Each doubling giving you an extra 0.1 seems like a pretty big deal to me. It may be only explain a small percentage of the variance, but I would expect that to be true for most things. Are there many other factors that are much more important? I feel like we are applying selective rigour here if a lot of the other things we care about are even less important.
I would also expect this to be an underestimate for methodological reasons:
Rating scales with a ceiling will naturally reduce reported effect sizes if people are capping out.
Measurements error will naturally reduce the effect size.
Many people will achieve higher income only by working harder and longer hours and paying more taxes… if they are reporting more happiness even net of this disutility then the gross effect must be larger.
Worth noting that although those factors likely increase the expected strength of the relationship between money and happiness, when it comes to interpreting that strength, there are factors potentially reducing the proportion of the relationship that can be explained by “more money causes more happiness:”
Reverse causality (Being happier plausibly makes you earn more money through various social and health impacts)
Confounding variables (E.g. being a hard worker makes you happier, and being a hard worker just happens to make you more money on average)
Also, if you perceive success (i.e. status) as being strongly associated with having higher income, then the actual mechanism by which higher income raises your happiness may be through a status gain, rather than a consumption increase. And as status is a positional good, this would be a reason to down-revise our expectation that increasing a person’s consumption at these levels will actually increase a society’s net happiness.
Each doubling giving you an extra 0.1 seems like a pretty big deal to me. It may be only explain a small percentage of the variance, but I would expect that to be true for most things. Are there many other factors that are much more important? I feel like we are applying selective rigour here if a lot of the other things we care about are even less important.
I would also expect this to be an underestimate for methodological reasons:
Rating scales with a ceiling will naturally reduce reported effect sizes if people are capping out.
Measurements error will naturally reduce the effect size.
Many people will achieve higher income only by working harder and longer hours and paying more taxes… if they are reporting more happiness even net of this disutility then the gross effect must be larger.
Worth noting that although those factors likely increase the expected strength of the relationship between money and happiness, when it comes to interpreting that strength, there are factors potentially reducing the proportion of the relationship that can be explained by “more money causes more happiness:”
Reverse causality (Being happier plausibly makes you earn more money through various social and health impacts)
Confounding variables (E.g. being a hard worker makes you happier, and being a hard worker just happens to make you more money on average)
Also, if you perceive success (i.e. status) as being strongly associated with having higher income, then the actual mechanism by which higher income raises your happiness may be through a status gain, rather than a consumption increase. And as status is a positional good, this would be a reason to down-revise our expectation that increasing a person’s consumption at these levels will actually increase a society’s net happiness.
Good points.
Note that, if you are going to start thinking about these cofounders, you have to consider cofounders working against this relationship as well:
there is often a trade-off between more lucrative and more personally rewarding jobs
intuitively I think people who get more stressed are harder workers, though I’m certainly not confident in this claim.