Gender and Community Management of Water Infrastructure:Evidence from a Randomized Evaluation in Kenya*

Jessica Leino†

University of California Berkeley Economics and Science, Environment and Development Group at Harvard’s Center for International Development

This Draft: October 2007First Draft: August 2007

Abstract

Despite a wide consensus that women’s participation is important for managing local public goods, little evidence exists on whether gender advocacy is effective at boosting participation and improving outcomes. I examine how advocacy efforts can affect the participation of women and how women’s participation in turn may affect water infrastructure maintenance among usergroups responsible for maintaining newly improved water sources in western Kenya. Half the communities were randomly selected to receive an intervention verbally encouraging them to increase female participation on their user committees. This intervention increased the number of women on committees by an average of 20 percent and more than doubled the probability that the chairperson was female, with these differences persisting over time. However, increasing women’s participation did not impact maintenance outcomes or maintenance quality. There is also no evidence that increases in women’s participation on water user committees altered other outcomes in the community. These results suggests that gender advocacy can be a useful means of boosting female participation, with little distortion in the effectiveness of these committees in delivering public goods.

* This research is supported by the USDA/Foreign Agricultural Service, Swedish International Development Agency, the Finnish Fund for Local Cooperation in Kenya, Google.org, the UCB Institute of Business and Economics Research, a Graduate Research Fellowship from the National Science Foundation, the Science, Environment and Development Group at Harvard’s Center for International Development, and the Institute of Business and Economic Research at Berkeley. I thank the staff of ICS, IPA, and NYG for their assistance in the field. I thank Saumitra Jha, Marit Rehavi and especially Edward Miguel, Michael Kremer, and Alix Zwane for their support and helpful comments. Preliminary draft, comments welcome. All errors are my own.† 549 Evans Hall #3880, Department of Economics, University of California, Berkeley, CA 94720-3880, USA, leino@econ.berkeley.edu.

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The World Bank views the third Millennium Development Goal—to promote gender equality and empower women—as a central component to its overall mission to reduce poverty and stimulate economic growth. (World Bank 2006)

Specific interventions to address gender inequality should be an intrinsic part of all MDG-based investment packages. They should also address systemic challenges such as … increased representation at all levels of governance.(UNDP 2005)

Promoting gender equity and increasing women’s participation is now seen as both a key goal in

its own right and a crucial component of projects designed to meet the targets of the Millennium

Development Goals. Development agencies and funders are increasingly emphasizing the role

of women in all facets of development (World Bank 2001, UNDP 2005, World Bank 2006,

World Bank 2007). One major area where women’s participation is a key focus for both equity

and efficiency reasons is the management of local public goods, including infrastructure projects

in the water sector. 1 Progress in the water sector is needed to meet another Millennium

Development Goal of halving the proportion of people without sustainable access to safe

drinking water and basic sanitation, and “women play a central part in the provision,

management, and safeguarding of water” (Declaration of the International Conference on Water

and the Environment, 1992; quoted in Brooks 2002). Indeed, increasing women’s participation

in community development projects in this sector has become a central project outcome: for

instance, in the World Bank’s Ghana Second Community Water and Sanitation Project, “the

number of gender-balanced water and sanitation committees is a key performance measure”

(World Bank, Gender and Development Group, 2002).

Despite a wide consensus that women’s participation is important for managing local

public goods, little evidence exists on whether commonly advocated policies—such as gender

advocacy and quota systems—are effective at boosting female participation and improving other

outcomes and whether tradeoffs arise in attempts to meet these dual objectives simultaneously.

In this paper, I use data collected from a water quality improvement project in rural Kenya to

1 In addition, many service delivery projects in developing countries now explicitly target women as the primary beneficiaries of programs. Mexico’s Oportunidades program is one well-known example; in this program, women receive cash transfers if their children attend school and receive regular health checkups. The decision to direct transfers exclusively to women was “motivated by growing evidence that when women control household resources, children’s health and nutrition improve” (IFPRI 2001). An example of a study that provides such evidence is Duflo’s (2000) examination of the extension of an old-age pension in South Africa; she finds large and significant gains in child nutrition for the female grandchildren of grandmothers who received the pension.

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examine whether encouraging women to participate on local water management committees

increases active female participation and alters the effectiveness of the committees in managing

the water resource. I also examine how the intervention to boost female participation interacts

with the structure of financial support offered to communities. The project took place in 334

communities that were participating in NGO projects that provided infrastructure to improve

local drinking water sources. The NGOs provided training in how to manage and maintain the

source to a committee of water users elected by the community, and then handed the

infrastructure over to the water user committee to manage. I worked with the NGOs to design

and implement an intervention that aimed to boost female membership on committees and

encourage women to take up leadership positions on the committees. 2 The intervention

consisted of several components: advance efforts to encourage women to attend the community

meeting at which user committees would be selected, holding the meetings at a convenient time

for women to attend, and speeches by NGO facilitators on the importance of women’s

participation. This intervention was cross-cut with another set of interventions that provided

various forms of financial support to a randomly selected subset of communities. Communities

were randomly selected to receive the interventions; the sample of communities participating in

the infrastructure project was stratified on baseline community characteristics, which NGO was

overseeing the infrastructure and committee training, and the year in which the project would be

implemented and randomly assigned to receive a package of interventions. After the

interventions were implemented, data was collected on user committees and infrastructure

maintenance over a three year period.

I use the exogenous variation created by the random assignment of the female

participation intervention and financial support to communities to identify the effects of

increased women’s involvement on user committee composition and maintenance outcomes. I

estimate the reduced-form average treatment effect of receiving the intervention and use an

instrumental variables approach to identify the local average treatment effect of the participation

of women who became committee members due to the intervention. I also use non-parametric

estimation techniques to explore whether the effects of the interventions differs over the

2 I designed and implemented the local water management committee intervention as a separate component of a larger study (joint with Michael Kremer, Ted Miguel and Alix Zwane) that examines the health effects of improvements in source water quality.

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distribution of gender ratios on user committees. I further compare the results of the randomized

evaluation to non-experimental estimates of the effects of female participation.

I find that the female participation intervention increased the number of women on

committees by an average of 20 percent. Women occupy almost one additional leadership

position and are more than twice as likely to chair committees on the average committee that

received the intervention. Differences in the gender composition of user committees are

persistent nearly three years after the intervention. These results suggest that interventions to

improve female participation can be successful, even when the intervention is non-binding. The

female participation intervention did not lead to differential selection on the user committees:

there are no differences in the average wealth, education, social connectedness or other

characteristics of either men or women on committees that received the intervention (though

there are differences between the average man and the average woman committee member).

