Abstract: (37 Views)
Introduction: In light of the growing importance of happiness and subjective well-being as the ultimate measure of development and the core of "happiness economics," this study focuses on Iran during the period of 2011–2024 (as an example of a shock-affected economy) to examine the relationship between income and happiness and to test the moderating role of income inequality and economic growth. Its primary objective is to propose and implement an innovative and indigenous framework for analyzing this relationship, which can potentially serve as an effective tool for monitoring and evaluating public policies.
Method: This study utilizes panel data from Iranian provinces (2011–2021) within an integrated Python-based analysis framework. An advanced mixed-methodology is employed, incorporating Bayesian modeling, machine learning algorithms, and non-parametric methods. To enhance accuracy and interpretability, Ridge regression (for managing multicollinearity) and the SHAP method (for model interpretation) are also applied.
Findings: Data analysis reveals that in Iran's economy, the decline in real purchasing power is the primary factor influencing happiness, rather than income inequality. The relationship between income and happiness follows an increasing and nonlinear trend. The effect of inequality was insignificant in advanced models, and only the "persistent materialism" hypothesis was confirmed. The results, derived from advanced Bayesian and machine learning methods, are robust and reliable.
Discussion: This research demonstrates that in Iran's economic context, preserving real purchasing power and controlling inflation have a more direct impact on happiness than reducing inequality. The findings highlight the need to localize mainstream happiness theories and prioritize economic stability in policy-making. The proposed framework also provides a practical tool for monitoring the impact of policies on subjective well-being.
Method: This study utilizes panel data from Iranian provinces (2011–2021) within an integrated Python-based analysis framework. An advanced mixed-methodology is employed, incorporating Bayesian modeling, machine learning algorithms, and non-parametric methods. To enhance accuracy and interpretability, Ridge regression (for managing multicollinearity) and the SHAP method (for model interpretation) are also applied.
Findings: Data analysis reveals that in Iran's economy, the decline in real purchasing power is the primary factor influencing happiness, rather than income inequality. The relationship between income and happiness follows an increasing and nonlinear trend. The effect of inequality was insignificant in advanced models, and only the "persistent materialism" hypothesis was confirmed. The results, derived from advanced Bayesian and machine learning methods, are robust and reliable.
Discussion: This research demonstrates that in Iran's economic context, preserving real purchasing power and controlling inflation have a more direct impact on happiness than reducing inequality. The findings highlight the need to localize mainstream happiness theories and prioritize economic stability in policy-making. The proposed framework also provides a practical tool for monitoring the impact of policies on subjective well-being.
Type of Study: orginal |
Received: 2025/12/7 | Accepted: 2026/06/28
Received: 2025/12/7 | Accepted: 2026/06/28
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Social Welfare Quarterly
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