Land and Soil Experimental Research 2013
Ethiopia, 2013
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Reference ID
ETH_2013_LSER_v01_EN_M_v01_A_OCS
Producer(s)
Central Statistical Agency of Ethiopia
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Metadata
Created on
Sep 23, 2020
Last modified
Nov 08, 2022
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10228
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Identification
Survey ID Number
ETH_2013_LSER_v01_EN_M_v01_A_OCS
Title
Land and Soil Experimental Research 2013
Country
| Name | Country code |
|---|---|
| Ethiopia | ETH |
Study type
Living Standards Measurement Study [hh/lsms]
Abstract
The Land and Soil Experimental Research 2013, was conducted as a joint collaboration with The World Bank (LSMS Team), the Central Statistical Agency of Ethiopia (CSA) and the World Agroforestry Center (ICRAF) in an effort to improve the quality of agricultural data, particularly with respect to land area and soil fertility measurements in Ethiopia. The aim of the LASER study was to assess the data quality associated with a number of possible measurement methodologies associated with land area, soil quality, and crop production while piloting the use of each method and assessing the feasibility of implementation in national household surveys. Accurate and timely crop production statistics are critical to adequate government policy responses and the availability of accurate measures are pivotal to establishing credible performance evaluation systems. However, agricultural statistics are often marred by controversy over methods and overall quality, leading to inertia at best, or entirely incorrect policy actions. Major advances in recent years in technologies and practices offer an opportunity to improve on some of the indicators commonly used to measure agricultural performance.
Considerable efforts were made in the 1960s and 1970s, primarily by the Food and Agriculture Organization (FAO), to build a body of knowledge on agricultural statistics based on sound research which, over the years, has proven invaluable to researchers and practitioners in the field of agriculture. However, little new knowledge has been generated over the past few decades and much of the available methodological outputs are now obsolete in view of the changing structure of the sector, driven by global and local trends in both the agronomics of farming and the environment. Measuring land area and soil quality was essential in properly estimating the factors that both promoted and hindered agricultural productivity. It is also critical to assess the accuracy of the key output variable, crop production, in order to validate the methodologies used to collect harvest data as well as analyse the impact of various input measurements on yield estimates. By measuring these components using a variety of methods it was possible to identify the implications of using each and move forward with the superior methods in future household surveys. LASER was implemented across three administrative zones of the Oromia region, namely: East Wellega, West Arsi, and Borena. In total, 1018 households were interviewed, with nearly 1800 agricultural fields selected for objective land area and soil fertility measurement.
Considerable efforts were made in the 1960s and 1970s, primarily by the Food and Agriculture Organization (FAO), to build a body of knowledge on agricultural statistics based on sound research which, over the years, has proven invaluable to researchers and practitioners in the field of agriculture. However, little new knowledge has been generated over the past few decades and much of the available methodological outputs are now obsolete in view of the changing structure of the sector, driven by global and local trends in both the agronomics of farming and the environment. Measuring land area and soil quality was essential in properly estimating the factors that both promoted and hindered agricultural productivity. It is also critical to assess the accuracy of the key output variable, crop production, in order to validate the methodologies used to collect harvest data as well as analyse the impact of various input measurements on yield estimates. By measuring these components using a variety of methods it was possible to identify the implications of using each and move forward with the superior methods in future household surveys. LASER was implemented across three administrative zones of the Oromia region, namely: East Wellega, West Arsi, and Borena. In total, 1018 households were interviewed, with nearly 1800 agricultural fields selected for objective land area and soil fertility measurement.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
Households
Scope
Notes
The study covered the following topics:
- Household identification
- Interview details
