Hunger Safety Net Programme Survey 2016
Kenya, 2016
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Reference ID
KEN_2016_HSNPS_v01_EN_M_v01_A_OCS
Producer(s)
Oxford Policy Management Limited
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Oct 19, 2020
Last modified
Nov 08, 2022
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Identification
Survey ID Number
KEN_2016_HSNPS_v01_EN_M_v01_A_OCS
Title
Hunger Safety Net Programme Survey 2016
Country
| Name | Country code |
|---|---|
| Kenya | KEN |
Study type
Other Household Survey [hh/oth]
Series Information
The Kenya Hunger Safety Net Programme Survey 2016 was developed by Oxford Policy Management Ltd (OPM) for carrying out the impact evaluation of the second phase of the Hunger Safety Net Programme implemented in Mandera, Marsabit, Turkana and Wajir counties in Kenya. The first phase of the HSNP ran from 2009 to 2013. OPM also conducted the evaluation of HSNP phase 1. Data from HSNP Phase 1 Randomised Controlled Trial is available on the World Bank Microdata Catalog. The HSNP was scaled up under Phase 2 in July 2013. Phase 2 was contracted to run until March 2018. The purpose of collecting new data for this evaluation was to gather richer information than was already available through the HSNP Management Information System (MIS) data, such as on key outcome areas like poverty and consumption, and to enable an estimate. The household survey for HSNPS 2016 consists of three tools:
i) Household questionnaire
ii) business questionnaire
iii) Livestock trader questionnaire
i) Household questionnaire
ii) business questionnaire
iii) Livestock trader questionnaire
Abstract
The Hunger Safety Net Programme (HSNP) is a social protection project being conducted in the Arid and Semi-Arid Lands (ASALs) of northern Kenya. The ASALs are extremely food-insecure areas highly prone to drought, which have experienced recurrent food crises and food aid responses for decades. The HSNP is intended to reduce dependency on emergency food aid by sustainably strengthening livelihoods through cash transfers. The pilot phase ran from 2009 to 2013. The second phase has been launched in July 2013 and contracted to run until March 2018. Oxford Policy Management (OPM) was responsible for the monitoring and evaluation (M&E) of the programme under the pilot phase, as well as the second phase of implementation. Within the impact evaluation component for Phase 2, OPM used a range of analytical methods within an overarching mixed-method approach. The quantitative impact evaluation of HSNP Phase 2 compares the situation of HSNP2 beneficiaries and control households, relying on the Regression Discontinuity approach, integrated by a targeted Propensity Score Matching approach. In addition to the analysis at the household level, a Local Economy-Wide Impact Evaluation (LEWIE) was conducted to investigate the impact of the HSNP2 on the local economy, including on the production activities of both beneficiary and non-beneficiary households. A single round of data collection based on a household and business survey underpins the household quantitative impact evaluation and the LEWIE study. The objective of the survey is to collect household and business data to provide an assessment of the programme's impact on the local economy, as well as beneficiary households. The household survey is a survey of 5,979 people, carried out between 13 February and 29 June 2016 in 187 sub-locations across the four counties of Mandera, Marsabit, Turkana and Wajir. The survey covered modules on household demographic characteristics, livestock, assets, land, transfers, food and non-food consumption, food security, saving and borrowing, jobs, business, livestock trading and subjective poverty. In addition to the household survey, a business questionnaire was conducted in the three main commercial hubs of each county. Overall, 282 business questionnaires were administered in the four counties. The purpose of the survey was to learn more about local economic activities and livelihoods in the HSNP counties, and the data was used for the LEWIE analysis. The aim was to capture information on three main sectors of the local economy:
1. Retailing - shops that sell retail goods on which a price mark-up is applied
2. Services
3. Producers - businesses that transform inputs into outputs
Lastly, since livestock trading is a very important activity in the HSNP counties, livestock traders have been interviewed to understand better how the market works. In each county, three main livestock markets were targeted for interviews.
