Corruption in Cyclone Relief and Reconstruction: Evidence from a Public Fund Distribution in Bangladesh

After the 2009 cyclone ‘Aila’, the Prime Minister of Bangladesh announced a special assistance of Tk. 20,000 (∼$300) to rebuild the houses of the affected households. We examine the role of networks in determining the incidence and extent of corruption associated with this grant by using two rounds of a household-level survey collected before and after the announcement and distribution of the grant. Our results inform that although bribery and missing grants were considerably lower in the rebuilding grant than the generally perceived level of corruption, network formation played an important role in the grant allocation and distribution process. In fact, households endogenously developed political networks to be able to bribe for enlistment for and receipt of the grant, as evident from the positive and significant influence of political networks on the probabilities and amounts of bribes and missing grants. Consequently, although the fund was channeled to disaster-affected villages, household-level allocation and distribution may have suffered from considerable irregularities. Our research may provide guidance for curbing corruption as it highlights the hindering yet central role of political connections in the distribution of post-disaster relief funds.

Authors

Institutions

Publication Details

Journal
The Journal of Development Studies
Published
2025-08-18
DOI
https://doi.org/10.1080/00220388.2025.2543251
Primary Topic
Corruption and Economic Development
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Corruption in Cyclone Relief and Reconstruction: Evidence from a Public Fund Distribution in Bangladesh

Asad Islam, Mustafa Kamal, Shaikh Eskander
The Journal of Development Studies
Corruption and Economic Development
article

Corruption in Cyclone Relief and Reconstruction: Evidence from a Public Fund Distribution in Bangladesh

Asad Islam, Mustafa Kamal, Shaikh Eskander
article en

Abstract

After the 2009 cyclone ‘Aila’, the Prime Minister of Bangladesh announced a special assistance of Tk. 20,000 (∼$300) to rebuild the houses of the affected households. We examine the role of networks in determining the incidence and extent of corruption associated with this grant by using two rounds of a household-level survey collected before and after the announcement and distribution of the grant. Our results inform that although bribery and missing grants were considerably lower in the rebuilding grant than the generally perceived level of corruption, network formation played an important role in the grant allocation and distribution process. In fact, households endogenously developed political networks to be able to bribe for enlistment for and receipt of the grant, as evident from the positive and significant influence of political networks on the probabilities and amounts of bribes and missing grants. Consequently, although the fund was channeled to disaster-affected villages, household-level allocation and distribution may have suffered from considerable irregularities. Our research may provide guidance for curbing corruption as it highlights the hindering yet central role of political connections in the distribution of post-disaster relief funds.

The Journal of Development Studies
University of Tasmania (AU), University of Alabama at Birmingham (US), Centre for Development Economics (IN), London School of Economics and Political Science (GB)
Peace, Justice and strong institutions
Openalex Percentile: Top 72%
Corruption and Economic Development
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.