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How was the Weekend? How the Social Context Underlies Weekend Effects in Happiness and other Emotions for US Workers

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  • John F. Helliwell
  • Shun Wang

Abstract

In this paper we estimate the size of weekend effects for seven emotions and then explore their main determinants for the working population in the United States, using the Gallup/Healthways US Daily Poll 2008-2012. We first find that weekend effects exist for all emotions, and that these effects are not explained by sample selection bias. Full-time workers have a larger weekend effects than do part- time workers for all emotions except sadness, for which weekend effects are almost identical for all workers. We then explore the sources of weekend effects and find that workplace trust and workplace social relations, combined with differences in social time spent with family and friends, together almost fully explain the weekend effects for happiness, laughter, enjoyment and sadness, for both full-time and part-time workers, with significant but smaller proportions explained for the remaining three emotions - worry, anger and stress.

Suggested Citation

  • John F. Helliwell & Shun Wang, 2015. "How was the Weekend? How the Social Context Underlies Weekend Effects in Happiness and other Emotions for US Workers," NBER Working Papers 21374, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:21374
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    References listed on IDEAS

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    1. Mark P. Taylor, 2006. "Tell me why I don't like Mondays: investigating day of the week effects on job satisfaction and psychological well‐being," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 169(1), pages 127-142, January.
    2. John Helliwell & Shun Wang, 2014. "Weekends and Subjective Well-Being," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 116(2), pages 389-407, April.
    3. Semih Tumen & Tugba Zeydanli, 2014. "Day-of-the-Week Effects in Subjective Well-Being: Does Selectivity Matter?," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 119(1), pages 139-162, October.
    4. Wang-Sheng Lee, 2013. "Propensity score matching and variations on the balancing test," Empirical Economics, Springer, vol. 44(1), pages 47-80, February.
    5. Daniel Kahneman & Alan B. Krueger, 2006. "Developments in the Measurement of Subjective Well-Being," Journal of Economic Perspectives, American Economic Association, vol. 20(1), pages 3-24, Winter.
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    Cited by:

    1. Bhuiyan, Muhammad Faress & Ivlevs, Artjoms, 2019. "Micro-entrepreneurship and subjective well-being: Evidence from rural Bangladesh," Journal of Business Venturing, Elsevier, vol. 34(4), pages 625-645.
    2. Liu, Xinyan & Wang, Lu & Liu, Xiaowen & Zhai, Xiuxiu, 2024. "The impact of privacy violations on subsequent consumer preferences for anthropomorphized products," Journal of Business Research, Elsevier, vol. 174(C).
    3. John F. Helliwell & Lara B. Aknin & Hugh Shiplett & Haifang Huang & Shun Wang, 2017. "Social Capital and Prosocial Behaviour as Sources of Well-Being," NBER Working Papers 23761, National Bureau of Economic Research, Inc.
    4. John F. Helliwell & Haifang Huang & Max B. Norton & Shun Wang, 2019. "Happiness at Different Ages: The Social Context Matters," Springer Books, in: Mariano Rojas (ed.), The Economics of Happiness, chapter 0, pages 455-481, Springer.
    5. Samahita, Margaret & Holm, Håkan J., 2020. "Mining for Mood Effect in the Field," Working Papers 2020:2, Lund University, Department of Economics.
    6. Sergey Smetanin, 2022. "Pulse of the Nation: Observable Subjective Well-Being in Russia Inferred from Social Network Odnoklassniki," Mathematics, MDPI, vol. 10(16), pages 1-38, August.
    7. Ming-Chang Tsai, 2019. "The Good, the Bad, and the Ordinary: The Day-of-the-Week Effect on Mood Across the Globe," Journal of Happiness Studies, Springer, vol. 20(7), pages 2101-2124, October.
    8. Siqing Shan & Xijie Ju & Yigang Wei & Zijin Wang, 2021. "Effects of PM 2.5 on People’s Emotion: A Case Study of Weibo (Chinese Twitter) in Beijing," IJERPH, MDPI, vol. 18(10), pages 1-21, May.

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    More about this item

    JEL classification:

    • I31 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - General Welfare, Well-Being
    • J81 - Labor and Demographic Economics - - Labor Standards - - - Working Conditions

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