However, increasing women’s participation does not significantly impact maintenance outcomes

or maintenance quality in this setting. In this context, increasing women’s participation has no

negative impact on project outcomes; I can reject negative impacts greater than about five

percent. It seems that the intervention was able to successfully overcome social costs to female

participation and that any negative impacts of the lower average education and experience of

female committee members is offset by other factors in which women might have a comparative

advantage, such as monitoring costs or information about the resource. I also find no evidence

that increases in women’s participation on user committees have spillover impacts on other

outcomes in the community (such as income-generating activities or other activities such as tree

planting). These results suggests that gender advocacy can be a useful means of boosting female

participation, with little distortion in the effectiveness of these committees in delivering public

goods.

Section II provides a more detailed motivation for the paper that draws on the relevant

literature on local public goods management and gender. Section III describes the data and the

project from which the data is collected. Section IV presents the empirical strategy and Section

V discusses the results. Section VI concludes.

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II. Motivation for Promoting Female Participation in LPG Management

In order to meet the dual objectives of increasing women’s participation and improving

the effectiveness of local public goods delivery, a social planner might choose the level of

participation and other inputs to maximize a social welfare function in which female

participation enters the utility function both directly and as an input into the production function

for management outcomes, subject to budget and other constraints. The project outcomes about

which the social planner cares are the quantity and quality of the public good provided by the

project. In this paper, which examines water infrastructure projects, I focus on outcome

measures that are correlated with the ultimate outcomes of interest for the social planner and that

community resource managers can impact: water quality and the life span of the infrastructure

project.3 How any tradeoffs between increasing women’s participation and these project

outcomes should be valued is a normative question, but examining the direction and magnitude

of how changes in participation affect project outcomes provides useful information for assessing

policy choices.

Some discussion of the existing literature is useful at this point. Several policy papers

argue that improving equity will improve outcomes, so there is no tradeoff between increasing

women’s participation and project quality (e.g., Pandolfelli et al. 2007, IDA 2007). Though the

empirical evidence on which such claims are based is limited, a number of arguments have been

proposed for the channels through which female participation might impact project outcomes and

these arguments can generate useful hypotheses that can be tested empirically. The most

commonly-cited motivation for boosting female participation is based on a case study literature

that suggests that women and men may value public goods (or their by-products) differently, and

in some cases, women’s preferences are more aligned with the preferences of a benevolent social

planner. For example, if women value the health of their children more than men, and unclean

water is responsible for a large fraction of infant death and illness due to diarrheal diseases,

women may have a greater incentive to ensure that a local water source is maintained and kept

clean. A further reason why women’s participation may improve the management of natural

resources is because women’s social networks provide them with prior experience with

3 For a given budget, the project cost will determine how much of the good can be provided. In the case of infrastructure projects with high up-front construction costs, if management inputs can extend the lifespan of the project, the amortized cost of the infrastructure decreases and more of the public good can be provided over a longer time period for a given budget.

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collective action (Agarwal 2000). In addition, since women are major users of these goods,

women’s involvement in creating rules for managing the resource may be especially important

for ensuring long-term compliance within the community (Zwarteveen and Meinzen-Dick 2001).

The gender of the primary users and managers of a resource may also impact how it is

managed because traditional gender roles facilitate different costs of information and monitoring.

Due to gendered divisions of labor, women are often the primary users of these resources and in

the course of their use acquire specialized knowledge about the resource. They may also have

lower costs to monitoring the resource. For instance, women (who, in many societies, devote

several hours a day to collecting water) may have lower costs of collecting information on the

maintenance status of a water source. In both of these examples, placing women in charge of

managing the resource may lead to better maintenance outcomes. Women may have fewer

outside employment options and may thus be able to devote more time to committee work.

On the other hand, the social position of the resource managers in the community may

interact with gender in determining the effectiveness of resource management. For example, if

women have more social distance from (often male) community leaders, women may be less

effective managers if they are unable to persuade influential community members to ascribe to

their management decisions or to prevent corruption from impacting the provision of the public

good. Alternatively, women, who have lower levels of education on average and are less likely

to work outside the home, may also have less management experience and may be less effective

leaders, at least initially.4

Though existing work has posited several plausible channels through which female

participation might impact outcomes, much of the empirical evidence on the effect of women’s

participation in local governance and public good management is hampered by concerns about

reverse causality and omitted variables bias. Retrospective analyses (e.g., Prokopy 2004,

Weinberger and Jutting 2001) and case studies (e.g., INSTAW-UN 1990, Fortmann and

Rocheleau 1985, Geisler 1993, Stonich 1989, Thomas-Slayter, Sodikoof and Reynolds 1996,

Wijk-Sijbesma 1998, Gross, Wijk, and Mukherjee 2001) cannot convincingly establish a causal

relationship between between womens’ participation in local government and the quality of

4 Of course, this discussion ignores heterogeneity within a gender; wealth, education, and other differences may well be more significant than gender in determining the effectiveness of resource managers.

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service provision.5 It is difficult to determine whether the inclusion of women causes a

particular outcome to occur or if the fact than an outcome occurs encourages the participation

and inclusion of women. It is also difficult to rule out the possibility that some other factor is

driving both women’s participation and the outcome. Cross-country studies of the relationship

between women’s participation and the quality of governance, usually measured by corruption,

(e.g. Dollar, Fisman and Gatti 2001, Swamy et al. 2001) and meta-analyses of local community-

based projects (e.g., Narayan, 1995; Gross et al., 2001; van Wijk et al, 2002) are particularly

vulnerable to these concerns, as women are more likely to be elected or participate in progressive

areas where outcomes may be better for other reasons.

There is even less work on the mechanisms by which women’s participation might affect

outcomes. The only studies that provide well-identified evidence on the impacts of increased

participation ascribe differences in outcomes to different preferences (Chattopadhyay and Duflo

2004) or to discrimination (Duflo 2006). Both studies utilize the fact that since 1993, one-third

of the seats and presidencies of the rural village councils in India have been reserved for women,

and reserved seats are allocated amongst constituencies randomly. Chattopadhyay and Duflo

(2004) show that village councils headed by women were more likely to invest in public

infrastructure for drinking water, and, more generally, that councils dominated by a particular

gender were more likely to invest in goods important to that gender, where the importance of a

good to a gender was measured by the number of complaints made to the village council by that

gender about that specific public good. In a related paper, Topalova and Duflo (2004) analyze

the outcomes for women village council leaders. They show that, according to objective data

from technical audits of the number and quality of public goods available in the villages, women

provide more and better quality public goods than men do. Moreover they find that, on average,

women take significantly fewer bribes than men. However, subjective data ranks women’s

5 To take one example, Prokopy (2004) examines participation of women in water committees in 45 villages in two Indian states. All committees examined had one third female membership, as mandated by the state reservation system. The author compares committee and project performance four to six months after project initiation, and concludes that women’s participation (as measured by monetary contributions, attendance at committee meetings, and asking questions at meetings) does not matter for project success but that overall community participation does matter. As all committees have the same structure, Prokopy lacks a counterfactual with which to compare the level of female membership. The findings presented may also be vulnerable to omitted variable bias of unknown magnitude, as both participation and project success may be driven by unobserved community specific factors, making her results difficult to interpret.

