EVALUATING THE IMPACT OF COMMUNITY LED TOTAL
SANITATION PROGRAMS IN MALI – Baseline Analysis
VERY PRELIMINARY DRAFT - DO NOT CIRCULATE WITHOUT AUTHORS’ PERMISSION
INDEX
I Executive Summary
II The intervention
III The evaluation
IV Methodology
1. Sampling framework
2. Power calculations conducted ex-ante
3. Random allocation
V Implementation of CLTS
VI Baseline Survey
1. Community Survey
2. Household survey
3. Water, sanitation, and hygiene results from the baseline survey
a. Access to sanitation
b. Access to drinking water
4. Child health
1
5. Experimental Games on Cooperation
Appendix 1: Balance of pre-treatment covariates
Appendix 2: Baseline Information
Executive Summary
Behavioral change is a key ingredient for successful adoption of better sanitation practices in rural
Africa. Sanitation programs have, for some time now, incorporated the need to raise awareness
and emphasize the benefits of toilet usage. These endeavors, often combined with subsidies
linked to toilet construction by households, seek to create a demand for sanitation goods. Yet,
progress in securing the desired outcomes from sanitation programs has been slow. Moreover,
benefits of sanitation largely take the form of externalities, which individuals do not take into
account when making their own decisions about investments. This makes sanitation promotion at
the household level particularly challenging.
It is in this background that an approach adopted in South Asia has drawn attention. At the heart
of this approach is a shift away from the provision of subsidies for toilets to individual households
and a promotion of behavioral change at individual-level towards emphasizing collective decisionmaking in order to produce 'open defecation-free' villages. The objective of the intervention is to
reduce the incidence of diseases related to poor sanitation and manage public risks posed by the
failure to safely confine the excreta of some community members. The way to achieve this
objective is by empowering communities motivated to take collective action. Local governments
and other agencies perform at best a facilitating role. There is a growing recognition that this
approach, referred to as Community-Led Total Sanitation (CLTS), may help with the reduction of
open defecation practices. However, no rigorous impact evaluation of CLTS has been conducted so
far. This study presents the results of the baseline analysis of a randomized controlled trial for
studying the effect of CLTS in rural Mali. As a result, sound evidence will become available to see
to what extent CLTS improves health outcomes and what is driving collective action in order to
increase sanitation coverage.
The direct recipients of the intervention are members of rural communities in Mali who aspire to
live in a cleaner environment. The donor community, international organizations, and
governments in developing countries will benefit from having simple and clear evidence on the
effectiveness of an innovative program for improving sanitation in rural areas. They will learn
whether the program has worked or failed to achieve its objective of eradicating open defecation,
and about key factors explaining success and failure. This evaluation aims to provide useful
information to help guide decisions on how to help meet the MDG sanitation target.
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The intervention
The intervention works in the following manner1: communities are facilitated (by means of
government and NGOs staff) to conduct their own appraisal and analysis of open defecation
(OD) and take their own action to become ODF. At the heart of CLTS lies the recognition that
merely providing toilets does not guarantee their use, nor results in improved sanitation and
hygiene. Earlier approaches to sanitation prescribed high initial standards and offered subsidies
as an incentive. But this often led to uneven adoption, problems with long-term sustainability
and only partial use. It also created a culture of dependence on subsidies. Open defecation and
the cycle of fecal–oral contamination continued to spread disease in spite of such subsidies.
In contrast, CLTS supporters focus on the behavioral change needed to facilitate real and
sustainable improvements – investing in community mobilization instead of hardware, and
shifting the focus from toilet construction for individual households to the creation of “open
defecation-free” villages. By raising awareness that as long as even a minority of people in the
village continue to defecate in the open everyone is at risk of disease, CLTS aims to trigger the
community’s desire for change, propel them into action and encourage innovation, mutual
support and appropriate local solutions, in order to foster greater ownership and sustainability.
The main goal of CLTS is to obtain ODF villages. Even if CLTS does not completely eliminate OD,
positive effects on health and behavioral outcomes can be expected in participating
communities2. Providing sound quantitative evidence of CLTS's claims is the main objective of
the proposal. So far, evidence on the success of CLTS has not been based on rigorous impact
analysis studies. CLTS was introduced in West Africa through a Sub-Regional Workshop
implemented in November 2008. A workshop was implemented soon after in Mali. It gathered
60 participants from main national agencies (Environment & Sanitation, Health, Water Supply),
main National NGO networks (traditional communicators, community health, women
associations, etc.) and INGOs. As part of the workshop, the full triggering process was
implemented in 15 villages (CLTS pilot). This workshop was an effective demonstration on the
feasibility of CLTS in Mali.
By mid-June 2009, the 15 pilot villages became fully ODF, raising the proportion of families
equipped with latrines from 30% on average to 100%. Therefore, around 14,000 people gained
access to improved sanitation and acquired safe hygiene practices. In Mali, the Open Defecation
Free (ODF) status has been defined as follows: “each family has a latrine equipped with a cover
that limits the proliferation of flies from the pits; all members of the family exclusively use such
latrine to defecate; each latrine is equipped with a hand washing device (water + soap / water +
ash bucket)”.
1
For a detailed information on program description, see Box 1.
A community is considered to be participating in CLTS as soon as it agrees to meet with the program's facilitators. Then
the community will go through all the stages of the program with the possibility of be certified ODF at the end of the
process. Certification is six months after the beginning of the program. UNICEF pilot study in 261 communities in Africa
showed 90% success rate in achieving ODF and the end of the six-month period.
2
3
The evaluation study described in this proposal involves 120 communities in the Region of
Koulikoro.
Box 1: Program Description
Open Defecation (OD) is still practiced by 28% of the population in rural areas in Mali,
contaminating water sources and food and rapidly spreading diseases. Community Led Total
Sanitation (CLTS) is an innovative methodology for mobilizing communities to completely
eliminate open defecation (OD).
The intervention works in the following manner:
Step 1 (pre-triggering): a group of trained-CLTS people visit the community and request a date to
discuss sanitation-related issues for the following days. Care is taken so that no other major
manifestations are planned on that day to ensure the availability of a large number of
community members.
Step 2 (triggering): Three to four facilitators meet with the community on a convened day. The
visit may last anything between 3 to 5 hours. People are made to express their views on
sanitation issues and their needs. In general, the discussion is led by three to four persons who
talk for the community. When open defecation is identified as an issue, facilitators encourage
the community to make a map of the ODA (open defecation areas). Facilitators help them to get
an estimate of the quantity of human excrement produced each year. They also guide them in
assessing out-of-pocket yearly expenditures. Village leaders are also asked to take the
facilitators to visit the ODA. Facilitators show them how contamination to food and water occurs
by air contact / hand contact / via flies. Other activities may be planned with the objective to
help the community to become aware of the extent of the sanitation problem and trigger a
response. Making open defecation salient, providing information on contamination and letting
people become aware of the extent of the issue are all means employed to trigger behavioral
responses. Facilitators make an example of the first person that commits to build/use a latrine
and encourage others to follow. Commitments are written down and a timeframe for
building/repairing latrines is also set. Facilitators encourage community members to specify the
type of latrines. Usually, the whole session is videotaped.
Step 3 (monitoring): A local team is hired to conduct the monitoring (often comprising the
facilitators from the triggering phase). Monitoring involves visits of the community twice a week
for a period of 1-3 months. During these visits, the team talks to the village leaders, visits
households who are supposed to be building latrines, provides reminders to those who forgot,
congratulates those who did, update the community map of ODA, provides support to the
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community members regarding construction materials, organizes children’s gathering and
singing of slogans, informs the community about progress in other villages. The local monitoring
team often request community leaders to accompany them during their tours of the locality.
Radio journalist or other media people, as well as the Mayor or his representative, are also
sometimes invited during the monitoring visits as a mean to increase external pressure to
respect commitments. Each week a report is sent to the CLTS project manager with indicators of
monitoring. A household is considered to have attained the objective of CLTS if a latrine is built
and used by every household member, if the latrine is equipped with a cover that limits the
proliferation of flies from the pits, and if the latrine has some soap/water or ash/water to clean
hands.
