Unveiling Income Inequality Amidst Data Gaps: International Evidence

Professor Introduction

R.Z | Ph.D. in Economics

Home Institute： University of Wisconsin

Project Description

This study explores the complexities of assessing income inequality in the presence of data gaps. By employing innovative methods and data imputation techniques, the research aims to address the shortcomings of traditional income inequality assessments and provide a more nuanced understanding of the true disparities in income distribution. Ultimately, this research contributes to the discourse on measuring income inequality and informs policy interventions aimed at addressing socio-economic disparities.

Project Keywords

Project Outline

Part 1 :  Introduction to Income Inequality
• Definition and significance of income inequality
• Historical context and global trends in income inequality
• Challenges in measuring income inequality

Part 2: Theoretical Framework
• Overview of economic theories related to income inequality (e.g., Kuznets Curve, Lorenz Curve, Gini Coefficient)
• Discussion of the implications of income inequality on economic growth and social stability
• Review of traditional methods for measuring income inequality

Part 3:  Data Gaps and Their Implications
• Identification of common sources of data gaps in income inequality research
• Impact of data gaps on the accuracy and reliability of income inequality assessments
• Case studies of countries with significant data gaps

Part 4:  Innovative Methods for Addressing Data Gaps
• Introduction to data imputation techniques (e.g., multiple imputation, machine learning algorithms)
• Application of these techniques to income inequality data
• Evaluation of the strengths and limitations of different imputation methods

Part 5:  Empirical Analysis Using International Data
• Selection of countries with varying levels of data availability
• Collection and preprocessing of income data from multiple sources
• Application of imputation techniques to address data gaps

Part 6:  Case Studies of Income Inequality
• Detailed examination of income inequality in selected countries
• Analysis of the effectiveness of imputation techniques in revealing true income disparities
• Comparison of imputed results with traditional assessments

Part 7:  Policy Implications and Recommendations
• Discussion of the policy implications of improved income inequality measurements
• Recommendations for addressing income inequality based on empirical findings
• Strategies for enhancing data collection and reporting practices

Part 8: Future Directions in Income Inequality Research
• Identification of emerging trends and challenges in income inequality research
• Exploration of new data sources and innovative analytical methods
• Suggestions for future research directions to further improve income inequality assessments

Part 9: Data Analysis and Reporting
• Collection and analysis of relevant data using imputation techniques
• Interpretation of findings and implications for income inequality measurement
• Preparation of comprehensive reports and presentations

Part 10: Conclusion and Policy Recommendations
• Summarizing key findings from the research
• Policy recommendations for addressing income inequality
• Suggestions for future research directions

Part 11: Reporting and Presentation
•  Writing a comprehensive research report with clear structure, concise language, and accurate data presentation
•  Preparing and delivering an engaging oral presentation of the research background, methods, results, and conclusions

Suitable for

High School Students:  
•  Interested in economics, income inequality, and data analysis
• Basic knowledge of economics and statistics

University Students:
• Majoring in economics, data science, or related fields, seeking to deepen understanding and engage in research
• Familiar with basic economic theories, statistical methods, and data analysis techniques

Researchers and Educators:
• Professionals with in-depth knowledge in economics, income inequality, and data science
• Educators aiming to incorporate current research trends into their teaching and academic work