Copestake, James
(2023).
Impact assessment in complex contexts of rural livelihood transformations in Africa. Part 1- Longitudinal household income data.
[Data Collection]. Colchester, Essex:
UK Data Archive.
10.5255/UKDA-SN-852064
How can the impact of development activities intended to benefit poor men, women and children caught up in complex processes of rural transformation best be assessed?
The research set out to develop and evaluate a protocol for impact assessment based on self-reported attribution without the use of comparison groups as an alternative to experimental or quasi-experimental designs based on statistically inferred attribution.
The three year project, starting in September 2012, was led by James Copestake at the University of Bath, and conducted in collaboration with three NGOs - Self Help Africa, Farm Africa, and Evidence for Development. It was jointly funded by the UK Economic and Social Research Council (ESRC) and Department for International Development DFID. The research piloted the approach with four projects: two in Ethiopia and two in Malawi.
Strand 1 comprised a baseline and two rounds of annual monitoring of food security and income at the household level by NGO staff.
Strand 2 comprised two rounds of annual in-depth interviewing to elicit self-reported attribution from intended project beneficiaries.
All data collected from these strands is deposited with UK Data, with this entry comprising the data for Strand 1.
Data description (abstract)
The individual household method (IHM) was developed by Evidence for Development as a reliable, standardised method of collecting and using household income data that is suitable for operational use. IHM work involves both in-person data collection and the use of specialised analytical software, open-IHM, which can be used to manage complex household data and produce reports, models and predictions to inform policy-making.
This data set includes anonymised data from project areas Masumbankunda, Malawi; Karonga, Malawi; Tigray, Ethiopia; Assela, Ethiopia.
Please also see related file on Qualitative Impact Assessment (QUIP) data which includes some qualitative data collected from a sub-sample of the same households included in this study (only Round 2 files - Round 1 households were not from the same sample set).
| Data creators: |
| Creator Name |
Affiliation |
ORCID (as URL) |
| Copestake James |
University of Bath |
|
|
| Contributors: |
| Name |
Affiliation |
ORCID (as URL) |
| Allan Claire |
Farm Africa |
|
| Thomas Erin |
Gorta Self Help Africa |
|
| Ellis Wolf |
Evidence for Development |
|
| Petty Celia |
Evidence for Development |
|
|
| Sponsors: |
ESRC, Department for International Development(DFID)
|
| Grant reference: |
ES/J018090/1
|
| Topic classification: |
Natural environment
Social welfare policy and systems
Economics
Labour and employment
|
| Keywords: |
household income, rural development, malawi, ethiopia
|
| Project title: |
Impact assessment based on self-reported attribution in complex contexts of rural livelihood transformations in Africa.
|
| Alternative title: |
Longitudinal household income data for 4 rural livelihoods projects in Malawi and Ethiopia 2012-2015
|
| Grant holders: |
James Copestake
|
| Project dates: |
| From | To |
|---|
| 9 September 2012 | 8 September 2015 |
|
| Date published: |
04 Feb 2016 16:18
|
| Last modified: |
15 Dec 2023 11:45
|
| Collection period: |
| Date from: | Date to: |
|---|
| 10 September 2012 | 9 September 2015 |
|
| Geographical area: |
Masumbankunda, Malawi; Karonga, Malawi; Tigray, Ethiopia; Assela, Ethiopia. |
| Country: |
Ethiopia, Malawi |
| Spatial unit: |
No Spatial Unit |
| Data collection method: |
The individual household method has been developed by Evidence for Development to overcome problems with widely-used surveys and extend household economy methodology – notably the household economy approach (HEA) – to provide more detailed household-level analysis, as well as facilitating studies in both urban and rural areas. Whereas HEA studies collect information on ‘typical’ households from defined sections of the population through group interviews, the individual household method collects information on actual households directly from their members. This enables IHM studies to identify more complex variation across populations than is possible with the HEA and to model the impact of changes on a much wider range of population groups, with data disaggregated by demographics (gender and age), income levels and other chosen characteristics.
The individual household method differs from most other household budget surveys by collecting data through a semi-structured interview rather than a standard questionnaire format, as well as by using specialised software which allows data checking and analysis to be carried out in the field. These innovations reduce the risk of errors in data collection, and allow any errors that do occur to be identified and corrected early in the process. Rapid analysis can also provide up-to-date information needed by decision makers.
The first stage of IHM research is the identification of livelihood zones and selection of survey sites within the zone. After sampling decisions have been made and locations have been selected, contextual information on the local economy is collected from focus groups including women and men involved in different economic activities. This provides interviewers with data that can be used to cross-check responses from individual households.
Selected households are then interviewed, following a structure that is designed to include all relevant income sources and related details without unnecessary questions. The interview covers household demography, assets, crop and livestock production, employment (including day labour, petty trade, self-employment and salaried work undertaken by men, women and children in the household), wild foods and non-market transfers. Other personal or household characteristics relevant to the study (for example, the gender of the household head or the educational level of each member of the household) are also recorded during the interview. |
| Observation unit: |
Household |
| Kind of data: |
Numeric |
| Type of data: |
Cohort and longitudinal studies |
| Resource language: |
English |
|
| Data sourcing, processing and preparation: |
On the day of collection, interview data is entered into open-IHM software and checked for internal consistency, biological adequacy and disparities with observed living conditions. If anomalies are found or if any further information is needed the household is revisited, and where necessary datasets are amended. The software can then generate output that shows: (1) household budgets and food requirements; (2) incomes, disaggregated by source; (3) disposable incomes; (4) households above or below the locally-defined standard of living; (5) assets; (6) simulated effects of changes in price(s) or production.
Details on how to install and use the software are included with the dataset downloads.
|
| Rights owners: |
| Name |
Affiliation |
ORCID (as URL) |
| Copestake James |
University of Bath |
|
| Petty Celia |
Evidence for Development |
|
|
| Contact: |
| Name | Email | Affiliation | ORCID (as URL) |
|---|
| Copestake, James | j.g.copestake@bath.ac.uk | University of Bath | Unspecified | | Petty, Celia | celia.petty@evidencefordevelopment.org | Evidence for Development | Unspecified |
|
| Notes on access: |
The Data Collection is available for download to users registered with the UK Data Service.
|
| Publisher: |
UK Data Archive
|
| Last modified: |
15 Dec 2023 11:45
|
|
Available Files
Data and documentation bundle
Data
Documentation
Read me
Data collections
Software
Website
Edit item (login required)
 |
Edit Item |
