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Understanding institutional persistence: Exposure to community-driven development and the value of autonomy and democracy
Last registered on June 14, 2019

Pre-Trial

Trial Information
General Information
Title
Understanding institutional persistence: Exposure to community-driven development and the value of autonomy and democracy
RCT ID
AEARCTR-0002709
Initial registration date
February 20, 2018
Last updated
June 14, 2019 7:26 AM EDT
Location(s)
Region
Primary Investigator
Affiliation
Institute for International Economic Studies
Other Primary Investigator(s)
PI Affiliation
NGO Forum for Public Health
PI Affiliation
Stockholm University
Additional Trial Information
Status
Completed
Start date
2015-08-04
End date
2018-12-31
Secondary IDs
Abstract
Why don't communities adopt democratic or inclusive institutions after a community-driven development program, despite professing higher pro-social values in surveys? Using a novel field experiment which elicits ex-ante valuation of different decision-making processes, combined with a randomly-assigned community-driven development program, we distinguish between three potential explanations: experimenter demand effects in surveys; preferences over different approaches to decision-making; and resistance to change from vested interests.
External Link(s)
Registration Citation
Citation
Cocciolo, Serena, Ahasan Habib and Anna Tompsett. 2019. "Understanding institutional persistence: Exposure to community-driven development and the value of autonomy and democracy." AEA RCT Registry. June 14. https://doi.org/10.1257/rct.2709-2.0.
Former Citation
Cocciolo, Serena et al. 2019. "Understanding institutional persistence: Exposure to community-driven development and the value of autonomy and democracy." AEA RCT Registry. June 14. https://www.socialscienceregistry.org/trials/2709/history/48098.
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Experimental Details
Interventions
Intervention(s)
We evaluate a CDD program consisting of a package of technical advice and subsidies for the installation of new sources of safe drinking water in rural Bangladeshi communities with highly arsenic-contaminated drinking water. The program has strong participatory components, requiring decisions to be taken by unanimous consensus in the presence of project staff at community meetings at which different social groups are represented; the most important decisions concern the location of new sources of safe water within the community. The consensus-based approach contrasts sharply with local, informal decision-making processes, which are often restricted to elites and influential individuals and in which women play only a restricted role.

We evaluate whether exposure to democratic practices via the CDD program alters preferences over different types of institutional arrangements with respect to the future implementation of an intervention to provide a local public good: in this case, a communal source of safe drinking water. To measure preferences over institutional arrangements, we implement a novel field experiment which elicits preferences over three potential decision-making processes: decision-making in the perceived best interest of the community by implementing agency staff; decision-making using the community's own, pre-existing institutions; and consensus-based community decision-making. We elicit participants' differential willingness to pay (WTP) for these different institutional arrangements by offering a series of choices between two decision-making processes and two subsidy levels. To make the elicitation procedure incentive compatible and strategy-proof, we randomly assign 34 communities to receive a new water source. For these communities, we randomly extract one approach-subsidy pair, and we implement the new project under the option most preferred on average in the community.
Intervention Start Date
2015-10-15
Intervention End Date
2018-12-31
Primary Outcomes
Primary Outcomes (end points)
The main hypothesis we will test is that valuation of the consensus-based approach increases with the exposure to our CDD program, relative to both decision-making by an external agent and decision-making by local institutions. Therefore, our main outcomes of interest are:
1) WTP for consensus-based community decision-making vs decision taken by implementing agency staff;
2) WTP for consensus-based community decision-making vs decision-making using the community's own, pre-existing institutions.
Primary Outcomes (explanation)
We calculate WTP for approach A vs approach B as the highest difference in community contribution requirement between approach A and B, at which the participant does not choose approach B. We let contribution requirements for option A take the following values: 5,000 BDT; 4,000 BDT; 3,500 BDT; 3,250 BDT; 3,000 BDT; 2,750 BDT; 2,500 BDT; 2,000 BDT; 1,000 BDT. We keep the contribution requirement for option B fixed at 3,000 BDT. If the participant chooses option A at all prices up to and including 3,500 BDT, the WTP for A vs B is 500. We assign WTP for A vs B as = -3,000 BDT if the participant always chooses approach B at any community contribution variation.
Secondary Outcomes
Secondary Outcomes (end points)
We also evaluate how the distribution of willingness to pay changes with exposure to CDD. Additionally, we will explore whether the main effect is mediated by an effect of the CDD program on expected outcomes associated to each decision-making process, specifically: new water source location and own contribution.
Secondary Outcomes (explanation)
For each participant, we randomly extract one approach-pair and we elicit beliefs on expect location and own contribution at the marginal subsidy-pair.
Experimental Design
Experimental Design
We conducted the CDD program in 171 communities eligible for receiving the arsenic mitigation program. The mean community size is 153 households. We selected communities for inclusion based on their baseline level of arsenic contamination: (i) communities where more than 25% of sources of drinking water are arsenic-contaminated; (ii) or communities where arsenic-contaminated water sources are geographically concentrated. We randomly select 129 communities for receiving the program at public lotteries. Treated communities are further randomly assigned to three requirements for co-funding the installation costs: no contributions; cash contributions; labor contributions. Under the CDD program, communities first select locations for the subsidized safe sources of drinking water and agree on how to divide the community contributions, where applicable. These decisions are taken by consensus at a community meeting with representation of women and the poor, and in the presence of project staff who act as moderators. Communities must then raise or coordinate the community contributions before the wells are installed. Communities also take responsibility for maintenance and if necessary repair of the wells after they are installed.

