Technical Report
Effective Strategies for Reaching
the Poor
Poverty Targeting
Anton Simonowitz*
The commitment of the Microcredit
Summit a year ago to reach the worlds poorest families, has raised the
profile of poverty ? focussed microfinance as a poverty - alleviation tool.
The first step is obviously to establish who are “the poorest” which the
Summit usefully defined as those people in the bottom fifty percent of
the people, living below a country’s nationally defined poverty-line.
This target poses a challenge
for microfinance institutions (MFIs), to reach this target group, to demonstrate
that they have been reached, and to develop strategies to alleviate poverty
amongst this group.
The Small Enterprise Foundation
(SEF), workiing in the impoverished former homeland areas of the Northern
Province, South Africa, has long made a commitment to reaching the poorest.
Over time we have come to realise more and more that this is no easy task.
Challenges lie in three main areas:
-
effective targeting mechanisms
to ensure that a high number of the target group are reached;
-
developing effective support
mechanisms which provide savings and credit services within a framework
which develops the capacity of members to maintain sustainable businesses
;
-
developing impact monitoring
systems which provide a learning environment for all staff and members,
which can demonstrate the success or failure of the programe to alleviate
poverty.
SEF dose not have all the answers,
nor have we thought of many of the questions! However, we are actively
pursuing improvements in all of these areas, which we believe are the key
to realising the bold objective of the Summit.
SEF was set up as a poverty-alleviation program. One of the poorest areas
in the country was selected as the operational area, and a credit methodology
was designed which offered small loans through group-based lending , following
the theory that small loans and high transaction cost in terms of
time spent to enter the program and during meetings, would deter
all but the very poorest form joining.
In reality SEF found that the need for credit is so great that comparatively
wealthy people would join the program, and remain members for a long time
in the hope of larger future loans. Not only did this mean that we were
not just reaching the poor, but we found that membership of better off
members served as an active deterrent for the very poor, and the target
population was not being helped.
In response to this, the Tshomisano Program (TCP)1 was set up with the
mandate to develop an active targeting system which would allow identification
of the poorest people. TCP targets the poorest 30 percent of the population
of the province, which more or less corresponds to the bottom
fifty percent of those living below the poverty-line.
Work to develop a targeting system, drawing on the experience of Professor
Sukor Kasim with CASHPOR, resulted in the Visual Indicator of Poverty test
( VIP ). This involves field workers scoring the external conditions of
people’s houses according to a check list. Thus those people living in
houses constructed from mud bricks, with poor quality thatch roofing, small
windows and in a general state of disrepair, tend to be selected
as the poorest. Those with cement bricks, zinc roofing, larger windows,
a pit latrine and generally better constructed housing, do not qualify
to benefit from the program.
This system was operationalised and used for some years by the program.
However, reports of problems by field staff raised concerns.
These mostly centered on people who had been denied access to the program
despite obvious signs of poverty and the support of members of the community,
on the basis of their housing conditions. There were also reports of people
joining the programe who the field staff felt were not poor, but who qualified
on the basis of the VIP.
A pilot study was set up to compare Participatory Wealth Ranking (PWR)
with the VIP. PWR allows communities to rank themselves according to their
own perceptions of poverty. Detailed discussions are held with a large
number of people in each community to define poverty, and to rank the community
according to their criteria. A map is first drawn by a community group
and a household list is then generated from this, and the names written
on to individual cards. Reference groups are then set up to assess the
relative wealth of the households, by sorting the cards into piles with
the poorest in one pile, the next poorest in the next and so on. The results
are triangulated by using a minimum of three reference groups-consistency
between the groups verifying the results.
The comparison of the VIP with PWR demonstrated the inaccuracy of a system
based on static, externally judged criteria, when compared against local
judgment of poverty. Many instances were cited of people living in poverty,
whilst having reasonable housing conditions, constructed prior to the main
earner dying or deserting the family. In addition there are many people
who are living in poor quality housing, constructing new homes or having
their main home elsewhere who falsely qualified as amongst the poorest
under the VIP.
In comparing the VIP and PWR, the VIP was seen to be at best 70% consistent
with the PWR results (in some cases below 50%). Perhaps more worryingly,
however, was the inclusion of large numbers of households from the richest
segments of the community amongst those defined to be the poorest by the
VIP. In some cases one - third of the list of households defined as the
poorest by the VIP was actually made up of some of the richest in the community,
as determined through PWR.
These results convinced SEF of the need to operationalise PWR in place
of the VIP. The system has now been operationalised, with staff being trained
and assessed, and an operational manual produced.The method has proved
to be very reliable in terms of ranking households according to the criteria
considered important by the communities with which TCP works. Criteria
most commonly used to define poor households are : lack of food and shelter
; unemployment; lack of income ; large numbers of dependents; children
not attending school ; and lack of clothes.
