Chapter 16: Redefining Sustainability: The Role of a Happy Planet Index in Enhancing SDG

Purpose: The study aims to enrich sustainable development assessments by integrating the Happy Planet Index (HPI) with Sustainable Development Goals (SDGs) using locally weighted scatterplot smoothing (LOESS) regression, revealing complex trade-offs among well-being, environmental efficiency, and broader sustainability objectives to guide more nuanced and effective policy actions.

Need for study: This study is needed to address the limitations of traditional economic metrics in sustainable development by offering a holistic framework that incorporates well-being and environmental sustainability, thus providing a more comprehensive understanding of and approach to achieving global sustainability goals.

Methodology: The methodology involves using LOESS (locally weighted scatterplot smoothing) regression to analyse the nuanced interactions between the HPI scores and SDGs, facilitating a deeper understanding of the complex relationship among environmental efficiency, well-being, and sustainability.

Findings: The optimal LOESS model adjustment of SDG scores with the HPI highlights stark national disparities: countries like North Macedonia, Cyprus, and Turkey underperform due to urbanization, inequality, instability, and environmental issues, whereas Finland, Sweden, and Denmark excel in SDG achievements, likely due to robust welfare, environmental policies, political stability, and infrastructure.

Practical implications: This study’s practical implications suggest that integrating HPI with SDGs can guide policymakers towards more effective, balanced strategies for sustainable development, acknowledging the trade-offs between well-being and environmental efficiency to achieve global sustainability goals.