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performance as village managers worse than men’s performance. Duflo (2006) attributes the

divergence in results to “the widespread perception that women are not competent leaders.”

In the experimental economics literature, there are some studies that may be helpful in

efforts to understand the underlying mechanisms by which gender might affect project outcomes.

Several experimental studies examine whether women supply differing levels of public goods or

are more cooperative than men (e.g., Solow and Kirkwood 2002, Eckel and Grossman 1998,

Nowell and Tinkler 1994). However, conclusions seem to be sensitive to the form of the

experiment performed and laboratory conditions may be quite different from real-world

situations.

III. Description of Project and Data

This paper uses data from a project implemented by several non-governmental

organizations (NGOs) that provided infrastructure for improved water quality in 334

communities in Western Kenya, facilitated the creation of user committees to manage and

maintain the local infrastructure, and provided additional financial support to a randomly

selected subset of the user committees. Due to administrative and funding constraints, the

project was implemented over a period of three years, with groups of communities phased in to

the project beginning in 2004, with the order of phase-in determined randomly. This paper

examines the impact of an intervention that encouraged women to take on a greater leadership

role in their communities’ user committees on both female participation and committee

performance.

The technology for improving water quality in this project is spring protection. Naturally

occurring springs are an important source of drinking water in East Africa, but when unprotected

this water is vulnerable to contamination, particularly from human and animal fecal matter.

Spring protection seals off the source of a naturally occurring spring and encases it in concrete so

that water flows out from a pipe rather than seeping from the ground, where it is vulnerable to

contamination from surface runoff. In a study of the health impacts of source water quality

improvements, my coauthors and I find that spring protection improves the quality of water at

the source, reducing fecal contamination by approximately three quarters, and has positive health

benefits for households: diarrhea among young children in treatment households falls about one-

fifth after up to thirty months of spring protection (Kremer et al. 2007). We also find that

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communities value this technology: we estimate willingness to pay (WTP) for improved source

water by analyzing how households change their choice of water source – and in particular, the

distance they are willing to walk to collect water – in response to the improvements generated by

spring protection, in a conditional logit discrete choice model. The revealed preference results

indicate that the average valuation of spring protection is on the order of US$4.52-9.05 per

household per year in an area where per the daily agricultural wage is around $2.20 (Kremer et

al. 2007).

In the project studied in this paper, the NGO coordinates and funds the engineering works

for spring protection, but requires a community contribution of approximately ten percent of the

total cost of protection, typically in the form of locally available materials (e.g., sand and stones)

that can be gathered by the community as well as unskilled labor provided by the community to

excavate the site and dig drainage trenches. After construction, protected springs require little

maintenance relative to wells with mechanical pumps, but some efforts are necessary to maintain

water quality and to extend the life of the protected spring. (Well-maintained springs can last for

up to 50 years, while poorly maintained springs deteriorate in 5 to 10 years.) Maintenance

activities include clearing the drainage ditches surrounding the spring so that the concrete

encasement does not become waterlogged and crack, and keeping the water catchment area for

the spring free of rubbish and the vegetation surrounding the spring slashed to prevent

contamination via seepage and to allow for maximum water flow.

In this area of Kenya, it is common for committees of users to perform these and other

maintenance activities at water sources. When implementing projects like this water quality

improvement program, NGOs typically follows a standard model for transferring control of the

infrastructure to the community. The NGO facilitates a community meeting where community

members elect a group of 9 to 12 users of the water source to form a management committee.

The committee members are provided with training by the NGO and government facilitators on

community leadership and how to manage the water source, but are then typically given no

further financial support in maintaining the water source.

For this particular water quality program, several variants on the standard model of

community management were introduced. First, in a randomly selected half of communities,

NGO staff administered a “female participation intervention” in which NGO facilitators used a

specially designed script to encourage women to participate on the user committees and explain

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the benefits of women’s leadership in maintaining water resources. Several other steps were also

taken to boost women’s participation at springs selected for the intervention. At these springs,

community meetings were held in the afternoons, when women typically have fewer domestic

tasks. The NGO has found that afternoon meetings are successful in boosting the attendance of

women, and that women are more likely to volunteer to be on the user committee if other women

are present at the community meeting. Prior to the community meetings at springs selected for

the female participation intervention, the local village elders (ligurus) were also informed that

the NGO was particularly interested in having women attend the community mobilization

meeting, and were asked to make a strong effort to notify women about the meeting and

encourage them to attend.

The female participation intervention was cross-cut with another randomized intervention

that varied the level of and delivery mechanism for external financial support for spring

maintenance, so that an equal number of springs in each maintenance intervention group were

exposed to the participation intervention. (Sample sizes for each of these cells are shown in

Table 1.) Committees also were randomly selected to receive one of three financing

interventions. The status quo model of infrastructure maintenance in this area is for the

government or an NGO to construct the infrastructure in a community; a committee of users is

then responsible for managing and maintaining the infrastructure with no further assistance from

the outside funder. One third of water management committees in this project followed this

financing model. At the second third of committees, the NGO provides a monthly grant to fund

maintenance of the spring. The user committee is responsible for maintenance activities at the

spring, and all maintenance costs above and beyond the NGO grant are the responsibility of the

local community. At the final third of committees, the NGO contracts directly with a spring

maintenance worker from the community to maintain the spring. The user committee and the

NGO jointly monitor the activities of the spring maintenance worker, but decisions on whether to

contract with or renew contracts with the worker is ultimately the responsibility of the NGO.

The monthly payment to the spring maintenance workers is equivalent to two days wages

at the local agriculture day labor rate (approximately $2.20 per day), as the NGOs estimate that

maintenance tasks will take approximately two full days each month. The spring maintenance

worker’s monthly pay is equivalent to the amount of the committee grant.

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The sample of communities participating in the infrastructure project was stratified on

baseline community characteristics, which NGO was overseeing the infrastructure and

committee training, and the year in which the project would be implemented and then randomly

assigned to receive a package of interventions. Table 1 shows the numbers of committees

receiving each combination of the participation and finance interventions at each of the 334

communities that participated in the project.6 The randomization of springs into the female

participation and finance interventions groups succeeded in creating comparable groups along

observable dimensions; there are no significant differences among groups in baseline water

quality (as measured by total and fecal coliform counts), number of households served, and

distance of the water source from a tarmac road (Table 2, Panel B).

Data

As protection of springs and formation of user committees occurred over a several year

period, some groups of user committees have a longer data collection history. Each committee

has between three and five observations on maintenance outcomes and information on user

committee composition over a two to three year period.

