Analysing aid activities has been in the centre of academic research; nevertheless, it is demanding to conduct long-term time series analyses due to missing data. Although there are several methods available to overcome this challenge, their distortion effect may result in unpredicted impacts on aid allocation. Thus, this paper aims to analyse the long-term motivations of US aid allocation with panel regression models. Two methods of handling missing data were tested in order to answer the question whether there is a significant difference in the results or not. Results suggest that there are several tools in the hands of a researcher to overcome missing data problems without any distorting effects. Furthermore, results reinforce the idea that US aid allocation has mainly been motivated by its economic drivers (export possibilities) rather than by war or conflict fears in the long run.

Keywords: Aid Allocation, Missing Data, Panel Regression

JEL Classification: F35, C15, C33