Access to safe drinking water: experimental evidence from new water sources in Bangladesh

Publication Details

3ie Funded Evaluation, DPW1.1006. A link to the completed study will appear here when available.

Anna Tompsett,Ahasan Habib, Selene Ghisolfi, Serena Cocciolo
Institutional affiliations
None specified
Grant-holding institution
None specified
South Asia
Environment and Disaster Management, Health Nutrition and Population
None specified
Gender analysis
None specified
Gender analysis
Equity Focus
None specified
Evaluation design
Difference-in Difference (DID), Instrumental Variables (IV), Randomised Control Trials (RCT)
Ongoing 3ie Funded Studies
3ie Funding Window
Development Priorities Window 1


This study seeks to evaluate the effect of a programme of subsidies and technical advice to provide new and safe sources of drinking water on household water quality


Access to safe drinking water remains limited in Bangladesh where almost 100 million people drink water contaminated by fecal matter, and 39 million people drink water that is contaminated with arsenic at international standards. While the magnitude of the problem of providing access to safe drinking water is clear, there is a surprising lack of consensus about the remedy. Drinking water may be contaminated by pathogens from source water, during transport from the source, or during storage. Disentangling these channels empirically is difficult because households that live nearer safe water sources may differ in other respects that also affect their drinking water quality, for example, income or education. The impact evaluation aims to measure the causal impacts of source water quality and transport time on household water quality in rural Bangladesh.

Research questions

The impact evaluation will answer the following questions:

  1. What is the effect of the safe drinking water programme on household water quality, measured by both arsenic contamination and contamination with fecal bacteria?
  2. What is the effect of the programme on people’s behaviour with respect to collecting drinking water: on source quality, distance travelled to collect water and storage practices?
  3. What are the causal effects of water source quality and distance to safe drinking water on household water quality?


Intervention design

The intervention is designed to improve access to safe drinking water in rural Bangladesh. Its consists of a package of subsidies and technical advice to build new sources of water, which provide drinking water that is free of both arsenic and bacterial contamination. The subsidies range in value from 90 to 100 per cent of the cost of water source installation. The intervention was carried out in treatment units of between 50 and 250 households, dividing larger villages in several treatment units along natural boundaries. In treatment areas, communities decide the location of new water sources by unanimous consensus in community meetings. Subsidies for one new water source were offered in treatment units with less than 150 households, and two new water sources in treatment units with more than 150 households.

Theory of change

As new water sources are provided, households adopt these sources i.e. they change their behaviour to regularly collect water from the new sources, and as a result, household drinking water improves. A key assumption is that a substantial number of individuals will adopt new sources of safe drinking water. However, providing new sources of safe drinking water may also have heterogeneous unintended consequences, depending on their effect on transport times and storage practices.

Evaluation design

To causally estimate changes in average household water quality, the study exploits a random assignment of the safe drinking water programme to 114 out of a total of 152 study communities via public lottery. A difference-in-differences approach will be used to evaluate how changes in household bacterial contamination vary with changes in source contamination, transport distance and storage. In addition, an instrumental variables analysis which exploits the random assignment to treatment and the fact that baseline data could be used to predict where in a village a community will decide to install a water source, will be carried out.

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