1. Retailing - shops that sell retail goods on which a price mark-up is applied
2. Services
3. Producers - businesses that transform inputs into outputs
Lastly, since livestock trading is a very important activity in the HSNP counties, livestock traders have been interviewed to understand better how the market works. In each county, three main livestock markets were targeted for interviews.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
Households
Scope
Notes
(a) HOUSEHOLD SURVEY:
Household characteristics
Household listing
Livestock ownership and trading
Assets and land ownership
Household's main dwelling characteristics
Food and non-food consumption
Agricultural activities
Informal and formal transfers
Household food security
Subjective poverty
Saving and borrowing
Household jobs and business activities.
(b) BUSINESS SURVEY:
Type of business and business characteristics (i.e. number of employees, number of hours worked by business owner and employees, value of wages, cost of inputs, revenues and location of economic transactions).
(c) LIVESTOCK TRADER SURVEY:
Location of economic transactions, expenditure on taxes, transport, fodder, hired labour, volume of trade, livestock prices.
Household characteristics
Household listing
Livestock ownership and trading
Assets and land ownership
Household's main dwelling characteristics
Food and non-food consumption
Agricultural activities
Informal and formal transfers
Household food security
Subjective poverty
Saving and borrowing
Household jobs and business activities.
(b) BUSINESS SURVEY:
Type of business and business characteristics (i.e. number of employees, number of hours worked by business owner and employees, value of wages, cost of inputs, revenues and location of economic transactions).
(c) LIVESTOCK TRADER SURVEY:
Location of economic transactions, expenditure on taxes, transport, fodder, hired labour, volume of trade, livestock prices.
Topics
| Topic | Vocabulary |
|---|---|
| Poverty | FAO |
| Nutrition | FAO |
| Agriculture & Rural Development | FAO |
| Livestock | FAO |
| Food (production, crisis) | FAO |
Keywords
| Keyword |
|---|
| Poverty |
| Food Security |
| Local Economy |
| Livestock |
| Agriculture |
| Arid and semi-arid lands |
| Hunger Safety Net |
| Kenya |
Coverage
Geographic Coverage
Regional
Universe
(a) At the household level, the study population consists of all the households in the four HSNP counties (i.e. Mandera, Marsabit, Turkana and Wajir). Within a household, the survey covered all de jure household members (usual residents).
(b) At the market level, the survey covered a random sample of businesses in the three main commercial hubs of each county. The following categories of businesses were excluded from the listing:
- Temporary stalls or mobile sellers located outside permanent kiosks
- Banks
- Education institutions (schools, universities etc.)
- Health facilities
(c) The livestock trader survey was conducted in the three main livestock markets of each county. To the extent possible, livestock traders have been sampled in order to achieve a balance between those trading large animals, those trading small or medium value animals, those trading only within the HSNP counties and those who also trade outside the HSNP counties.
(b) At the market level, the survey covered a random sample of businesses in the three main commercial hubs of each county. The following categories of businesses were excluded from the listing:
- Temporary stalls or mobile sellers located outside permanent kiosks
- Banks
- Education institutions (schools, universities etc.)
- Health facilities
(c) The livestock trader survey was conducted in the three main livestock markets of each county. To the extent possible, livestock traders have been sampled in order to achieve a balance between those trading large animals, those trading small or medium value animals, those trading only within the HSNP counties and those who also trade outside the HSNP counties.
