You guys successfully nerdsniped me with this trends-in-happiness stuff, and now I’m trying to back away from the rabbit hole before it pulls me in (I actually downloaded the General Social Survey and started playing with the data! so many variables!). But here are the most salient things I’ve learned, for people curious about what this research means:
1. The paper that originally got me nerdsniped, “The Paradox of Declining Female Happiness” (Stevenson and Wolfers 2009), used data from the U.S. General Social Survey, so I’ve mostly looked at that. There are other data sources (see e.g. this interesting response to S&W 2009) that don’t have some of the GSS’ flaws. But I get the impression that the GSS is pretty popular with researchers.
2. The most important thing you need to know about the happiness measures on the GSS is that they are extremely coarse-grained. The survey item which produced the big “paradoxical” result about female happiness was the following question:
‘‘Taken all together, how would you say things are these days – would you say that you are (3) very happy, (2) pretty happy, or (1) not too happy?’’
Those are the only three options. The GSS does also ask about satisfaction with some specific areas of life, like finances and work (with 4 possible responses), and also asks about whether you have a happy marriage (same exact 3 options as on the general happiness question).
The only observed trend here, then, is increases/decreases in the fraction of respondents occupying each of these three boxes. Given that fact, I was really impressed with Stevenson and Wolfers 2008 (which I promo’d yesterday), in which the authors claim they can estimate, from just this information, the effects of time and demographic on the mean and variance of an underlying continuous distribution – without assuming the functional form of that distribution, and while simultaneously having to estimate the cutoffs that slice that continuum into the three boxes! I still have a “sounds fake but okay” reaction to this – I’m surprised the model is identifiable at all, and am kinda concerned about the stability of the estimates.
Technicalities aside, I was really excited about being able to get the variance as well as the mean, because given these 3 boxes, “happiness inequality” seems more morally salient to me than mean/median happiness trends.
Why? Well, think about the categories. I honestly am not sure what to make of people opting for “pretty happy” instead of “very happy,” or vice versa. If I imagine the General Social Survey people knocking on my door at various times in my past, I can imagine myself answering one or the other of those two on the basis of, like, how the past week had gone. I don’t see myself as aiming, in life, for a state of being that is consistently “very happy” as distinguished from “pretty happy.” Indeed, part of me reflexively bristles at the (callous?) indifference to outward circumstances that I imagine such a state would require!
On the other hand, the times in my life when I would have answered “not too happy” (the lowest possible option) are sharply distinguished from the others, and encompass some states of misery which I would very much like to prevent in others.
So, insofar as any “overall trend” here would mix together these two distinctions, it’s hard to interpret. But a decrease in variance, toward a mean that is at least somewhere in the middle, implies that we are raising people up from the “not too happy” box – which is all I care about.
Hence I was encouraged to hear that variance on this question has declined greatly, across and especially within groups, to the point of swamping the mean shift.
3. That still isn’t the full story though. Because remarkably few people use the lowest category. Either people are far happier than I (and the conventional wisdom) would imagine, or they are putting on an artificially happy face for the researchers.
Here are the male and female trend lines for the “not too happy” response (from the online data explorer, check it out):

You’ll note that they line up very closely, which is interesting. But also, they’re consistently between 10% and 20%. Apparently the remaining 80% of the U.S. population has been either “pretty happy” or “very happy” for the past 4 and a half decades! A golden age!
I first noticed this when I was working with the data offline and drilling down into a specific category – I think it was “married women who report their marriages are ‘not too happy’” (n.b. this is from the marital happiness question, not the general one). And I noticed that suddenly everything was really noisy, because my sample sizes were as small as 20-40 people per year. (For marital happiness this phenomenon is even more extreme – it’s more like 5% of women who say “not too happy,” with a full 60-70% reporting “very happy.”)
We appear to be studying, and fretting over, the slight variations in bliss level of a mostly blissed-out populace. Since this does not resemble the actual country I live in, something must have gone wrong with our measuring apparatus.









