Modeling the Happiness-Sustainability Nexus via Graphical Lasso and Quantile-on-Quantile Regression

TL;DR

This study explores the complex, nonlinear relationship between happiness and sustainability across countries using advanced statistical methods, revealing that their connection varies significantly depending on the context and distributional extremes.

Contribution

It introduces a novel combination of Graphical Lasso and Quantile-on-Quantile Regression to analyze the heterogeneous and nonlinear nexus between happiness and sustainability.

Findings

Happiness and sustainability are directly linked with a partial correlation of 0.21.

The relationship varies across the distribution, being positive in low-happiness/high-sustainability countries.

The link is asymmetric and most significant at distributional extremes.

Abstract

This paper investigates the nexus between subjective well-being and sustainability, proxied by the Sustainable Development Goals (SDG) Index, using cross-country data from 126 nations in 2022. While prior research has highlighted a positive association between happiness and sustainable development, existing approaches largely rely on linear regressions or correlation-based measures that mask distributional heterogeneity, multicollinearity, and potential nonlinear dependence. To address these limitations, we employ a two methodological framework combining Graphical Lasso, and Quantile-on-Quantile Regression (QQR). The Graphical Lasso identifies a direct conditional link between happiness and sustainability after controlling for governance, income, and life expectancy, with a partial correlation of about 0.21. On the other hand, QQR reveals heterogeneous effects across the joint distribution: sustainability gains are positively associated with happiness for low-happiness but high-sustainability countries, negatively associated in high-happiness but low-sustainability contexts, and essentially neutral elsewhere. These findings suggest that the happiness-sustainability link is modest, asymmetric, and context-dependent, underscoring the importance of moving beyond mean-based regressions. From a policy perspective, our results highlight that institutional quality, income, and demographic factors remain the dominant drivers of both happiness and sustainability, while the interplay between the two dimensions is most pronounced in distributional extremes.