Big Data for Computing Social Well-Being Indices of the Russian Population

Applied Econometrics, Vol. 50, pp. 43-66

Posted: 7 Aug 2018

See all articles by Dean Fantazzini

Dean Fantazzini

Moscow School of Economics, Moscow State University; National Research University Higher School of Economics

Marina Shakleina

Moscow State University

Natalia Yuras

Moscow State University

Date Written: 2018

Abstract

The article builds indices of social well-being based on Google Trends Data for predicting VCIOM indices. The Google indices were computed using a Google Trends dataset for 2006–2016 containing 512 search queries relative to housing conditions, income, education, etc., and applying factor analysis. Bayesian Model Averaging was then used to select the indexes of individual social well-being mostly associated with the VCIOM indices which measure the social well-being of the Russian population. Additional regression models and forecasting exercises confirmed the previous results. Based on the Google Trends Data, the indices of the subjective social well-being are statistically reliable, as evidenced by a strong correlation between the observed and predicted values of the VCIOM indices.

Keywords: VCIOM Indices, Big Data, Google Trends, Factor Analysis, Bayesian Model Averaging

JEL Classification: С52, I32

Suggested Citation

Fantazzini, Dean and Shakleina, Marina and Yuras, Natalia, Big Data for Computing Social Well-Being Indices of the Russian Population (2018). Applied Econometrics, Vol. 50, pp. 43-66. Available at SSRN: https://ssrn.com/abstract=3215502

Dean Fantazzini (Contact Author)

Moscow School of Economics, Moscow State University ( email )

GSP-2, Leninskie Gory
Moscow, 119992
Russia
+7 495 5105256 (Phone)
+7 495 5105267 (Fax)

HOME PAGE: https://sites.google.com/site/deanfantazzini/

National Research University Higher School of Economics ( email )

Myasnitskaya street, 20
Moscow, Moscow 119017
Russia

HOME PAGE: http://www.hse.ru/org/persons/11532644

Marina Shakleina

Moscow State University ( email )

GSP-2, Leninskie Gory
Moscow, 119992
Russia

Natalia Yuras

Moscow State University ( email )

GSP-2, Leninskie Gory
Moscow, 119992
Russia

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