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Economic and Financial Models for Pricing and Setting Sanitation Tariffs for the Benefit of the Urban Poor (Ghana)
Last registered on October 15, 2014


Trial Information
General Information
Economic and Financial Models for Pricing and Setting Sanitation Tariffs for the Benefit of the Urban Poor (Ghana)
Initial registration date
October 15, 2014
Last updated
October 15, 2014 5:55 PM EDT
Primary Investigator
University of Virginia
Other Primary Investigator(s)
PI Affiliation
University of Notre Dame
Additional Trial Information
On going
Start date
End date
Secondary IDs
This project involves two RCTs to measure the impact of alternative pricing models and information interventions on access to improved sanitation services in peri-urban West Africa.

The market for improved sanitation services (mechanized desludging in particular) is important: sanitation services have high externalities for the local communities. A government may want to intervene in the market for sanitation services but find it difficult to do so as they are unable to observe values for the consumers or costs for the service providers. We will measure the underlying values of services for customers, measure the cost of providing services for desludging operators, and measure the impact of information on the level of satisfaction of households with their desludging operators and whether they continue to use them on future desludgings. This information can then be used to help in designing interventions by the government which will improve the market structure of sanitation services.

In Accra, Ghana, a more advanced sanitation service market, we introduce a call center system aimed at improving linkages between desludging providers and customers, and test the impact on desludging prices, customer satisfaction, and desludger business revenue.

In a related study in Burkina Faso, a less developed market where manual desludging is still prevalent, we test the effect of alternative pricing models on: the average price of mechanical desludging, takeup of mechanical desludging, and willingness to pay for sanitation services.
External Link(s)
Registration Citation
Johnson, Terence and Molly Lipscomb. 2014. "Economic and Financial Models for Pricing and Setting Sanitation Tariffs for the Benefit of the Urban Poor (Ghana)." AEA RCT Registry. October 15. https://doi.org/10.1257/rct.338-1.0.
Former Citation
Johnson, Terence, Molly Lipscomb and Molly Lipscomb. 2014. "Economic and Financial Models for Pricing and Setting Sanitation Tariffs for the Benefit of the Urban Poor (Ghana)." AEA RCT Registry. October 15. http://www.socialscienceregistry.org/trials/338/history/2894.
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Experimental Details
In advanced peri-urban communities such as Accra, the market for sanitation services is already relatively well developed, but households continue to face difficulties in finding and hiring sanitation service providers. As a result, households may not complete necessary desludgings as quickly as they would like, creating local health and sanitation concerns as they wait to have the desludgings completed. In addition, households often hire middlemen to find desludging service providers who substantially increase costs for desludging. This project tests the impact of improving linkages between desludging operators and households through creating a call center in which they can interact. We test the impact of access to the call center on prices and service quality.
Intervention Start Date
Intervention End Date
Primary Outcomes
Primary Outcomes (end points)
Price of mechanical desludging, quality of desludging service, stability of client-provider matches, desludging service provider profitability, search costs (time)
Primary Outcomes (explanation)
Quality of desludging service will be measured by a combination of customer satisfaction metrics, such as: cleanliness and completeness of service, promptness of service scheduling, and rate of price renegotiation. Stability of client-provider matches will be measured through reported repeat client-provider matches and likelihood to recommend or use the same provider again.
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
We begin with a census of desludging operators and owners in Accra to enroll in the call center. At baseline, we will survey 4,500 households. Of these, 3,600 participants will receive the phone number for the call center, and 900 will serve as a control group. An additional sample of approximately 2,000 households in treatment clusters will be given the call center phone number, but will not be surveyed.
Experimental Design Details
The call center will remain in operation for a period of just over one year. During this time, the call center will collect data related to calls matching clients with desludgers. The clients who call will state their location, and will be connected to the lowest cost available desludger for their neighborhood selected through the moving average auction. The call center will not pre-negotiate or purchase desludgings. It will only connect clients and desludgers, who will then negotiate a price for the service. Two days after being assigned a desludger, the call center will call the client to conduct a follow-up survey about the quality of service provided during the desludging, as well as the price. Price data will then be used to allocate work over time. One year after the baseline survey, we will return to the same households from the baseline sample to conduct an endline survey.
Randomization Method
Randomization was done at the cluster level by computer using statistical software, and balanced by neighborhood block.
Randomization Unit
The treatment is randomized by clusters of household groups. We have identified up to 60 eligible households in each cluster, but not all of these households will be surveyed. In control clusters 12 households will be surveyed at baseline. In treatment clusters 24 households will be surveyed at baseline, and up to 26 additional households will receive the call center phone number without completing a survey.
Was the treatment clustered?
Experiment Characteristics
Sample size: planned number of clusters
225 (150 treatment and 75 control)
Sample size: planned number of observations
4,500 at baseline: 3,600 treatment and 900 control
Sample size (or number of clusters) by treatment arms
Treatment (receive call center number): 150 clusters.
Total households: 3,600 surveyed at baseline, plus up to 2,000 receiving only the call center number but not surveyed
Control: 75 clusters
Total households: 900
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
The minimum detectable standardized effect size for this study depends on the value of intra-cluster correlation (rho). We estimate that the value of rho is between 0.05 and 0.2, which corresponds to an MDES of 0.17 to 0.27 with power of 0.9 and significance level of 0.05.
IRB Name
University of Virginia
IRB Approval Date
IRB Approval Number
IRB Name
University of Notre Dame
IRB Approval Date
IRB Approval Number
Post Trial Information
Study Withdrawal
Is the intervention completed?
Is data collection complete?
Data Publication
Data Publication
Is public data available?
Program Files
Program Files
Reports, Papers & Other Materials
Relevant Paper(s)