Kahneman's $75,000 Happiness Plateau Was a Bracket Midpoint (PNAS 2023)

“There is no further progress beyond an annual income of ~$75,000.” Daniel Kahneman and Angus Deaton wrote that sentence in 2010, and it has been quoted for fifteen years. In 2023, Kahneman went back to it with a former rival and pointed out something odd: $75,000 “is simply the midpoint of the ‘60 to 90K’ income category.” The survey never measured a threshold at 75. It measured a bracket.

So does money stop buying happiness at some number? Short answer from the 2023 PNAS paper by Matthew Killingsworth, Daniel Kahneman and Barbara Mellers: for most people, no. Average happiness kept rising with income in the data they reanalysed. The plateau is real only for the least happy 15 to 20 percent, whose happiness stops improving with income at roughly $100,000.

What did the 2010 study actually measure?

Kahneman and Deaton analysed “more than 450,000 responses” to the Gallup-Healthways Well-Being Index, collected in 2008 and 2009. Respondents answered yes or no questions about the previous day: did you experience happiness, enjoyment or frequent smiling during a lot of the day, and did you experience worry or sadness? Each person’s score was a fraction between 0 and 1.

The curves rose with income, then flattened. The evidence for flattening, per the 2023 paper, was that the two top income categories (90 to 120k and 120k or more) gave statistically indistinguishable averages despite large samples. Everything after that was interpretation, including the round number that travelled into headlines.

What did Killingsworth find in 2021?

Killingsworth’s study used experience sampling instead of next-day recall. The paper reports “1,725,994 experience-sampling reports from 33,391 employed US adults,” prompted on their phones and asked, “How do you feel right now?” on a continuous scale from “Very bad” to “Very good.” His average happiness rose in a straight line against the logarithm of income, past $200,000, with no bend at all.

Two studies by two serious researchers, two opposite headlines. Kahneman and Killingsworth agreed the contradiction was their responsibility, asked Mellers to facilitate, and ran an adversarial collaboration.

What did the joint reanalysis find?

They tested a two-part hypothesis: an unhappy minority whose misery eases with income up to a threshold and then stops, and a happier majority whose happiness keeps climbing. Using quantile regression on Killingsworth’s data, with separate slopes below and above $100,000, they found both patterns at once. The slopes at the low end of the happiness distribution, from the paper’s Table 1:

Percentile of happiness	Slope up to $100k	Slope above $100k
5% (least happy)	2.34 (t = 4.7)	0.25 (t = 0.5)
10%	1.75 (t = 6.6)	0.52 (t = 1.4)
15%	1.90 (t = 8.4)	0.34 (t = 1.0)
20%	1.84 (t = 8.5)	0.62 (t = 1.8)
30%	1.33 (t = 6.3)	1.21 (t = 4.3)

The paper states that slopes above $100k were not statistically significant for the bottom three percentiles and only marginal (P = 0.08) at 20%. By the 30th percentile the two slopes are nearly equal, so the line is straight. At the top of the distribution the direction reverses: the slope above $100k for the 85th percentile accelerates (P = 0.023), the opposite of what a ceiling effect predicts.

In the authors’ words, “the flattening pattern exists but is restricted to the least happy 20%.” Among happier people, “happiness increases steadily with log(income), and even accelerates in the happiest group.”

Why did the 2010 paper overstate it?

The authors blame a ceiling effect. In the Gallup data at high incomes, average positive affect was 89% of a perfect score. When most people pick the maximum, the items cannot tell a happy person from a very happy one. Their analogy is a cognitive test most healthy people pass perfectly: it measures dementia, and tells you nothing about differences between sharp minds.

By that logic the 2010 items were better read as a measure of unhappiness, and “Unhappiness diminishes with increasing income, but there is no further progress beyond ~$75,000” would have been a defensible headline. They add that standard practice of reporting averages assumes the whole distribution shifts together, a homogeneity assumption nobody had checked.

How big is the income effect anyway?

Smaller than the argument suggests. The paper reports a correlation of 0.09 between average happiness and log income in the experience-sampling data, and a gap of “about five points on a 100-point scale” between median happiness at $15,000 and $250,000 household income. The 2010 paper put a roughly fourfold income difference on par with being a caregiver, twice the effect of being married, about equal to a weekend, and under a third of a headache.

Two calculations of my own, using only those published figures. A correlation of 0.09 means log income accounts for about 0.8 percent of the variance in happiness (0.09 squared is 0.0081). And $250,000 is about 16.7 times $15,000, roughly 4.1 doublings, so five points over four doublings is about 1.2 points per doubling of income on the median. That figure assumes a straight line between the medians, which the paper does not claim.

What does this imply for novelty, goals and money?

Mostly that income is a real but modest lever, and that its payoff differs by where you start. For people near the bottom of the happiness distribution, the first $100,000 matters a great deal and the next dollars little, which is consistent with misery that salary does not reach. For everyone else the association keeps going.

It does not follow that effort aimed at a more varied life is wasted or that it beats a raise. Neither of the two studies measured novelty, goal progress or how people spend. If you want evidence on those, read separate work: Dunn, Aknin and Norton’s 2008 spending experiment tested who the money goes to, and the oddball effect covers how unfamiliar days stretch in memory. Those are different claims from the one the income papers make.

One comparison the paper does license: the effect of a fourfold income gap sat in the same range as ordinary daily circumstances such as a weekend or a headache. If a gap that large is similar in size to a headache, small changes to daily life are not obviously trivial next to it, though the paper does not compare them.

What the evidence does not establish

• Causation. The authors say plainly that “increase” and “gain” describe “cross-sectional associations,” not what happens when a particular person’s pay rises.
• Anything about people outside the sample. Killingsworth’s participants were employed US adults between 18 and 65 who chose to download an app, and the Gallup respondents were US residents surveyed in 2008 and 2009.
• Why the unhappiest 20% flatten. Heartbreak, bereavement and clinical depression are the authors’ suggested examples, offered without a test.
• That the 2023 paper settles the debate for everyone. Deaton did not participate, and one author on each side is not the whole field.
• The dollar threshold itself. $100,000 is the dividing line the authors chose in order to make the two datasets comparable.

I read the full text of the 2023 PNAS paper (open access). The 2010 and 2021 papers are described here only as the 2023 authors quote and summarise them.

Money buys less of a sense of control than people expect, a theme in the Whitehall studies of job control.

Where does that leave a goal that costs nothing?

If money gives a small, uneven return, the more portable question is what the cheap, repeatable parts of a week do. A conversation with a barista or a neighbour is one tested example, and a deliberately unfamiliar Saturday is another. Both are free, and both depend on actually leaving the house in the morning. People who want an outside witness on that kind of daily behaviour can read how DontSnooze works.