What does this research mean for the field?

The geographic clustering of happiness across European Union countries is driven by the spatial concentration of underlying socioeconomic and institutional determinants rather than a direct contagion of happiness between neighboring countries. Novelty: ClaimNovelty.INCREMENTAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

What question did this study set out to answer?

Investigate whether geographic proximity directly influences subjective wellbeing across the European Union or whether clustering is driven by shared socioeconomic determinants.

September 3, 2026WorldOpen Access

Does Geographic Proximity Matter for Happiness? Spatial Panel Evidence from the European Union (2015–2024)

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Authors

JSJorge de Andrés Sánchez

Discussion

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Overview

Spatial panel analysis finds happiness clustering across European Union countries stems from shared socioeconomic factors, indicating that regional wellbeing lacks direct cross-border contagion.

Key Points

Investigate whether geographic proximity directly influences subjective wellbeing across the European Union or whether clustering is driven by shared socioeconomic determinants.
Analyzed a panel of 270 observations across 27 European Union Member States from 2015 to 2024 using Cantril Ladder scores and six World Happiness Report determinants.
Tested spatial autocorrelation using Moran’s I and estimated non-spatial random effects alongside spatial autoregressive (SAR-RE), spatial error (SEM-RE), and combined SARAR-RE models with a three-nearest-neighbor weight matrix.
GDP per capita, social support, and freedom showed statistically significant positive associations with happiness, perceptions of corruption showed a negative association, and healthy life expectancy and generosity were not statistically significant.
Non-spatial models with country random effects and year fixed effects absorbed spatial dependence, leaving no significant residual spatial autocorrelation across the 2015–2024 period.
Spatial econometric models (SAR-RE and SEM-RE) did not significantly improve model fit, demonstrating that happiness clustering reflects geographic concentration of socioeconomic factors rather than direct contagion.

Cite This Study

Jorge de Andrés Sánchez (2026) studied this question.

synapsesocial.com/papers/6a993586636c6408cfa7db8b https://doi.org/10.3390/world7090152

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September 3, 2026WorldOpen Access

Does Geographic Proximity Matter for Happiness? Spatial Panel Evidence from the European Union (2015–2024)

View Full Paper

Ask AI

Bookmark

Authors

JSJorge de Andrés Sánchez

Discussion

Member takes

Overview

Spatial panel analysis finds happiness clustering across European Union countries stems from shared socioeconomic factors, indicating that regional wellbeing lacks direct cross-border contagion.

Key Points

Investigate whether geographic proximity directly influences subjective wellbeing across the European Union or whether clustering is driven by shared socioeconomic determinants.
Analyzed a panel of 270 observations across 27 European Union Member States from 2015 to 2024 using Cantril Ladder scores and six World Happiness Report determinants.
Tested spatial autocorrelation using Moran’s I and estimated non-spatial random effects alongside spatial autoregressive (SAR-RE), spatial error (SEM-RE), and combined SARAR-RE models with a three-nearest-neighbor weight matrix.
GDP per capita, social support, and freedom showed statistically significant positive associations with happiness, perceptions of corruption showed a negative association, and healthy life expectancy and generosity were not statistically significant.
Non-spatial models with country random effects and year fixed effects absorbed spatial dependence, leaving no significant residual spatial autocorrelation across the 2015–2024 period.
Spatial econometric models (SAR-RE and SEM-RE) did not significantly improve model fit, demonstrating that happiness clustering reflects geographic concentration of socioeconomic factors rather than direct contagion.

Cite This Study

Jorge de Andrés Sánchez (2026) studied this question.

synapsesocial.com/papers/6a993586636c6408cfa7db8b https://doi.org/10.3390/world7090152

View Full Paper

Ask AI

Bookmark