Built, Not Born: How Education Predicts Billionaire Wealth

Michael Jan Kendzia (), Tomas Neville and Maya Gadgil ()
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Michael Jan Kendzia: Zurich University of Applied Sciences (ZHAW)
Tomas Neville: Zurich University of Applied Sciences (ZHAW)
Maya Gadgil: Zurich University of Applied Sciences (ZHAW)

No 17994, IZA Discussion Papers from Institute of Labor Economics (IZA)

Abstract: This study investigates the key drivers behind the wealth accumulation of America’s 100 richest self-made billionaires, using data from the Forbes 400 list. Focusing on five individual and contextual factors—education, innovation, networks, inheritance, and geographic origins—the research applies regression analysis to evaluate the statistical significance and predictive power of each. The results show that education, especially from elite institutions, is a strong and consistent predictor of wealth. Innovation, measured by patents and entrepreneurial activity, shows the strongest correlation, emphasizing its centrality in modern wealth creation. Networks—both personal and professional—also play a crucial role, though they interact with other variables. In contrast, inheritance and geographic origins, while influential, exhibit weaker statistical associations. Notably, 89% of the cohort received little or no family funding, underscoring the importance of individual agency and external investment. The findings challenge assumptions about inherited wealth and highlight the role of human capital, innovation ecosystems, and urban opportunity structures in financial success.

Keywords: education and innovation; entrepreneurship; wealth accumulation; social mobility; economic mobility (search for similar items in EconPapers)
JEL-codes: D31 J24 L26 O31 (search for similar items in EconPapers)
Date: 2025-07
New Economics Papers: this item is included in nep-sbm
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