Step 4 (certification): At the end of the monitoring phase, the Mayor or his representative, the
District Chief of Health or his representative, the Regional Director for Sanitation or his
representative form an external committee whose mission is to evaluate the village for
certification as an Open Defecation Free (ODF) community. , the Open Defecation Free (ODF)
status has been defined as follows: each family must have a latrine equipped with a cover that
limits the proliferation of flies from the pits; all members of the family exclusively use such
latrine to defecate; each latrine is equipped with a hand washing device (water + soap / water +
ash bucket)”. Certification is the occasion for a big ceremony, with a sign erected recognizing the
community as ODF. This is organized as a highly visible event with much media coverage and
important persons invited to attend.
To summarize, under a CLTS intervention, communities are facilitated (by means of government
and NGOs staff) to conduct their own appraisal and analysis of open defecation and take their
own actions to become ODF. By raising awareness that as long as even a minority continues to
defecate in the open everyone is at risk of disease, CLTS triggers the community’s desire for
change, propels them into action and encourages innovation, mutual support and appropriate
local solutions, thus leading to greater ownership and sustainability.
Program design
How CLTS programs in other parts of the world were designed as well as in-depth contextual
knowledge of rural regions of Mali have helped UINCEF design the CLTS program for Mali.
UNICEF is thus in charge of providing information on the intervention, providing training for local
capacity to implement CLTS and help with the overall organization of operations.
Implementation design
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Implementers are trained individuals who are responsible for the triggering and/or the
monitoring phases. They include:
- civil servants (from various sectors: sanitation, health, social services, local)
- national NGO (réseau des communicateurs traditionnelles, confédération des associations
féminines and fédération des associations de santé communautaires) and international NGO
(SNV, Plan international- Mali, Action contre la faim).
In 2009, about 60 people were trained during a national-level workshop. These training sessions
are practical and often include training on pilot sites.
Targeting of CLTS
CLTS is a community-level intervention, so that all community members in selected localities are
targeted. In each district, the intervention starts with a cluster of 15 of the most insalubrious
villages (e.g., those where less than half of the population has access to a latrine). To be eligible,
these villages or peri-urban localities must have more than 450 inhabitants, sufficiently clustered
housing and an open defecation problem. Once the intervention is completed in the first 15
villages of a district, it spreads to neighboring villages with the support of the most motivated
community leaders from the initial group.
The evaluation
The current project comprises an impact evaluation of CLTS in rural Mali. For this evaluation, we
have identified important outcomes that may be affected by CLTS and designed a study to
evaluate the impact of CLTS on these outcomes of interest. They include the following:
1) Psychological outcomes: knowledge, risk perceptions, self efficacy;
2) Community outcomes: level of cooperation, level of trust, social cohesion, wealth
disparities, leadership, speed of diffusion of the new practice of latrine use within social
networks;
3) Intermediary sanitary outcomes: building latrines, quality of latrines built (door, roof,
concrete slab), use of latrines (smell, presence of feces, worn-off path to latrines), building
of hand washing stations (presence of soap and water), hand hygiene behavior (presence
of dirt on women’s hands, sampling bacteria on hands), water quality (testing for
bacteriological content), quantity of flies, outdoors presence of fresh feces;
4) Final sanitary outcome: community status towards becoming ODF (“open-defecation
free”);
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5) Health outcomes: diarrheal illness for children under 2 and under 5, child
anthropometrics, self-reported health status by household members, reports on
community health by traditional healers and health clinic staff, health expenditures,
burden of care, out-of-pocket health expenditures;
6) Non-health outcomes: school attendance, time use, women's safety.
We will give careful attention to the question of sustainability the intervention: even if
communities achieve ODF status at the end of the short intervention, on average in six
months, whether these benefits persist over time, i.e. whether ODF status is maintained one
year after the intervention is an important question to investigate.
We will also examine the cost effectiveness of the intervention: UNICEF claims the
intervention is very cheap, but heavy monitoring is needed. We will conduct a thorough analysis of
the cost of the intervention.
Finally, we intend to look at the scalability of CLTS: how easy would it be to scale up this
intervention?
Methodology
This evaluation study will rely on quantitative and qualitative methods. To estimate the causal
effect of CLTS we need to construct a valid counterfactual in order to calculate what would have
happened in the absence of the intervention. The gold standard approach is one based on
random assignment of the intervention. We plan to conduct a random assignment at the
community level in order to test impact on some of the outcomes mentioned above. The other
approach is meant to help understand why the intervention works or fails to work. We will
conduct a thorough evaluation of the operations of the program as implemented in the study
communities, as well as qualitative in-depth analysis of potential threats to maintaining the ODF
status after the intervention has ended.
Random allocation ensures that on average, treated and untreated communities share the same
observables and unobservables. Random assignment to treatment also overcomes the main
selection problem found in evaluations, where those who are selected to receive the program
may have different attributes than those who were not selected in the first place. These
differences can be caused by observable attributes, more wealthy communities, more engaged
leaders, better weather, etc, may be more willing to engage in CLTS programs, or by
unobservable dimensions too. What is more important is that such differences can be affecting
the outcomes we want to measure. Comparing these two different groups will confound the
program impact with differences in observable and unobservable attributes. Random
assignment to the program eliminates selection bias because it ensures that on average,
communities receiving the program are similar to the ones that do not receive it.
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Although random assignment is at the community level, the basic units of analysis of this
evaluation are households. There we will split the intended outcomes in outcomes observed on
children and outcomes observed on adults. We are interested in health outcomes for children
under two and under five, given the fact that diarrhea is among the main causes of child
mortality and CLTS aims to positively impact such indicator. Also, we are interested at looking at
morbidity and school attendance for school age children. Finally, improved sanitation is
supposed to produce a redistribution in the use of time at the household level. To assess
impacts of time use, we will study time allocation of adults and children after the intervention.
Another very relevant question is whether, as argued by defenders of CLTS (Kar and Chambers,
2008, among many others), CLTS intervention provides a higher satisfaction than interventions
granting government subsidies to build toilets or latrines. Unfortunately, the program does not
comprise different interventions (subsidies vs. CLTS for example), so we will inquire about head
of household perceptions about both potential intervention both in treatment and control
communities.
Conservative power calculations were calibrated in order to at least detect a 10% decrease in
diarrhea incidence among 2-years old children. UNICEF has observed that migration is relatively
low in areas where the program has already been implemented, so we do not expect much
attrition. This decrease in diarrhea can be expected even if the village does not become fully
ODF, but take up levels are lower. Ninety percent of the communities that have participated in
the program were certified ODF by Unicef.
As explained in more detail in the data collection section below, the evaluation comprises
gathering data at three different points in time: a) baseline, before program implementation, b)
first (reduced) administrative follow up: immediately after the intervention finishes, c) full follow
up 12 months after program implementation in order to assess longer-term effects and
sustainability. We would be able to gather panel data at the community and at the household
level. Also, there will be a series of random visits to collect other information at different points
in time: these visits will be used to supplement information on health, school attendance, latrine
usage and water quality.
While random assignment allows comparing average outcomes across communities, we would
also perform multivariate regression analysis in order to improve the precision of our estimates
and control for any potential pre-treatment differences. Panel data allows us to use a difference
in difference design and also to include initial (before the intervention) characteristics of
households and communities. Standard errors will be clustered at the community level, and
compared to block-bootstrapped ones too in order to correct for serially correlated errors
arising from the short nature of the panel used.
8
Before collecting baseline (and randomization) we will make sure that the communities included
in the study understand and agree to be part of the study, meaning that they accept to work on
sanitation issues with CLTS either right away or two years later. Program take up is implied by
the acceptance of this protocol for treated communities. Randomization is done after the
baseline is conducted, so, if a community does not want to be part of the study it will not bias
our estimates.
One of the main concerns of random assignment is the potential contamination of the control
group. This happens for example when there are interactions between members of CLTS
communities and members of control communities. This is a problem in the presence of shared
activities. For example, children in control and treatment communities may share schools; adults
may operate on the same markets, etc. The problem is that these interactions may cause
changes in the control group. At the extreme, control communities and CLTS communities
experience the same change, then we will not be able to detect any effect. We will carefully
explain the sample selection method (see section XXX) in order to avoid contamination and
ensure geographic representativeness.
