How to predict how much you‘ll earn

Posted on under Today's research

You can go to a palmist, a Tarot reader, or a career counselor to get an idea of your likely future earnings. They will probably be about as accurate as each other.

Now, for the first time, an interesting piece of research enables researchers to rank the most important factors that predict future affluenc –and the findings might surprise you.

What the researchers say:  The researchers have used machine learning to rank the most important determinants of future affluence. Education and occupation were the best predictors – but surprisingly, a person’s ability to delay instant gratification was also among the most important determinants of higher income, beating age, race, ethnicity and height. Published in Frontiers in Psychology, the study suggests that interventions to improve this “delay discounting” could have literal payoffs in terms of higher income attainment.

Many factors are related to how much money a person will earn, including age, occupation, education, gender, ethnicity and even height. Behavioral variables are also implicated, such as one relating to the famous “marshmallow test.” This study of delay discounting, or how much a person discounts the value of future rewards compared to immediate ones, showed children with greater self-control were more likely to have higher salaries later in life.

But the study’s lead author says more traditional ways of analyzing data have been unable to indicate which of these factors are more important than others.

“All sorts of things predict income. We knew that this behavioral variable, delay discounting, was also predictive — but we were really curious how it would stack up against more common-sense predictors like education and age. Using machine learning, our study was the first to create a validated rank ordering of age, occupation, education, geographic location, gender, race, ethnicity, height, age and delay discounting in income prediction.”

Traditional methods used by psychologists (such as correlations and regression) haven’t allowed for a simultaneous comparison of different factors relating to an individual’s affluence. This study collected a large amount of data – from more than 2,500 diverse participants – and split them into a training set and a test set. The test set was put aside while the training set produced model results. The researchers then went back to the test set to test the accuracy of their findings.

Unsurprisingly, the models indicated that occupation and education were the best predictors of high income, followed by location (as determined by zip code) and gender – with males earning more than females. Delay discounting was the next most-important factor, being more predictive than age, race, ethnicity or height.

The researchers hope their approach will be part of a new era in data analysis. “This was amazing because it allowed us to check our findings and replicate them, giving us much greater confidence that they were accurate.

The study’s authors caution that the data sample was purposely limited to the United States and it is possible that the rank order of variables that predict salary may differ in other countries.

Said the lead author: “I would love to see a replication of this study in another culture. I also would be very interested in future studies aiming to reduce delay discounting. There is much debate about whether delay discounting is a stable trait or whether it is malleable – longitudinal studies could help settle that.”

So, what? The issue of delayed gratification is a big one currently and has sharply divided psychologists—who argue that it is a good thing which ought to be encouraged—and geneticists and many neuroscientists (as a psychologist and a behavioral neurogeneticist I have a foot in all three disciplines) who say that delayed gratification is unnatural to humans (or indeed any other species) and only happens in certain contexts. These will vary from individual to individual according to their DNA and/or their neurobiology.
Delayed gratification may well be associated with higher earnings for some but in evolutionary and genetic terms it is quite unnatural for one human to possess more than another—except by instant gratification (quickly grabbing the largest share of food or mates). It may be that what the researchers are actually measuring is not delayed gratification but something closer to strategic cunning.

The other problem with the study is whether it is measuring association or causation. Is it just that delayed gratification is associated with some people with higher earnings or does it cause them to have higher earnings? The methodology of the research cannot answer that question.

What now? In business and in science practitioners often confuse association with causality. The two are quite different and getting them mixed up has led to findings that can’t be replicated and businesses that fail