Does exposure to richer and poorer neighborhoods influence wellbeing?

Donggen Wang*, Tim Schwanen, Zidan Mao

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

22 Citations (Scopus)


Geographical differences in wellbeing have attracted increased attention in the science of happiness literature and recent research has become particularly interested in high-resolution spatial differentiation within cities. This study contributes to this literature by analyzing the relationships between subjective wellbeing and relative income at the neighborhood level using activity-travel survey data from 2010 in Hong Kong. In contrast to previous studies, the analysis concentrates not only on life satisfaction but also on pleasure derived from daily activities in the city, and considers relative income in people's residential neighborhood and the neighborhoods where they conduct different types of daily activity. The results suggest that social comparisons with regard to income matter to life satisfaction as well as emotional wellbeing, that the effects occur for both the residential neighborhood and the urban places where daily activities are undertaken, and that downward income comparisons tend to have stronger effects on wellbeing than upward comparison. One theoretical implication that follows from the analysis is that the impact of social comparison in the science of happiness needs to be theorized as dynamic, mobile and contingent upon people's daily trajectories through time and urban space.

Original languageEnglish
Article number102408
Publication statusPublished - Dec 2019

Scopus Subject Areas

  • Development
  • Sociology and Political Science
  • Urban Studies
  • Tourism, Leisure and Hospitality Management

User-Defined Keywords

  • Hong Kong
  • Income
  • Life satisfaction
  • Neighborhood
  • Pleasure
  • Social comparison
  • Wellbeing


Dive into the research topics of 'Does exposure to richer and poorer neighborhoods influence wellbeing?'. Together they form a unique fingerprint.

Cite this