Contrary to the widely accepted fantasy of the self-made bootstrapping successful wealthy person, blind luck has more to do with success than working hard or being intelligent. The world is rarely really a true meritocracy. That isn’t to say that there aren’t hardworking rich people, there of course are. What it means is that there are hardworking rich people, hardworking middle-class people, and hardworking poor people; the difference being mostly blind luck.
In other words, if we tossed five exceptionally hardworking people into a system with ninety-five mediocre workers, the five would not filter themselves to the top income bracket. Their average income may be marginally higher than the average income overall, but they would for the most part be distributed fairly evenly throughout the one hundred worker population.
The mostly false idea that rich people are rich because they work harder also goes in the other direction. The same people who buy into this idea often also believe that poor people are poor because they are immoral, degenerate, lazy, or some combination of many negative traits, which is an equally problematic world-view.
Role of luck in success: Empirical evidence
The first line of evidence that begins to chip away at the belief that hard work matters more than luck is the fact that it is mathematically impossible for the world’s richest people to be a gazillion times smarter and harder working than the average first-world worker. For example, the average lifetime earnings for an American with only a high school degree is $900,000. Jeff Bezos is currently worth about $112 billion. Does Jeff Bezos really work 124,444,444.44% harder than the average person with a high school degree? Can he really be 124,444,444.44% smarter than the average high school graduate? Absolutely not. Bezos is probably very smart and worked very hard, but he had a metric fucktonne of good luck, and that good luck is responsible for almost all of his wealth.
Do rich people put in more hours? Rowlingson and Connor (2011) talk about the amount of hours put in by high-earners and lower-earners:
“People in management and senior professional occupations in 2003 were most likely, of all occupations, to be working more than 45 hours per week (19 per cent), but such long hours were also fairly common in the skilled trades occupations (17 per cent) and among process plant and machine operatives (15 per cent). There were, therefore, relatively minor differences between these occupations in terms of hours worked, but there were major differences in terms of average weekly earnings… The management and senior professionals were therefore receiving more than double the salary, on average, of the machine operatives but not, it seems, working double the hours”
We’ve all heard the phrase, “work smarter, not harder.” So, could intelligence explain the huge discrepancies in pay between occupations putting in roughly the same hours (the most labor-intensive physically difficult occupations getting the short stick)? No, or at least, very little of the discrepancy can be explained by intelligence. Zagorsky (2007) analyzed IQ and income. The average IQ is by definition 100. As the graphic shows, with those of average IQ and above, there is virtually no relationship with wealth and intelligence.
Low IQs are somewhat more numerous at the lowest incomes, but this still leaves the overall strength of the correlation weak (considering how many high-earners have IQs below 100). All these relationships are even weaker once you look at wealth (net worth) instead of annual income.
In sum, there is a very, very slight relationship to wealth and income well below average IQ, but it is not meaningful, and is nearly non-existent at average and above IQ. The irony is that such results should justify helping the poor more and blaming them less for their situation.
Even competitiveness can’t adequately explain differences in wealth. Noe and Fang (2019) studied this question:
“For most standard statistical distributions of luck, no degree of competitiveness can ensure that talent always trumps luck. In some cases, increased competition even favors the talentless… We showed in this paper that, in a wide range of settings, such as analyst forecasting competitions and innovation races, talent cannot be identified by competition. In fact, increasing competition can sometimes favor luck rather than talent because of a subtle, game elevation effect.”
Everything from simulations to evaluations of real-life outcomes signalize the central role of luck in success. Furtado (2019) simulated 100,000 games of Risk to see how important luck versus strategy was; luck was the single most important factor, confirming what the author found in the academic literature.
Pluchinio, Biondo, Rapisarda (2018) ran simulations based on their talent versus luck (TvL) model where they considered individuals with talent (intelligence, skills, ability, etc.) normally distributed in the interval around a given mean, randomly placed in fixed positions with periodic boundary conditions and surrounded by a certain number of “moving” events such as someone got lucky, someone else didn’t. Their results reflect the Pareto (1897) distribution exhibited in real life. They conclude that their results highlight the failures of a “naive meritocracy” paradigm, a paradigm “which fails to give honors and rewards to the most competent people, because it underestimates the role of randomness among the determinants of success.”
Pluchino, Biondo, and Rapisarda (2019) cite statistician and risk analyst Nassim Nicholas Taleb (2007, 2012), financial expert and adjunct professor for Columbia law school Michael J. Mauboussin (2012), Frank (2016), and Watts (2011) to support their assertion that the “fundamental role of luck/chance in our life, as well as that of unpredictable events not under our control, has been, traditionally, strongly underestimated.” Rowlingson and Connor (2011) point out that not only do wealthy people often luck out from inheriting wealth from their parents, but “parents also transfer human, social and cultural capital to their children.” This of course increases the likelihood that children can expand or at least maintain the wealth inherited from their parents, even if they work no harder than the person who didn’t inherit such things.
Johnson and Reed (1996) concluded that the best way to become rich was not so much through hard work but being born to the right parents. They identify that, while hard work often can move you up to the next income bracket, there is a good deal of immobility at the extreme upper and lower wealth brackets; in other words, it is particularly difficult for rich people to become poor no matter how uncompetitive and lazy, and it is extremely difficult to work yourself out of rock bottom no matter how hard you try. It is not that either of these thing is impossible to accomplish, but that they are very difficult and subject to chance far more than effort or lack thereof. Along these lines, Hobcraft (1998) and Treasury HM and CASE (1999) confirmed that children from more impoverished backgrounds have significantly more difficulty overcoming the “brute luck” of the parental lottery, and that this is a major factor in determining future socio-economic chances in life.
