It is based on the book "The Levelling" by Micheal O'Sullivan
Polarity in geopolitical terms is defined as the way which power is distributed in the international system. There are three current models regarding polarity including unipolarity, bipolarity, and multipolarity. This type of system is not only related in the macro global context but the regional context as well.
These ideas are discussed by author Michael O’Sullivan in his book “The Levelling: What’s Next After Globalization”, where he discusses the impacts of a changing trends on the world in the future. His main theory is that the world is shifting towards a multipolar world instead of a globalized one where countries exert various degrees of regional as well as global dominance.
The main factors described in his model included Country GDP, Population Size, Regional Economic Role (Regional GDP), UN Human Development Index Relative to Region, Existence of an Imperial Legacy, Military Size & Sophistication (Absolute Military Spending, Number of fighter jets, Number of ships), and Regional Grouping Participation (NATO or European Union).
In order to examine the theory behind this book we created a unique dataset based on the variables described in his model. We then used this dataset to see if his theory was indeed accurate and if these variables could be used to predict geopolitical strength. We also included some additional variables not mentioned in his model that we thought would provide a more accurate representation as well.
After dividing the sovereign nations of the world into different geographical regions we calculated various regional ratios of variables instead of using the absolute global values to get a better picture of the regional effect of each state as well. We then created a regression model using the Comprehensive Index of National Capability (CINC) as a dependent variable to run our various chosen model variables against to see if they correlated.
We also collected around 100,000 tweets regarding the NATO summit in early December 2019 and analyzed them for sentiment to see how people were feeling about this important geopolitical organization.
In conclusion we determined that this model is a fairly accurate for determining a nations place on the CINC ranking. While this is not exactly what the author was theorized in his book it was as close as we could come given the data available and the time frame we had available to complete this project. In fact there are many limitations to this project mostly based around the availability and reliability of the data itself and the inability to quantify intangible variables for modeling geopolitical strength.
In the future we might want to get past historical data for many of these important variables and see how they have changed over time. New research also suggests it is far too simple to simply correlate GDP with the CINC as there are many past historical examples of this not accurately interpreting the reality of the growth of certain nations.
Based on our analysis we can conclude that the author’s theory is relatively correct regarding the correlation between various variables and the Composite Index of National Capability. While the real struggles exist in actually determine an accurate dependent variable and also with the data collection itself, this topic remains highly relevant in the modern world. Our sentiment analysis also reveals people feel pretty negatively about globalism right now if using the most recent NATO summit as a barometer. Overall, we would suggest a more in-depth and detailed analysis of this phenomena and we do not think that it can be so simply reduced to specific variables and formula equations.
t-test
F-test
Regression