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Happy People or Happy Places? A Multilevel Modeling Approach to the Analysis of Happiness and Well-Being


  • Dimitris Ballas
  • Mark Tranmer


This article aims to add a regional science perspective and a geographical dimension to our understanding of substantive questions regarding self-reported happiness and well-being through the specification and use of multilevel models. Multilevel models are used with data from the British Household Panel Survey and the Census of UK population to assess the nature and extent of variations in happiness and well-being to determine the relative importance of the area (district, region), household, and individual characteristics on these outcomes. Having taken into account the characteristics at these different levels, we are able to determine whether any areas are associated with especially positive or negative feelings of happiness and well-being. Whilst we find that most of the variation in happiness and well-being is attributable to the individual level, some variation in these measures is also found at the household and area levels, especially for the measure of well-being, before we control for the full set of individual, household, and area characteristics. However, once we control for these characteristics, the variation in happiness and well-being is not found to be statistically significant between areas.

Suggested Citation

  • Dimitris Ballas & Mark Tranmer, 2012. "Happy People or Happy Places? A Multilevel Modeling Approach to the Analysis of Happiness and Well-Being," International Regional Science Review, , vol. 35(1), pages 70-102, January.
  • Handle: RePEc:sae:inrsre:v:35:y:2012:i:1:p:70-102

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    Cited by:

    1. Vanchai Ariyabuddhiphongs & Joseph Li, 2016. "Buddhist Good Karma of Giving, Optimism, and Happiness Among Thai Female Sex Workers," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 127(2), pages 903-917, June.
    2. Eric Morris & Erick Guerra, 2015. "Mood and mode: does how we travel affect how we feel?," Transportation, Springer, vol. 42(1), pages 25-43, January.
    3. Nicola Pontarollo & Mercy Orellana Bravo & Joselin Segovia Sarmiento, 2017. "The determinants of subjective wellbeing in a developing country: The Ecuadorian case," JRC Working Papers JRC109319, Joint Research Centre (Seville site).
    4. repec:spr:jhappi:v:18:y:2017:i:6:d:10.1007_s10902-016-9790-5 is not listed on IDEAS
    5. Borchers, Allison M. & Xiarchos, Irene & Beckman, Jayson, 2014. "Determinants of wind and solar energy system adoption by U.S. farms: A multilevel modeling approach," Energy Policy, Elsevier, vol. 69(C), pages 106-115.
    6. Karl Aiginger & Kurt Kratena & Margit Schratzenstaller & Teresa Weiss, 2014. "Moving towards a new growth model," WWWforEurope Deliverables series 3, WWWforEurope.
    7. Ivlevs, Artjoms & Veliziotis, Michail, 2015. "Local-Level Immigration and Life Satisfaction: The EU Enlargement Experience in England and Wales," IZA Discussion Papers 9513, Institute for the Study of Labor (IZA).


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