Luck, a case study: Donald J. Trump
Donald Trump had the luck of being born to an already successful business man. He was born with resources and the coaching of how to use the financial and business systems to his benefit. This means, he didn’t have to actually be particularly innovative, clever, or hardworking. That he wasn’t a business prodigy is evidenced by his numerous failures: Trump steaks from 2007, Trump’s Expedia rip-off from 2006 (GoTrump.com), Trump Airlines from 1989, Trump Vodka from 2006, Trump Mortgage from 2006 (I guess his business acumen didn’t see the housing bubble coming), the board game from 1989 called Trump: The Game, Trump Magazine from 2007, Trump University, Trump Ice natural spring water from 2004, Tour de Trump bike races from 1989, Trump on the Ocean restaurant catering from 2012, The Trump Network vitamin pyramid scheme from 2009, Trumped! talk radio show from 2004, and Trump News Media in 1998, just to name a few.
All of those ventures were colossal flops. But unlike most people he had large amounts of money, the know-how to shift the consequences from his failures onto other people, and name recognition to lean on and prevent his failures from completely ruining him. Much of this turns on a watershed moment from the late 80s and early 90s.
After having Resorts International wrestled away from him in a legal battle with Merv Griffin (so much for the art of the deal) and his Taj Mahal casino venture filing for bankruptcy with nearly $3 billion in debt, Trump hired a guy named Steve Bollenbach as his CFO in 1990. Bollenbach showed Trump how to shrewdly avoid the $900 billion in debt that he had personally guaranteed in the Taj Mahal fiasco, and spoon-fed Trump his winning formula; licensing his name out rather than risking more of his own money in projects (Gallagher, 2017).
Donald Trump is an excellent case example of the profound power of luck complimented with a deficiency in ethical scruples. He was lucky to be born with money and a businessman dad who could show him the business world and give him connections in it. He was lucky he stumbled across Bollenback at the right time. And he was lucky to have a last name that he could convince other people to pay him money to let them use it.
The rich are often smart, hardworking, and competitive. However, the same is generally equally true for middle-class and poverty-level individuals. Luck is likely the single most important factor explaining the differences between the different levels of income. Luck in being born to wealth, luck in being born to parents with connections, luck in having access to better education, and even luck with IQ and biological temperament (though the latter two seem to play much smaller roles).
This means people at the middle and lower incomes should be enabled to be protected to a minimal degree from the vicissitudes of life that may crush a person who otherwise may have created and innovated. The extreme wealth of those on top should finance this. Such an argument is not simply about emotional appeals to help people down on their luck, but a logical argument that, given the fact that lower-income people are as likely to have innovative ideas as the ultra-rich, we should be investing in these people rather than just the ultra-rich. In essence, we would be taking a strategy similar to stock market investors who have a diversification strategy whereby they invest in promising small companies in addition to large ones. Duds will inevitably also be invested in, but there will be an overall net benefit. We would be helping society socially and financially, increasing total prosperity.
References and Citations
- Frank, R. H. (2016). Success and luck: Good fortune and the myth of meritocracy. Princeton, New Jersey: Princeton University Press.
- Furtado, B. A. (2019). Contributions of talent, perspective, context and luck to success. ArXiv, 1–9. Retrieved from http://arxiv.org/abs/2001.00034
- Gallagher, T. (2017). President-elect Trump: Is the past prologue? Society, 54(1), 10–13. https://doi.org/10.1007/s12115-016-0093-6
- Hobcraft, J. (1998). Intergenerational and life-course transmission of social exclusion: Influences and childhood poverty, family disruption and contact with the police. CASEpaper 15, (November 1998). Retrieved from http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=pubmed&cmd=Retrieve&dopt=AbstractPlus&list_uids=14117133739273129565related:XY4OEFci6sMJ
- Johnson, P., & Reed, H. (1996). Two nations: The inheritance of poverty and affluence. https://doi.org/10.1920/co.ifs.1996.0053
- Mauboussin, M. J. (2012). The success equation: Untangling skill and luck in business, sports, and investing. Harvard Business Review Press.
- Noe, T. H., & Fang, D. (2019). Does the cream rise to the top? Luck, Talent, success, and merit. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3456646
- Pareto, V. (1897). The New Theories of Economics. Journal of Political Economy, 5(4), 485–502. https://doi.org/10.1086/250454
- Pluchinio, A., Biondo, A. E., & Rapisarda, A. (2018). Talent versus luck: The role of randomness in success and failure. Advances in Complex Systems, 21(03n04), 1850014. https://doi.org/10.1142/S0219525918500145
- Pluchino, A., Biondo, A. E., & Rapisarda, A. (2019). Exploring the role of talent and luck in getting success. Acta Physica Polonica B Proceedings Supplement, 12(1), 17. https://doi.org/10.5506/APhysPolBSupp.12.17
- Rowlingson, K., & Connor, S. (2011). The ‘deserving’ rich? Inequality, morality and social policy. Journal of Social Policy, 40(3), 437–452. https://doi.org/10.1017/S0047279410000668
- Taleb, N. N. (2007). The black swan: The impact of the highly improbable. New York City: Random House.
- Taleb, N. N. (2012). Antifragile. In Antifragile. New York City: Random House.
- Treasury HM, & CASE. (1999). Persistent poverty and lifetime inequality: The evidence. Proceedings from a Workshop Organised HM Treasury CASE, (10). Retrieved from http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=pubmed&cmd=Retrieve&dopt=AbstractPlus&list_uids=related:RUBDPLbfmwMJ
- Watts, D. J. (2011). Everything is obvious: Once you know the answer. Crown Business. Zagorsky, J. L. (2007). Do you have to be smart to be rich? The impact of IQ on wealth, income and financial distress. Intelligence, 35(5), 489–501. https://doi.org/10.1016/j.intell.2007.02.003