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Health and well-being in the great recession

Author

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  • Nikolaos Askitas
  • Klaus F. Zimmermann

Abstract

Purpose - – The purpose of this paper is to investigate the extent to which the authors can use internet search data in order to capture the impact of the 2008 Financial and Economic Crisis on well-being. Design/methodology/approach - – The authors look at the G8 countries with a special focus on USA and Germany and investigate whether internet searches reflect the “malaise” caused by the crisis. The authors focus on searches that contain the word “symptoms” and are thought to proxy self-diagnosis and those that contain “side effects” and are thought to proxy treatment. Findings - – The authors find that “malaise” searches spike in a fashion coincident with the crisis and its contagion timeline across the G8 countries. The authors show that results based on search recover previously known stylized facts from the economics of health, well-being and the business cycle. Research limitations/implications - – Internet penetration is high across the G8 countries. The authors nonetheless cannot get a good handle on the part of the population, which is not online. Moreover the authors cannot get a good grip on all confounding factors. More research would be necessary with access to search microdata. Originality/value - – The authors propose global proxies for diagnosis and treatment based on the “search buzz” for symptoms and side effects. The authors can thus capture trends on a global scale. This approach will become increasingly important.

Suggested Citation

  • Nikolaos Askitas & Klaus F. Zimmermann, 2015. "Health and well-being in the great recession," International Journal of Manpower, Emerald Group Publishing Limited, vol. 36(1), pages 26-47, April.
  • Handle: RePEc:eme:ijmpps:v:36:y:2015:i:1:p:26-47
    DOI: 10.1108/IJM-12-2014-0260
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    Citations

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    Cited by:

    1. Nikos Askitas, 2015. "Calling the Greek Referendum on the nose with Google Trends," RatSWD Working Papers 249, German Data Forum (RatSWD).
    2. Siliverstovs, Boriss & Wochner, Daniel S., 2018. "Google Trends and reality: Do the proportions match?," Journal of Economic Behavior & Organization, Elsevier, vol. 145(C), pages 1-23.
    3. Luca Bonacini & Giovanni Gallo & Fabrizio Patriarca, 2021. "Identifying policy challenges of COVID-19 in hardly reliable data and judging the success of lockdown measures," Journal of Population Economics, Springer;European Society for Population Economics, vol. 34(1), pages 275-301, January.
    4. Simionescu, Mihaela & Zimmermann, Klaus F., 2017. "Big Data and Unemployment Analysis," GLO Discussion Paper Series 81, Global Labor Organization (GLO).
    5. Yu Qin & Hongjia Zhu, 2018. "Run away? Air pollution and emigration interests in China," Journal of Population Economics, Springer;European Society for Population Economics, vol. 31(1), pages 235-266, January.
    6. Botezat, Alina, 2017. "Austerity plan announcements and the impact on the employees’ wellbeing," Journal of Economic Psychology, Elsevier, vol. 63(C), pages 1-16.
    7. Chiara L. Comolli & Daniele Vignoli, 2019. "Spread-ing uncertainty, shrinking birth rates," Econometrics Working Papers Archive 2019_08, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    8. Kronenberg, Christoph & Boehnke, Jan R., 2019. "How did the 2008-11 financial crisis affect work-related common mental distress? Evidence from 393 workplaces in Great Britain," Economics & Human Biology, Elsevier, vol. 33(C), pages 193-200.
    9. Gutiérrez, Antonio, 2022. "Movilidad urbana y datos de alta frecuencia [Urban mobility and high frequency data]," MPRA Paper 114854, University Library of Munich, Germany.

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