I agree that we can and should try to be Bayesian but, if we do, we still don’t get a slam-dunk result that economic growth will increase average happiness (at least, in already rich countries).
The story that often gets told to explain why the Easterlin Paradox holds refers to hedonic adaptation, social comparison, and evolution. We are very good at getting used to lots of things but we do continue to notice our status relative to others. How much material prosperity do we really need, given humans are basically naked apes who evolved to live in the savannah? We might imagine getting richer would make a difference to us, but think about the last thing you were really excited to buy, then think about how you’ve stopped paying attention to it. Therefore, we can explain both why money would matter in the cross-section and why it wouldn’t matter in the time-series. So noticing that money makes individuals happier at a time does not, by itself, require us to conclude that economic growth would increase average happiness.
What’s more, there are some reasons to worry that modernity is not good for humans. As I said in my earlier post:
Notably, Hidaka (2012) argues that depression is rising as a result of modernity, and points to the fact that “modern populations are increasingly overfed, malnourished, sedentary, sunlight-deficient, sleep-deprived, and socially-isolated”.
In other words, you can’t just assume that economic growth increases happiness—that’s exactly the point. If you’re going to already take it as given, then there’s no purpose in having the debate.
That is entirely fair. It’s reasonable to not accept the cross-sectional results as having any information value for your prior. So I should have have said we can start with a prior from the HLI meta-analysis results (which if I remember correctly are pretty statistically significant). Then when we get the information from the Easterlin and O’Connor paper, where the results are the same as our prior, but not statistically significant, to say that the new information does not shift our prior results at all. So even though the Easterlin and O’Connor paper does not give us much information one way or the other, it still seems reasonable to say there is no reason to think that the results are likely to be much lower than the HLI results?
I don’t think this makes sense, no, sorry. The HLI meta-analysis results are from cash transfers, which make a few individuals happier over time, not looking at the average of an entire society. It’s well-studied that people care about their relative income, not just their absolute income. So we should be particularly worried about extrapolating from what works for individuals to what works for societies—especially where we think the benefit to the individual could be from comparisons. Hence, I think it is not justified to start from the HLI numbers.
IIRC, in the HLI cash transfer meta-analysis, we found that cash transfers had no effect on those in nearby villages (‘across-village’ effect). In other words, there was, on average, no relative income effect. I was puzzled by it and I find it hard to believe—our CEA does, however, despite my disbelief, assume there are no negative spillovers from cash transfers. I was puzzled by this because there’s such consistent evidence of a relative income effect in rich countries. I also thought it was weird the effect from cash transfers was zero. To put this in context, imagine a bunch of people down the road from you get given $40,000 for each household. Would you expect that to have no effect on you? It wouldn’t make you envious? Or, it wouldn’t make you excited that this might happen to you? I’d expect the effect of income to be (almost) wholly relative in rich countries, but not that there was no relative income effect in the very poor. However, there wasn’t loads of across-village data in the HLI meta-analysis, so I didn’t update much. It would be good to have a bigger and better analysis of the relative income effect in very poor contexts.
I agree that we can and should try to be Bayesian but, if we do, we still don’t get a slam-dunk result that economic growth will increase average happiness (at least, in already rich countries).
The story that often gets told to explain why the Easterlin Paradox holds refers to hedonic adaptation, social comparison, and evolution. We are very good at getting used to lots of things but we do continue to notice our status relative to others. How much material prosperity do we really need, given humans are basically naked apes who evolved to live in the savannah? We might imagine getting richer would make a difference to us, but think about the last thing you were really excited to buy, then think about how you’ve stopped paying attention to it. Therefore, we can explain both why money would matter in the cross-section and why it wouldn’t matter in the time-series. So noticing that money makes individuals happier at a time does not, by itself, require us to conclude that economic growth would increase average happiness.
What’s more, there are some reasons to worry that modernity is not good for humans. As I said in my earlier post:
In other words, you can’t just assume that economic growth increases happiness—that’s exactly the point. If you’re going to already take it as given, then there’s no purpose in having the debate.
Michael,
That is entirely fair. It’s reasonable to not accept the cross-sectional results as having any information value for your prior. So I should have have said we can start with a prior from the HLI meta-analysis results (which if I remember correctly are pretty statistically significant). Then when we get the information from the Easterlin and O’Connor paper, where the results are the same as our prior, but not statistically significant, to say that the new information does not shift our prior results at all. So even though the Easterlin and O’Connor paper does not give us much information one way or the other, it still seems reasonable to say there is no reason to think that the results are likely to be much lower than the HLI results?
I don’t think this makes sense, no, sorry. The HLI meta-analysis results are from cash transfers, which make a few individuals happier over time, not looking at the average of an entire society. It’s well-studied that people care about their relative income, not just their absolute income. So we should be particularly worried about extrapolating from what works for individuals to what works for societies—especially where we think the benefit to the individual could be from comparisons. Hence, I think it is not justified to start from the HLI numbers.
IIRC, in the HLI cash transfer meta-analysis, we found that cash transfers had no effect on those in nearby villages (‘across-village’ effect). In other words, there was, on average, no relative income effect. I was puzzled by it and I find it hard to believe—our CEA does, however, despite my disbelief, assume there are no negative spillovers from cash transfers. I was puzzled by this because there’s such consistent evidence of a relative income effect in rich countries. I also thought it was weird the effect from cash transfers was zero. To put this in context, imagine a bunch of people down the road from you get given $40,000 for each household. Would you expect that to have no effect on you? It wouldn’t make you envious? Or, it wouldn’t make you excited that this might happen to you? I’d expect the effect of income to be (almost) wholly relative in rich countries, but not that there was no relative income effect in the very poor. However, there wasn’t loads of across-village data in the HLI meta-analysis, so I didn’t update much. It would be good to have a bigger and better analysis of the relative income effect in very poor contexts.