Socio-Economic and Behavioral Effects of Improved Urban Drainage in Bangladesh

Last registered on June 15, 2023
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Pre-Trial

Trial Information

General Information

Title
Socio-Economic and Behavioral Effects of Improved Urban Drainage in Bangladesh
RCT ID
AEARCTR-0011481
Initial registration date
June 08, 2023

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
June 15, 2023, 4:24 PM EDT

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Locations

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Primary Investigator

Name
Angelika Budjan
Affiliation
University of Stuttgart
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Other Primary Investigator(s)

PI Name
Cristina Cibin
PI Affiliation
Universität Heidelberg
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PI Name
Khalid Imran
PI Affiliation
Universität zu Köln
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PI Name
Robin Moellerherm
PI Affiliation
Universität Heidelberg
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PI Name
Jingke Pan
PI Affiliation
Universität Heidelberg
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Additional Trial Information

Status
In development
Start date
2023-06-15
End date
2024-11-30
Keywords
Behavior, Environment & Energy, Health
Additional Keywords
JEL code(s)
D1, D9, H43, H54, Q54
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
We study the effect of improvements in urban drainage infrastructure for flood prevention on affected households with a survey in Barishal, Bangladesh. Specifically, our project analyzes the socio-economic and behavioral effects of drainage improvements on affected households. Improvements in drainage systems are a key component for flood control and climate change adaptation in many urban settings around the globe. We will use a spatial regression discontinuity design with the distance to the boundaries of the area benefiting from the project as a running variable. We will complement this analysis with a grid-cell level analysis on the likelihood and length of experiencing a flooding event during the rainy season using satellite imagery as an objective measure of risk exposure.
External Link(s)

Registration Citation

Citation
Budjan, Angelika et al. 2023. "Socio-Economic and Behavioral Effects of Improved Urban Drainage in Bangladesh." AEA RCT Registry. June 15. https://doi.org/10.1257/rct.11481-1.0
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Experimental Details

Interventions

Intervention(s)
Our project studies the effects of an improvement of urban drainage infrastructure funded by the KfW in the city of Barishal, Bangladesh, on climate resilience of affected households. The intervention consists of improvement of the existing urban drainage network in the commercial center of the city, since the current network is not able to handle the demands under heavy rainfall which leads to frequent flooding.
Intervention Start Date
2023-07-01
Intervention End Date
2024-02-29

Primary Outcomes

Primary Outcomes (end points)
Flood risk, household level:
- Observed flooding (satellite images)
- Reported flooding
- Stated flood risk perceptions

Socio-economic outcomes, household level:
- Spending behavior
- Food security and dietary adequacy
- Assets
- Aspirations, life satisfaction

Education:
- Health outcomes, individual level
- Likelihood of suffering from waterborne/vectorborne diseases
- Frequency of visits to health centers
- Child health (early childhood, children under 5)

Behavioral outcomes, individual level:
- Changes in littering behavior
- Changes in norm enforcement
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
To identify the causal effect of the improved drainage network, we will use the supply-side determinants of drainage infrastructure in a spatial regression discontinuity design (RDD). Specifically, we will exploit discontinuity arising from variations in access to the gravity fed canals of the drainage network based on the flow direction of the drainage canals. We will complement this analysis with a difference-in-differences analysis for a subsample.
Experimental Design Details
Not available
Randomization Method
No direct randomization. The research team had no influence on the location of the infrastructure project.
Randomization Unit
Households
Grid cells
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
2,000 households
Sample size: planned number of observations
2,000 households
Sample size (or number of clusters) by treatment arms
1,000 households treatment and 1,000 households control
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Regression Discontinuity with uniform distribution around the boundary: 0.25 standard deviations (alpha = 0.05, (1 - beta) = 0.8).
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
Universität Heidelberg
IRB Approval Date
2023-05-23
IRB Approval Number
FESS-HD-2023-008
Analysis Plan