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Enhancing existing systems to provide detailed analysis for national cash transfer programs, aiming to lift households out of poverty and improve livelihoods through strategic planning and data collection.
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Strengthening existing information systems to provide improved analysis to support the design of cash transfer programmes John Seaman Evidence for Development
Planning a large scale e.g. national, CT programme will require information to estimate the resources required to reach a stated objective: • The number of poor/ eligible households and people. • The severity of poverty, however this is defined. • Variation in the rate and severity of poverty between years e.g. with variation in crop production. + information to define appropriate, practical targeting criteria i.e. the relationship between household poverty, and household/ personal characteristics. (+ market information)
The information needed to plan a large cash transfer (CT) programme will depend on the programme objective Possible objectives include: • the relief of destitution and/ or assisting specific groups e.g. the very poorest households, the elderly, the ill. • poverty reduction e.g. to bring all households up to a defined standard of living. • giving households sufficient money to allow them to invest and save, to increase their income and security in the long-term.
The difficulty in getting this information will vary with the objective: CT targeted at the poorest 10% of the population, or specific easily identified groups e.g. the elderly could be planned on the basis of a reasonably reliable census. More ambitious objectives will require much more information i.e. • The number of poor/ eligible households and people; the severity of poverty; variation in the rate and severity of poverty between years + targeting information + market information Information on poverty is not currently available in most poorer African countries. National Household budget/ income/ expenditure surveys are infrequently updated, usually not available and there are serious questions about data quality.
The household economy approach (HEA) is a possible source of information: • HEA is cheap to use, has relatively low skill requirements and is defensibly accurate. • Some national data sets already exist. However: HEA provides ‘averaged’ information on income and household characteristics and this is not sufficient to meet the requirements for planning CT.
HEA, Zambezi West Bank, Zambia Sources of food (% requirement) by wealth group Sources of cash income (ZK) by wealth group + assets & contextual information e.g. on market use. Data: Household economy profiles. FEWSNET/FEG
Good quality household income/ expenditure data can also be obtained on small samples of households...
Salima, Malawi, one village, cash income/ adult equivalent after household food energy needs met.
A pilot was recently conducted tested in Zambia * to test a proposed method which would: • retain the practical advantages of HEA i.e. low cost, ease of use on large geographical areas. • while extending the range of information obtained to include that required for CT planning. * Supported by RHVP/DfID & CARE
The proposed method (‘HEA+’) • an additional ‘very poor’ wealth group is added to the HEA data set. This should allow an approximation of the shape of the complete wealth distribution. • Assuming that individual households can be placed (by village informants) in their correct HEA wealth group: additional information can be obtained from individual households within each wealth group by rapid interview e.g. on demography, assets, illness.
HEA 10% Percent in wealth group 30% 60% Income/MK Person/year Poor Middle Better-off
D B C A The ‘very poorest’ wealth group
HEA + HEA+ Model Additional wealth groups allow an approximation of the complete income distribution
The pilot study Two parallel surveys were conducted in the same village. • Using HEA, with the addition of a ‘very poorest’ wealth group. • Information on individual household income was gathered from every household. i.e. the study used two independent methods to estimate household income in the same reference period (February 2005 – March 2006)
What can HEA+ do? Area (+ census) gives cost of increasing income to SOLT or other threshold Modelled income change e.g. following crop failure, price change HH characteristics within wealth group e.g. number of elderly etc