Impact assessment in complex contexts of rural livelihood transformations in Africa. Part 1- Longitudinal household income data

Impact assessment in complex contexts of rural livelihood transformations in Africa. Part 1- Longitudinal household income data

Abstract copyright data collection owner. 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).

Keywords:
household income,rural development,malawi,ethiopia,2016

Cite this dataset as:
Copestake, J., 2016. Impact assessment in complex contexts of rural livelihood transformations in Africa. Part 1- Longitudinal household income data. UK Data Service. https://doi.org/10.5255/UKDA-SN-852064.

Export

Creators

James Copestake
Rights Holder
University of Bath

Contributors

Claire Allan
Other

Erin Thomas
Other

Ellis Wolf
Other

Celia Petty
Other, Rights Holder

Coverage

Collection date(s):

From 10 September 2012 to 9 September 2015

Geographical coverage:

Masumbankunda, Malawi; Karonga, Malawi; Tigray, Ethiopia; Assela, Ethiopia.

Documentation

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.

Funders

Economic and Social Research Council (ESRC)
https://doi.org/10.13039/501100000269

Impact assessment based on self-reported attribution in complex contexts of rural livelihood transformations in Africa.
ES/J018090/1

Department for International Development
https://doi.org/10.13039/501100000278

Publication details

Publication date: 4 February 2016
by: UK Data Service

Version: 1

Original data publication URL: https://doi.org/10.5255/UKDA-SN-852064

DOI: https://doi.org/10.5255/UKDA-SN-852064

URL for this record: https://researchdata.bath.ac.uk/id/eprint/180

Contact information

Please contact the Research Data Service in the first instance for all matters concerning this item.

Contact person: James Copestake

Departments:

Faculty of Humanities & Social Sciences
Social & Policy Sciences