A new GLO Discussion Paper argues that big data can measure happiness and help making good policy decisions.
The Global Labor Organization (GLO) is an independent, non-partisan and non-governmental organization that functions as an international network and virtual platform to stimulate global research, debate and collaboration.
GLO Discussion Paper No. 634, 2020
Big Data and Happiness – Download PDF
by Rossouw, Stephanie & Greyling, Talita
GLO Fellows Stephanie Rossouw and Talita Greyling
Stepahnie Rossouw 
Talita Greyling
Author Abstract: The pursuit of happiness. What does that mean? Perhaps a more prominent question to ask is, ‘how does one know whether people have succeeded in their pursuit’? Survey data, thus far, has served us well in determining where people see themselves on their journey. However, in an everchanging world, one needs high-frequency data instead of data released with significant time-lags. High-frequency data, which stems from Big Data, allows policymakers access to virtually real-time information that can assist in effective decision-making to increase the quality of life for all. Additionally, Big Data collected from, for example, social media platforms give researchers unprecedented insight into human behavior, allowing significant future predictive powers.
GLO Discussion Papers are research and policy papers of the GLO Network which are widely circulated to encourage discussion. Provided in cooperation with EconStor, a service of the ZBW – Leibniz Information Centre for Economics, GLO Discussion Papers are among others listed in RePEc (see IDEAS, EconPapers). Complete list of all GLO DPs – downloadable for free.
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