Stormwater Management and Climate Change Adaptation Impact Evaluation 2014
The Senegal Stormwater Management and Climate Change Adaptation Impact Evaluation, Baseline Survey (SMCCAIE-BL) 2014 was collected for DIME’s impact evaluation on community engagement mechanisms in the preservation of public spaces and drainage infrastructures. It is carried out in the context of the World Bank-assisted Stormwater Management and Climate Change Adaptation Project (PROGEP), which is implemented by the Dakar Municipal Development Agency (ADM) in Senegal. It will inform strategies through which PROGEP and similar projects can achieve their community engagement objectives, which are vital to the sustainability and return on these investments. Furthermore, it will contribute to our understanding of community directed development (CDD) interventions in urban settings. Data collected through the IE, including at baseline, will improve our understanding of populations living in PROGEP areas and inform the better targeting of project activities and other investments in these and similar settings.
Kind of data
Sample survey data [ssd]
Producers and sponsors
Trinity College of Dublin
Trinity College of Dublin
DECIE, World Bank
Nordic Development Fund
UK-DFID Trust Fund
The PROGEP IE uses a randomized controlled trial (RCT) study design. Given a list of areas, such a study design assigns the focal intervention to some areas completely at random, while other areas remain without the intervention. With a sufficiently large number of areas over which to randomize, such a procedure ensures that, on average, those areas assigned to receive the intervention (the "treatment" group) are statistically equivalent to those areas not assigned to receive the intervention (the "control" group). In the absence of the intervention, we would expect that outcomes in the treatment and control groups would remain identical, as they are both exposed to the same influences on average. With the intervention, however, we introduce a new factor which only affects the treatment group. We can therefore confidently attribute any differences in outcomes following the treatment to the intervention alone. Additional details on sampling provided in the Impact evaluation study design section of the report provided as related material.
Deviations from sample design
A first challenge in data collection resulted from the fluid nature of urban communities in the study area. As mentioned in Section IV (OQP Intervention), quartiers and CBOs are sometimes dynamic units. At the time of the baseline survey, a small subset of pre-identified quartiers (4) and CBOs (16), identified earlier in the study design process, could not be located. Missing quartiers and CBOs were replaced. This issue did not reemerge during the follow-up, suggesting that the “missing” quartiers and CBOs were anomalies. While it is perhaps not so unusual for CBOs to disband, the disappearance of a geographic unit such as a quartier warrants further attention. It should be noted, however, that the list of quartiers was created by PROGEP’s SFs, and so the four missing quartiers are likely due to errors in that process.
A second challenge related to locating households and CBOs for the follow-up (or endline) survey. The household and CBO surveys are both panel surveys, which means that the same households and CBOs were surveyed at baseline and follow-up. While identifying CBOs at follow-up was relatively straightforward – particularly for those in the treatment group – identifying households in the baseline sample was more complicated given the absence of a formal system of street names and addresses.
At baseline, GPS coordinates for each household were taken in addition to other identifying information. These coordinates were to be the primary means of re-identifying households. These data, however, turned out to be of little use due to the density of the cities of Pikine and Guédiawaye and the lack of precision in GPS measurement (e.g. a precision of 100 meters can include the totality of houses in one quartier). To overcome this challenge, enumerators relied on neighbor networks and baseline “addresses” to locate the correct households. If a household could not be initially located, the enumerator followed a replacement protocol. These measures allowed us to achieve a low attrition rate: out of the 2,400 households surveyed at baseline, only 115 could not be included in the endline survey, an attrition rate of less than 5%. Table 6 of the survey report summarizes the target and achieved sample sizes for the household and CBO surveys at baseline and endline.
Dates of collection
Mode of data collection
Computer Assisted Personal Interview [capi]
The household questionnaire collected information on
(i) household demographics,
(ii) livelihoods and income sources,
(iii) socioeconomic characteristics,
(iv) health outcomes,
(v) exposure to flooding,
(vi) knowledge of flood risk mitigation methods, and
(vii) attitudes towards community participation and one’s general responsibilities vis-à-vis the community (and vice-versa), including a “decision activity” section designed to measure willingness to contribute to a public good.
Enumerators also recorded their direct observations of the general cleanliness of the immediate area around the household.
At endline, an additional set of questions were asked about the OQP to measure household awareness and perception of the intervention. As the endline was collected after the rainy season of 2016, questions related to flooding were also added for 2015 and 2016. Table 5 summarizes the sections included in the baseline and endline surveys.
Use of the dataset must be acknowledged using a citation which would include:
- the Identification of the Primary Investigator
- the title of the survey (including country, acronym and year of implementation)
- the survey reference number
- the source and date of download
Carol Newan and Tara Mitchell, Trinity College of Dublin, Marcus Holmlund, World Bank. Senegal Stormwater Management and Climate Change Adaptation Impact Evaluation, Baseline Survey (SMCCAIE-BL) 2014. SEN_2014_SMCCAIE-BL_v01_M. Dataset downloaded from [URL] on [date].
Disclaimer and copyrights
The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses.
DECIE, World Bank
DECIE, World Bank
Development Data Group
The World Bank
Documentation of the DDI
Version 01 (March 2016)
Version 02 (May 2019) - Identical to v01 with variable level metadata, additional contact person and endline data collection dates.