Decentralization and Local Public Goods: How does allocation of decision-­making authority affect provision?
Last registered on November 26, 2018


Trial Information
General Information
Decentralization and Local Public Goods: How does allocation of decision-­making authority affect provision?
Initial registration date
November 21, 2018
Last updated
November 26, 2018 2:11 PM EST
Primary Investigator
Columbia University
Other Primary Investigator(s)
PI Affiliation
Stockholm University, Sweden
PI Affiliation
NGO Forum for Public Health, Dhaka, Bangladesh
Additional Trial Information
Start date
End date
Secondary IDs
National Science Foundation Grant 0624256
The purpose of the study is to determine conditions under which participation by the community in the provision of the social services which the community needs improves access to those services. Access to services such as sanitation, health care and education remains inadequate for much of the world's population, including disadvantaged communities in the United States. No consensus exists about how to improve access to services. Many policy-makers, like the World Bank, have embraced the view that access to services would improve if users of services participated in providing those services, and more generally that local participation is necessary to improve the performance of all development projects. The hypothesis that users of services have more information about their needs and a greater interest in a good outcome than does a remote central organization is reasonable. However, local control can also lead to control by a few powerful people for their own benefit, a community may lack technical knowledge and may be unable to exploit economies of scale. In this study, we implement three organizational interventions designed to provide access to safe drinking water in Bangladesh. In each type of intervention, the authority to make decisions regarding the provision of safe water will be allocated differently to test the hypothesis that community participation improves outcomes.
External Link(s)
Registration Citation
Habib, Ahasan, Malgosia Madajewicz and Anna Tompsett. 2018. "Decentralization and Local Public Goods: How does allocation of decision-­making authority affect provision?." AEA RCT Registry. November 26.
Former Citation
Habib, Ahasan et al. 2018. "Decentralization and Local Public Goods: How does allocation of decision-­making authority affect provision?." AEA RCT Registry. November 26.
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Experimental Details
We implement the following interventions. The collaborating NGO offers sources of safe drinking water in villages and contributes to the cost of the safe water in the form of a loan. One intervention is based on the traditional model, in which the collaborating NGO makes all decisions about the source of safe water and how it will be provided. Another intervention will represent the opposite extreme on the spectrum of community participation. The NGO will ask the village residents to make all decisions. The third intervention is an intermediate one, in which the NGO restricts the way in which the village residents participate in the provision of safe water. Discussions with NGOs and case studies suggest testing an intervention which strives to achieve broad participation across socio­economic groups in planning and execution and requires public disclosure to the village of every decision made and identity of its supporters.

A control group of villages will receive no intervention at all. Importantly, we will not be withholding assistance from villages. Currently, funding is not available to offer assistance to all villages affected by the arsenic problem. We will extend such assistance immediately if funding becomes available.
Intervention Start Date
Intervention End Date
Primary Outcomes
Primary Outcomes (end points)
Whether the household is using safe drinking water; the household's costs of accessing drinking water; whether the household participated in the planning and implementation of the new source of water or will participate in its management.
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
The original study design was to: i) randomly select 250 villages from eligible villages in the study area (those in which a large percentage of wells is contaminated with arsenic, the main threat to safe water in the study area, and which have not yet received an intervention to provide safe water,); ii) randomly select one hundred of these villages to receive no intervention; iii) implement the three interventions in fifty villages each, randomly selected among the villages not assigned to control.
Experimental Design Details
Randomization Method
Randomization Unit
Was the treatment clustered?
Experiment Characteristics
Sample size: planned number of clusters
250 villages
Sample size: planned number of observations
10,000 households (40 in each village)
Sample size (or number of clusters) by treatment arms
100 control villages; 50 villages in each of the three treatment arms
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB Name
Columbia University Morningside
IRB Approval Date
IRB Approval Number
Post Trial Information
Study Withdrawal
Is the intervention completed?
Intervention Completion Date
June 30, 2011, 12:00 AM +00:00
Is data collection complete?
Data Collection Completion Date
November 30, 2011, 12:00 AM +00:00
Final Sample Size: Number of Clusters (Unit of Randomization)
We attempted treatment in 127 villages (reduced from planned 150 because of budgetary constraints). Treatment was not feasible in 19 villages because tubewell construction was not feasible. Final treatment sample in villages in which tubewells were feasible consisted of 108 villages. 100 villages were in the control group.
Was attrition correlated with treatment status?
Final Sample Size: Total Number of Observations
7,427 households surveyed at baseline and 7,341 households surveyed at follow-up
Final Sample Size (or Number of Clusters) by Treatment Arms
Main sample for which we have both baseline and follow-up data: 107 treated villages (we lost all baseline data for one village) in which tubewells were feasible, 36 villages in top-down approach, 36 villages in regulated community participation approach, 35 villages in community approach, 84 villages in matched control group.
Data Publication
Data Publication
Is public data available?

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Program Files
Program Files
Reports and Papers
Preliminary Reports
Relevant Papers