Cross-National Analysis of Income Inequality (2000–2023): Structural Patterns and Policy Implication

This project presents a detailed empirical investigation into income inequality trends across six countries—USA, UK, Germany, India, South Africa, and Pakistan—spanning from 2000 to 2023. Using data from the World Inequality Database (WID), the study explores pre-tax labor income distributions to isolate market-driven disparities, independent of redistributive policy effects.

The analysis applies descriptive statistics, regression modeling, and visual analytics to quantify inequality through two indicators:

p90p100: income share held by the top 10%

pall: income distribution across the entire population

Objectives and Scope:
Detect global and country-level income inequality trends

Examine the disparity between developed and developing economies

Assess inequality stability vs. volatility in different institutional contexts

Recommend evidence-based policy interventions

Tools and Methods Used:
Data Source: World Inequality Database (WID)

Statistical Software: STATA

Techniques Applied:

Linear regression modeling with robust standard errors

Histograms and time-series visualization of income shares

Diagnostic tests: residual plots, Shapiro-Wilk, and VIF

Variables:

Income shares (p90p100, pall)

Country-specific alternate measures (e.g., usa2, uk2)

Key Findings:
Developed Economies (USA, UK, Germany):

Relatively stable inequality, with marginal increases in top 10% shares.

Top 10% income share ranges:

USA: ~42%

UK: ~36%

Germany: ~32%

Developing Economies (India, South Africa, Pakistan):

Exhibit persistently high and volatile inequality.

South Africa shows the highest concentration, averaging 55% of national income among the top 10%.

Cross-Country Observations:

Disparities in trends signal the impact of structural factors, including:

Weak labor markets

Informal economies

Limited access to quality education and healthcare

Policy Recommendations:
For Developed Nations:

Enhance progressive taxation

Strengthen middle-income wage growth policies

For Developing Nations:

Invest in education, healthcare, and formal labor markets

Improve institutional capacity and governance

Foster inclusive economic participation

Globally:

Promote international financial transparency

Adopt cooperative frameworks to address wealth concentration and capital flight

Skills Demonstrated:
Econometric modeling and diagnostics

Cross-country comparative analysis

Data cleaning and standardization

Interpretation of income distribution metrics

Policy formulation based on empirical findings

Relevance and Impact:
This project underscores the urgent need to address structural inequality through data-driven, country-specific policies. It contributes to ongoing global discussions on economic justice, development, and social cohesion, and provides a robust analytical foundation for economists, policymakers, and development agencies working toward inclusive growth.