Money matters for life satisfaction (especially if you are good at math)

Today’s blog post focuses on a new paper, just published in PLOS ONE. In it, we ask whether numeracy seems to make a difference to life satisfaction (and how). The paper is open source and can be downloaded for free by using this link.

Bjälkebring, P., & Peters, E. (2021). Money matters (especially if you are good at math): Numeracy, verbal intelligence, education, and income in satisfaction judgments. PLOS ONE, 16(11), e0259331. https://doi.org/10.1371/journal.pone.0259331.

Using a large, diverse sample of Americans (N= 5,748), we demonstrated that people better at math made more money. For every one additional question they answered correctly on an eight-item math test, they reported $4,062 more in annual income. People better at math also were more satisfied with their lives than those with lower math ability, suggesting—perhaps not surprisingly—that income matters to life satisfaction.

However, we also wanted to think about the idea that numeracy might change how people looked at the world around them. We thought that the relation between numeracy and life satisfaction might not be as simple as greater numeracy = higher income and higher life satisfaction. Research on income and life satisfaction suggests that how satisfied we are with our income depends on how we feel it compares to other people’s incomes. For example, if I make $50,000 a year, I might be very satisfied, but if someone tells me that a newly hired colleague makes $60,000 for the same work, I will likely feel less satisfied. Hence, how I feel about my salary will depend on how it compares to others’ incomes. These are called relative-income effects.

But people better at math tend to compare numbers more than those worse at math. Might they compare incomes more? Consistent with this, life satisfaction among people better at math related much more to their incomes; they were happier if their income was higher. For people worse at math, their life evaluations depended much less on income. As a result, people better at math had the highest life satisfaction (when they had high incomes) and the lowest life satisfaction (when they had lower incomes). Thus, the same income was valued differently by those better and worse at math. See Figure 1.

Figure 1. The people that scored 8 questions correct on our math test both had the highest and the lowest life satisfaction depending on their income.

Finally, those better at math were happier with every income increment; no clear income satiation point was seen among them. For people worse at math, however, they were happier with more income only up until about $50,000, after which earning more made little difference. Those worse at math may derive their life satisfaction from sources other than income. See Figure 2.

Figure 2. People that scored highest on our math test (red line) was more influenced by their income and their line was steeper compare to those who scored lower, meaning they were influenced more. You can also see that at points lower than the average income (to the left of the arrow) the red line is on the bottom, but at higher incomes (to the right of the arrow) the red line is on top indicating that math ability is most beneficial for those with higher than average incomes.

More detail about our methods:

Participants were panel members of the Understanding America Study, which is maintained by the University of Southern California (USC). An address-based sampling method was used to recruit participants. Panel members have completed modules over time and were paid accordingly (e.g., $5 for a 5-minute module). Only panelists who completed all relevant measures were included in analyses, resulting in a final N= 5,748 in our sample.

Participants answered an eight-question math test, as well as questions about their income, income satisfaction, and life satisfaction. In analyses, we controlled for verbal intelligence and education and their interactions with income, as well as personality traits and other demographics.

Lastly, we would like to thank our funders, the Swedish Research Council (VR; DNR-2016-00507) to P. B. and the National Science Foundation (SES‐1155924, SES‐1558230 and SES-2017651) to E. P. The content of this paper is solely the responsibility of the authors and does not necessarily represent the official views of our funders, USC, or UAS.

The paper is open source so you can download the paper for free by using this link.

This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Meaning that you can reuse the text, figures and graphs on your blog, journal newspaper, book etc., as long as original authors and source are credited.