Information on user committee membership and changes in user committee membership

were collected to construct a roster of committee membership over time. A short survey was

administered to all user committee members immediately following their selection to the user

committee. Data collected includes members’ demographic information (e.g. age, education,

ethnicity), individual “social capital” measures (e.g. voluntary associational activities), and

knowledge of current spring maintenance conditions. The NGOs also provided all user

committees with a receipt book and a log book, and encouraged all committees to record

essential project data at all committee meetings. User group records were coded to obtain

information on: community contributions for construction and maintenance (both in cash and in

kind), attendance at committee meetings, financial records, and other committee activities. In

addition to the data from user committee records, field officers also administered a twice yearly

survey to the whole committee to obtain additional information on committee activities,

6 I have complete data for at least one followup round on 314 of the user committees. The 20 committees with incomplete data do not have significantly different baseline characteristics (results not shown).

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including data on repairs undertaken, income-generating activities implemented, and strategies

for managing financial resources.

To assess the quality of maintenance, enumerators made unannounced visits to the

springs several times each year, where they completed a standard survey instrument in which

they estimated how long it had been since a variety of maintenance tasks were performed and

how well each maintenance task was being performed. These maintenance tasks included: the

estimated number of days since the storm drains were unclogged, the time since the drainage

trenches have been cleaned, and the time since the catchment area surrounding the spring was

last cleared of brush. Enumerators completing the maintenance assessments were unaware of the

package of interventions that a given spring had received. During these visits, spring water

samples were also collected. The water samples were taken to a local laboratory for analysis,

where total coliform counts and e. coli counts (e. coli are an indicator bacteria for the presence of

diarrhea-causing fecal coliforms) were measured using the Colilert testing method (which is

easy-to-use and error-resistant in field laboratory conditions).

IV. Empirical Strategy

To assess the effectiveness of the female participation intervention on maintenance

outcomes at the spring, I examine a number of different measures of committee performance.

Due to the random assignment of the interventions to communities, any differences in outcomes

among the groups can be attributed to the interventions. In the discussion that follows, I focus

on maintenance activities and maintenance quality outcomes observed by trained enumerators, as

self reports seem unreliable (they have a very low correlation with enumerator reports; results

not shown). Regressions of committee actions on water quality measures show that maintenance

activities have a statistically significant impact on water quality, though the specific committee

activities that have in impact differ across the rainy and dry seasons (results not shown). Also,

over the three-year study period, I cannot directly observe the lifespan of the infrastructure.

However, I can look at factors that are plausibly correlated with infrastructure life, such as the

number of unrepaired cracks in the concrete structure of the spring, or eroded pipes. Regressions

of these factors on maintenance actions (such as clearing trenches) are statistically significant

(results not shown).

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The panel dataset contains between three and five observations on maintenance outcomes

and committee composition for each spring, with each round of data collection spaced

approximately six months apart. I first estimate the average treatment effect for committees that

received the intervention. The basic specification for the maintenance regressions is:

Outcomeit = α + β1Genderi + β2Granti + β3Contractori + ∑tγtroundt +

∑iGroupi*∑itSeasonit + ∑it Seasonit + ∑iGroupi + ∑itδXit + eit

where i indexes springs and t indexes round. Regressions include season-group fixed effects

throughout the analysis to account for seasonal differences in the need for maintenance and

possible differences among groups of springs in construction quality and committee training.

Regressions also include survey-round fixed effects and are clustered at the spring level. The

coefficients of interest are the betas on assignment to the gender and finance intervention groups.

Some specifications also include interaction terms to capture the effects of receiving both

participation and financing interventions. Other specifications also control for a variety of

characteristics of current user committee members (e.g., mean education level, mean age, mean

hygiene knowledge), the Xit in the specification above.

I examine the effects of the interventions on a variety of maintenance outcomes and I also

calculate the mean effect size over several baskets of (not perfectly correlated) maintenance

outcomes. To calculate mean effects, I use a technique that normalizes each of the K outcomes

in a given basket of outcomes by the standard deviation of the outcome, then tests the null

hypothesis of no average effect for all outcomes in the basket.7 I also use instrumental variables

to examine the effect of an exogenous change in the percentage of women on the user committee

on maintenance outcomes. The IV results can be interpreted as the local average treatment

effect: the effect on maintenance that can be attributed to the change in committee composition

caused by the intervention.

7 See Bloom et al. (2006), O’Brien (1984), Tamhane and Logan (2003), and Kling, Katz, Leibman, and Sonbanmatsu (2004) for more details and applications of this method.

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V. Results on Participation and Maintenance Outcomes

Participation

The female participation intervention was successful in boosting women’s participation

on water management committees. Figure 1 shows the distribution of women on user

committees in communities that received and did not receive the intervention. The number of

women on user committees that received the participation intervention increased by an average

of one woman, over a 20 percent increase, and this increase is statistically significant at the one

percent level (Table 2, Panel A). Furthermore, the female participation intervention seems to

have had a substantive impact; one possible community response to the intervention would be to

increase the committee size and simply add women to user committee membership rosters.

However, the average committee size is unchanged between groups, and the number of females

occupying leadership positions on the committee increases by 0.6 women on average, a 20

percent increase. The probability that the committee chair was female more than doubled with

the intervention: 27 percent of user committees that did not receive the intervention had female

committee heads, while 63 percent of user committees that received the intervention were headed

by females. Committees that received the participation intervention are also significantly more

likely to have a female secretary or assistant secretary.

Note that, on average, the number of women on committees is reasonably high in the

absence of the intervention. It could be that women are already quite well represented on user

committees and the marginal effect of the participation intervention is small in terms of

increasing effective female participation. However, the intervention did increase the proportion

of committees with a female majority by over 53 percent and increased the number of

committees with a 2/3 majority of female members by over 47 percent. If the effects of women’s

participation are nonlinear, perhaps because it is costly for women to communicate when men

are in the majority or because building consensus becomes easier with a significant majority, this

shift may be even more important for committee performance.

For a subset of user committees, I am able to compare the pre-intervention gender

composition to the post-intervention gender composition on average (Table 3) and over the

distribution of pre-intervention gender compositions (Figure 2). In this subset of 207

communities, one NGO implementing had already conducted an initial mobilization of user

committees in these communities prior to their involvement in the project and the introduction of

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the user committee interventions (which required re-mobilization of the user committees).

Committees that had fewer women before the intervention increased the number of women the

most. The intervention had the largest impact on committees where women were least likely to

be elected in the absence of the intervention. Advocacy efforts like this participation

intervention may thus be more successful than might be expected from a non-randomized study.

