Impact Evaluation of the Lesotho Child Grants Programme and the Sustainable Poverty Reduction through Income, Nutrition and access to Government Services project
Lesotho, 2017 - 2018
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Reference ID
LSO_2017-2018_CGP-SPRINGS_v01_EN_M_v01_A_OCS
Producer(s)
Silvio Daidone, Noemi Pace, Ervin Prifti, Spatial Intelligence
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Metadata
Created on
Oct 14, 2020
Last modified
Oct 14, 2020
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Identification
Survey ID Number
LSO_2017-2018_CGP-SPRINGS_v01_EN_M_v01_A_OCS
Title
Impact Evaluation of the Lesotho Child Grants Programme and the Sustainable Poverty Reduction through Income, Nutrition and access to Government Services project
Country
| Name | Country code |
|---|---|
| Lesotho | LSO |
Study type
Other Household Survey [hh/oth]
Abstract
The datasets include a household survey, a non-farm business survey and a community survey which were collected between November 2017 and January 2018 to document the welfare and economic impacts of the Lesotho Child Grants Programme (CGP) and the Sustainable Poverty Reduction through Income, Nutrition and access to Government Services project (SPRINGS) on direct beneficiaries and the spillover effects in the local economies. The data look specifically at several CGP and SPRINGS outcome and output indicators, related to the following areas: consumption and poverty, dietary diversity and food security, income, agricultural inputs and assets, children well-being, financial inclusion, gardening and operational efficiency of both programmes.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
Households
Scope
Notes
The scope of the household survey includes:
- HOUSEHOLD ROSTER: socio-demographic characteristics, education (ever attended, currently attending, grade attending, educational expenses)
- CROP PRODUCTION: crops planted, area planted, crops harvested, harvest used for own-consumption, crops sold, crops sharecropped-out)
- HOMESTEAD GARDENING: vegetables planted and fruits grown, vegetables planting techniques, number of vegetables harvests, vegetables and fruits processed and processing techniques, vegetables and fruits sales
- LIVESTOCK PRODUCTION: type and number of livestock owned, purchased, sold, value of purchases and sales, sales of livestock by-products
- AGRICULTURAL INPUTS: type of crops/livestock input used/owned/ rented/borrowed/used for free, and value of purchases and rentals
- NON-FARM ENTERPRISES: type of non-farm business, number of employees, wages paid, input expenses, including from local businesses, sales and value of assets
- FAMILY LABOUR AND TIME USE: type of wage labour (formal/casual), intensity of labour and wage received, time spent farming/herding livestock/ engaged in non-farm business/doing chores/ participating in social meetings and gatherings, child labour hazards
- PUBLIC TRANSFERS: type of public programme and value received
- FOOD CONSUMPTION: type of food eaten in the last 7 days and value (74 items)
- NON-FOOD CONSUMPTION: type of consumption in the last 7 days (frequent items) and in the last 3 months (non-frequent items)
- PURCHASE LOCATION: location of the market transaction
- CHILDREN FEEDING PRACTICES: young children feeding practices module, following WHO and UNICEF guidelines
- WOMEN DIETARY DIVERSITY: minimum dietary diversity for women module, following FAO guidelines
- FOOD SECURITY: Food Insecurity Experience Scale module, following FAO guidelines
- HEALTH: type of health care provider consulted in the last three months and expenditures
- SAVINGS AND LENDING: type of saving, amount saved, frequency of savings, use of money saved, purchase on credit and amount, type of loans, amount borrowed and outstanding amount, use of the amount borrowed
- FINANCIAL LITERACY: budget keeping, concept of interest rate
- RISK ATTITUDES: general willingness to take risk, willingness to take risk in agriculture and risk-taking in borrowing and investment on a 1-10 likert scale, choice of lotteries with a certain equivalent and a risky game
- HOUSING AND WEALTH: housing conditions (floor, walls, roof, toilet), type of occupancy, access to electricity, ownership of durables
- DECISION-MAKING: one woman and one man responding to decision-making in the household
- ASPIRATIONS AND EXPECTATIONS: Cantrill's ladder of life in two and five years, expectations about income, locus of control via Internality, Powerful Others and Chance scale by Levenson
- ANTHROPOMETRICS: height, weight, mid-upper arm circumference
- CGP OPERATIONAL PERFORMANCE: CGP payment collection, type of payment, instructions abut CGP use
- SPRINGS OPERATIONAL PERFORMANCE: engagement, training activities and perceptions concerning: a) savings groups; b) homestead gardening; c) nutrition training; d) market clubs; e) One-Stop/Shop Citizen days
The scope of the community survey includes:
- KEY INFORMANT CHARACTERISTICS: gender, age, role in the community
- CIVIL INFRASTRUCTURE: number of villages in the community, access by road, walking distance between chief house and main road, quality of main road, name of nearest town
