Spatial analysis of subjective well-being in Japan

Anqi Li, Takaki Sato, Yasumasa Matsuda

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

This study investigates subjective well-being in Japan using a survey of 22,539 respondents in 46 prefectures in December 2019. We applied a Bayesian hierarchical model to the self-reported well-being respondents, supposing that well-being is decomposed into regional and individual factors. As a result, regional heteroscedasticity and individual factors are identified jointly, which clarifies the interesting features of Japanese subjective well-being. From the identified regional factors in prefectural levels, we find that Social Welfare Expenditure (SWE) per capita and Ratio of Forest Area (RFA) are positively related to subjective well-being. Some prefectures in Capital Region, which are at the bottom of happiness ranking, are correlated with lower SWE and FRA. In addition, coastal areas in Tohoku region damaged by the 2011 tsunami and nuclear plant accidents also have relatively lower subjective well-being. This finding suggests that residents in the regions have not recovered and require additional mental and physical public support.

Original languageEnglish
Pages (from-to)87-110
Number of pages24
JournalJapanese Journal of Statistics and Data Science
Volume5
Issue number1
DOIs
Publication statusPublished - 2022 Jul

Keywords

  • Bayesian hierarchical model
  • Great East Japan Earthquake and Tsunami
  • Happiness survey
  • Regional heteroscedasticity
  • Spatial error model
  • Subjective well-being

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