The percentage of women on committees also stays quite constant over time, and the

difference between committees that received and did not receive the female participation

intervention is persistent. Table 3 shows the percentage of female committee members at each

follow-up visit for each group of springs. Even three years after the intervention, the difference

between the groups is remarkably stable. The persistence of this effect suggests that a relatively

simple advocacy intervention can help to permanently overcome social costs that may hinder

women’s participation in the absence of the advocacy effort. Given that the intervention was

voluntary and that no follow-up interventions were conducted after the initial intervention, this

persistence suggests that the initial change in membership did not lead to adverse changes in

outcomes, which would likely have led to a shakeup in committee membership. Additionally,

this persistence is not due solely to tenure effects for the initial committee members. Committee

membership rotates frequently; the turnover rate on committees averaged around 16 percent over

the study period. The rate of change of membership was slightly higher in committees that

received the female participation intervention (16.8 percent versus 14.1 percent) and most of this

difference is due to higher turnover of female members on committees that received the

intervention. In this setting, long-term increases in women’s participation can be achieved

without mandatory reservation policies and without distorting the effectiveness of public goods

delivery.

Selection onto user committees

Using data from surveys of user committee members,8 I find no significant differences in

the characteristics of women on committees that did and did not receive the female participation

8 Over 91 percent of initial user committee members completed a survey, and almost 90 percent of all 4,153individuals who ever served as committee members completed a member survey. Committee members who did not complete the survey were more likely to leave the committee prior to the end of the study and were less likely to be in leadership positions. Non-surveyed members were slightly more likely to be female (results not shown).

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intervention (see Table 4).9 There are also no significant differences between the men on

committees that received and did not receive the intervention. The participation intervention did

not appear to encourage more educated women or women who had a better understanding of

hygiene behavior to join committees, nor did it appear to displace males who were better or

worse qualified than the average male. The lack of differential selection due to the female

participation intervention suggests that the quality of committee members does not appear to be

suffering as a result of the intervention. Further, because there is not differential selection any

effects of the intervention on committee performance can be attributed to the increased female

participation and not to other changes in committee composition.

In general, female committee members have 1.3 fewer years of education than male

members (5.6 versus 6.9 years) and are about six years younger (38 versus 44). Women report

making about three times as many trips to the water sources to collect water than do male

members (20 versus 7 trips in the past week), which is unsurprising given that water collection is

frequently viewed as women’s work in this region. Thus, committees that received the female

participation intervention have slightly lower mean education levels and slightly more existing

monitoring capabilities. Male and female members have similar levels of involvement in the

community (as measured by participation in other community activities) and have similar

knowledge of hygiene behaviors.

There are also very few differences in the characteristics of men and women members of

committees that received grant funding under the financing intervention or committees in

communities where maintenance was conducted by a private contractor (results not shown).

These results contrast with Kremer and Gugerty (2004), who find in their study of women’s

groups in Kenya that financial and other support for groups provided by an NGO program

changed the composition of the groups, drawing in younger and wealthier women who were

more likely to be employed in the formal sector. Perhaps there is less selection in this case

because funds made available to committees were publicly earmarked for a specific purpose

(spring maintenance) and there was less discretion over the use of the funds. In addition, the

funding amounts involved in this study were significantly smaller.

9 Results shown in Table 4 are for members initially selected to user committees, but results including members who joined committees later are very similar (results not shown).

16

Maintenance outcome results

There is no significant effect on maintenance outcomes from receiving the female

participation intervention. Table 5 shows reduced form estimates for a basket of outcome

measures capturing the natural log of the time (measured in days) since a variety of maintenance

activities were last performed and the mean effect over all outcomes in the basket. The point

estimates on the indicator of assignment to the participation intervention are very close to zero in

all specifications, as are the mean effects. With 95 percent confidence, I can reject differences in

outcomes between committees that received and did not receive the intervention of more than

around eight percent (as measured at the mean for the comparison group).10 Table 6 shows the

results for outcome variables that quantify the quality of maintenance at the water source, as

measured on a scale from 1= very poor to 5= excellent. Once again, the point estimates on the

indicator of assignment to the female participation intervention are very close to zero, as are the

mean effects. With 95 percent confidence, I can reject differences in outcomes larger than about

five percent (as measured at the mean for the comparison group).

The instrumental variables estimates of the local average treatment effect of the

intervention also show no negative impacts of changes in participation induced by the

intervention (Table 7). As could be expected from Figure 1 and Table 3, the first stage result for

the effect of the female participation intervention on the percentage of women members on the

committee is strong (results not shown). However, the increase in the percentage of women on

the committee due to the participation intervention has no effect on a wide variety of

maintenance outcomes. The IV results are also very similar for committees that have female

chairs due to the intervention (results not shown). Thus, women who joined committees or took

on leadership positions due to the intervention do no worse at maintaining the spring than the

committee members they replaced, though they do not do better either. The results in Tables 5

through 7 imply that we are able to reject the null hypothesis that encouraging women to

participate more in managing community water sources leads to significant declines (or

increases) in maintenance quality. In this context, increasing women’s participation does not

distort the quality of public goods provision in communities.

10 Also note that there is significant variation in all outcome variables, even after accounting for seasonal variation (results not shown). The standard deviations of the outcome variables for the comparison group are shown in Table 5.

17

I also use non-parametric Fan regressions to examine whether the effects of these

interventions differs over the distribution of gender ratios on user committees. Figure 3 graphs

the difference in outcomes between committees that received the participation intervention and

committees that did not by pre-intervention gender composition, with bootstrapped standard

errors. There are not significant differences in outcomes for any part of the distribution, which

suggests that committees on which participation changed the most due to the intervention are

able to maintain the same level of effectiveness of public goods provision.

Financing interventions and interactions

It is useful to compare the results on maintenance outcomes from the female participation

intervention to the results of other user committee interventions to provide a benchmark for the

observed effect sizes. On average, there seems to be some improvement in maintenance

outcomes and maintenance quality at water sources where the committee received a grant. In

communities where private contractors were responsible for maintenance, there is a large and

significant impact on maintenance outcomes and maintenance quality (Tables 5 and 6).

However, this effect seems sensitive to monitoring effort; from January 2007, the implementing

NGOs began working with government water officers to monitor private contractors on a

monthly basis. In a specification in which round is interacted with assignment to the grant and

contractor groups to allow for differential effects over time, I find that outcomes improve

substantially in the last round of data collection after the increases in monitoring effort began

(results not shown).

Committees that were randomly selected to receive both the female participation

intervention and either the grant or the private contractor intervention did not perform

significantly differently. Conditional upon assignment to the gender and financing groups, there

is no differential effect of providing financial assistance to groups that received the participation

intervention. Thus, committees with higher female participation do as well on average at

managing resources and supervising workers as other committees.

