• Medientyp: E-Book
  • Titel: Causality Between the Built Environment and Subjective Wellbeing : Applying Difference-in-Differences and Synthetic Control Methods to Longitudinal Data From England
  • Beteiligte: Chen, Jerry [Verfasser:in]; Wan, Li [Verfasser:in]
  • Erschienen: [S.l.]: SSRN, [2023]
  • Umfang: 1 Online-Ressource (26 p)
  • Sprache: Englisch
  • DOI: 10.2139/ssrn.4430978
  • Identifikator:
  • Schlagwörter: subjective wellbeing ; built environment ; relocation ; causal inference ; longitudinal study ; synthetic control methods ; difference-in-differences ; UK Understanding Society
  • Entstehung:
  • Anmerkungen: Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments April 24, 2023 erstellt
  • Beschreibung: Causality between the built environment and subjective wellbeing has thus far been segmentally explored and partially quantified. We identify two unresolved challenges in the literature. Firstly, a reliance on cross-sectional data produces associative findings. Secondly, a reductive approach to regress aggregate subjective wellbeing on limited and disparate built environment measurements risks significant confounding effects. We address the research gaps by leveraging residential relocation as a natural experiment to investigate the causality between built environment change and subjective wellbeing (measured with composite score of negatively phrased General Health Questionnaire-12 items). Two causal inference methods (difference-in-differences and synthetic control) are applied and compared. The use of the ‘Understanding Society’ dataset (The UK Household Longitudinal Study, 2009-2019), combined with holistic locational attributes (Area Classification at the Lower Super Output Area level as per the UK Census) for exploring such causality is novel in literature. Specifically, to estimate the wellbeing effects of residential relocation, we compare movers (treatment n=773) to non-movers (control n=4,619). To estimate the effects of built environment change, we compare movers with a change of built environment type (n=506) to those moving into the same built environment type (n=267). Our research design incorporates novel extensions to the canonical forms of both causal inference methods – staggered difference-in-differences and generalised synthetic control methods – to accommodate individual-level data with multiple relocation timepoints.Our results show immediate and enduring positive causal effects of residential relocation, equivalent to an average improvement of 8% in subjective wellbeing level compared to non-movers. Among movers, moving to a different built environment improves subjective wellbeing by 13% compared with moving to the same built environment type. Without a change in built environment type, the positive causal effects become negligible. We find the distress associated with the relocation is transitory, and preliminary evidence that relocation decisions are formed over years and influenced by acute stressors. We hypothesise that residential relocation and built environment change jointly alleviate existing distresses but play different and limited roles in delivering multi-dimensional subjective wellbeing benefits. We believe causal inference has wide application in urban planning research, and the potential to drive adaptive and human-centric policymaking
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