After project implementation in treated communities, we carry out a field experiment where we elicit both stated and incentivized preferences over three different decision-making processes, each of which could be used to take decisions regarding installation of a future source of safe drinking water. The three decision-making processes are: decision-making in the perceived best interest of the community by implementing agency staff; decision-making using the community's own, pre-existing institutions; and consensus-based community decision-making, as in the original CDD program.

We will carry out the follow-up field experiment in all study communities in which installation of a new safe water source is expected to be hydro-geologically feasible. For communities where we know that installation of a safe water source is unlikely to be hydro-geologically feasible, it does not make sense to ask questions about a new, hypothetical source of safe drinking water. The expected sample size is 165 communities: 42 control communities and 123 communities that received the CDD program. Selectively dropping some treated communities potentially induces imbalance between treated and control groups, if the conditions which lead to failure in installation are not as good as randomly assigned, so we will report results with and without the area most highly affected by hydrogeological constraints to installation, which are geographically clustered.

The field experiment is an incentivized willingness to pay (WTP) elicitation. Specifically, we elicit participants' differential (WTP) for different institutional arrangements by offering a series of choices between two decision-making processes and two subsidy levels. For each pair of decision-making processes, we ask respondents to choose between one decision-making process at a baseline subsidy level, and the alternative decision-making process at a varying subsidy level. The baseline subsidy level corresponds to a community contribution of 3,000 Bangladeshi taka per installed tubewell. Choosing one decision-making process over another decision-making process paired with a lower (higher) subsidy rate implies a positive (negative) differential WTP for the first decision-making process. We will implement the WTP elicitation on average in 42 households per community, for a total of 6,905 participants. The study households in the main sample are randomly selected from administrative lists.

After administering the field experiment, we then assign 34 communities to receive a new water source by public lottery. For treated communities, this may be additional to the water source already offered under the original CDD program. For each community selected to receive a new water source, we determine the decision-making process and the subsidy level for the implementation as follows: first, we randomly select two out of the three decision-making approaches; second, we extract one pair of subsidy levels from those which were offered during the elicitation process; finally, we apply majority rule on the resultant choice between two combinations of decision-making approaches and subsidy level. This design makes the elicitation procedure incentive compatible and strategy-proof: each community has a positive probability of receiving the new source, and respondents should truthfully report their preferences, as long as they believe there is a non-zero probability that their preferences influence the final decision. The design also ensures that no choices expressed by any participant are revealed at any stage of the experiment, preventing confounding factors due to peer pressure or reputation concerns, and minimizing risks for individuals involved in the study.
Experimental Design Details
Randomization Method
We randomly assign communities to receive the original CDD program by public lottery, stratified by Union Parishad. We also randomly select communities to receive the additional safe water source construction program by public lottery, stratified by Union Parishad. Each community selected to receive a new water source is randomly assigned at the same public lottery to a choice between one decision-making process at the baseline subsidy, and an alternative decision-making process. The final decision-making process and subsidy for implementation are then determined as described in the experimental design above.
Randomization Unit
Each randomization is performed at Treatment Unit level. Treatment Units consist of groups of 50-250 households, defined along natural geographic boundaries using administrative lists, GPS data and satellite imagery. We use the language “treatment unit” and community interchangeably in this document.
Was the treatment clustered?
Yes
Experiment Characteristics
Sample size: planned number of clusters
We carried out the CDD program in 171 communities, 129 selected to receive the intervention and 42 assigned to the control group We conduct the follow-up field experiment in all communities recruited in the CDD program excluding those treated communities where, based on hydro-geological constraints experienced during the implementation of the CDD program, we expect the installation of a new safe water source to be hydro-geologically unfeasible. The remaining sample consists of 165 communities, 42 assigned to the control group and 123 treated communities.
Sample size: planned number of observations
Outcomes using household survey data: 6,905 households (target). Treatment Unit outcomes: 165.
Sample size (or number of clusters) by treatment arms
The arsenic mitigation program was designed as follows: 42 control Treatment Units; 129 treated Treatment Units, evenly divided over three contribution requirements: no contributions; cash contributions; labor contributions.

After excluding those treated communities where, based on hydro-geological constrained experienced during the implementation of the CDD program, we expect the installation of a new safe water source to be hydro-geologically unfeasible, the remaining sample consists of: 42 control Treatment Units; 123 treated Treatment Units: 42 communities in the waiver group; 42 communities in the cash contributions group; 39 in the labor contributions group.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
According to our most conservative power calculation, which relies only on the variation at community level, with standard significance level at 5% and power 80%, the minimum detectable effect is 0.50 standard deviations for the baseline comparison between control and treated communities. With our preferred specification at participant level, the minimum detectable effect reduces to 0.28-0.36 standard deviations, assuming intra-cluster correlations between 0.3 and 0.5. The intra-cluster correlation range is based on the distribution of the WTP for participatory decision-making measured during a related lab-in-the-field experiment carried out in the same communities.
Supporting Documents and Materials

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IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
Ethical & Independent Review Services
IRB Approval Date
2018-02-15
IRB Approval Number
17078-01A
Analysis Plan
Analysis Plan Documents
Pre-Analysis Plan

MD5: c5800d97a352286f51dc3f598a55b1ba

SHA1: f6f3145ebbd524470ff3db4b521ce0bcc0744198

Uploaded At: June 14, 2019

Post-Trial
Post Trial Information
Study Withdrawal
Intervention
Is the intervention completed?
No
Is data collection complete?
Data Publication
Data Publication
Is public data available?
No
Program Files
Program Files
Reports and Papers
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