Community spillovers

Even though increasing female participation does not impact maintenance outcomes,

such advocacy efforts may have spillover effects elsewhere in the community, for instance due to

18

increased female leadership capacities. I can also use the exogenous variation in committee

membership generated by the female participation intervention to explore whether ‘social capital

externalities’ exist for participation on user committees. Externalities could occur at both the

individual level and for the community level.11 User committees are often springboards for other

economic activities: for instance, user committees may band together for income generating

activities (IGA) to cover maintenance expenses for the spring and distribute extra profits among

themselves, and user committees might also become rotating savings and credit associations

(ROSCAs). Membership on a user committee might thus bring access to additional income for

an individual. User committees might also perform a ‘bridging’ function, wherein committee

members gain access to either other committee members who are highly placed in society or to

outsiders (e.g., government representatives, local chiefs, etc.) with whom they might not have

come into contact in the absence of being a committee member. Such connections could

generate positive benefits to committee members such as leads on jobs or prestige. At the

community level, spring user committees might also assist with the development of other local

public goods. For instance, a committee could assist other groups with organizing a fundraiser

(called a harambee in Kiswahili) for improving a school compound.

I find no evidence that committees that received the participation intervention participate

in more income generating activities, or engage in more activities that are beneficial to the

community (such as tree planting). I do, however, find suggestive evidence that committees that

receive grants are more likely to engage in income generating activities, likely because they use

the grant money as startup funds for the activity (Table 8).12

VI. Discussion and Conclusions

Using data from a unique randomized evaluation of community-managed water projects,

I evaluate the effects of interventions to encourage female participation on user committees and

interventions to provide different forms of financial support for maintenance activities. I find

that encouraging women to take up management roles on user committees works to increase

11 Participating on local user committees may be quite costly for members, as they may involve a significant time commitment with no salary. The time commitment makes it less likely that community members with full time, formal sector employment will become committee members. However, if there are externality benefits that accrue to committee members, the costs of participation may be altered. 12 It is difficult to investigate effects of community participation on individual members at this time, as I only have individual-level data on committee members at the time they joined the committee.

19

women’s participation. To the extent that this is a desirable outcome in and of itself, the

intervention was successful. In this context, it is possible to increase women’s participation

without sacrificing the quality of project outcomes: there is no tradeoff in meeting the dual

objectives of increasing female participation and having well-managed local public goods.

Further, depending on the relative costs of men’s and women’s time and the quantities of time

needed, increased women’s participation may lead to greater social efficiency if the total cost of

time spent on management activities for local public goods is decreased for the same level of

management output. There is no evidence of spillovers to other areas of community

development from increased women’s participation. Gender advocacy can thus be a useful

means of increasing female participation, with little distortion in the effectiveness of these

committees in delivering public goods.

20

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Figure 1: Distribution of Women on User Committees

01

23

45

Ke

rne

l De

nsity

0 .2 .4 .6 .8 1Percent women

GE No GE

Epanechnikov kernel with optimal bandwidth

Distribution of Women on User Committees

24

Figure 2: Difference in Percent Women on User Committee Before and After Intervention

-.0

50

.05

.1.1

5.2

.25

.3D

iffe

ren

ce in

Pe

rce

nt

Wo

me

n

0 .2 .4 .6 .8 1Percentage women on spring user committee prior to intervention

Treatment - Comparison

Quartic Kernel, Bandwidth = .8

Difference in Percent Women Versus Percent Women at Baseline:Fan Regression

25

Figure 3: Fan regression of difference in days since trenches last cleared across groups

-20

02

04

0D

iffe

ren

ce in

Day

s si

nce

tre

nch

es la

st c

lear

ed

0 .2 .4 .6 .8 1Percentage women on spring user committee prior to intervention

Treatment - Comparison

Quartic Kernel, Bandwidth = .8

Difference in Trenches Last Cleared Versus Percent women:Fan Regression

26

Table 1: Sample Sizes for Interventions

Grant Private Contractor No Financial Support TotalFemale Participation Intervention 58 54 56 168No Female Participation Intervention 55 54 57 166Total 113 108 113 334

Table 2: User Committee Summary Statistics

Female participation intervention

No Female participation intervention Difference

mean (sd)

# obs mean (sd)

# obs

(Int.-No Int.)

Panel A: Committee characteristicsNumber of people on committee 9.18 164 9.18 164 0.00

(0.59) (0.60) [0.065]Number of women on committee 5.99 164 4.91 164 1.08

(1.06) (1.79) [0.162]***% women on committee 0.65 164 0.54 164 0.12

(0.11) (0.19) [0.017]***Chair female 0.63 164 0.27 164 0.36

(0.48) (0.44) [0.051]***Vice chair female 0.53 156 0.56 156 -0.03

(0.50) (0.50) [0.057]Secretary female 0.62 164 0.48 164 0.15

(0.49) (0.50) [0.055]***Treasurer female 0.76 164 0.74 164 0.02

(0.43) (0.44) [0.048]Ass't secretary female 0.78 153 0.67 157 0.12

(0.41) (0.47) [0.050]**Number of leadership positions filled 5.34 164 5.39 164 -0.05

(0.69) (0.68) [0.075]Number of female leaders 3.58 164 2.99 164 0.59

(1.12) (1.41) [0.141]***% women leaders 0.67 164 0.55 164 0.12

(0.19) (0.25) [0.025]***Panel B: Baseline characteristics

baseline E. Coli counts (MPN) 115 134 153 134 (38)(297) (364) [40.6]

baseline total coliform counts (MPN) 1689 134 1704 134 (15)(853) (825) [102]

Number of households that use spring 24.06 139 24.40 137 -0.34(14.79) (11.57) [1.600]

Distance (m) to nearest tarmac road 531.31 139 468.04 137 63.27(780.85) (785.05) [94.26]

total community contribution 8439.05 166 9798.45 163 -1359.40(4521.99) (14342.15) [1,168]

27

Table 3: Percentage of female members on water user committees over time

Group Obspre-

interventionat

mobilizationfollowup

1followup

2followup

3followup

4followup

5

NYG (Female Part. Int.) 105 46.64 67.25 66.79 65.72 66.07(26.68) (8.32) (8.38) (9.78) (12.23)

NYG (No Female Part. Int.) 101 48.18 56.78 56.77 56.61 56.59(26.00) (20.87) (20.65) (21.01) (20.54)

Difference -1.54 10.47 10.02 9.11 9.48

South Wanga (Female Part. Int.) 20 61.48 63.44 61.91 66.41 (7.75) (8.81) (10.07) (13.58)

South Wanga (No Female Part. Int.) 20 47.99 49.66 52.44 47.74 (14.27) (14.01) (12.98) (14.24)

Difference 13.49 13.78 9.47 18.66

ICS 2005 protection (Female Part. Int.) 19 64.04 63.44 64.41 65.21 68.56 (10.37) (9.16) (10.04) (13.12) (14.46)

ICS 2005 protection (No Female Part. Int.) 22 47.86 50.84 50.32 53.41 53.85 (18.16) (18.85) (18.47) (18.56) (15.06)

Difference 16.17 12.60 14.09 11.80 14.71

ICS 2004 protection (Female Part. Int.) 23 59.30 59.37 60.59 61.84 61.34 63.06 (18.11) (18.44) (18.24) (18.61) (18.68) (18.59)

ICS 2004 protection (No Female Part. Int.) 23 50.18 47.28 49.65 49.99 49.49 55.52 (15.64) (14.29) (13.14) (12.43) (13.30) (13.83)

Difference 9.12 12.09 10.95 11.84 11.85 7.55

28

Table 4: Characteristics of user committee members

Women Men

Part. Int.No Part.

