Global Ease of Living Index: a machine learning framework for longitudinal analysis of major economies
arXiv:2502.06866v3 Announce Type: replace 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 essential to comprehend the long-term implications 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 infrast
The paper is published amidst ongoing global economic shifts and disruptions, motivating new frameworks for comprehensive socio-economic analysis.
This machine learning framework provides a transparent and multi-dimensional approach to quantifying quality of life, offering a more nuanced understanding of economic conditions beyond traditional metrics.
The development of a Global Ease of Living Index could lead to more robust and data-driven policy-making, impacting how major economies are assessed and managed.
- · International organizations
- · Policymakers
- · Data scientists
- · Economists
- · Traditional economic models
- · Simple quality of life metrics
The index could become a standard for evaluating national economic health and citizen welfare.
Governments might re-prioritize policies based on specific dimensions revealed by the index, leading to shifts in resource allocation.
Enhanced transparency could influence capital flows and investment decisions, favoring countries that demonstrate improvements in the index over time.
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Read at arXiv cs.LG