- WAGES AND AGRICULTURAL PRICES: wage for adult men doing casual labour in crop and livestock production, wage for adult women doing casual labor in crop production and domestic work, wage for adolescents doing casual labour, cost of renting tractor or a plough, cost of basal and top-dressing fertilizer
- RETAIL PRICES: retail prices of food and non-food items
- HEALTH SERVICES PROVISION: type of service provider, location, use by community members, availability of medicines, HIV testing and ARV
- SCHOOL SERVICES PROVISION: type of service provider, location, use by community members, availability of meals, fees charged
- PUBLIC PROGRAMMES: availability of pubblic programmers and type of services/goods offered
The scope of the non-farm business survey includes: type of non-farm business, number of employees, wages paid, input expenses, including from local businesses, sales and value of assets
- HOUSEHOLD ROSTER: socio-demographic characteristics, education (ever attended, currently attending, grade attending, educational expenses)
- CROP PRODUCTION: crops planted, area planted, crops harvested, harvest used for own-consumption, crops sold, crops sharecropped-out)
- HOMESTEAD GARDENING: vegetables planted and fruits grown, vegetables planting techniques, number of vegetables harvests, vegetables and fruits processed and processing techniques, vegetables and fruits sales
- LIVESTOCK PRODUCTION: type and number of livestock owned, purchased, sold, value of purchases and sales, sales of livestock by-products
- AGRICULTURAL INPUTS: type of crops/livestock input used/owned/ rented/borrowed/used for free, and value of purchases and rentals
- NON-FARM ENTERPRISES: type of non-farm business, number of employees, wages paid, input expenses, including from local businesses, sales and value of assets
- FAMILY LABOUR AND TIME USE: type of wage labour (formal/casual), intensity of labour and wage received, time spent farming/herding livestock/ engaged in non-farm business/doing chores/ participating in social meetings and gatherings, child labour hazards
- PUBLIC TRANSFERS: type of public programme and value received
- FOOD CONSUMPTION: type of food eaten in the last 7 days and value (74 items)
- NON-FOOD CONSUMPTION: type of consumption in the last 7 days (frequent items) and in the last 3 months (non-frequent items)
- PURCHASE LOCATION: location of the market transaction
- CHILDREN FEEDING PRACTICES: young children feeding practices module, following WHO and UNICEF guidelines
- WOMEN DIETARY DIVERSITY: minimum dietary diversity for women module, following FAO guidelines
- FOOD SECURITY: Food Insecurity Experience Scale module, following FAO guidelines
- HEALTH: type of health care provider consulted in the last three months and expenditures
- SAVINGS AND LENDING: type of saving, amount saved, frequency of savings, use of money saved, purchase on credit and amount, type of loans, amount borrowed and outstanding amount, use of the amount borrowed
- FINANCIAL LITERACY: budget keeping, concept of interest rate
- RISK ATTITUDES: general willingness to take risk, willingness to take risk in agriculture and risk-taking in borrowing and investment on a 1-10 likert scale, choice of lotteries with a certain equivalent and a risky game
- HOUSING AND WEALTH: housing conditions (floor, walls, roof, toilet), type of occupancy, access to electricity, ownership of durables
- DECISION-MAKING: one woman and one man responding to decision-making in the household
- ASPIRATIONS AND EXPECTATIONS: Cantrill's ladder of life in two and five years, expectations about income, locus of control via Internality, Powerful Others and Chance scale by Levenson
- ANTHROPOMETRICS: height, weight, mid-upper arm circumference
- CGP OPERATIONAL PERFORMANCE: CGP payment collection, type of payment, instructions abut CGP use
- SPRINGS OPERATIONAL PERFORMANCE: engagement, training activities and perceptions concerning: a) savings groups; b) homestead gardening; c) nutrition training; d) market clubs; e) One-Stop/Shop Citizen days
The scope of the community survey includes:
- KEY INFORMANT CHARACTERISTICS: gender, age, role in the community
- CIVIL INFRASTRUCTURE: number of villages in the community, access by road, walking distance between chief house and main road, quality of main road, name of nearest town
- WAGES AND AGRICULTURAL PRICES: wage for adult men doing casual labour in crop and livestock production, wage for adult women doing casual labor in crop production and domestic work, wage for adolescents doing casual labour, cost of renting tractor or a plough, cost of basal and top-dressing fertilizer
- RETAIL PRICES: retail prices of food and non-food items
- HEALTH SERVICES PROVISION: type of service provider, location, use by community members, availability of medicines, HIV testing and ARV
- SCHOOL SERVICES PROVISION: type of service provider, location, use by community members, availability of meals, fees charged
- PUBLIC PROGRAMMES: availability of pubblic programmers and type of services/goods offered
The scope of the non-farm business survey includes: type of non-farm business, number of employees, wages paid, input expenses, including from local businesses, sales and value of assets
Coverage
Geographic Coverage
Village Coverage.