The system is not yet perfect. There have been considerable challenges
faced in designing a cost-effective operational system based on participatory
mapping and wealth ranking, particularly given the size of the target villages
(commonly 3-4000 people). However, we believe that the method is effective
in identifying the poorest in a way which is transparent and acceptable
to the communities with which we work.
Case-Study: Wealth Ranking in Bhungeni
Faced with a village of
almost 5,000 people and eight field workers expecting to be trained in
PWR and to have the effectiveness of the method demonstrated to them, we
realized the challenge facing us in using the method in South Africa. Villages
are usually not tightly knit communities, but sprawling areas with several
hundred, if not thousand households, with high mobility and differentiation.
Wealth Ranking relies on people’s knowledge of each other - could this
apply in the South African context?
Mapping
We commenced the task by
mapping the village (on the floor of a church, using chalk). About 30 people
arrived for an introductory meeting. After some discussion it was agreed
that people should divide themselves into groups according to section.
Initially three sections were formed, and the participants easily grasped
the concept of mapping and began the task. Quickly it became apparent that
there were in fact 6 rather than 3 sections. Some sections were under-represented
in the meeting, and there was some difficulty in these sections in drawing
the map. Some participants, therefore, left to find people from the other
sections to join in. Obtaining good representation from all sections of
the village is critical to the successful mapping of a large village.
Mapping proceeded easily (and noisily), and within three hours we had mapped
and listed the names of 736 households. Importantly by generating six rather
than three sections, the number of households which had to be ranked per
section was more or less 100 (approximately the number of cards people
can sort before participants become).
Participants assisted with writing a list of household names, the facilitators
checking that these were the names commonly used, copying these names on
to cards, and making a copy of the map onto flip chart paper. The handing
over of these tasks to the participants is essential to enable the facilitators
to monitor and facilitate, rather than attempting to undertake three time-consuming
tasks in each section.
The mapping was a great success. There were no problems in identifying
and naming all the households. In one section for example, six people managed
to map and name 211 households. The map was compared with one previously
done by SEF under the VIP system and its accuracy was confirmed.
Further experience of mapping even larger village has shown that even 1000
households can be mapped and names listed in 2-3 hours, provided there
is good representation from all sections or the village.
Ranking
The next challenge was how
to rank the 736 households. Ranking involves discussing concepts of poverty
and wealth, so as to stimulate thinking and to gain a consensus for ranking.
The cards are then discussed in turn and thereby sorted into different
piles dependent on the wealth of the household. The ranking is repeated
for at least three different reference groups so as to ensure triangulation
and consistency of the results.
The process is time consuming and strenuous, and once people become tired,
the accuracy of the ranking is rapidly lost, therefore to attempt to sort
more than 100 cards (ideally much less) is problematic.
Division of the village into sections achieved part of the solution?however,
one section numbers over 200 households. The card sorting process, therefore,
had to be very carefully monitored so as to stop the process when participants
became tired. If a sorting was not completed, then unsorted cards are kept
separate and used as the first cards in the next reference group. In the
case of a very large section, the sections were divided into two for each
ranking and each half treated separately.
At the end of each session all cards were carefully mixed so as to ensure
that each reference group received a mixture of cards.
Achieving Consistency within the Village
There is a danger that dividing
up the village may make the results between sections not comparable. Consistency
between the sections is achieved by comparing information given during
the ranking, and taking notes of the information given is essential. Descriptions
of the characteristics of people in each ranking pile is the basis by which
comparisons can be made between sections of the village and between village.
In Bhungeni by comparing the information given in each section, it was
apparent that there were no significant differences in the criteria used
to rank the different sections and thus the results were comparable.
Using WR Results to Find a Cut off Point for Selecting
the Poor
Information defining the
different wealth levels is also useful for deciding the cut off point for
inclusion into the program. Rather than choosing an arbitrary point, decisions
can be made based on knowledge about poverty and the average ranking score
for people at different levels of poverty.
Tshomisano has used information given from a number of different rankings
to define common characteristics of the very poor?our target group. During
each ranking much information is given about why people are sorted into
each group and therefore, the common characteristics for each pile. By
using the generalized list it is possible to select those piles which correspond
to the target population, and the cut off point is drawn at this
level, rather than at a arbitrary point. During the ranking exercise, notes
are made for any household where the reference group has a long discussion
or has problem placing the card. These are usually the households where
there is inconsistency between rankings. The notes provide information
which allows for these households to be correctly placed.
Effective identification of the target group is the first step in reaching
the poorest. The transparency of the PWR process strengthens the commitment
of staff as they can see that they are working with the poorest. The process
also builds community support, and reduces the chances of dissatisfaction
in the community over the selection process.
The next step is to work with the poor in a way, which ensures the success
of the poorest. Too often the poorest are the most likely to fail and drop-out
from the programme. The challenges and SEF’s experiences of this are discussed
in my next article.
*Development Adviser,
The Small Enterprise Foundation, South Africa.
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