Ethiopia - Land and Soil Experimental Research 2013

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The Land and Soil Experimental Research (LASER) 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 analyze 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.

Type: 
Microdata
Acronym: 
LASER 2013
Languages Supported: 
English
Topics: 
Topic not specified
Geographical Coverage: 
Ethiopia
Economy Coverage: 
Economy Coverage not specified
Release Date: 
September 1, 2016

Last Updated

Last Updated: 
January 30, 2020

Harvest System ID

Harvest System ID: 
Microdata

Harvest Source ID

Harvest Source ID: 
8924
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.
Version Description: 
v02 (October 2017)
Publisher Name: 

Development Data Group; The World Bank

Study Type: 
Living Standards Measurement Study [hh/lsms]
Primary Investigator Name, Affiliation: 
Central Statistical Agency of Ethiopia; Government of Ethiopia
Sampling Procedure: 
The objectives of the sample design for the Land and Soil Experimental Research study (LASER) 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.
Questionnaires: 
The LASER survey consisted of three questionnaires: 1. Post-Planting Questionanire 2. Crop-Cutting Questionnaire 3. Post-Harvest Questionnaire
Data Collector(s) Name: 
Central Statistical Agency of Ethiopia
Supervision: 
Each team was led by one supervisor who traveled with the team at all times. The supervisor was the overall coordinator and supervisor for the fieldwork, he/she was responsible for ensuring the team completed all duties in a timely and high-quality manner. If the enumerators experienced any problems or needed assistance, they reported to the supervisor. The supervisor was also responsible for completing the following activities: 1. Coordination of fieldwork within assigned Enumeration areas. 2. Supervision of questionnaire administration and measurements, including spot checking some questionnaires with the household and repeating some measurements. 3. Coordination of transportation of soil samples to laboratory. 4. Household listing in each Enumeration area. 5. Communicate with Kebele officers about the timing of crop cutting. 6. Transmission of data to head office. 7. Communication with head office.
Data Editing: 
Data collection for LASER 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.).
Other Processing: 
The LASER 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 labor - Assets - Livestock - Pre-harvest labor - Parcel roster - Crop damage - In-field measurement
Time Periods: 
August, 2017

No Visualizations Available.

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 Land and Soil Experimental Research (LASER) 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 analyze 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.

FieldValue
Modified Date
2020-04-15
Release Date
Identifier
65ae347c-ae8a-483d-8e85-489fd5aa27ec
License
License Not Specified
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Acronym: 
LASER 2013
Type: 
Languages Supported: 
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.
Time Periods: 
August, 2017
Supervision: 
Each team was led by one supervisor who traveled with the team at all times. The supervisor was the overall coordinator and supervisor for the fieldwork, he/she was responsible for ensuring the team completed all duties in a timely and high-quality manner. If the enumerators experienced any problems or needed assistance, they reported to the supervisor. The supervisor was also responsible for completing the following activities: 1. Coordination of fieldwork within assigned Enumeration areas. 2. Supervision of questionnaire administration and measurements, including spot checking some questionnaires with the household and repeating some measurements. 3. Coordination of transportation of soil samples to laboratory. 4. Household listing in each Enumeration area. 5. Communicate with Kebele officers about the timing of crop cutting. 6. Transmission of data to head office. 7. Communication with head office.
Economy Coverage: 
Primary Investigator Name, Affiliation: 
Central Statistical Agency of Ethiopia; Government of Ethiopia
Publisher Name: 
Development Data Group; The World Bank
Terms of Use: 
Version Description: 
v02 (October 2017)
Geographical Coverage: 
Data Classification of a Dataset: 
Sampling Procedure: 
The objectives of the sample design for the Land and Soil Experimental Research study (LASER) 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.
Release Date: 
Thursday, September 1, 2016
Last Updated Date: 
Thursday, January 30, 2020
Questionnaires: 
The LASER survey consisted of three questionnaires: 1. Post-Planting Questionanire 2. Crop-Cutting Questionnaire 3. Post-Harvest Questionnaire
Data Editing: 
Data collection for LASER 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.).
Other Processing: 
The LASER 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 labor - Assets - Livestock - Pre-harvest labor - Parcel roster - Crop damage - In-field measurement
Harvest Source: 
Harvest System ID: 
8924
Citation Text: 
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].
Modified date: 
18291
Study Type: 
Living Standards Measurement Study [hh/lsms]
Primary Dataset: 
Yes
Mode of Data Collection: 

Computer Assisted Personal Interview

Data Collector(s) Name: 

Central Statistical Agency of Ethiopia

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This dataset is made available under the World Bank Microdata Research License

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