A new Yale study suggests that human inclination for risk-taking is stable during a person’s lifetime, much like other personality traits.
The study was a collaboration between psychology professor Gregory Samanez-Larkin, and researchers at the Max Planck Institute for Human Development in Germany and the University of Basel in Switzerland. It analyzed data culled from the German Socio-Economic Panel, a longitudinal study of more than 44,000 Germans aged 18 to 85 who were surveyed over a period of 10 years. The study suggests both that people tend to take fewer risks as they get older and — more significantly, according to Samanez-Larkin — that people’s willingness to take risks remains stable relative to their peers’ over time, with the exception of the stressful periods at the beginning and end of life. The study was published Jan. 28 in the Journal of Personality and Social Psychology.
Samanez-Larkin noted that relative to their peers, a person’s degree of risk-taking remains stable.
“Say we’ve got, like, five 35-year-olds,” Samanez-Larkin said. “The most risk-taking one is still the most risk-taking one relative to their peers at 45. They’re still the most risk-taking, but they’re slightly less risk-taking than they were when they were 35. And so are the four people below them.”
Samanez-Larkin said this finding supports the notion that one’s inclination to take or avoid risks may be a personality trait. The study suggests that, like many personality traits, one’s relative willingness to take risks is relatively stable.
The study also suggests that though overall risk-taking tends to decrease with age, different types of risk-taking shift in different ways as people age. Social risk-taking and financial risk-taking, for instance, do not seem to experience the gradual decline physical risk-taking does over time, Samanez-Larkin said. The study suggests that social risk-taking — specifically, willingness to trust others — stays relatively flat across one’s lifespan and financial risk-taking stays relatively flat until just before retirement, when it declines.
“Most people assume that people become more risk-averse as they get older,” Samanez-Larkin said. “You think, like, oh, old people don’t do risky stuff. They don’t skateboard and bungee jump and things like that … [But], if we look across different domains, we can see: How does the risk-taking change in different domains? And is it the same as the recreational one? And it’s not, really.”
Samanez-Larkin said this finding might have implications for further research into areas like financial fraud involving the elderly, who are often considered more susceptible to con artists because of age-related declines in judgment but, according to the study, may actually be less financially risk-taking than younger people.
The study itself is notable for the large scale and longitudinal nature of its data set, University of Basel professor and study co-author Rui Mata said. Mata added that research like this is often hampered by a lack of suitable and sufficient data.
“In a way, it’s been a question of searching for data,” Mata said. “We’ve had this idea that we want to understand age differences in risk-taking — what are the cultural and individual life determinants for this? But we didn’t have the right data for this, because ideally what you’d have is data that follows people over time.”
Mata said that though the data used in the study is subject to bias because it was mostly self-reported, he and his colleagues were lucky to find it. It was only a “chance encounter” with researchers from the German Institute for Economic Research that alerted them to the potential of the data set, he said.
Yaniv Hanoch, a professor at Plymouth University who has also researched risk-taking, also said the study’s team was fortunate to find such a data set. Hanoch said he hopes similar sets will come forward as companies like Google begin to get involved in the capture and analysis of “big data.”
In addition to risk-taking measures, variables in the German Socio-Economic Panel include household composition, employment, occupations, earnings and health and satisfaction indicators.