Producers and sponsors
Primary investigators
| Name |
|---|
| Oxford Policy Management Limited |
Funding Agency/Sponsor
| Name | Abbreviation | Role |
|---|---|---|
| UK Department for International Development | DFID | Programme and Evaluation Funder |
| Goverment of Kenya | GoK | Programme Funder |
Sampling
Sampling Procedure
(a) HOUSEHOLD SURVEY
The household survey used a two-stage sampling approach, for which the sample frame was defined by sub-locations and households in the HSNP Management Information System (MIS) data. The MIS data are data from a census of nearly all households in the four HSNP counties. The census contains the information that was gathered in respect of these households during the registration for the HSNP programme, their Proxy Means Test (PMT) score and their assignment to the HSNP cash transfers, as well as information about all payments received by all households since the start of Phase 2. The HSNP acknowledges that a small number of the population was recognised to be missed and was registered at a later date. The sampling procedure was intended to cover the different sample requirements of the impact evaluation approaches, including the Local Economy-Wide Impact Evaluation (LEWIE), the quantitative impact evaluation based on the Regression Discontinuity (RD) approach, and the Propensity Score Matching (PSM) back-up.
Drawing the sample consisted of two stages:
1. First stage: sampling of sub-locations
2. Second stage: sampling of households within a sub-location.
The sampling process yielded a sample of 187 sub-locations, including the 24 that were sampled with certainty. 11 sub-locations were sampled twice, and one sub-location was sampled three times. 44 sub-locations were selected in Mandera, 46 in Wajir, 48 in Marsabit and 49 in Turkana. In each sub-location 32 households were sampled. In a few sub-locations there were insufficient households to select the desired LEWIE sample, resulting in fewer than 32 households sampled. Overall, 6,384 households were sampled.
(b) BUSINESS SURVEY
A business questionnaire was conducted in the three main commercial hubs of each county. The purpose of the survey was to learn more about local economic activities and livelihoods in the HSNP counties, and the data was used for the LEWIE analysis. In each sub-location, a sample of at least seven businesses from each category was targeted. Since no sampling frame for local businesses was available, the survey research teams in each county undertook a listing exercise of all businesses on the main commercial centre of the selected sub-locations. Once the listing was completed, the team leader sampled the required number of businesses using a step sampling approach. Overall, 282 business questionnaires were administered in the four counties. The business survey is not representative of any commercial hubs.
(c) LIVESTOCK TRADER SURVEY
Since livestock trading is a very important activity in the HSNP counties, a number of livestock traders have been interviewed to understand better how the market works. In each county, three main livestock markets were targeted for interviews. Each enumerator team was asked to interview four traders in each of the sub-locations, leading to a total sample size of 12 livestock trader interviews per county. Sampling of livestock traders was mostly done purposively. To the extent possible, team leaders sampled livestock traders in order to achieve a balance between those trading large animals, those trading small or medium value animals, those trading only within the HSNP counties and those who also trade outside the HSNP counties. The livestock trader survey is not representative of any livestock markets.
The household survey used a two-stage sampling approach, for which the sample frame was defined by sub-locations and households in the HSNP Management Information System (MIS) data. The MIS data are data from a census of nearly all households in the four HSNP counties. The census contains the information that was gathered in respect of these households during the registration for the HSNP programme, their Proxy Means Test (PMT) score and their assignment to the HSNP cash transfers, as well as information about all payments received by all households since the start of Phase 2. The HSNP acknowledges that a small number of the population was recognised to be missed and was registered at a later date. The sampling procedure was intended to cover the different sample requirements of the impact evaluation approaches, including the Local Economy-Wide Impact Evaluation (LEWIE), the quantitative impact evaluation based on the Regression Discontinuity (RD) approach, and the Propensity Score Matching (PSM) back-up.
Drawing the sample consisted of two stages:
1. First stage: sampling of sub-locations
2. Second stage: sampling of households within a sub-location.
The sampling process yielded a sample of 187 sub-locations, including the 24 that were sampled with certainty. 11 sub-locations were sampled twice, and one sub-location was sampled three times. 44 sub-locations were selected in Mandera, 46 in Wajir, 48 in Marsabit and 49 in Turkana. In each sub-location 32 households were sampled. In a few sub-locations there were insufficient households to select the desired LEWIE sample, resulting in fewer than 32 households sampled. Overall, 6,384 households were sampled.
