ETH_2021_ESPS-W5_v01_M
Socio-Economic Panel Survey 2021-2022
Wave 5
Name | Country code |
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Ethiopia | ETH |
Living Standards Measurement Study [hh/lsms]
The fifth wave of the Ethiopia Socioeconomic Panel Survey (ESPS 2021/22) has been implemented by the Ethiopian Statistical Service with technical support from the Living Standards Measurement Study (LSMS), World Bank. ESPS-5 covers all regions of the country except Tigray. Therefore, the survey is nationally representative and provides national and regional estimates for rural and urban areas except for Tigray. It collects detailed socioeconomic information from the same households over time to monitor national and global goals, understand the dynamics of well-being in rural and urban areas, and to support policy and program evaluations. The fifth wave was conducted from September 12, 2021, to June 30, 2022. It interviewed 4,999 households from 438 enumeration areas.
The Ethiopia Socioeconomic Panel Survey (ESPS) is a collaborative project between the Ethiopian Statistical Service (ESS) and the World Bank Living Standards Measurement Study-Integrated Surveys on Agriculture (LSMS-ISA) team. The objective of the LSMS-ISA is to collect multi-topic, household-level panel data with a special focus on improving agriculture statistics and generating a clearer understanding of the link between agriculture and other sectors of the economy. The project also aims to build capacity, share knowledge across countries, and improve survey methodologies and technology. ESPS is a long-term project to collect panel data. The project responds to the data needs of the country, given the dependence of a high percentage of households on agriculture activities in the country. The ESPS collects information on household agricultural activities along with other information on the households like human capital, other economic activities, and access to services and resources. The ability to follow the same households over time makes the ESPS a new and powerful tool for studying and understanding the role of agriculture in household welfare over time as it allows analyses of how households add to their human and physical capital, how education affects earnings, and the role of government policies and programs on poverty, inter alia. The ESPS is the first-panel survey to be carried out by the Ethiopian Statistical Service that links a multi-topic household questionnaire with detailed data on agriculture.
Sample survey data [ssd]
Version 01: Anonymous dataset for public distribution
2023-07-20
The scope of the ESPS-5 study includes:
Household: Household characteristics; household roster; education; health (including anthropometric measurement for children); labor and time use; financial inclusion; digital financial services, assets ownership; food and non-food expenditure; household nonfarm activities and entrepreneurship; food security and shocks; dietary quality, safety nets; housing conditions; physical and financial assets; credit; tax and transfer; urban agriculture practices (Crop and Livestock); climate risk perception, and other sources of household income.
Community: Informant roster; basic information; access to basic services; economic activities; agriculture (only for rural EAs); infrastructure; community organizations; resource management; changes in the community; key events; community needs, actions, and achievements; Agriculture Mechanization and Video-Based Agricultural Extension, and local retail price information.
Post harvest: Household roster; crop roster; crop harvest by field; unit and size codes; harvest labor; crop disposition.
Post planting: Parcel Roster; field roster; crop roster; seeds roster; miscellaneous questions for the holder.
Livestock: ownership; change in stock; breeding; house, water, and feed; animal health; milk production; egg production; animal power and dung; household roster.
National
Regional
Urban and Rural
The survey covered all de jure households excluding prisons, hospitals, military barracks, and school dormitories.
Name | Affiliation |
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Ethiopian Statistical Service (ESS) | Government of Ethiopia |
Name | Affiliation |
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The World Bank | |
National Bank of Ethiopia | Government of Ethiopia |
Name | Role |
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World Bank | Funded the study |
Foreign Commonwealth and Development Office | Funded the study |
Government of Ethiopia | Funded the study |
Bill and Melinda Gates Foundation | Funded the study |
The sampling frame for the second phase ESPS panel survey is based on the updated 2018 pre-census cartographic database of enumeration areas by the Ethiopian Statistical Service (ESS). The sample is a two-stage stratified probability sample. The ESPS EAs in rural areas are the subsample of the AgSS EA sample. That means the first stage of sampling in the rural areas entailed selecting enumeration areas (i.e., the primary sampling units) using simple random sampling (SRS) from the sample of the 2018 AgSS enumeration areas (EAs). The first stage of sampling for urban areas is selecting EAs directly from the urban frame of EAs within each region using systematic PPS. This is designed to automatically result in a proportional allocation of the urban sample by zone within each region. Following the selection of sample EAs, they are allocated by urban rural strata using power allocation which is happened to be closer to proportional allocation.
The second stage of sampling is the selection of households to be surveyed in each sampled EA using systematic random sampling. From the rural EAs, 10 agricultural households are selected as a subsample of the households selected for the AgSS, and 2 non-agricultural households are selected from the non-agriculture households list in that specific EA. The non-agriculture household selection follows the same sampling method i.e., systematic random sampling. One important issue to note in ESPS sampling is that the total number of agriculture households per EA remains at 10 even though there are less than 2 or no non-agriculture households are listed and sampled in that EA. For urban areas, a total of 15 households are selected per EA regardless of the households’ economic activity. The households are selected using systematic random sampling from the total households listed in that specific EA.