- Crop-cutting
- Household member roster
- Field roster
- Parcel roster
- Field details
- Harvest
- Crop disposition
- Crop details
- Harvest labour
- Assets
- Livestock
- Pre-harvest labour
- Parcel roster
- Crop damage
- In-field measurement
- Household identification
- Interview details
- Crop-cutting
- Household member roster
- Field roster
- Parcel roster
- Field details
- Harvest
- Crop disposition
- Crop details
- Harvest labour
- Assets
- Livestock
- Pre-harvest labour
- Parcel roster
- Crop damage
- In-field measurement
Topics
| Topic | Vocabulary |
|---|---|
| Agriculture & Rural Development | FAO |
| Food (production, crisis) | FAO |
| Land (policy, resource management) | FAO |
| Impact evaluation | FAO |
Coverage
Geographic Coverage
Regional
Producers and sponsors
Primary investigators
| Name | Affiliation |
|---|---|
| Central Statistical Agency of Ethiopia | Government of Ethiopia |
Producers
| Name | Role |
|---|---|
| World Agroforestry Centre | Soil analysis |
| The World Bank | Training and technical support |
Sampling
Sampling Procedure
The objectives of the sample design for the Land and Soil Experimental Research study were multifaceted and included indicators related to soil properties, crop type, and socio-economic characteristics, among others. Because there were multiple indicators, calculating the sample size based on the variance of a single indicator was not the preferred approach. Instead, practical sampling allocation with implicit stratification was used. Three administrative zones of the Oromia region were selected based primarily on agroecology and geographic diversity. Secondary consideration was made for the availability of local soil research centers that were used for soil processing. The three selected zones were East Wellega, West Arsi and Borena. Using the Central Statistical Agency of Ethiopia (CSA) and the Agricultural Sample Survey (AgSS) as the sampling frame, a total of 85 Enumeration Areas (EAs) were selected.
Weighting
Refer to World Bank data
Data Collection
Dates of Data Collection
| Start | End |
|---|---|
| 2013-09-12 | 2013-09-12 |
Data Collection Mode
Computer Assisted Personal Interview [capi]
Data Processing
Data Editing
Data collection for the study was completed via Computer-Assisted Personal-Interview (CAPI). Each enumerator and supervisor had a personal laptop computer equipped with the Census and Survey Processing System (CSPro), based CAPI application for the Post-Planting, Crop-Cutting, and Post-Harvest questionnaires. Each team was provided with a flash drive, to share data from enumerator to supervisor, and a wireless router, to share consolidated team data with the World Bank project manager. Supervisors were instructed to share data at the close of EA, and only after reviewing all completed questionnaires. Data review and cleaning took place via supervisor review, periodic error reports generated by the World Bank project manager, unplanned CSA supervisor household visits to cross-check responses, and ultimately data review and standard checks (possible value ranges, outliers, etc.).
Access policy
Contacts
| Name | Affiliation | URL | |
|---|---|---|---|
| Data Administrator | Central Statistical Agency of Ethiopia | [email protected] | Link |
| LSMS Data Manager | The World Bank | [email protected] | Link |
Confidentiality
https://microdata.worldbank.org/index.php/terms-of-use
Access conditions
https://microdata.worldbank.org/index.php/terms-of-use
Citation requirements
Use of the dataset must be acknowledged using a citation which would include:
- the Identification of the Primary Investigator
- the title of the survey (including country, acronym and year of implementation)
- the survey reference number
- the source and date of download
Example:
Central Statistical Agency of Ethiopia (CSA). Land and Soil Experimental Research (LASER) 2013, Ref. ETH_2013_LASER_v02_M. Dataset downloaded from [URL] on [date].
- the Identification of the Primary Investigator
- the title of the survey (including country, acronym and year of implementation)
- the survey reference number
- the source and date of download
Example:
Central Statistical Agency of Ethiopia (CSA). Land and Soil Experimental Research (LASER) 2013, Ref. ETH_2013_LASER_v02_M. Dataset downloaded from [URL] on [date].
Disclaimer and copyrights
Disclaimer
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 use of the data or for interpretations or inferences based upon such uses
Metadata production
DDI Document ID
DDI_ETH_2013_LSER_v01_EN_M_v01_A_OCS_FAO
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Office of Chief Statistician | OCS | Food and Agriculture Organization | Adoption of metadata for FAM |
| Development Data Group | DECDG | The world Bank | Documentation of the study |
DDI Document version
ETH_2013_LSER_v01_EN_M_v01_A_OCS_v01