Producers and sponsors
Primary investigators
| Name | Affiliation |
|---|---|
| Silvio Daidone | FAO |
| Noemi Pace | FAO |
| Ervin Prifti | FAO |
| Spatial Intelligence |
Producers
| Name | Role |
|---|---|
| Spatial Intelligence | Data collection and data processing |
| United Nations International Children's Fund | Collaboration |
| Ministry of Social Development | Collaboration |
Funding Agency/Sponsor
| Name | Abbreviation | Role |
|---|---|---|
| Food and Agriculture Organization | FAO | Funding |
Sampling
Sampling Procedure
The impact evaluation design of the CGP and SPRINGS programmes consists of a post-intervention only non-equivalent control group study. Since neither randomization nor regression discontinuity were possible, a propensity score matching (PSM) approach was the only feasible option for the evaluation. To improve the comparability between the households groups, the evaluation team used the National Information System for Social Assistance (NISSA) registry data to match households with and without CGP based on their socio-demographic characteristics.
Before implementing this procedure, the evaluation team took the following decisions concerning the list of households in NISSA to be included in the PSM analysis:
1. Including only households having at least one household member below 18 years of age
2. Including households residing in one of the six districts of Berea, Butha-Buthe, Leribe, Mafeteng, Maseru, Mohale's Hoek.
3. For the comparison group they considered only households living in villages without either CGP or SPRINGS
4. Excluding households living in community councils where CGP had been implemented for more than seven years and less than four years.
The objective of the first condition was to target the same typology of households, i.e. those eligible for the CGP. The second condition aimed to limit the extent of the fieldwork to similar agro-ecological areas, while the third condition was needed to minimize the extent of spillovers, which could lead to bias in impact estimates. Finally, the fourth condition aimed to make households as comparable as possible in terms of CGP receipt at community level.
Overall, the service provider surveyed 2014 households, 1550 of whom were eligible for the CGP (8212 individuals), while 464 were not (2106 individuals). The former group is used to analyze the impacts of CGP and SPRINGS on programme beneficiaries, while the full set of 2014 households is used for a spillover analysis. Among the eligible households interviewed by the service provider, 1343 were targeted by the PSM analysis, while the remaining 207 households were on the list of potential substitutes provided among those with similar propensity scores (13.35 percent replacement rate).
Before implementing this procedure, the evaluation team took the following decisions concerning the list of households in NISSA to be included in the PSM analysis:
1. Including only households having at least one household member below 18 years of age
2. Including households residing in one of the six districts of Berea, Butha-Buthe, Leribe, Mafeteng, Maseru, Mohale's Hoek.
3. For the comparison group they considered only households living in villages without either CGP or SPRINGS
4. Excluding households living in community councils where CGP had been implemented for more than seven years and less than four years.
The objective of the first condition was to target the same typology of households, i.e. those eligible for the CGP. The second condition aimed to limit the extent of the fieldwork to similar agro-ecological areas, while the third condition was needed to minimize the extent of spillovers, which could lead to bias in impact estimates. Finally, the fourth condition aimed to make households as comparable as possible in terms of CGP receipt at community level.
Overall, the service provider surveyed 2014 households, 1550 of whom were eligible for the CGP (8212 individuals), while 464 were not (2106 individuals). The former group is used to analyze the impacts of CGP and SPRINGS on programme beneficiaries, while the full set of 2014 households is used for a spillover analysis. Among the eligible households interviewed by the service provider, 1343 were targeted by the PSM analysis, while the remaining 207 households were on the list of potential substitutes provided among those with similar propensity scores (13.35 percent replacement rate).
Data Collection
Dates of Data Collection
| Start | End |
|---|---|
| 2017-11-15 | 2018-01-18 |
Data Collection Mode
Computer Assisted Personal Interview [capi]
Data Collectors
| Name | Abbreviation |
|---|---|
| Spatial Intelligence | SiQ |
Data Processing
Data Editing
Data was cleaned and edited by the data provider. The datasets were made anonymous, by removing sensitive fields, such as names and surnames, GPS coordinates, village names, to avoid identification of respondents.
