Open Access

UNVEILING AFFLUENCE: A BIG DATA PERSPECTIVE ON WEALTH ACCUMULATION AND DISTRIBUTION

https://doi.org/10.55640//ijmcsit-v02i06-03

pdf

Dr. Carlos A. Benítez ¹ , Prof. Prashant Singh Baghel ¹ ,

⁴ School of Data Science and Public Policy, Universidad de los Andes, Colombia

⁴ Centre for Data Analytics and Social Policy, Indian Institute of Technology Delhi, India

Abstract

The global landscape of wealth distribution is characterized by significant disparities, with a growing concentration of wealth at the apex. This article presents a comprehensive big data analysis of wealth accumulation patterns, aiming to uncover the multifaceted factors contributing to extreme wealth and its implications. Leveraging a large dataset of global billionaires, we investigate the "5 Vs" of big data—Volume, Velocity, Variety, Veracity, and Value—to systematically examine trends, drivers, and societal impacts. Our findings illuminate the complex interplay of economic, social, and technological forces in shaping wealth dynamics, offering insights into the institutional drivers, sectoral influences, and individual attributes associated with extraordinary wealth. The study contributes to the ongoing discourse on wealth inequality by providing an empirical, data-driven perspective on a critical contemporary issue.

Keywords

Wealth accumulation, wealth distribution, big data analytics, socioeconomic analysis

References

Njangang, H., Beleck, A., Tadadjeu, S., & Kamguia, B. (2022), ‘Do icts drive wealth inequality? evidence from a dynamic panel analysis’, Telecommunications Policy, 46(2), 102246. Available at: https://doi.org/10.1016/j.telpol.2021.102246.

Torgler, B. and Piatti, M. (2013) ‘Extraordinary wealth, globalization, and corruption’, Review of Income and Wealth, 59(2), pp. 341–359. Available at: doi:10.1111/roiw.12027.

Kong, G., Xu, L. and Zhang, W. (2022) ‘The benevolence of the billionaires: Evidence from China’s Hurun Rich List’, Finance Research Letters, 48, p. 103030. Available at: doi: 10.1016/j.frl.2022.103030.

Ghosh, S. (2016) ‘Billionaire wealth, firm performance and Financial Crisis: An empirical analysis for India’, South Asian Journal of Macroeconomics and Public Finance, 5(2), pp. 133–156. Available at: doi:10.1177/2277978716671050.

Bagchi, S. and Svejnar, J. (2013) ‘Does wealth inequality matter for growth? the effect of billionaire wealth, income distribution, and poverty’, SSRN Electronic Journal [Preprint]. Available at: doi:10.2139/ssrn.2351448.

Jacobs, D., 2015 ‘Extreme wealth is not merited’, Oxfam Discussion Papers.

Hemingway, A. and Rozworski, M. (2020) ‘Canadian billionaires’ wealth skyrocketing amid the pandemic’, Ottawa, ON, CA: Canadian Centre for Policy Alternatives.

Frémeaux, N. and Leturcq, M. (2022) ‘Wealth accumulation and the gender wealth gap across couples’ legal statuses and matrimonial property regimes in France’, European Journal of Population, 38(4), pp. 643–679. Available at: doi:10.1007/s10680-022-09632-5.

Hamermesh, D. and Leigh, A. (2022) ‘“Beauty too rich for use”: Billionaires’ assets and attractiveness’, SSRN Electronic Journal [Preprint]. Available at: doi:10.2139/ssrn.4114299.

Wai, J. and Lincoln, D. (2016) ‘Investigating the right tail of wealth: Education, cognitive ability, giving, network power, gender, ethnicity, leadership, and other characteristics’, Intelligence, 54, pp. 1–32. Available at: doi: 10.1016/j.intell.2015.11.002.

List, J., Shaikh, A., & Xu, Y. (2016) ‘Multiple hypothesis testing in experimental economics’, Experimental Economics. Available at: https://doi.org/10.3386/w21875

Gillis, A.S. (2021) ‘The 5 Vs of big data, Data Management.’ Available at:Vs-of-big-data (Accessed: 07 May 2023).

Nguyen, T.L. (2018) ‘A framework for five big Vs of Big Data and organizational culture in firms’, 2018 IEEE International Conference on Big Data (Big Data) [Preprint]. Available at: doi:10.1109/bigdata.2018.8622377.

Hamermesh, D. and Leigh, A. (2021) “Beauty too rich for use”: Billionaires’ assets and attractiveness [Preprint]. Available at: doi:10.3386/w29361.

Jesús Fernández-Villaverde, Hurtado, S., and Galo Nuño (2023), ‘Financial Frictions and the Wealth Distribution’, Econometrica, 91(3), pp.869–901. doi: https://doi.org/10.3982/ecta18180.

Kohlrausch, G. and Goncalves, S. (2023) ‘Wealth distribution on a dynamic complex network’ [Preprint]. doi:10.2139/ssrn.4673263.

Piper, R. (2023). The Institutional Drivers Contributing to Billionaire Wealth at the Sector Level. Class, Race Corporate Power, [online] 11(1). doi: https://doi.org/10.25148/crcp.11.1.010593.

Gastwirth, J.L., Luo, R. and Pan, Q. (2024). A statistical examination of wealth inequality within the Forbes 400 richest families in the United States from 2000 to 2023. METRON. doi: https://doi.org/10.1007/s40300-024-00267-6.

Dataset - Billionaires CSV File, https://corgis-edu.github.io/corgis/csv/billionaires/ [Accessed on 20 March 2024]

Most read articles by the same author(s)

1 2 3 4 5 6 7 8 9 10 > >>

International Journal of Modern Computer Science and IT Innovations

UNVEILING AFFLUENCE: A BIG DATA PERSPECTIVE ON WEALTH ACCUMULATION AND DISTRIBUTION

Abstract

Keywords

References

Most read articles by the same author(s)

Similar Articles