行审查，但仍然在监督员账户中记录笔记，并相应地拒绝问卷。第二阶段的数据清理也是在现场进行的，这是由于在Stata中生成的额外错误报告，这些报告随后通过电子邮件或DropBox发送到现场团队。现场监督员收集其分配的报告，并与调查员协调审查、调查和收集错误。由于错误报告的快速周转，当团队仍在EA操作时，如果有必要，可以进行回访。数据中错误的纠正被输入到被拒绝的问卷中，并返回到总部。

数据清理过程在实地工作和初步分析的过程中分几个阶段进行。第一阶段是在访谈过程中进行的。由于使用了CAPI软件，因此当调查员提问并记录信息时，如果记录的信息不符合该变量的先前定义规则，则立即提供错误消息。例如，如果12岁受访者的教育水平被指定为研究生。第二阶段发生在现场监督员审查问卷时。调查解决方案软件允许如果调查员不进行更正，则错误信息保留在数据中。调查员可以写注释来解释数据看起来不正确的原因。例如，如果前面提到的12岁受访者实际上是一位天才，已经完成了研究生学习。下一阶段发生在数据转移到总部时，世界银行的NSO工作人员将再次审查数据以查找错误，并验证调查员和监督员关于异常情况的注释。在适当的情况下，在访谈“批准”之后还进行了额外的清理，以解决系统性错误并组织数据模块以保持一致性和有效使用。在初步分析期间还进行了逐个案例的清理，具体针对超出范围和异常变量。所有清理活动都是由NSO领导的，世界银行LSMS-ISA团队提供了技术援助。