Another concern that often arises with randomized experiments is that control units may be
receiving similar benefits from other interventions. We will monitor control villages to ensure
this does not happen and document this aspect of the design.
UNICEF conducts strict monitoring follow-ups during the intervention period3 (first 3 months),
which will be used to inform on the operations of the intervention. These monitoring indicators
are carefully recorded and their quality is ensured. We will supplement this work in two ways by
collecting more indicators during the intervention period and after the end of the intervention.
Note that UNICEF also plans to access administrative school data to monitor the evolution of
school attendance in the future. While such information will become available after the impact
evaluation is conducted, we believe this evaluation would greatly help in defining future steps in
terms of UNICEF conducting their own evaluations.
We will give careful attention to the variation in impacts across different groups, so treatment
will be interacted with gender and age indicators, pre-existing characteristics of communities in
terms of collective decision-making, among others in order to identify how these factors may
explain why some people or some communities gain more than others from the program.
Looking at heterogeneity in program impacts also helps in shading light on the mechanism
behind program’s success (or failure).
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The second part of the evaluation consists of gathering some important qualitative information.
Here we will conduct in-depth interviews with key stakeholders (community leaders, community
sanitation committee, and other persons or group of persons having a say in the decision to
adopt basic sanitation) in participating communities. All the previous PRAs (Participatory Rural
Appraisals) conducted in CLTS interventions in South Asia point to the role of leaders as a key
factor in the success of the intervention. This dimension seems to be crucial when looking at the
issue of sustainability, e.g., why some villages succeed in maintaining ODF status after the end of
the intervention while others fail. Descriptive evidence (Water and Sanitation Report, 2007)
argues that lowering diarrhea incidence is only possible if the community is in fact ODF.
Otherwise, even if most community members use toilets, diarrhea incidence is still very high.
Information on community attributes will also be gathered in order to develop a deeper
knowledge about which communities may be more likely to become ODF. For example,
Chambers (2008) provide some characteristics that make the community more prone to
successfully engage in CLTS programs, like settlement size, soil fertility, polluted water supply,
high incidence of diarrhea, other health interventions in the community, etc. Those are key
aspects that need to be systematized together with the quantitative evaluation explained above
to recommend possible improvements to the design for the future.
The two approaches mentioned above (random assignment with regression analysis and
qualitative information) will allow the team to have a very complete and holistic evaluation
using sound methodologies that will provide answers to issues related with the impact of the
intervention in several dimensions and in issues related with sustainability too. Moreover, the
evaluation will result in some new inputs to be included in the design in future programs,
monitoring indicators and evaluation of similar interventions. [see section xx for more details]
In addition, as it will be carefully explained in section xx we are very interested in monitoring
intermediate outcomes related to water quality, condition and use of latrines, etc.
Given the growing use of CLTS programs all over the developing world, a serious and external
evaluation to see if such programs work is essential. This will be one of the first evaluations
using impact evaluation techniques with quantitative data [and random assignment]. It will also
complement already existing evidence on CLTS. Another advantage of this evaluation is that it
will look carefully at behavioral outcomes that are behind the adoption of better sanitation
practices and that are often overlooked in evaluations related to sanitation, which tend to focus
more on health outcomes. It is widely accepted that better sanitation improves health, yet there
is still much debate over what a cost-effective way to deliver a sanitation intervention may be.
Success in delivery will very much depend on whether the program is able to identify
bottlenecks that impede adoption of better sanitation practices and whether it is able to solve
the issues that are identified.
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4. Sampling framework
Our first survey for the evaluation of CLTS is meant to provide accurate and up-to-date
information in the Koulikoro region of Mali. These data represent the state of the world without
the program in place, and thus our population of interest is limited to villages where CLTS is not
yet implemented.
CLTS targets small villages (from 30 to 70 households). Our population of interest is further limited
to those villages.
CLTS typically intervenes in villages that are a significant distance apart from one another. There
are two reasons for that. First, physical contamination of fecal elements through air and water
from neighboring communities may limit the benefits from the intervention and discourage the
adoption of clean practices in the targeted villages. Second, CLTS relies on social contagion to
generate a demand for the services it provides. Through word of mouth, neighboring villages gets
organized to directly request the support of CLTS in helping them change sanitation practices. It is
thus important for the study that the sampling strategy allows us to respect this additional
“spacing” constraint. We thus use systematic sampling in order to ensure that our study villages
are all sufficiently distant from each other.
Finally, in order to study adoption diffusion within villages, we included a social network module
to the survey. The need for these data required us to conduct a census of all households in each of
the sample villages.
1) Sampling method
The Primary Sampling Unit is the village. We draw a systematic sample based on the following
steps:
(i) We pick a village at random from the sampling frame (the sampling frame is described
below),
(ii) We draw a circle of radius 10km around the village and we pick another village at random
from the sampling frame excluding the area around the previous village,
(iii) We repeat steps (i) and (ii) until we get 120 villages or exhaust the sampling frame.
We conducted a census of all households in the sample villages. Our main survey module (the
household questionnaire) gathered detailed information on households living in the sample
villages with at least one child below age 10. We also collected information at the village level, and
at the household and individual levels for all household members.
2) Sampling frame
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We included in the sampling frame all villages with sizes between 30 to 70 households located in
the Koulikoro region, excluding the villages where CLTS is already in place. Our main source of
information was the Census data from 1998 (Infrastructure du Recensement 1998). We updated
village size using population growth rates obtained from the 2009 Census. Unfortunately, the 2009
Census was not yet released at the date we built the sampling frame. We complemented these
data with the list of CLTS villages obtained from the Koulikoro Sanitation Office (Direction
Regionale de l’Assainissement de Koulikoro). Based on the two main targeting criteria discussed
previously (village size and CLTS status), we created a sampling frame of 402 villages.
Using our sampling strategy (explained above), we drew 121 villages that are at least 10km
distance from each other. We then computed sampling weights that indicate how many villages
each of our sample villages represent. These sampling weights will be used to estimate averages
for our study population of interest.
5. Power calculations conducted ex-ante
Ex-ante, our power calculations for assessing change in prevalence of diarrhea under the age of 2
using DHS data for rural Mali indicated that we needed a total of 120 villages with over 25-30
children under the age of 2. This would allow us to detect a 10% decrease in diarrhea from a
baseline prevalence of 10% for the Koulikoro region. Diarrhea prevalence was expected to be
much higher in our sample, since we focus only on CLTS eligible communities. Using preliminary
data, we re-did our power calculations for the same variable. We have a total of 4532 (37 per
cluster on average) children under the age of 2 and the diarrhea prevalence for our sample is 13%
(sd 0.0029) for children under 5 and 23% (sd 0.0081) for children under 2.4 Our revised power
calculations indicate that we are able to detect an effect size equivalent to 0.10, with our observed
sample size. The intra-cluster correlation coefficient (ICC) was also calculated with our data, and
corresponds to 0.04771 (CI 95%: 0.03307 - 0.06235). The ICC obtained from the data is higher than
the one used in the original calculations.
6. Random allocation
We conducted the random allocation, and we present the balance of some of the relevant
covariates below. We decided to conduct the random allocation so as to check ex ante that the
average cooperation level of the second and third round of the games and the community average
latrine coverage where balanced. We used an algorithm that re-randomized until balance was
achieved for these two variables. Balance was achieved after 5 iterations. We then check balance
for a list of covariates as explained below. As it can be observed, for all the variables considered,
there is no statistically differences in their means. Columns 5 and 6 of table 4.1 show p-values and
t-statistics respectively which do not allows us to reject the null hypothesis of no differences in
means.
4
All the power calculations were done assuming a power=0.80
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Also, Appendix 1 shows that there are no statistically significant differences in means for
selected variables present in the baseline survey between treatment and control communities.
Finally, we performed several probit estimations regressing the probability of treatment as a
function of observable community characteristics and none of the regressors were statistically
significant.
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7. Implementation of CLTS
Unicef and the Directorate of Sanitation of Koulikoro (DNACPN) have successfully finished the
triggering process in the 60 communities assigned to the treatment group. At the time of this
report, Unicef has not yet provided complete information on the total communities that are ODF
certified.5 Nevertheless, they are progressing according to the Calendar of Certifications we will
show later in the report.
