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Big Data Measures of Well-Being: Evidence From a Google Well-Being Index in the United States

Author

Listed:
  • Yann Algan

    (Sciences Po, Paris)

  • Elizabeth Beasley

    (CEPREMAP)

  • Florian Guyot

    (Sciences Po, Paris)

  • Kazuhito Higa

    (Kyushu University)

  • Fabrice Murtin

    (OECD)

  • Claudia Senik

    (Paris School of Economics)

Abstract

We build an indicator of individual subjective well-being in the United States based on Google Trends. The indicator is a combination of keyword groups that are endogenously identified to fit with the weekly time-series of subjective well-being measures disseminated by Gallup Analytics. We find that keywords associated with job search, financial security, family life and leisure are the strongest predictors of the variations in subjective well-being. The model successfully predicts the out-of-sample evolution of most subjective well-being measures at a one-year horizon. Un indicateur de bien-être subjectif est construit pour les États-Unis sur la base des données de Google Trends. L’indicateur est une combinaison de mots-clés qui sont identifiés pour reproduire les séries hebdomadaires de bien-être subjectif de Gallup Analytics. Nous trouvons que les mots-clés associés à la recherche d’emploi, à la sécurité financière, à la vie de famille et aux loisirs sont les plus forts prédicteurs des variations du bien-être subjectif. Le modèle prévoit l’évolution hors échantillon de la plupart des mesures de bien-être à l’horizon d’un an.

Suggested Citation

  • Yann Algan & Elizabeth Beasley & Florian Guyot & Kazuhito Higa & Fabrice Murtin & Claudia Senik, 2016. "Big Data Measures of Well-Being: Evidence From a Google Well-Being Index in the United States," OECD Statistics Working Papers 2016/3, OECD Publishing.
    • Handle: RePEc:oec:stdaaa:2016/3-en
    DOI: 10.1787/5jlz9hpg0rd1-en
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    Cited by:

    1. K. I. Shaklein, 2018. "Monitoring of Global and National Consumer Trends — Importance Stage of Strategizing (Based on Rabbit Industry)," Administrative Consulting, Russian Presidential Academy of National Economy and Public Administration. North-West Institute of Management., vol. 1(7).
    2. Fantazzini, Dean & Shakleina, Marina & Yuras, Natalia, 2018. "Big Data for computing social well-being indices of the Russian population," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 50, pages 43-66.
    3. Krzysztof Drachal & Daniel González Cortés, 2022. "Estimation of Lockdowns’ Impact on Well-Being in Selected Countries: An Application of Novel Bayesian Methods and Google Search Queries Data," IJERPH, MDPI, vol. 20(1), pages 1-24, December.
    4. Arnaud Joskin, 2017. "Working Paper 04-17 - Qu’est-ce qui compte pour les Belges ? Analyse des déterminants du bien-être individuel en Belgique [Working Paper 04-17 - Wat telt voor de Belgen? Analyse van de determinante," Working Papers 1704, Federal Planning Bureau, Belgium.

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