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Just a perfect day? Developing a happiness optimised day schedule

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  • Kroll, Christian
  • Pokutta, Sebastian

Abstract

With the Day Reconstruction Method (DRM), Kahneman, Krueger, Schkade, Schwarz, and Stone (2004) introduced an important approach in subjective well-being (SWB) research to explore how people experience daily activities. A major unresolved question for laypeople and scholars alike resulting from this research, however, is the neglect of saturation and scarcity effects in this area of study. To fill this gap, we apply methods from optimisation research to the field of SWB. Combining utility functions with DRM data allows us to generate an optimal day schedule: It differs considerably from how people usually spend their time, whereby the distribution of activities is remarkably even. The results show how a paradigm shift away from a focus on increasing Gross Domestic Product towards greater well-being at the macrolevel could play out at the microlevel with potential consequences for how we might live our day-to-day lives.

Suggested Citation

  • Kroll, Christian & Pokutta, Sebastian, 2013. "Just a perfect day? Developing a happiness optimised day schedule," Journal of Economic Psychology, Elsevier, vol. 34(C), pages 210-217.
    • Handle: RePEc:eee:joepsy:v:34:y:2013:i:c:p:210-217
    DOI: 10.1016/j.joep.2012.09.015
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    References listed on IDEAS

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    1. Helliwell, John F., 2003. "How's life? Combining individual and national variables to explain subjective well-being," Economic Modelling, Elsevier, vol. 20(2), pages 331-360, March.
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    More about this item

    Keywords

    Day Reconstruction Method; Time use; Affect; Subjective well-being; Optimisation;
    All these keywords.

    JEL classification:

    • I10 - Health, Education, and Welfare - - Health - - - General
    • J22 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Time Allocation and Labor Supply
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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