The main obstacle that the CLTS implementing team faced was the training and mobilization of the
human resources needed to trigger the intervention. This was a significant burden imposed by the
requirements of the impact evaluation, resulting from the sampling framework6 (needed to avoid
contamination and to ensure geographic representativeness). Communities were located farther
apart compared to the way CLTS is usually conducted in Mali. However, the implementation team
successfully managed to complete the triggering and so far the rest of the intervention is going as
scheduled.
Below we summarize the main qualitative findings resulting from the triggering process and the
plan of action committed by the communities.
Table 1 presents the result by “cercle”, or administrative units within the area of Koulikoro.
5
As it can be seen later in the report the Feb-March period is very demanding in terms of human
resources in the field. Not all members of the teams could be contacted at the time of the writing
of this report.
6
For detailed information on the sampling framework see Appendix 1.
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The intervention will affect a total of 32,585 people. Communities have committed to building
2045 new latrines.
The CLTS team collects a wide range of qualitative information on the triggering. Different aspects
of the process are documented and there is an assessment of what key components of the
triggering process went well and which ones did not. The main categories that are considered are
the following7:
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
Community welcome
Team’s introduction
Cartography, map of OD areas
Splitting adults and infants into separate groups
Choice of leaders
March of shame (“Marche de la honte”)
Calculation of the volume of feces per day/month/year
Calculation of health expenditures in CFA
Naming the main three diseases present in the community
Community engagement to build/repair latrines
Visit to existing latrines/hand-washing stations
Determination of date for achieving ODF status
7
Each team produces a list of the different categories to be considered, but those are not
completely pre-defined, so here we present the most important ones that are repeated across
villages.
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There is not a completely unified criterion for gathering information about the triggering
process, and in some cases, not all the twelve criteria are mentioned. We attempted a unified
classification for the items stated above in order to identify the items that may have been
more successful/problematic at the triggering process. Table 2A summarizes the information
resulting from Unicef’s qualitative report.
As mentioned above, not all the criteria were observed in each community, as seen in the
second column of Table 2A (# Obs). A value of “1” means that the item in question went well
during the triggering and a value of “0” means it did not work as well as expected. The mean
and the standard deviation are calculated based on the number of times that were mentioned
either as positive or negative.
The communities seem well aware of the most common diseases, since they could be
identified most of the time.8 The same applies to the calculation of the volume of feces and
health expenditures. Also, there seems to be no problems surrounding drawing a village map
to identify the OD areas.
Fifty-nine communities successfully identified at least one leader (with three leaders most of
the time).
One item that appears particularly problematic was to carry out the shame march with adults.
Finally, the team gives an overall appraisal to the whole triggering process. Such appraisal
takes four different values (see Table 2B below) going from best to worst outcomes:
8
The most common mentioned diseases are diarrhea, malaria, cough and stomachache.
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1.
2.
3.
4.
Lighting a match in a gas station "gratter une allumette dans une station d’essence"
Promising Flame "flamme prometteuse"
Scattered sparks "étincelle éparpillée"
Total failure "allumette mouillée"
On average, the overall triggering process was successful (Lighting a match in a gas station) in
28.3% of the communities and a “promising flame” in 66.7% of communities. These values vary a
lot within each cercle, but there is only one case (Koulikoro) where the third category is at 20%. No
village was given a ranking of “allumette mouillée“, or total failure.
17
The systematization of the qualitative information is very useful in order to link it to the main
outcome variables of the impact study. We will review and add new questions to the follow up
survey in order to capture relevant aspects of CLTS (triggering, time to ODF certification,
monitoring visits, role of community leaders, etc.).
Table 3 shows the date committed for each community to be ODF certified. As it can be observed,
several communities achieved certification in late 2011 or early 2012. 9
9
We will update this table as soon as the information becomes available.
18
19
8. Baseline Survey
Here, we present the main results from the baseline survey. A full set of tables resulting from the
baseline survey is available in Appendix 2.
The baseline information we collected consisted of several modules:
-Community Survey: the community survey was a census of the communities, gathering
information about basic infrastructure, water sources, latrines, open defecation areas, distance to
health centers, school, mosques and paved roads. All of the village features were geo-referenced.
The main results are described in section xx
--Household Survey: the household survey was conducted among all households with children
under the age of 10. Out of the total number of households per community, over 85% had
children under 10. The survey collected basic demographic and socio-economic information,
information on child health, measurement of child anthropometrics, household hygiene and
sanitation practices (both direct questions and an observational module), water services, social
networks, and social capital. The main summary statistics are presented in section xx
-Water Quality survey (see section xx)
-Experimental Games Forms (see section xx)
5.a Community Survey
This survey was conducted in the republic of Mali, in the region of Koulikouro which covers an area
of 90,120 km2 and has a population of 1,516,486 people. The region of Koulikoro is subdivided in 7
administrative units called circles; Figure a.1 shows the number of villages selected in each circle,
totaling 121.
Figure a.1: Location of communities, number of communities sampled per circle shown in ()
20
A total of 4569 households where interviewed10, 94% of the questionnaires were fully answered,
5% were partially completed, and 1% refused completion. Partially completed questionnaires
mainly have information on health missing, given the fact that some caretakers could not be
located at the time of the interview or on two repeated visits.
Figure a.2 questionnaire completion
10
Households that completed the full questionnaire were households where there was at
least one child under the age of 10. For the remaining households we collected basic
information which was processed together with the community survey.
21
The field work took place during the dry season of 2011 from April 12th to June 17th. After 3
weeks of training, nearly 60 numerators were organized into 11 teams to complete data collection.
Each team was supervised by a field supervisor that oversaw data collection, conducted the
village-level surveys, and reviewed the household survey questionnaires daily. On average, each
team spent 4 days in a village in order to complete the survey. Upon their arrival, enumerators
conduct a census to ensure that the village complied with the selection criteria and report overall
statistics including: water access, sanitation, basic social services and survey response rate.
Figure 3 presents statistics on water and sanitation conditions for the sample of villages. As it can
Figure a.3
be observed, all the villages satisfy the criteria for CLTS inclusion in terms of percentage of
latrinization. Panel (b) displays the number of Open Defecation Areas. Private latrine coverage
fluctuates between regions, as it can be observed in Figure a.4. The areas with higher coverage are
the ones that are nearer to Bamako.
22
Figure a.4
5.b Household survey
Below we present initial results for the baseline survey. We note the data cleaning process is
continuing, thus these results should be considered preliminary.
We collected information for 4569 households. There is information for 7449 and 4532 children
under the age of five and two respectively. Table b.1 presents descriptive statistics on key
variables for our intervention.
The average number of households per community is 48 and 38 for households with children
under the age of ten. There are an average of 62 children under 5 per community.11 In terms of
variables that are relevant for our sanitation intervention, we observe that latrine coverage is well
below Unicef criteria of 60% latrine coverage). Also, self reported Open Defecation Rates are much
higher for infants and children as compared to adults. Higher rates are also reported for male
adults than for females. There is an average of 4 water sources per community, and households
usually fetch their water from shallow wells, which are more prone to contamination than deep
wells (see section on water and sanitation).
In terms of the game results (see section d for further details) we observe an average final level of
cooperation of rounds 2 and 3 of 75%, and an increase in 7% from initial cooperation.
11
For information under children under two and diarrhea incidence, please refer to
section 3.
23
5.c Water, sanitation, and hygiene results from the baseline survey
Out of the almost 13 million people living in Mali, only 56% have access to an improved water
source and only 36% have access to an improved sanitation facility (UNICEF 2010). Although it is
known that access to improved facilities is poor, little is known regarding the features and quality
of these services in Mali and how they influence child health. This section presents preliminary
results from our baseline survey conducted in Mali in the region of Koulikoro among 121 rural
villages.
Water, sanitation, and hygiene data collection methods included community level surveys with
key informants; personal interviews at households with at least one child under five; observations
of household sanitation, water, and hygiene facilities; and water quality sampling of village
drinking water sources and household stored water.
