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Sanitation and Welfare: Evidence from a Natural Experiment in Panama
Last registered on June 19, 2017


Trial Information
General Information
Sanitation and Welfare: Evidence from a Natural Experiment in Panama
Initial registration date
June 19, 2017
Last updated
June 19, 2017 3:53 PM EDT
Primary Investigator
CAF - Development Bank of Latin America
Other Primary Investigator(s)
Additional Trial Information
On going
Start date
End date
Secondary IDs
What are the effects of sanitation interventions on welfare? Every year, thousands of citizens in developing countries die as a consequence of poor water and sanitation conditions. This situation is particularly harsh for young children and newborns, as acute diaharreal disease has huge negative consequences on this population. Consequently, estimating the effects of interventions on sanitation infrastructure on health and other welfare conditions of poor households is crucial, in order to determine the effectiveness of these programs. We exploit a potential natural experiment that took place in Panama recently. The San Miguelito project is a huge sanitation infrastructure intervention, in which thousands of households in Panama City's poorest district get access to the sewage system. However, planning and execution errors imply that certain sectors of the district are no included in the project, leaving a big number of houses, comparable to those that will be treated, out of the intervention. After checking if there is balance between treatment and control groups, and adjusting for any imbalances between them, we will exploit this natural experiment through a difference in differences estimation, to determine the impact of the San Miguelito project on several welfare and health indicators, including prevalence of parasites on stool samples for children below 5 years. To account for potential spillover effects, we also include a distant control group, composed of households living in a different district far away of San Miguelito, but that shares similar socioeconomic characteristics. We hypothesize that the intervention has positive effects on several health and anthopometric indicators, such as diarrhea disease on young children, weight and height, and in other important dimensions, such as school attendance, productivity, or psychological health.
External Link(s)
Registration Citation
CAF, Pilar. 2017. "Sanitation and Welfare: Evidence from a Natural Experiment in Panama." AEA RCT Registry. June 19. https://doi.org/10.1257/rct.2268-1.0.
Former Citation
CAF, Pilar. 2017. "Sanitation and Welfare: Evidence from a Natural Experiment in Panama." AEA RCT Registry. June 19. http://www.socialscienceregistry.org/trials/2268/history/18819.
Experimental Details
Intervention Start Date
Intervention End Date
Primary Outcomes
Primary Outcomes (end points)
Health indicators, anthopometric measures, school attendance, productivity, psychological health, sexual and reproductive rights
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
The ideal evaluation design would consist of randomizing the access to the sewage system. This would assure comparability between households with and without access, and lead to a robust impact estimation of the intervention. Nevertheless, operative, logistical, and ethical reasons make this design unfeasible in this context.

On the other hand, this project can be considered as a natural experiment due to some of its particular characteristics, although available information as of now is not completely certain on this matter. The selection criteria used to determine the intervention places and coverage zones were associated with geographical and spatial features related to the San Miguelito basins. Therefore, the absence of differences in health and community welfare dimensions between treated and control households would not be surprising. If this were the case, a comparison of both household groups before and after the intervention would lead to reliable impact estimators.

Nonetheless, both groups could differ in observable and unobservable characteristics that could affect outcomes in health and welfare, which would hinder the identification of causal effects. Balance testing on observable characteristics using information produced by the baseline will help determine whether or not these differences exist. The presence of balance would ratify the existence of a natural experiment.

On the contrary, if balance between both groups does not exist, quasi-experimental techniques should be employed for impact calculation. In this particular case, the combination of matching and difference-in-differences methods would be suggested. In this scenario, the information collected in the baseline is useful to determine which households in the control group possess characteristics more closely related to those of the treatment group. Among the different matching techniques available, Propensity Matching Score, Balance-Sample Size Frontier Matching, and Genetic Matching are the most distinguished. Besides, the nature of this intervention makes it reasonable to use other impact evaluation techniques, such as a Geographic Regression Discontinuity or Instrumental Variables. Once household matching is accomplished, a difference-in-differences model would compare variations in outcomes on both groups.

In addition, taking into account possible spillover effects, an alternative control group was established using households located in the Panama North District, which is located far away from San Miguelito but shares similar sociodemographic characteristics. The same difference-in-differences and matching approach would be used to compare outcomes in both control groups to quantify the spillover effect.
Experimental Design Details
Randomization Method
Randomization Unit
Was the treatment clustered?
Experiment Characteristics
Sample size: planned number of clusters
Sample size: planned number of observations
2505 households
Sample size (or number of clusters) by treatment arms
835 households for treatment group, 835 for San Miguelito control group, 835 for Panama Norte control group
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB Name
Hospital del NiƱo
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)