Other Processing
Anonymization of the datasets was conducted by the Office of Chief Statistician, using various Statistical Disclosure Control (SDC) methods.
All direct identifiers have been removed from the dataset. Additionally, labels have been removed from the electoral district variable. Household member age in years and months have been recoded into 13 and 7 intervals, respectively. The relationship to the household head was recoded into six categories, and enterprise codes were recoded into five categories. For the household-level data, local suppressions were applied, which resulted in the suppression of 3 records for age, 9 for community council and electoral district, 7 records for the relationship to household head, 22 for the highest level of education, 2 records for debt ID, and 36 for monetary transfers. At the farm level, local suppression was applied to crops, livestock and farm inputs, resulting in the suppression of 2.6%, 0.85%, and 0.6% records, respectively.
For the community dataset, we also re-coded age into the 13 intervals, and suppressed one value for the electoral district. Finally, for the business dataset, we also recode enterprise codes into the same six categories as in the household dataset.
All direct identifiers have been removed from the dataset. Additionally, labels have been removed from the electoral district variable. Household member age in years and months have been recoded into 13 and 7 intervals, respectively. The relationship to the household head was recoded into six categories, and enterprise codes were recoded into five categories. For the household-level data, local suppressions were applied, which resulted in the suppression of 3 records for age, 9 for community council and electoral district, 7 records for the relationship to household head, 22 for the highest level of education, 2 records for debt ID, and 36 for monetary transfers. At the farm level, local suppression was applied to crops, livestock and farm inputs, resulting in the suppression of 2.6%, 0.85%, and 0.6% records, respectively.
For the community dataset, we also re-coded age into the 13 intervals, and suppressed one value for the electoral district. Finally, for the business dataset, we also recode enterprise codes into the same six categories as in the household dataset.
Access policy
Contacts
| Name | Affiliation | |
|---|---|---|
| Silvio Daidone | FAO | [email protected] |
| Noemi Pace | FAO | [email protected] |
| Ervin Prifti | FAO | [email protected] |
Confidentiality
The users shall not take any action with the purpose of identifying any individual entity (i.e. person, household, enterprise, etc.) in the micro dataset(s). If such a disclosure is made inadvertently, no use will be made of the information, and it will be reported immediately to FAO
Access conditions
Micro datasets disseminated by FAO shall only be allowed for research and statistical purposes. Any user which requests access working for a commercial company will not be granted access to any micro dataset regardless of their specified purpose. Users requesting access to any datasets must agree to the following minimal conditions:
- The micro dataset will only be used for statistical and/or research purposes;
- Any results derived from the micro dataset will be used solely for reporting aggregated information, and not for any specific individual entities or data subjects;
- The users shall not take any action with the purpose of identifying any individual entity (i.e. person, household, enterprise, etc.) in the micro dataset(s). If such a disclosure is made inadvertently, no use will be made of the information, and it will be reported immediately to FAO;
- The micro dataset cannot be re-disseminated by users or shared with anyone other than the individuals that are granted access to the micro dataset by FAO.
- The micro dataset will only be used for statistical and/or research purposes;
- Any results derived from the micro dataset will be used solely for reporting aggregated information, and not for any specific individual entities or data subjects;
- The users shall not take any action with the purpose of identifying any individual entity (i.e. person, household, enterprise, etc.) in the micro dataset(s). If such a disclosure is made inadvertently, no use will be made of the information, and it will be reported immediately to FAO;
- The micro dataset cannot be re-disseminated by users or shared with anyone other than the individuals that are granted access to the micro dataset by FAO.
Citation requirements
Silvio Daidone, Food and Agriculture Organization of the United Nations; Noemi Pace, Food and Agriculture Organization of the United Nations; Ervin Prifti, Food and Agriculture Organization of the United Nations. Lesotho Child Grants Programme and the Sustainable Poverty Reduction through Income, Nutrition and access to Government Services project - Impact Evaluation Survey 2018. Ref. LSO_2018_CGPSPRINGS. 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_LSO_2017-2018_CGP-SPRINGS_v01_EN_M_v01_A_OCS_FAO
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Office of Chief Statistician | OCS | Food and Agriculture Organization | Metadata adapted for FAM |
| Silvio Daidone | Food and Agriculture Organization | Metadata producer |
DDI Document version
LSO_2017-2018_CGP-SPRINGS_v01_EN_M_v01_A_OCS_v01