The Case Analysis of African Union - Prime Academic Study

Table of Contents

Problem Definition
Variables
Hypothesis
Method
Reference List

Problem Definition

The African Union (AU) was chosen as the international organization for the study design. AU is a modern union of 55 African republics, founded in 2002 as the successor of the Organization of African Unity (AU, 2022). The general objectives of this organization include the implementation of any reforms and structural changes to strengthen intra-African relations between countries, establish political-economic ties, and promote the sustainable development of the continent. Thus, the central thrust of the organization’s professional activities is to address Africa’s internal problems, including the threats of terrorist conflicts, the promotion of fair political elections, and the resolution of environmental problems (ICG, 2021). Meanwhile, the AU aims to improve Africa’s positioning in the international geopolitical arena by increasing the investment and tourism attractiveness of the regions.

One of the strategic objectives of AU was to eliminate armed conflicts on the continent to create a safe environment for people, tourism, and business. To this end, the Lusaka Protocol was created in 2016 to implement measures to reduce conflicts by 2020 significantly (Momanyi, 2016). However, the practical agenda was drastically different from expectations, as it is indicated that the number of violent conflicts increases every year during the period; including a 36% increase in 2019 compared to 2018 (Allison, 2020). In other words, AU leadership’s response to the problem has been ineffective. There are many possible reasons for subpoenas not meeting expectations, and an in-depth study of them is of interest. Thus, the articulated challenge for future research is to identify the patterns and reasons for the increase in armed conflict in AU countries contrary to the roadmap adopted in 2016.

Variables

The number of armed conflicts is used as a dependent factor for future research, which is a continuous numerical variable. The influencing factors on this variable, i.e., the independent factors, are determined by the annual budget and the dynamics of the total population for AU over time. In addition, it is proposed to use the population happiness index as an additional independent variable. Establishing the potential influence of multiple independent factors on the dependent variable is the subject of a statistical analysis proposed for a future study.

Hypothesis

The working hypothesis is that the three independent factors statistically affect the number of armed conflicts in AU. Specifically, it is expected that the larger the annual budget, the fewer conflicts were observed. On the other hand, it is expected that the larger the population of countries, the greater the number of conflicts observed. Finally, the happier the population of countries, the less conflict was observed.

Method

This study is implemented by observing generalized patterns for AU in particular and individual member countries of the union. Since two independent variables can have a conflicting relationship, it is recommended that detailed studies be conducted on the largest countries in the region and that data for all regions for AU be summarized. Publicly available data on the number of armed conflicts is used for the study. In particular, an excellent source is the UCDP, which allows the calculation of conflicts by year for different countries of the world (UCDP, 2022). To collect data on independent variables, it is recommended to use AU government reports, annual budget documentation, and publicly available data on population dynamics. Platforms reporting happiness index data are also used to collect reliable material for further analysis.

The data processing methodology uses statistical tools to find answers to hypotheses. Since all variables are represented by numerical continuous scales, the use of correlation and regression analyses proves to be an effective strategy. This includes multiple regression tests to determine collective effects. In addition, a three-factor ANOVA can also be used to obtain relevant results.