Access to sanitation
Access to improved sanitation among the study households was low at baseline. Only 4% of
households reported having access to an improved latrine by JMP standards (private latrine with a
concrete slab). However, 34% reported having access to a private latrine (improved or
unimproved) and 29% reported having access to a neighbor’s latrine. Respondents reported that
93% of children under five, 62% of children age 5-10 years, 56% of adult women and 44% of adult
males practice open defecation. On average, households have to walk 3.6 (SD 5.3) minutes to the
location where they most often practice open defecation. About half of the respondents (54%)
reported that the open defecation area was located outside the village. Most respondents (62%)
agreed with the statement “Most people do not use latrines for defecation in this community.”
24
When asked if it was safe for women and young girls to go to the open defecation area, 23% said it
was not safe during the night and 9% reported that it was not safe during the day. Almost onethird (28%) of respondents reported that women do not have privacy when practicing open
defecation and 4% reported that women have been harassed or attacked during defecation. Those
households with access to a private latrine were twice as likely to be satisfied with their sanitation
situation (69%) than those without access to a private facility (32%). When asked if they agreed
with the statement “It’s shameful to defecation in the open air (not in a latrine),” 3% strongly
disagreed, 16% disagreed, 44% agreed, and 30% strongly agreed.
Observations of toilets confirmed that most latrines were unimproved pit latrines. About half
(53%) of latrines were observed to have a cover over the pit, 5% had water available inside the
latrine, 3% had soap available inside the latrine, 66% had visible water/urine around the pit, 7%
had feces present around the pit, and 63% had visible flies in the latrine.
The majority (85%) of households reported that they did not have a specific place in their
household to wash their hands. Almost no households were observed to have soap (<0.05%) or
water present (<0.05%) at a hand-washing station.
Access to drinking water
The majority of households reported accessing public wells as their main drinking water source. A
total of 43% of households report using an improved water source, including borewells (31%), a
piped system (2%), or a protected well (10%). The majority of households use an unprotected
open well (56%).
A water sampling field team visited each village and took a census of the drinking water sources.
At each drinking water source, enumerators identified the type of source, collected a water
sample, and recorded the GPS coordinates of the location. In addition, up to 8 households in each
village were visited to collect a stored drinking water sample. Households were selected by
counting every 7th household on a village census list.
A volume of 100ml was collected for each water sample in a sterile bottle. Water samples were
kept on ice and processed by the field team on site in the village within 6 hours. A defined
substrate assay was used to enumerate the most probable number (MPN) of E. coli and total
coliform in each sample (IDEXX, Westbrook, ME). For every 20 samples processed, the team ran
one sample in duplicate and one blank sample. The blank sample was prepared by filling a sterile
bottle with sealed bottled water purchased by the field team. The detection limit for both types of
fecal indicator bacteria ranged from 1 to 2419 MPN per 100ml of water sample. For statistical
analysis, a value of 0 was substituted in for all samples below the detection limit and the value of
2419 was substituted in for all samples that were above the detection limit. To normalize the data,
+1 was added to all values and then the data were log10 transformed.
The majority of households reported accessing public wells as their main drinking water source. A
total of 37% (N=1627) of households use a public unprotected shallow well, 31% (N=1368) use
deep borewells, 10% (N=455) have their own private open shallow well, 8% (N=362) use a
25
neighbor’s open well, 6% (N=276) access public protected shallow wells , 2% (N=77) have their
own protected shallow well, 2% (N=75) use their neighbor’s protected shallow well, 1% (N=54) use
a public tap, and only 0.5% (N=20) use a private tap located on their household premises.
The water field team collected a total of 395 source water samples and 845 household stored
water samples. On average, 3 sources and 7 household stored waters were sampled in each
village. The most common type of water source sampled in villages was an open shallow well
(66%), followed by borewell (22%) and protected well (10%). Very few piped water connections or
surface waters were sampled. A large proportion of samples were over the detection limit for
total coliform (70%), thus quantitative analysis in this report will focus on levels of E. coli. Shallow
wells (including both open and protected wells) had the highest contamination levels of fecal
indicator bacteria (Table 1). Shallow wells had a mean of 6 log E. coli more than borewells (deep
tubewells) and piped water taps (t-test, df=393, P<0.001).
Household stored water was highly contaminated with a mean of 5 log E. coli per 100ml. The
water team observed that almost all households store water in a covered jarre (92%, N=775), a
traditional pot with the capacity to hold approximately 20 liters. At the time of sampling, 54% of
households reported that they had filtered their stored drinking water through a cloth, <1%
reported using chlorine, <1% reported boiling, while the remainder (45%) reported that they had
not treated their water.
Table XXX. Levels of fecal indicator bacteria in drinking water sources and household stored water
for drinking. All results reported per 100ml water sample.
Type of sample
N
Median
E. coli
Household stored
water
Borewell
Open well
Protected well
Piped water
Surface water
845
178
86
260
39
5
2
<1
1733
517
<1
795
Mean (SD)
log E. coli
5.0 (2.2)
Median
total
coliform
>2419
Mean (SD)
log total
coliform
7.4(0.9)
0.8 (2.0)
6.9 (1.2)
6.1(1.3)
0.1 (0.3)
6.5 (0.8)
17
>2419
>2419
16
>2419
3.1(2.5)
7.8(0.3)
7.7(0.2)
3.5(2.5)
7.8(0)
The households participating in this study are mostly accessing their drinking water from shared
public shallow wells that are highly contaminated with fecal indicator bacteria. Both source
samples and household stored water samples routinely exceeded the international guidelines for
drinking water set by the World Health Organization of 0 E. coli and 0 total coliform per 100 ml of
water. Considering that open defecation is prevalent, unimproved sanitation facilities are
common, and that shallow wells are the main source of drinking water in the study villages, the
waterborne fecal contamination is likely from unsafe management of human feces. The planned
26
CLTS intervention has the potential to improve drinking water quality in the study villages through
improved coverage and quality of latrines.
Child health
Mothers were asked to report symptoms of gastrointestinal illness for all children under five in
each household for recall periods of 48 hours and 2 weeks. Diarrhea was defined as 3 or more
loose/watery stools in 24 hrs. One out of every 5 children was reported to have had diarrhea in the
past two days (20%), and the two-week period prevalence was 27%.
The height and weight was measured of each child under five years of age in enrolled households.
Z-scores were calculated using WHO standard methods. The mean Z-scores of height-for-age (HAZ),
weight-for-age (WAZ), and weight-for-height (WHZ) are presented in Table 5. A total of 31% of
children measured were considered stunted (HAZ z-score <-2), 29% were underweight (WAZ<-2),
and 19% were wasted (WHZ z-score<-2). There were no significant differences in mean Z-scores
between treatment and control villages (p>.2)
TableXX. Mean WAZ, WAZ, and WHZ scores of children under five.
HAZ
WAZ
WHZ
Mean
-1.2
-1.3
-0.9
SD
1.7
1.5
1.4
N
6483
6484
6200
% Z<-2
31%
29%
19%
5.d Experimental Games on Cooperation
We designed and conducted a series of 3 experimental games on cooperation over all study
communities in our sample. Our objective is threefold. The first one is to provide a descriptive
analysis of the level of cooperation within villages prior to the introduction of CLTS, and in
particular how this level correlates to other socio-demographic characteristics of these
communities (e.g., how it varies with the level of wealth, with the level of inequality, with the
source of livelihoods, the level of social cohesion between players etc.). Our second objective is to
try to explain the heterogeneity in the impacts of this program using the estimated level of
cooperation at baseline. This should help understanding the successes and failures to attain ODfree status. Finally, we want to test if CLTS may have had an impact of the level of cooperation
itself, through a learning-by-doing effect.
The games are voluntary contribution games where the choice of contribution is discrete (to
contribute or not to a common pot). If a villager decides to contribute, every participant (including
him) gets 1 point. If he chooses to not contribute, he gets 10 points. There are always more than
11 participants in the game (in average 25). The selection of participants is random. At the time
the census of a village is done, each household gets ½ chance of being selected to participate in
the game (the household gets to choose the member who participates). After this basic version of
27
the game, we conduct two other games of cooperation: one with communication between
players, the other where a leader can try to coordinate decisions. We randomly shuffle the
sequence of these two games over our sample communities.
At the beginning of each session enumerators explain the instructions and answer questions until
they are sure that all participants fully understand. Participants know in advance they will be
rewarded with prices according to the number of points accumulated during the session. Prices
are valuable items that are not related to sanitation. An experimental session lasts around 2 hours.
