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...
Gespeichert in:
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| Weitere Verfasser: | , , , , |
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Paris
OECD Publishing
2016
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| Schriftenreihe: | OECD Statistics Working Papers
no.2016/03 |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| 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. |
| Beschreibung: | 1 Online-Ressource (37 p.) 21 x 29.7cm. |
| DOI: | 10.1787/5jlz9hpg0rd1-en |
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| spelling | Algan, Yann VerfasserIn aut Big Data Measures of Well-Being Evidence From a Google Well-Being Index in the United States Yann, Algan ... [et al] Paris OECD Publishing 2016 1 Online-Ressource (37 p.) 21 x 29.7cm. Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier OECD Statistics Working Papers no.2016/03 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. Employment Economics United States Beasley, Elizabeth MitwirkendeR ctb Guyot, Florian MitwirkendeR ctb Higa, Kazuhito MitwirkendeR ctb Murtin, Fabrice MitwirkendeR ctb Senik, Claudia MitwirkendeR ctb FWS01 ZDB-13-SOC FWS_PDA_SOC https://doi.org/10.1787/5jlz9hpg0rd1-en Volltext |
| spellingShingle | Algan, Yann Big Data Measures of Well-Being Evidence From a Google Well-Being Index in the United States Employment Economics United States |
| title | Big Data Measures of Well-Being Evidence From a Google Well-Being Index in the United States |
| title_auth | Big Data Measures of Well-Being Evidence From a Google Well-Being Index in the United States |
| title_exact_search | Big Data Measures of Well-Being Evidence From a Google Well-Being Index in the United States |
| title_full | Big Data Measures of Well-Being Evidence From a Google Well-Being Index in the United States Yann, Algan ... [et al] |
| title_fullStr | Big Data Measures of Well-Being Evidence From a Google Well-Being Index in the United States Yann, Algan ... [et al] |
| title_full_unstemmed | Big Data Measures of Well-Being Evidence From a Google Well-Being Index in the United States Yann, Algan ... [et al] |
| title_short | Big Data Measures of Well-Being |
| title_sort | big data measures of well being evidence from a google well being index in the united states |
| title_sub | Evidence From a Google Well-Being Index in the United States |
| topic | Employment Economics United States |
| topic_facet | Employment Economics United States |
| url | https://doi.org/10.1787/5jlz9hpg0rd1-en |
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