Int.

Part. Int.-No Part.

Int. Part. Int.No Part.

Int.

Part. Int.-No Part.

Int.Mean (SD)

Mean (SD)

Difference(SE)

Mean (SD)

Mean (SD)

Difference(SE)

Age (years) 38.30 38.60 0.30 44.76 44.23 -0.52(11.20) (11.46) (0.57) (14.39) (14.23) (0.94)

Highest level of education completed 5.74 5.63 -0.11 7.04 6.90 -0.14(3.75) (3.79) (0.17) (3.45) (3.51) (0.22)

Farmer [y/n] 0.92 0.92 0.00 0.87 0.85 -0.02(0.27) (0.27) (0.02) (0.34) (0.36) (0.02)

Social capital index 2.73 2.72 -0.01 2.46 2.41 -0.05(1.65) (1.61) (0.09) (1.86) (1.72) (0.12)

Member of women's group? [y/n] 0.59 0.61 0.02 0.24 0.23 -0.01(0.49) (0.49) (0.03) (0.43) (0.42) (0.03)

Member of savings/credit group? [y/n] 0.55 0.53 -0.03 0.54 0.52 -0.03(0.19) (0.20) (0.02) (0.20) (0.21) (0.02)

Hygiene knowledge index 3.74 3.91 0.18 3.77 3.61 -0.16(2.10) (2.13) (0.12) (1.96) (1.98) (0.12)

Iron roof indicator 0.78 0.79 0.01 0.71 0.68 -0.03(0.41) (0.41) (0.02) (0.46) (0.47) (0.03)

Distance from spring (minutes) 9.31 9.58 0.28 7.75 8.06 0.31(7.62) (7.91) (0.43) (5.92) (6.21) (0.41)

Parent of youngest child in compound? [y/n] 0.62 0.59 -0.03 0.74 0.73 -0.01(0.49) (0.49) (0.02) (0.44) (0.45) (0.03)

Pit latrine in compound? 0.92 0.91 -0.01 0.95 0.95 -0.01(0.27) (0.29) (0.02) (0.21) (0.25) (0.01)

# of bicycles owned 0.93 0.86 -0.06* 0.99 0.96 -0.03(0.73) (0.71) (0.04) (0.74) (0.64) (0.04)

Own mosquito net? 0.68 0.71 0.03 0.67 0.66 -0.01(0.47) (0.45) (0.03) (0.47) (0.47) (0.03)

Boiled water yesterday? [y/n] 0.26 0.25 0.00 0.26 0.27 0.01(0.44) (0.43) (0.03) (0.44) (0.45) (0.03)

# trips to spring in past 7 days 19.72 19.68 -0.05 5.74 5.80 0.05(12.07) (12.38) (0.68) (9.99) (9.18) (0.65)

# children in compound 4.23 4.32 0.08 4.42 4.26 -0.16(3.10) (3.61) (0.17) (3.65) (3.17) (0.21)

Observations 1044 901 553 699Notes: * significance at 10%, **, significance at 5%, *** significance at 1%

29

Table 5: Effects of User Committee Interventions on Maintenance Outcomes

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15) (16)

dependent variable: ln(days since last slashed) ln(days since trenches last cleared) ln(days since storm drain last cleared) mean effects

Indicator of assignment to participation int. 0.02 0.03 0.01 -0.01 -0.01 -0.01 -0.01 -0.01 -0.07 -0.03 0 0.07 0.02 0.00 0.08 0.06

(0.23) (0.21) (0.20) (0.04) (0.10) (0.08) (0.07) (0.10) (0.65) (0.19) (0.02) (0.41) (0.39) (0.19) (0.19) (0.36)

Indicator for assignment to 'Grant' group -0.16 -0.14 -0.17 -0.19 -0.14 -0.07 -0.18 -0.14 -0.17 -0.14 -0.16 -0.14 0.14 0.10 0.16 0.14

(1.75) (1.09) (1.86) (1.41) (1.52) (0.61) (1.99) (1.13) (1.48) (0.83) (1.30) (0.75) (1.90) (1.01) (2.11) (1.29)

Indicator for assignment to 'Contractor' group -0.25 -0.26 -0.29 -0.3 -0.39 -0.46 -0.45 -0.52 -0.38 -0.36 -0.42 -0.34 0.30 0.32 0.33 0.33

(2.62) (1.85) (2.91) (2.13) (3.92) (3.26) (4.57) (3.62) (3.04) (1.97) (3.40) (1.81) (3.83) (2.83) (4.25) (2.93)

Part. Int.*Grant -0.04 0.03 -0.13 -0.1 -0.06 -0.04 0.07 0.04

(0.22) (0.13) (0.71) (0.55) (0.23) (0.16) (0.46) (0.30)

Part. Int.*Contractor 0 0.04 0.15 0.13 -0.04 -0.17 -0.03 0.01

(0.01) (0.18) (0.74) (0.65) (0.17) (0.65) (0.37) (0.55)

Baseline ln(ecmpn) -0.05 -0.05 -0.04 -0.05 -0.04 -0.04

(2.20) (2.21) (1.99) (2.07) (1.49) (1.44)

Distance from spring (committee mean) 0 0 0.01 0.01 -0.01 -0.01

(0.14) (0.12) (0.82) (0.82) (0.92) (0.88)

Iron roof indicator? (committee mean) -0.4 -0.4 -0.32 -0.31 -0.73 -0.76

(2.04) (2.00) (1.73) (1.63) (2.78) (2.90)

Hygiene knowledge (committee mean) -0.05 -0.05 -0.07 -0.08 0 0.01

(0.97) (0.98) (1.18) (1.32) (0.01) (0.12)

Social capital (committee mean) 0.03 0.03 -0.02 -0.02 0 0

(0.40) (0.41) (0.34) (0.28) (0.03) (0.05)

Years of education (committee mean) 0.09 0.09 0.08 0.08 0.05 0.05

(3.05) (3.03) (2.22) (2.33) (1.24) (1.17)

Age (committee mean) 0 0 0 0 0 0

(0.17) (0.16) (0.28) (0.37) (0.14) (0.17)

Youngest child under 3? (committee mean) 0 0 0.01 0.04 0.22 0.21

(0.02) (0.01) (0.04) (0.16) (0.65) (0.61)

Constant 3.34 3.33 3.73 3.74 3.15 3.15 3.19 3.17 3.6 3.6 3.78 3.79

(20.20) (18.66) (8.28) (8.17) (13.07) (12.73) (6.27) (6.11) (7.61) (7.59) (5.24) (5.23)

Observations 1060 1060 955 955 1061 1061 958 958 556 556 511 511

R-squared 0.09 0.09 0.11 0.11 0.08 0.09 0.1 0.1 0.04 0.04 0.07 0.07

Mean (s.d.) of dep. var. in comparison group: 3.11 (1.15) 2.89 (1.19) 3.15 (1.09)

T-statistics in parenthesis below regression coefficients. All regressions are OLS and include season-group fixed effects and round fixed effects.