(b) BUSINESS SURVEY
A business questionnaire was conducted in the three main commercial hubs of each county. The purpose of the survey was to learn more about local economic activities and livelihoods in the HSNP counties, and the data was used for the LEWIE analysis. In each sub-location, a sample of at least seven businesses from each category was targeted. Since no sampling frame for local businesses was available, the survey research teams in each county undertook a listing exercise of all businesses on the main commercial centre of the selected sub-locations. Once the listing was completed, the team leader sampled the required number of businesses using a step sampling approach. Overall, 282 business questionnaires were administered in the four counties. The business survey is not representative of any commercial hubs.
(c) LIVESTOCK TRADER SURVEY
Since livestock trading is a very important activity in the HSNP counties, a number of livestock traders have been interviewed to understand better how the market works. In each county, three main livestock markets were targeted for interviews. Each enumerator team was asked to interview four traders in each of the sub-locations, leading to a total sample size of 12 livestock trader interviews per county. Sampling of livestock traders was mostly done purposively. To the extent possible, team leaders sampled livestock traders in order to achieve a balance between those trading large animals, those trading small or medium value animals, those trading only within the HSNP counties and those who also trade outside the HSNP counties. The livestock trader survey is not representative of any livestock markets.
Response Rate
Household survey response rate was 88.9 percent. For business survey and livestock trader survey, the response rate was 100 percent.
Weighting
Analysis weights are constructed to ensure that the analysis accounts for any household non-response rate at the sub-location level. They are calculated separately for the household quantitative impact evaluation and LEWIE sub-samples. Weights are calculated at both household and population level.
The household-level weight in the dataset is 'weight'
The population-level weight in the dataset is 'popweight'
There are no weights for Business survey and Livestock trader survey these surveys and samples are not representative at any level.
The household-level weight in the dataset is 'weight'
The population-level weight in the dataset is 'popweight'
There are no weights for Business survey and Livestock trader survey these surveys and samples are not representative at any level.
Data Collection
Dates of Data Collection
| Start | End |
|---|---|
| 2016-02-13 | 2016-06-29 |
Data Collection Mode
Computer Assisted Personal Interview [capi]
Data Processing
Data Editing
(a) QUALITY CHECKS
Given the data was electronically collected, it was continually checked, edited and processed throughout the survey cycle. A first stage of data checking was done by the survey team which involved:
(i) checking of all IDs
(ii) checking for missing observations
(iii) checking for missing item responses where none should be missing
(iv) first round of checks for inadmissible/out of range and inconsistent values.
(b) DATA PROCESSING
Additional data processing activities were performed at the end of data collection in order to transform the collected cleaned data into a format that is ready for analysis. The aim of these activities was to produce reliable, consistent and fully-documented datasets that can be analysed throughout the survey and archived at the end in such a way that they can be used by other data users well into the future. Data processing activities involved:
- Computing and merging in the sampling weights
- Reshaping datasets in order to produce data files for each unit of observation (households, household members, and businesses)
- Anonymising data by removing all variables that identify respondents such as names, address, GPS coordinates, etc.
- Classifying non-response and coding them using a pre-determined classification scheme
- Properly naming and labelling the variables in each dataset
Given the data was electronically collected, it was continually checked, edited and processed throughout the survey cycle. A first stage of data checking was done by the survey team which involved:
(i) checking of all IDs
(ii) checking for missing observations
(iii) checking for missing item responses where none should be missing
(iv) first round of checks for inadmissible/out of range and inconsistent values.
(b) DATA PROCESSING
Additional data processing activities were performed at the end of data collection in order to transform the collected cleaned data into a format that is ready for analysis. The aim of these activities was to produce reliable, consistent and fully-documented datasets that can be analysed throughout the survey and archived at the end in such a way that they can be used by other data users well into the future. Data processing activities involved:
- Computing and merging in the sampling weights
- Reshaping datasets in order to produce data files for each unit of observation (households, household members, and businesses)
- Anonymising data by removing all variables that identify respondents such as names, address, GPS coordinates, etc.