We conducted 121 experimental sessions between April and June 2011. One fourth of all
participants were male and average age among participants is 35.
In all three games, there are strong incentives to free-ride on the contributions of others. We find,
in line with the literature, that some free-riding occurs. In the baseline game (no communication,
no leader), 65% of participants contribute. When players are allowed to communicate for 5
minutes, 70% of them contribute. With a leader, we find that levels of cooperation again increase:
75% of all participants contribute. So, communication improves group efficiency and cooperation
under leadership leads to the highest levels of cooperation in these communities.
Finally, we also collect information on players’ expectations after each of the three contribution
decisions. We ask them to report how they think other contributions will look like (we use a visual
drawing with an empty pot/ pots with increasing levels of contribution / full pot). We find that
expectations get more accurate as we move from the baseline game to the two other games. We
also find that contributors are more optimistic than non-contributors, and finally, expectations are
positively correlated with the decision to contribute.
28
Appendix 1: Balance of pre-treatment covariates
Sections A-I
Section A: Demographics
Mean
Household size
Duration residency
Std. Error
Difference
Control
Treatment
Mean
N
Std. Error
t statistic
N
P-value
7.600
0.187
60
7.658
0.173
61
0.226
0.821
38.249
0.692
60
39.051
0.603
61
0.875
0.383
Main language
0.731
0.052
60
0.723
0.052
61
-0.107
0.915
Household head
0.136
0.003
60
0.135
0.003
61
-0.163
0.871
Male
0.491
0.003
60
0.490
0.004
61
-0.090
0.928
Age
18.754
0.154
60
18.802
0.167
61
0.214
0.831
0.582
0.008
60
0.588
0.008
61
0.495
0.622
0.878
0.025
60
0.895
0.019
61
0.548
0.584
0.669
0.052
60
0.668
0.050
61
-0.017
0.986
0.901
0.007
60
0.910
0.006
61
0.950
0.344
0.014
0.002
60
0.015
0.002
61
0.185
0.854
0.027
0.003
60
0.028
0.002
61
0.090
0.928
15.263
0.746
59
14.986
0.665
60
-0.278
0.782
Bambara
Main marital status
Married
Main religion
Muslim
Main ethnicity
Bambara
Resident Status
Actual residency
Bamako
Main reason for absence
Work
Time absent
*significant at 10% level, ** significant at 5 % level, *** significant at 1% level
29
Section B: Education and Economic Activity
Treatment
Mean
Control
Std. Error
N
Mean
Std. Error
Difference
N
t statistic
P-value
Attend to school
0.134
0.013
60
0.139
0.013
61
0.266
0.791
Days lost in school (last week)
0.593
0.126
57
0.465
0.094
57
-0.814
0.418
Current education
3.686
0.149
57
3.519
0.141
57
-0.818
0.415
Educational level achieved
0.589
0.048
60
0.564
0.053
61
-0.354
0.724
Read and write in some dialect
0.083
0.006
60
0.084
0.005
61
0.228
0.820
Worked or had a company (last week)
0.499
0.010
60
0.488
0.011
61
-0.749
0.455
Farmer
0.139
0.011
60
0.120
0.012
61
-1.170
0.244
Housewife
0.152
0.005
60
0.142
0.008
61
-1.042
0.299
Other
0.104
0.009
60
0.103
0.009
61
-0.142
0.887
Employee
0.008
0.001
60
0.008
0.001
61
0.071
0.943
Self-employed
0.122
0.009
60
0.114
0.010
61
-0.593
0.554
Worker without remuneration
0.314
0.013
60
0.321
0.017
61
0.359
0.720
Owner
0.047
0.006
60
0.039
0.005
61
-0.961
0.338
35.234
0.770
60
33.333
0.754
61
-1.765
0.080*
0.001
0.000
60
0.001
0.000
61
0.462
0.645
No work
0.011
0.004
60
0.017
0.004
61
1.059
0.292
Waiting
0.001
0.000
60
0.001
0.000
61
0.643
0.521
Illness
0.013
0.001
60
0.014
0.001
61
0.365
0.716
Whether
0.006
0.002
60
0.002
0.001
61
-1.821
0.071*
Retired
0.009
0.001
60
0.011
0.002
61
0.642
0.522
Other reason
0.102
0.009
60
0.105
0.009
61
0.270
0.788
Main Occupation
Wage
Hours worked (last week)
Looking for work or tried to create a company
Doesn't look ing for work because of:
*significant at 10% level, ** significant at 5 % level, *** significant at 1% level
Section C: Additional information about household members died in the last year
Treatment
Control
Difference
Mean
Std. Error
N
Mean
Std. Error
N
t statistic P-value
1.127
0.020
60
1.191
0.027
60
1.891
0.061*
Members died
Member 1
Male
Age
Main Cause of death: Paludism
Member 2
Male
Age
Main Cause of death: Paludism
Member 3
Male
Age
Main Cause of death: Paludism
0.095
23.582
0.329
0.008
1.877
0.031
60
60
60
0.121
21.341
0.328
0.009
2.154
0.026
61
60
60
2.216
-0.784
-0.040
0.029**
0.434
0.968
0.009
12.844
0.370
0.002
4.204
0.091
60
24
25
0.010
16.793
0.314
0.003
4.581
0.079
61
29
29
0.439
0.624
-0.469
0.661
0.535
0.641
0.000
2.500
0.000
0.000
1.500
0.000
60
2
2
0.001
46.000
0.267
0.001
17.541
0.194
61
5
5
0.992
1.481
0.820
0.323
0.199
0.450
*significant at 10% level, ** significant at 5 % level, *** significant at 1% level
30
Section D: Lack of food
Treatment
Mean
Std. Error
Control
N
Hungry at home (last 3
0.055
months) 0.010
Mean
Difference
Std. Error
N
t statistic
P-value
60
0.046
0.008
61
-0.695
0.488
First month
Month
3.121
0.203
32
3.250
0.289
24
0.377
0.708
Days
5.296
0.746
30
5.976
0.867
24
0.598
0.552
Month
2.900
0.181
28
3.271
0.235
24
1.268
0.211
Days
6.455
1.002
27
7.692
1.530
24
0.690
0.493
Month
3.884
0.223
28
4.079
0.196
19
0.620
0.538
Days
8.343
1.448
28
8.404
1.647
19
0.027
0.979
Second month
Third month
*significant at 10% level, ** significant at 5 % level, *** significant at 1% level
Section E: Incidence of crime
Treatment
Mean
Crime victim (last 12 months)
Murder/Homicide victims
Std. Error
Control
N
Mean
Std. Error
Difference
N
t statistic
P-value
0.109
0.011
60
0.086
0.009
61
-1.573
0.118
Total
1.074
0.056
9
1.271
0.183
8
1.079
0.298
Male
0.840
0.080
9
0.896
0.151
8
0.340
0.738
0.235
0.125
9
0.375
0.160
8
0.700
0.495
Total
1.135
0.046
39
1.134
0.056
40
-0.006
0.995
Male
0.870
0.061
39
0.853
0.054
40
-0.213
0.832
0.264
0.060
39
0.281
0.071
40
0.182
0.856
Total
1.000
0.000
10
1.154
0.154
13
0.872
0.393
Male
0.867
0.102
10
1.000
0.196
13
0.552
0.587
0.133
0.102
10
0.154
0.104
13
0.138
0.892
Total
1.095
0.074
14
1.077
0.077
13
-0.172
0.865
Male
0.786
0.114
14
0.654
0.131
13
-0.762
0.453
0.310
0.123
14
0.423
0.137
13
0.618
0.542
Total
1.038
0.038
20
1.077
0.077
13
0.510
0.613
Male
0.677
0.092
20
0.872
0.089
13
1.441
0.160
Female
0.360
0.093
20
0.205
0.110
13
-1.067
0.294
Female
Looting victims
Female
Rape victims
Female
Agression victims
Female
Other crime victims
*significant at 10% level, ** significant at 5 % level, *** significant at 1% level
31
Section F: Family planning
Treatment
Mean
Couples
