Income Inequality Analysis

This project explores global income inequality trends from 2000 to 2020 using World Development Indicators data.

Available Analyses

GINI Index Analysis

Explores factors affecting GINI coefficient across countries and time.

Top 10% Analysis

Investigates factors influencing income share held by the top 10%.

Bottom 10% Analysis

Examines factors impacting income share held by the bottom 10%.

Project Overview

This analysis uses machine learning techniques, specifically SHAP (SHapley Additive exPlanations) values, to identify which development indicators have the most significant impact on income inequality metrics.

Three different income inequality metrics are analyzed:

  • GINI Index - a measure of statistical dispersion representing income inequality
  • Income share held by the top 10%
  • Income share held by the bottom 10%