30

Table 6: Effects of User Committee Interventions on Maintenance Quality

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

dependent variable:quality of catchment area

maintenancequality of trench

maintenancequality of storm drain

maintenanceoverall maintenance

quality mean effects

Indicator of assignment to participation int. 0 0.09 0.06 0.11 0.12 0.24 -0.04 -0.01 0.04 0.11(0.04) (0.64) (0.77) (0.75) (1.32) (1.68) (0.47) (0.07) (0.73) (0.89)

Indicator for assignment to 'Grant' group 0.26 0.35 0.27 0.29 0.26 0.34 0.27 0.29 0.28 0.33(2.75) (2.56) (2.76) (2.08) (2.52) (2.19) (2.92) (2.08) (3.09) (2.52)

Indicator for assignment to 'Contractor' group 0.43 0.48 0.45 0.49 0.36 0.45 0.47 0.49 0.45 0.50(4.38) (3.36) (4.34) (3.27) (3.33) (2.87) (4.92) (3.42) (4.79) (3.65)

Part. Int.*Grant -0.17 -0.05 -0.17 -0.04 -0.11(0.91) (0.26) (0.81) (0.21) (0.62)

Part. Int.*Contractor -0.09 -0.09 -0.19 -0.04 -0.11(0.47) (0.41) (0.86) (0.21) (0.55)

Constant 3.13 3.17 2.43 2.44 3.12 3.18 2.65 2.67(23.21) (21.57) (4.85) (4.86) (18.53) (18.30) (6.40) (6.31)

Observations 807 807 806 806 561 561 733 733R-squared 0.06 0.06 0.08 0.08 0.09 0.09 0.15 0.15

T-statistics in parenthesis below regression coefficients. All regressions are OLS and include season-group fixed effects and round fixed effects.

31

Table 7: Instrumental variables estimates of effects of female participation on maintenance outcomes

(1) (2) (3) (4) (5) (6) (7) (8)ln(days since last

slashed)ln(days since trenches last

cleaned)ln(days since storm drain last

cleared) mean effects

Percentage of women on user committee 0.17 0.13 -0.08 -0.13 -0.52 -0.02 0.13 0.00(0.24) (0.17) (0.11) (0.17) (0.55) (0.02) (0.36) (0.14)

Indicator for assignment to 'Grant' group -0.12 -0.13 -0.11 -0.16 -0.14 -0.14 0.11 0.13(1.29) (1.43) (1.29) (1.77) (1.21) (1.13) (1.52) (1.73)

Indicator for assignment to 'Contractor' group -0.21 -0.24 -0.37 -0.42 -0.33 -0.39 0.27 0.31(2.21) (2.50) (3.76) (4.28) (2.59) (3.16) (3.42) (3.97)

Baseline ln(ecmpn) -0.05 -0.05 -0.04(2.17) (2.20) (1.44)

Distance from spring (committee mean) 0 0.01 -0.02(0.25) (0.68) (0.92)

Iron roof indicator? (committee mean) -0.44 -0.33 -0.75(1.95) (1.56) (2.38)

Hygiene knowledge (committee mean) -0.05 -0.06 -0.01(0.88) (1.00) (0.12)

Social capital (committee mean) 0.04 -0.01 0(0.56) (0.20) (0.03)

Years of education (committee mean) 0.09 0.07 0.05(2.49) (1.77) (1.25)

Age (committee mean) 0 0 0(0.31) (0.18) (0.11)

Youngest child under 3? (committee mean) 0.08 0.06 0.25(0.32) (0.20) (0.69)

Constant 3.45 3.2 3.08 3.2 3.81 3.77(8.07) (3.42) (6.84) (3.50) (5.49) (2.94)

Observations 1033 933 1035 937 542 500R-squared 0.09 0.1 0.08 0.1 0.03 0.06

T-statistics in parenthesis below regression coefficients. All regressions include season-group fixed effects and round fixed effects. Excluded instrument is assignment to the female

participation intervention.

32

Table 8: Effects of User Committee Interventions on Other Community Outcomes

(1) (2) (3) (4)

IGA? trees planted?

Indicator of assignment to participation int. -0.01 0 -0.02 -0.02(0.52) (0.09) (0.51) (0.41)

Indicator for assignment to 'Grant' group 0.07 0.08 0.07 0.08(2.10) (1.83) (1.57) (1.25)

Indicator for assignment to 'Contractor' group 0.05 0.06 0.1 0.07(1.39) (1.39) (2.15) (1.10)

Part. Int.*Grant -0.02 -0.03(0.36) (0.29)

Part. Int.*Contractor -0.03 0.04(0.46) (0.49)

Baseline ln(ecmpn) 0 0 0.01 0.01(0.54) (0.55) (0.68) (0.65)

Distance from spring (committee mean) 0 0 0 0(0.68) (0.64) (0.36) (0.36)

Iron roof indicator? (committee mean) 0.02 0.01 0.11 0.12(0.25) (0.21) (1.12) (1.21)

Hygiene knowledge (committee mean) 0.04 0.04 0 0(2.21) (2.23) (0.09) (0.20)

Social capital (committee mean) 0.03 0.03 -0.02 -0.01(1.18) (1.15) (0.54) (0.50)

Years of education (committee mean) 0.01 0.01 0.01 0.01(0.88) (0.84) (0.66) (0.73)

Age (committee mean) -0.01 -0.01 0 0(2.46) (2.43) (0.85) (0.90)

Youngest child under 3? (committee mean) 0.1 0.1 -0.1 -0.09(1.18) (1.17) (0.88) (0.78)

Constant 0.52 0.51 -0.18 -0.19(3.65) (3.61) (0.99) (1.01)

Observations 966 966 966 966R-squared 0.27 0.27 0.15 0.15T-statistics in parenthesis below regression coefficients. All regressions are OLS and include season-group fixed effects and round fixed effects.