Countries
Description
This dataset is extracted from the World Bank and Uppsala Conflict datasets. I take data related to the augmented Solow Growth Model (capital, education, labor, and GDP/Output) along with military spending data. I transform the data so that it's as a % of GDP. I exclude the technology factor as there is not enough sufficient data to account for this factor. I also use interstate war data using 0s and 1s for the "war presence" variable and 0s, 1s, and 2s for the "war intensity" variable. There are 97 countries included in this dataset. These countries can be found in my paper in the Appendix. For missing data, I use predictive mean imputation to fill in the gaps. I test whether the data for each variable is significantly different or not. I find that none of them are. In addition to this, I take the log transformations for GDP, labor, military spending, and capital. I find that there is autocorrelation when testing, thus I take the first difference of all the variables. This results in a growth metric. I find that military spending accounts for a large part of the explanatory power of the model. I also find that non-linear (quadratic) military spending is significant, as well as linear military spending. This implies that there are diminishing returns as a country spends more on its military in relationship to its GDP per capita growth (log).