Std. Error
Control
N
Mean
Std. Error
Difference
N
t statistic
P-value
1.384
0.037
60
1.402
0.039
61
0.321
0.749
Pregnancy
0.137
0.007
60
0.135
0.009
61
-0.184
0.854
Family planning method
0.087
0.010
60
0.102
0.012
61
0.954
0.342
Main method: Injection
0.378
0.050
52
0.367
0.050
52
-0.159
0.874
Pregnancy
0.141
0.016
58
0.152
0.017
60
0.450
0.654
Family planning method
0.092
0.014
58
0.086
0.015
60
-0.295
0.768
Main method: Injection
0.439
0.074
35
0.363
0.075
27
-0.710
0.480
Couple 1
Couple 2
*significant at 10% level, ** significant at 5 % level, *** significant at 1% level
32
Section G: Household assets
Treatment
Mean
Std. Error
Control
N
Mean
Std. Error
Difference
N
t statistic
P-value
Household assets
Radio
0.658
0.020
60
0.683
0.023
61
0.828
TV
0.109
0.012
60
0.121
0.013
61
0.712
0.410
0.478
DVD
0.032
0.005
60
0.046
0.007
61
1.712
0.089*
Phone
0.370
0.024
60
0.446
0.022
61
2.367
0.020**
Oil lamp
0.422
0.022
60
0.410
0.021
61
-0.389
0.698
Gas lamp
0.019
0.005
60
0.018
0.006
61
-0.114
0.910
Watch
0.464
0.017
60
0.486
0.018
61
0.879
0.381
Washing machine
0.004
0.002
60
0.005
0.001
61
0.259
0.796
Refrigirator
0.004
0.001
60
0.006
0.002
61
0.894
0.373
Bed
0.281
0.024
60
0.287
0.025
61
0.192
0.848
Matress
0.236
0.021
60
0.255
0.021
61
0.642
0.522
Mat
0.956
0.005
60
0.944
0.008
61
-1.278
0.204
Carpet
0.249
0.019
60
0.259
0.019
61
0.373
0.710
Torch
0.940
0.007
60
0.939
0.008
61
-0.105
0.916
Table
0.497
0.031
60
0.527
0.029
61
0.711
0.479
Chair
0.588
0.040
60
0.563
0.031
61
-0.492
0.624
Large stove
0.216
0.018
60
0.235
0.019
61
0.710
0.479
Improved stove
0.089
0.012
60
0.096
0.014
61
0.387
0.700
Small stove
0.003
0.001
60
0.002
0.001
61
-0.296
0.768
Shelves
0.003
0.001
60
0.002
0.001
61
-0.890
0.375
Closet
0.031
0.005
60
0.026
0.005
61
-0.812
0.418
Cooking pot
0.988
0.003
60
0.982
0.003
61
-1.637
0.104
Jug
0.957
0.020
60
0.966
0.013
61
0.413
0.680
Calebasse
0.940
0.020
60
0.921
0.021
61
-0.659
0.511
Mosquito net
0.933
0.010
60
0.948
0.008
61
1.169
0.245
Harvester
0.031
0.009
60
0.027
0.008
61
-0.297
0.767
Chariot
0.658
0.021
60
0.625
0.021
61
-1.106
0.271
Spade
0.358
0.024
60
0.417
0.026
61
1.675
0.097*
Plow
0.666
0.021
60
0.657
0.021
61
-0.321
0.749
Wheelbarrow
0.085
0.011
60
0.102
0.019
61
0.787
0.433
Sickle
0.739
0.021
60
0.725
0.023
61
-0.450
0.654
Hoe
0.961
0.006
60
0.961
0.005
61
0.019
0.985
Pick
0.668
0.025
60
0.652
0.025
61
-0.445
0.657
Ax
0.881
0.012
60
0.889
0.012
61
0.514
0.608
Watering
0.186
0.032
60
0.154
0.024
61
-0.818
0.415
Thresher
0.011
0.005
60
0.024
0.009
61
1.283
0.202
Sheller
0.017
0.007
60
0.008
0.003
61
-1.254
0.212
Mill
0.004
0.002
60
0.008
0.002
61
1.520
0.131
Boat
0.005
0.003
60
0.006
0.006
61
0.142
0.887
Motor boat
0.000
0.000
60
0.000
0.000
61 .
Car
0.003
0.001
60
0.003
0.002
61
0.287
0.775
Fishing net
0.065
0.018
60
0.032
0.011
61
-1.608
0.110
Bicycle
0.608
0.045
60
0.624
0.043
61
0.257
0.797
Motorcycle
0.292
0.020
60
0.280
0.022
61
-0.391
0.697
Tractor
0.001
0.001
60
0.002
0.001
61
0.695
0.488
Agricultural equipment
Other assets
*significant at 10% level, ** significant at 5 % level, *** significant at 1% level
.
33
Section H: Social capital
Treatment
Mean
Std. Error
N
Union
Active member
Member head
Months since is member
Years since is member
Position of responsability or power
Position of responsability or power in the past
Always attends to the meetings
Meeting each month
Association/Cooperative
Active member
Member head
Months since is member
Years since is member
Position of responsability or power
Position of responsability or power in the past
Always attends to the meetings
Meeting each month
Women's group
Active member
Member wife
Months since is member
Years since is member
Position of responsability or power
Position of responsability or power in the past
Always attends to the meetings
Meeting each month
Political asssociation
Active member
Member head
Months since is member
Years since is member
Position of responsability or power
Position of responsability or power in the past
Always attends to the meetings
Meeting each month
Religious group
Active member
Member head
Months since is member
Years since is member
Position of responsability or power
Position of responsability or power in the past
Always attends to the meetings
Meeting each month
Mean
Control
Std. Error
Difference
t statistic P-value
N
0.270
0.749
2.381
8.980
0.340
0.406
0.302
0.239
0.028
0.032
1.152
0.468
0.034
0.032
0.037
0.032
60
51
16
51
51
51
51
51
0.270
0.725
3.400
9.379
0.359
0.454
0.300
0.173
0.027
0.031
1.065
0.529
0.035
0.036
0.044
0.026
61
50
20
49
50
50
49
49
-0.005
-0.540
0.647
0.565
0.388
0.990
-0.026
-1.610
0.996
0.591
0.522
0.573
0.699
0.325
0.979
0.111
0.295
0.872
2.085
9.076
0.400
0.384
0.263
0.269
0.021
0.019
0.349
0.433
0.025
0.031
0.029
0.027
60
58
29
58
58
58
58
58
0.327
0.878
2.639
10.028
0.409
0.361
0.330
0.249
0.020
0.019
0.521
0.567
0.028
0.031
0.034
0.027
61
61
32
61
61
61
61
61
1.092
0.219
0.865
1.324
0.243
-0.529
1.507
-0.509
0.277
0.827
0.391
0.188
0.808
0.598
0.134
0.611
0.679
0.854
2.485
5.230
0.222
0.263
0.429
0.212
0.024
0.011
0.329
0.306
0.014
0.020
0.033
0.026
60
59
38
59
59
59
59
59
0.666
0.858
5.166
5.156
0.217
0.273
0.473
0.203
0.025
0.013
1.993
0.255
0.015
0.021
0.031
0.024
61
61
47
61
61
61
61
61
-0.369
0.260
1.198
-0.186
-0.261
0.360
0.961
-0.252
0.713
0.795
0.234
0.852
0.795
0.720
0.338
0.802
0.093
0.839
3.715
7.973
0.455
0.255
0.265
0.155
0.011
0.035
0.868
0.389
0.047
0.038
0.042
0.033
60
48
13
48
48
48
48
48
0.096
0.877
2.375
7.909
0.554
0.200
0.275
0.134
0.011
0.033
0.971
0.657
0.045
0.036
0.047
0.029
61
51
16
51
51
51
50
50
0.197
0.797
-1.006
-0.082
1.535
-1.051
0.153
-0.499
0.844
0.427
0.323
0.935
0.128
0.296
0.878
0.619
0.109
0.815
1.765
13.337
0.314
0.325
0.295
0.307
0.013
0.038
0.504
1.324
0.043
0.048
0.048
0.044
60
50
18
50
50
50
50
50
0.109
0.868
1.000
10.994
0.386
0.314
0.283
0.255
0.014
0.033
0.424
1.052
0.048
0.047
0.045
0.043
61
47
13
47
47
47
47
47
-0.006
1.048
-1.101
-1.374
1.114
-0.163
-0.183
-0.837
0.995
0.297
0.280
0.173
0.268
0.871
0.856
0.405
*significant at 10% level, ** significant at 5 % level, *** significant at 1% level
34
Section H: Social capital
Treatment
Mean
Std. Error
Savings or credit group
Active member
Member wife
Months since is member
Years since is member
Position of responsability or power
Position of responsability or power in the past
Always attends to the meetings
Meeting each month
Parents association
