Investigating the right tail of wealth: Education, cognitive ability, giving, network power, gender, ethnicity, leadership, and other characteristics

摘要

The extent to which people in the right tail of wealth are highly educated and cognitively able was examined in a sample of 18,245 ultra high net worth (UHNW) individuals with net worth's of USD $30 million plus. How education and ability related to religion, ethnicity, political affiliation, relationship status, country, industry, leadership, gender, net worth, giving, and network power was assessed. And whether gender, religion, ethnicity, or network power differences existed in the right tail of wealth was examined. Overall, these people were highly educated and cognitively able, and smarter (more educated) people were wealthier, gave more, and had more powerful social networks (but when controlling for multiple confounds the association between education/ability and wealth was found to be quite small). Females were underrepresented, and female CEOs needed to be more select to reach the top of a company. Males and billionaires gave the most, but females and UHNW individuals gave more of what they had. U.S. Blacks and self-made females had the highest network power. U.S. Blacks and Caucasians were similarly educated and cognitively able. Democrats had a higher education and cognitive ability level than Republicans. Married people dominated and were the most educated and cognitively able, but least likely to have inherited their money and give. The finance, banking, investment, and internet sectors dominated. Jewish individuals were overrepresented by a factor of about 234. Today, the typical UHNW individual profile includes U.S. married (Christian and Jewish) men who are largely Chairman and CEO, Republican, and earned their money in finance, banking and investments. This study provides evidence for the clustering of brains, wealth and power, and suggests that elite education may matter in the trajectory of developing expertise in wealth and power generation. (C) 2015 Elsevier Inc. All rights reserved.