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

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...

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Bibliographische Detailangaben
Beteilige Person: Algan, Yann (VerfasserIn)
Weitere beteiligte Personen: Beasley, Elizabeth (MitwirkendeR), Guyot, Florian (MitwirkendeR), Higa, Kazuhito (MitwirkendeR)
Format: Elektronisch E-Book
Sprache:Englisch
Veröffentlicht: Paris OECD Publishing 2016
Schriftenreihe:OECD Statistics Working Papers
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Links:https://doi.org/10.1787/5jlz9hpg0rd1-en
Zusammenfassung: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
Umfang:1 Online-Ressource (37 Seiten) 21 x 29.7cm
DOI:10.1787/5jlz9hpg0rd1-en