Active member
Member head
Months since is member
Years since is member
Position of responsability or power
Position of responsability or power in the past
Always attends to the meetings
Meeting each month
Athletic association
Active member
Member head
Months since is member
Years since is member
Position of responsability or power
Position of responsability or power in the past
Always attends to the meetings
Meeting each month
Other group
Active member
Member head
Months since is member
Years since is member
Position of responsability or power
Position of responsability or power in the past
Always attends to the meetings
Meeting each month
Cellular
Contacts
Besides previous organizations
Someone occupies a position of responsability, authority or power
Member of village council
Months since is member
Years since is member
Relative was in that position before
Recieved support or help from:
Family
Neighbor
Friend
leader
Imam
Politician
Civil servant
NGO
Other
Participation in the community
N
Mean
Control
Std. Error
Difference
t statistic P-value
N
0.185
0.500
3.353
5.145
0.285
0.276
0.454
0.150
0.020
0.048
0.706
0.373
0.036
0.041
0.052
0.027
60
51
21
51
51
51
51
50
0.187
0.564
4.532
4.673
0.309
0.286
0.523
0.186
0.019
0.044
1.154
0.388
0.037
0.040
0.050
0.035
61
52
26
52
52
52
52
52
0.085
0.988
0.822
-0.876
0.462
0.177
0.972
0.811
0.933
0.326
0.415
0.383
0.645
0.860
0.334
0.419
0.068
0.825
4.286
5.718
0.455
0.298
0.294
0.337
0.010
0.047
1.229
0.490
0.060
0.053
0.056
0.052
60
40
14
39
40
40
40
40
0.069
0.785
3.154
6.274
0.513
0.282
0.276
0.371
0.010
0.051
0.898
0.628
0.060
0.050
0.056
0.060
61
41
13
39
41
41
41
41
0.011
-0.579
-0.734
0.697
0.689
-0.218
-0.225
0.428
0.991
0.564
0.470
0.488
0.493
0.828
0.823
0.670
0.054
0.828
2.286
8.201
0.389
0.254
0.416
0.182
0.012
0.047
1.475
0.864
0.062
0.058
0.068
0.048
60
35
7
35
35
35
34
34
0.055
0.738
4.222
5.935
0.481
0.221
0.313
0.287
0.009
0.066
2.832
0.634
0.064
0.051
0.055
0.050
61
37
9
37
37
37
36
36
0.103
-1.094
0.556
-2.131
1.045
-0.433
-1.186
1.499
0.918
0.278
0.587
0.037**
0.300
0.666
0.240
0.139
0.097
0.791
3.028
8.655
0.469
0.315
0.412
0.243
0.275
7.103
0.014
0.042
0.957
0.811
0.045
0.047
0.053
0.043
0.019
0.521
60
42
12
42
42
42
42
42
60
58
0.125
0.827
1.313
8.553
0.395
0.363
0.481
0.295
0.360
7.505
0.014
0.036
0.530
0.624
0.045
0.047
0.052
0.042
0.020
0.496
61
51
16
50
51
51
51
51
61
61
1.468
0.648
-1.669
-0.101
-1.159
0.705
0.932
0.863
3.120
0.559
0.145
0.518
0.107
0.920
0.249
0.482
0.354
0.390
0.002***
0.577
0.152
0.416
3.963
8.303
0.534
0.012
0.036
0.723
0.630
0.032
60
60
28
60
60
0.162
0.430
4.148
8.535
0.493
0.013
0.035
1.024
0.662
0.037
61
58
25
58
58
0.581
0.274
0.150
0.254
-0.831
0.562
0.784
0.881
0.800
0.408
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
0.369
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.030
60
60
60
40
46
32
23
39
32
60
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
0.327
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.028
61
61
61
38
39
24
24
39
38
61
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
-1.026
0.307
*significant at 10% level, ** significant at 5 % level, *** significant at 1% level
35
Section H: Social capital
Treatment
Mean
Std. Error
Satements scale of 1 to 7 (strongly disagree to strongly agree)
Honest and reliable people
People interested in their situation
Someone can take advantage
Not interested in opinions
Most people offer their help
Accepted like community member
It's easy found someone reliable to care the children
If someone lost an animal other members help in the research
People return borrowed money
When I think in my community I feel proud
In life successful people have helped
Always is responsible for what happen to us in life
To get success in life we must have good relations
With the willingness always have success
In life you only get what you deserve
Someone who fails in life, is because never had any luck
Husband has the last word in the following decisions
Bring a sick child to the doctor
If a child doesn`t go to school, decide to go or not
Give permission to go to a child
Buy clothes or shoes to a child
How much money spend in food
Repair or renovate in the house
Buy furniture or appliances
When a woman receives an aditional income, how that money will be used
Give permision for a woman to visit a relative, friend or neighbor
Accompanying women when visiting someone
Help other women in the village
N
Mean
Control
Std. Error
Difference
t statistic P-value
N
5.582
4.223
4.316
3.710
5.751
6.056
6.027
5.904
5.589
5.886
5.558
3.953
5.745
5.483
5.111
5.163
0.049
0.120
0.107
0.135
0.056
0.037
0.053
0.055
0.049
0.046
0.052
0.096
0.056
0.046
0.105
0.061
60
60
60
60
60
60
60
60
60
60
60
60
60
60
60
60
5.596
4.033
4.355
3.790
5.687
6.066
5.941
5.697
5.522
5.862
5.445
3.943
5.751
5.493
4.997
5.208
0.049
0.097
0.094
0.133
0.059
0.037
0.050
0.061
0.047
0.053
0.051
0.087
0.064
0.045
0.081
0.064
61
61
61
61
61
61
61
61
61
61
61
61
61
61
61
61
0.192
-1.238
0.276
0.422
-0.795
0.195
-1.198
-2.513
-0.991
-0.352
-1.546
-0.078
0.068
0.156
-0.855
0.506
0.848
0.218
0.783
0.674
0.428
0.846
0.233
0.013**
0.324
0.726
0.125
0.938
0.946
0.876
0.394
0.614
0.783
0.724
0.634
0.580
0.826
0.913
0.825
0.447
0.914
0.674
0.657
0.018
0.022
0.026
0.019
0.013
0.010
0.019
0.024
0.012
0.022
0.026
60
60
60
60
60
60
60
60
60
60
60
0.798
0.799
0.671
0.634
0.810
0.894
0.766
0.475
0.927
0.680
0.615
0.015
0.020
0.023
0.020
0.014
0.011
0.025
0.027
0.010
0.025
0.025
61
60
61
61
61
61
61
61
61
61
61
0.662
2.482
1.064
1.972
-0.843
-1.252
-1.863
0.769
0.797
0.167
-1.149
0.509
0.014**
0.290
0.051*
0.401
0.213
0.065*
0.443
0.427
0.868
0.253
N
Mean
Std. Error
*significant at 10% level, ** significant at 5 % level, *** significant at 1% level
Section I: Social network
Treatment
Mean
People who can help you when you needed
People you can help when they needed
People you can help to organize a ceremony/celebration religious or traditional
People who can help you to organize a ceremony/celebration religious or traditional
3.362
3.373
3.884
3.844
Std. Error
0.099
0.098
0.161
0.166
Control
60
60
60
60
3.297
3.380
3.940
3.964
0.087
0.079
0.118
0.123
Difference
N
t statistic
61
61
61
61
-0.498
0.059
0.277
0.580
P-value
0.619
0.953
0.782
0.563
*significant at 10% level, ** significant at 5 % level, *** significant at 1% level
36
Appendix 2: Baseline Information
37
38
39
40
41
42
43
44
45
46
47