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Big Data Measures of Well-Being : Evidence From a Google Well-Being Index in the United States / Yann Algan ... [and others].

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Format:
Book
Government document
Author/Creator:
Algan, Yann, author.
Contributor:
Beasley, Elizabeth.
Guyot, Florian.
Higa, Kazuhito.
Murtin, Fabrice.
Senik-Leygonie, Claudia.
SourceOECD (Online service)
Series:
OECD Statistics Working Papers 18152031 ; no.2016/03.
OECD Statistics Working Papers 18152031 ; no.2016/03
Language:
English
Subjects (All):
Employment (Economic theory).
Economics.
United States.
Local Subjects:
United States.
Physical Description:
1 online resource (37 pages).
Place of Publication:
Paris : OECD Publishing, 2016.
System Details:
text file
Summary:
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.
Notes:
Title from title screen (viewed May 1, 2017).
Access Restriction:
Restricted for use by site license.

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