cc50liu/ChinaWorldBankAidLocationSelectionAfrica

China/World Bank Aid project location selection in Africa and impact using satellite images and machine learning # Using machine learning and satellite imagery to estimate aid's effect on wealth: comparing China and World Bank programs in Africa Code in support of a thesis for a Masters of Computational Social Science at Linköping University. - Thesis and Appendices (PDF) - AnalysisSteps explains the order the files were executed. Overview: - R: contains majority of the analysis code. The code - writes .csv files to the ./data/interim directory which are read by later scripts. - writes maps, charts, and figures to a ./figures directory - writes tables to a ./tables directory - reads shapefiles, aid project, and confounder data from a ./data directory - writes results to a ./results directory - python: scripts used to download satellite imagery over DHS points to NAISS (National Academic Infrastructure for Supercomputing in Sweden) - scripts: - batch utility scripts to run on Windows laptop and NAISS environment - slurm scripts to exeucte long-running R scripts on NAISS - env_conf: apptainer recipes to configure the NAISS python and RStudio environment where analysis runs