Democracy Index Analysis - Lab 1: Basic Data Wrangling and Plotting, Distributions

Project Overview

This project provides an in-depth analysis of the World Democracy Index dataset. It utilizes data manipulation techniques and statistical visualization methods in R to explore global democracy trends over time, specifically focusing on the years 2006 to 2022.

Objectives

• Load and process the Democracy Index data from various sources.
• Conduct comparative analyses of countries based on their democracy scores.
• Visualize global trends in democracy over time, including regional and country-specific patterns.
• Assess the impact of democracy index changes on socio-economic variables such as GDP, population, and incarceration rates.
• Estimate regime transition probabilities and display them via heatmaps.
• Display global data on a world map for visual analysis.

Key Features

Data Sources

• Democracy Index: Data scraped from Wikipedia's Democracy Index page and processed into meaningful insights.
• Additional Data: GDP (PPP) per capita, population size, incarceration rates, and land area data were also incorporated for further analysis.

Analysis and Visualizations

1. World Democracy Index Dataset:

   • Analysis of the top and bottom countries based on democracy index scores in 2022.
   • Comparative analysis of regional democracy index distributions.

2. Plotting Distributions:

   • Boxplots and density plots were created to explore the distribution of democracy scores by region.
   • Outliers were identified, and statistical summaries such as mean, variance, skewness, and kurtosis were calculated.

3. Country Comparisons & Trends:

   • Developed a custom R function to compare democracy index changes across countries and regions over time.
   • Grouped countries based on significant changes in democracy index between 2006 and 2022.

4. Regime Transitions:

   • Estimated the empirical probabilities of regime transitions (e.g., Full democracy to Authoritarian) between 2006 and 2022.
   • Displayed results via a heatmap for easy interpretation.

5. Additional Data Integration:

   • Integrated data on GDP per capita, population size, incarceration rates, and land area to explore relationships with democracy.
   • Performed regression analysis to assess the impact of democracy index on GDP and incarceration rates.

6. Cumulative Distribution Functions (CDFs):

   • Created CDFs to explore the distribution of GDP per capita, considering random country selection, population size, and land area.

7. World Map Visualizations:

   • Visualized the global democracy index on a world map, displaying both average scores and changes between 2006 and 2022.

8. Democracy Index Components:

   • Analyzed the five components of the Democracy Index (Electoral process, Functioning of government, Political participation, Political culture, Civil liberties).
   • Displayed a heatmap of the correlation between these components and ran a multiple regression analysis to predict GDP per capita.

Prerequisites

The following libraries are required to run this analysis:

library(tidyverse)
library(data.table)
library(rworldmap)
library(ggthemes)
library(reshape2)
library(e1071)
library(rvest)
library(corrplot)
library(moments)
library(spatstat.geom)

Instructions

1. Run the RMarkdown (Rmd) File:

   • This file contains all the analysis code, figures, and textual explanations.
   • Ensure all the necessary libraries are installed before running the script.

2. Output:

   • The final output should be an HTML file, which can be generated by knitting the Rmd file.

Results

The top five countries with the highest democracy scores in 2022 are: Norway, New Zealand, Iceland, Sweden, Finland. The bottom five countries in 2022 are: Afghanistan, Myanmar, North Korea, Central African Republic, Syria. Detailed country trends and regime change probabilities were calculated and displayed.