AidData Working Paper

Geostatistical Tools to Map the Interaction between Development Aid and Indices of Need

Date Published

May 18, 2018

Authors

Claudio Bosco, Natalia Tejedor-Garavito, Daniele de Rigo, Andrew J. Tatem, Carla Pezzulo, Richard Wood, Heather Chamberlain, Tom Bird

Publisher

Citation

Bosco, Claudio, Natalia Tejedor-Garavito, Daniele de Rigo, Andrew J. Tatem, Carla Pezzulo, Richard Wood, Heather Chamberlain, and Tom Bird. 2018. Geostatistical Tools to Map the Interaction between Development Aid and Indices of Need. AidData Working Paper #49. Williamsburg, VA: AidData

AidData Working Paper

Geostatistical Tools to Map the Interaction between Development Aid and Indices of Need

Date Published

May 18, 2018

Authors

Claudio Bosco, Natalia Tejedor-Garavito, Daniele de Rigo, Andrew J. Tatem, Carla Pezzulo, Richard Wood, Heather Chamberlain, Tom Bird

Citation

Bosco, Claudio, Natalia Tejedor-Garavito, Daniele de Rigo, Andrew J. Tatem, Carla Pezzulo, Richard Wood, Heather Chamberlain, and Tom Bird. 2018. Geostatistical Tools to Map the Interaction between Development Aid and Indices of Need. AidData Working Paper #49. Williamsburg, VA: AidData

In order to meet and assess progress towards global sustainable development goals (SDGs), an improved understanding of geographic variation in population wellbeing indicators such as health status, wealth and access to resources is crucial, as the equitable and efficient allocation of international aid relies on knowing where funds are needed most. Unfortunately, in many low-income countries, detailed, reliable and timely information on the spatial distribution and characteristics of intended aid recipients are rarely available. Furthermore, lack of information on the past distribution of aid relative to need also hinders assessments of the impacts of aid. High-resolution data on key social and health indicators, as well as how aid distribution relates to these indicators are therefore fundamental for targeting limited resources and building on past efforts. 

In this study, we show how modern statistical approaches combined with a new geographic database of aid distribution can be used to map the distribution of indicators with a level of detail that can support geographically stratified decision-making. Based on geo-located survey data from Demographic and Health Surveys (DHS) in Nigeria (2008 - 2013) and Nepal (2006 - 2011), Bayesian geostatistical models and machine learning approaches were used in combination with a suite of spatial data layers to create high-resolution predictive maps for (i) the rates of stunting in children under the age of five and (ii) the household wealth index. An ensemble model was also exploited for aggregating different modelling results to improve the modelling prediction capacity in Nigeria (for stunting 2008). By combining these maps with information on the disbursement of aid for increasing food security and alleviating poverty (AidData database - http://aiddata.org/), we quantified both the reported spatial distribution of aid relative to stunting and poverty, as well as how changes in these indices overtime related to aid disbursement. While many cases of aid disbursement lacked detailed spatial information, the results here demonstrate the potential of this approach and highlight the value of spatially disaggregated data on the distribution of aid.

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Available on GeoQuery
TUFF
Geocoded
SDG Coded
Natural Resource Concessions
Survey Results
Metadata
Publication Date
Apr 2016
Starting Year:
1997
Ending Year:
2014
Number of Entries:
20,952
File Size:

This is all geocoded projects from the Aid Management Platform (AMP) Aid Information Management System (AIMS) managed for Nepal. This dataset tracks 475 geocoded projects across 20952 locations, $5,941,663,576.00 in geocoded commitments and $3,221,565,559.00 in geocoded disbursements between 1997 and 2014.

Tags
Available on GeoQuery
TUFF
Geocoded
SDG Coded
Natural Resource Concessions
Survey Results
Metadata
Publication Date
Apr 2016
Starting Year:
1988
Ending Year:
2014
Number of Entries:
1,843
File Size:

This is all geocoded projects from the Development Assistance Database (DAD) Aid Information Management System (AIMS) managed for Nigeria. This dataset tracks 595 projects across 1843 locations, $2,116,331,293.00 in geocoded commitments and $6,093,125,384.00 in geocoded disbursements between 1988 and 2014.

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