Global Ease of Living Index: a machine learning framework for longitudinal analysis of major economies
Tanay Panat, Rohitash Chandra
TL;DR
The paper introduces the Global Ease of Living Index (EoLI), a longitudinal, multidimensional measure designed to quantify living conditions across major economies from 1970 to 2021. It combines Economic, Institutional, Quality of Life, and Sustainability sub-indices derived via Factor Analysis and Principal Component Analysis, with missing data addressed through Random Forest Regressor and Multiple Imputation by Chained Equations. The authors demonstrate a transparent, open data-driven framework, compare imputation methods, and analyze regional patterns to reveal how governance, health, and environmental factors jointly shape living standards beyond GDP alone. The work provides a practical tool for policymakers to identify gaps and track progress, while highlighting disparities with happiness-based measures and offering avenues for methodological enhancements and broader data inclusion.
Abstract
The drastic changes in the global economy, geopolitical conditions, and disruptions such as the COVID-19 pandemic have impacted the cost of living and quality of life. It is important to understand the long-term nature of the cost of living and quality of life in major economies. A transparent and comprehensive living index must include multiple dimensions of living conditions. In this study, we present an approach to quantifying the quality of life through the Global Ease of Living Index that combines various socio-economic and infrastructural factors into a single composite score. Our index utilises economic indicators that define living standards, which could help in targeted interventions to improve specific areas. We present a machine learning framework for addressing the problem of missing data for some of the economic indicators for specific countries. We then curate and update the data and use a dimensionality reduction approach (principal component analysis) to create the Ease of Living Index for major economies since 1970. Our work significantly adds to the literature by offering a practical tool for policymakers to identify areas needing improvement, such as healthcare systems, employment opportunities, and public safety. Our approach with open data and code can be easily reproduced and applied to various contexts. This transparency and accessibility make our work a valuable resource for ongoing research and policy development in quality-of-life assessment.