- Classifying non-response and coding them using a pre-determined classification scheme
- Properly naming and labelling the variables in each dataset
Data Appraisal
Data Appraisal
The datasets were then sent to the analysis team where they were subjected to a second set of checking and cleaning activities. This included checking for out of range responses and inadmissible values not captured by the filters built into the CAPI software or the initial data checking process by the survey team. A comprehensive data checking and analysis system was created including a logical folder structure, the development of template syntax files (in Stata), to ensure data checking and cleaning activities were recorded, that all analysts used the same file and variable naming conventions, variable definitions, disaggregation variables and weighted estimates appropriately.
Access policy
Contacts
| Name | Affiliation | |
|---|---|---|
| Fred Merttens | Oxford Policy Management Ltd | [email protected] |
| Virginia Barberis | Oxford Policy Management Ltd | [email protected] |
Confidentiality
See https://microdata.worldbank.org/index.php/terms-of-use
Access conditions
The datasets have been anonymised and are available as a Public Use Dataset. They are accessible to all for statistical and research purposes only, under the following terms and conditions:
1. The data and other materials will not be redistributed or sold to other individuals, institutions, or organisations without the written agreement of Oxford Policy Management Ltd.
2. The data will be used for statistical and scientific research purposes only. They will be used solely for reporting of aggregated information, and not for investigation of specific individuals or organisations.
3. No attempt will be made to re-identify respondents, and no use will be made of the identity of any person or establishment discovered inadvertently. Any such discovery would immediately be reported to Oxford Policy Management Ltd.
4. No attempt will be made to produce links among datasets provided by Oxford Policy Management Ltd, or among data from Oxford Policy Management Ltd and other datasets that could identify individuals or organisations.
5. Any books, articles, conference papers, theses, dissertations, reports, or other publications that employ data obtained from Oxford Policy Management Ltd will cite the source of data in accordance with the Citation Requirement provided with each dataset.
6. An electronic copy of all reports and publications based on the requested data will be sent to Oxford Policy Management Ltd.
The original collector of the data and the funding agencies bear no responsibility for use of the data or for interpretations or inferences based upon such uses.
1. The data and other materials will not be redistributed or sold to other individuals, institutions, or organisations without the written agreement of Oxford Policy Management Ltd.
2. The data will be used for statistical and scientific research purposes only. They will be used solely for reporting of aggregated information, and not for investigation of specific individuals or organisations.
3. No attempt will be made to re-identify respondents, and no use will be made of the identity of any person or establishment discovered inadvertently. Any such discovery would immediately be reported to Oxford Policy Management Ltd.
4. No attempt will be made to produce links among datasets provided by Oxford Policy Management Ltd, or among data from Oxford Policy Management Ltd and other datasets that could identify individuals or organisations.
5. Any books, articles, conference papers, theses, dissertations, reports, or other publications that employ data obtained from Oxford Policy Management Ltd will cite the source of data in accordance with the Citation Requirement provided with each dataset.
6. An electronic copy of all reports and publications based on the requested data will be sent to Oxford Policy Management Ltd.
The original collector of the data and the funding agencies bear no responsibility for use of the data or for interpretations or inferences based upon such uses.
Citation requirements
Oxford Policy Management Limited. Kenya Hunger Safety Net Programme Phase 2 (HSNP2) Survey, 2016, Version 2.1 of the public use dataset (March 2020). Ref: Ken_2016_HSN-P2_v01_M. 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_KEN_2016_HSNPS_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 |
| Virginia Barberis | OCS | Oxford Policy Management Ltd. | Data analyst |
DDI Document version
KEN_2016_HSNPS_v01_EN_M_v01_A_OCS_v01