The ESPS-5 kept all the ESPS-4 samples except for those in the Tigray region and a few other places. A more detailed description of the sample design is provided in Section 3 of the Basic Information Document provided under the Related Materials tab.
ESPS-5 planned to interview 7,527 households from 565 enumeration areas (EAs) (Rural 316 EAs and Urban 249 EAs). However, due to the security situation in northern Ethiopia and to a lesser extent in the western part of the country, only a total of 4999 households from 438 EAs were interviewed for both the agriculture and household modules. The security situation in northern parts of Ethiopia meant that, in Tigray, ESPS-5 did not cover any of the EAs and households previously sampled. In Afar, while 275 households in 44 EAs had been covered by both the ESPS-4 agriculture and household modules, in ESPS-5 only 252 households in 22 EAs were covered by both modules. During the fifth wave, security was also a problem in both the Amhara and Oromia regions, so there was a comparable reduction in the number of households and EAs covered there.
More detailed information is available in the BID.
ESPS-5 was conducted in 2021/22 and is the second wave of the new panel that began in 2018/19 with ESPS-4. Therefore, ESPS-5 data can be used both for cross-sectional and longitudinal analysis. In order to cater to both kinds of analysis, separate cross-sectional and longitudinal weights were calculated and included in the ESPS-5 data.
Cross-sectional analysis of panel data is concerned with making inferences about the target population of the survey at a given reference time, namely the time when the panel wave at hand was conducted. Cross-sectional weights are needed for each wave of a panel survey. Accordingly, ESPS-5 cross-sectional weights were calculated to represent the 2021/22 Ethiopia population (excluding Tigray) at regional and rural/urban levels. Similarly, cross-sectional sample weights had previously been calculated and disseminated for the ESPS-4 data. It must be noted that ESPS-5 cross-sectional weights were calculated for all the households interviewed during ESPS-5, regardless of whether they had been interviewed in ESPS-4 or not. In addition to pure cross-sectional analysis, cross-sectional weights attached to each wave of a panel survey also allow users to make inferences about net changes between two-panel waves.
For detailed information please refer to section 3.4 of the BID
The ESPS-5 survey consisted of four questionnaires (household, community, post-planting, and post-harvest questionnaires), similar to those used in previous waves but revised based on the results of those waves and on the need for new data they revealed. The following new topics are included in ESPS-5:
a. Dietary Quality: This module collected information on the household’s consumption of specified food items.
b. Food Insecurity Experience Scale (FIES): In this round the survey has implemented FIES. The scale is based on the eight food insecurity experience questions on the Food Insecurity Experience Scale | Voices of the Hungry | Food and Agriculture Organization of the United Nations (fao.org).
c. Basic Agriculture Information: This module is designed to collect minimal agriculture information from households. It is primarily for urban households. However, it was also used for a few rural households where it was not possible to implement the full agriculture module due to security reasons and administered for urban households. It asked whether they had undertaken any agricultural activity, such as crop farming and tending livestock) in the last 12 months. For crop farming, the questions were on land tenure, crop type, input use, and production. For livestock there were also questions on their size and type, livestock products, and income from sales of livestock or livestock products.
d. Climate Risk Perception: This module was intended to elicit both rural and urban households perceptions, beliefs, and attitudes about different climate-related risks. It also asked where and how households were obtaining information on climate and weather-related events.
e. Agriculture Mechanization and Video-Based Agricultural Extension: The rural area community questionnaire covered these areas rural areas. On mechanization the questions related to the penetration, availability and accessibility of agricultural machinery. Communities were also asked if they had received video-based extension services.
Start | End | Cycle |
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2021-09-16 | 2022-01-31 | Post-planting agriculture and livestock questionnaires |
2021-10-01 | 2022-01-31 | Crop cut questionnaire |
2022-04-01 | 2022-06-30 | Post-harvest questionnaire |
2022-04-01 | 2022-06-30 | Household and community questionnaires |
Name | Affiliation |
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Ethiopian Statistical Service | Government of Ethiopia |
Field supervisors in ESS branch offices provided routine supervision. Branch statisticians and supervisors were assigned to this project; the branch supervisors made extended visits to the EAs between September 2021 and June 2022. One field supervisor checked the work of enumerators in assigned EAs. The last visit was combined with community interviews conducted by the supervisors. Branch statisticians were also in the field to check the work of supervisors and enumerators.
World Bank staff and consultants also provided supervision. The extremely volatile security situation during the post-planting data collection period limited their visits to the post-harvest data collection period, April to June 2022.
Six training sessions were held for ESPS-5: two (in July 2021 and February 2022) for the Training of Trainers and four (in August, September, and October 2021 and March 2022) for field staff enumerators and supervisors. All six sessions emphasized not only the content of the questionnaires and Survey Solutions CAPI but also their practical applications in data collection and supervision. All the trainees had survey and CAPI experience, and most had participated in other ESS surveys.
