Isaac Liu
The proper allocation of foreign aid is likely to be of critical importance to its efficacy. In this paper, I present an analysis to test the hypothesis that official development assistance is allocated based on need in terms of deficits on indicators linked to the Sustainable Development Goals (SDGs). Within the framework of sustainable development priorities, I analyze data from over a hundred countries from 2012-2017 for multilateral and bilateral disbursements and 26 indicators. Using a novel mismatch index, I identify average misallocations of about 2% of the world total for each country, representing tens of billions of dollars in aggregate, and observe little change after the 2015 enactment of the SDGs. I also check Spearman rank coefficient measures which indicate a poor fit, especially for indicators new to the SDG agenda. In regression analysis, I find a weak but positive and usually significant relation between aid and need and that the quality of institutions and domestic resource mobilization is associated with aid while democracy is not. Finally, I identify and discuss disproportionate nations, mainly large population and middle-income countries. I offer several explanations and potential extensions.
This paper is available on SSRN at https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3776263.
Contains input data from various sources, as well as codebooks and country name lists for comparison across the datasets.
Stores output from the stata code. This includes intermediate/cleaned data, regression tables, and other tables of summary statistics and spearman correlations. Many of the final figures are combinations of smaller, intermediate figures for individual indicators.
Contains final submissions, paper drafts, and presentations. The main draft is here. The main presentation is here.
Contains the project source code in the Stata dofile Comparing_Sustainable_Development_Aid_and_Need.do. The only line any user may need to change in order to run the code is the location of the global "Root", which should be set to the root/main folder of this repository.
All datasets are public and available on the internet.
This repository is dedicated in memory of Joseph B. Serafin on January 24, 2021.