ESPS-5 was conducted in two visits, following the AgSS field schedule. For rural households, in the first visit, between September 2021 and January 2022, the post-planting agriculture, livestock, and crop cut questionnaires were administered. In the second visit, between April and June 2022, the post-harvest agriculture, household, and community questionnaires were administered. For urban households, there was a single visit, between April and June 2022, to administer the household and community questionnaires. A detailed description of the Training, Data Collection, Tracking & Monitoring process is provided in Section 4 of the Basic Information Document.
Reference Photo Album Reference photographs were used in the collection of food consumption and crop production quantities reported in non-standard units. The photographs depict food items or crops in non-standard units (and different sizes where applicable) and were meant to ensure uniformity in the non-standard unit amounts across respondents. The photos were collected in a systematic manner during the market survey where the item-unit weights were also collected. During the market survey, interviewers were instructed to follow strict protocols when taking the photographs such as including a reference object (typically a standard-sized bottle of water) to provide the respondent with a frame of reference for the size of the unit. For units with multiple sizes, all the relevant sizes were taken in the same photo for easier comparison by the respondent. The reference photos taken during the market survey were compiled into an album that was printed and provided to all interviewers. Item-specific photos were included for non-container units (e.g., piece, medeb, bunch) while only one photo of containers (e.g., tassa, kunna, jog) were included. The procedures used for the collection of the reference photos as well as the conversion factors followed the guidelines laid out in a forthcoming guidebook produced by the LSMS team, The Use of Non-Standard Units for the Collection of Food Quantity: A Guidebook for Improving the Measurement of Food Consumption and Agricultural Production in Living Standards Surveys.
Final data cleaning was carried out on all data files. Only errors that could be clearly and confidently fixed by the team were corrected; errors that had no clear fix were left in the datasets. Cleaning methods for these errors are left up to the data user.
Confidentiality declaration text |
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The ESPS collects confidential information on respondents. The confidential variables pertain to (i) names of the respondents to the household and community questionnaires, (ii) village and constituency names, (iii) descriptions of household dwelling and agricultural field locations, (iv) phone numbers of household members and their reference contacts, (v) GPS-based dwelling and agricultural field locations, (vi) names of the children of the head/spouse living elsewhere, (vii) names of the deceased household members, , and (viii) names of field staff. To maintain confidentiality, this information is not included in the ESPS public use data. To partially satisfy user interest in the geo-referenced location, while preserving the confidentiality of sample households and communities, modified EA-level coordinates are provided as part of the household geo-variable table. Modified coordinates are generated by applying a random offset within a specified range to the average EA value (following the Measure DHS approach). For households that have moved between waves 4 and 5 and are more than 5 km from their baseline location, the offset is with respect to the new household location. More specifically, the coordinate modification strategy relies on the random offset of EA center-point coordinates (or the average of household GPS locations by EA in ESPS) within a specified range determined by the urban and rural classification. For small towns and urban areas, an offset range of 0-2 km is used. In rural areas, where communities are more dispersed and the risk of the disclosure may be higher, a range of 0-5 km offset is used. Additionally, an offset range of 0-10 km is applied to 1% of EAs, effectively increasing the known range for all points to 10 km while introducing only a small amount of noise. Offset points are constrained at the zone level so that they still fall within the correct zone for spatial joins or point-in-polygon overlays. The result is a set of coordinates, representative at the EA level, that fall within known limits of accuracy. Users should take into account the offset range when considering different types of spatial analysis or queries with the data. Analysis of the spatial relationships between locations in close proximity would not be reliable. However, spatial queries using medium or low-resolution datasets should be minimally affected by the offsets Before being granted access to the dataset, all users have to formally agree: 1. To make no copies of any files or portions of files to which s/he is granted access except those authorized by the data depositor. 2. Not to use any technique in an attempt to learn the identity of any person, establishment, or sampling unit not identified on public use data files. 3. To hold in strictest confidence the identification of any establishment or individual that may be inadvertently revealed in any documents or discussion, or analysis. Such inadvertent identification revealed in her/his analysis will be immediately brought to the attention of the data depositor. |
Public use files, accessible to all
Use of the dataset must be acknowledged using a citation which would include:
Example:
Ethiopian Statistical Service. Ethiopia Socioeconomic Panel Survey, Wave 5 (ESPS-5) 2021-2022. Public Use Dataset. Ref: ETH_2021_ESPS-W5_v01_M. Downloaded from[URL] on [Date]
The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for the use of the data or for interpretations or inferences based upon such uses.
Name | Affiliation | |
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LSMS Database Manager | Development Economics Data Group (The World Bank) | lsms@worldbank.org |
World Bank Microdata Library | Development Economics Data Group (The World Bank) |
DDI_ETH_2021_ESPS-W5_v01_M_WB
Name | Affiliation | Role |
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Development Data Group | The World Bank | Documentation of the DDI |
2024-01-15
Version 01 (January 2024)