Hello, thanks for this! Exciting to see more concrete estimates out of QURI!
However, how much people prefer the first double of consumption over the second is an empirical question. And empirically, people get more utility from the first doubling of consumption than the second. Doubling twice creates 1.66 units rather than 2. An isoelastic utility function can represent this difference in preferences.
Isoelastic utility functions allow you to specify how much one would prefer the first double to the second with the η parameter. When η=1, the recipient values the first double the same as the second and is what the current CEA assumes. When η>1, recipients prefer the first doubling in consumption as worth more than the second. Empirically, η≈1.5. GiveWell recognises this and uses η=1.59 in their calculation of the discount rate:
I think your claims here (and the general conclusion) is a bit stronger than warranted. The analysis you link seems reasonably strong on a quick skim, but it is used for the UK:
This paper provides novel empirical evidence on the value of the elasticity of marginal utility, , for the United Kingdom. is a crucial component of the social discount rate (SDR), which determines the inter-temporal trade-offs that are acceptable to society. Using contemporaneous and historical data, new estimates are obtained using four revealed-preference techniques: the equal-sacrifice income tax approach, the Euler-equation approach, the Frisch additive-preferences approach and risk aversion in insurance markets. A meta-analysis indicates parameter homogeneity across approaches, and a central estimate of 1.5 for . The confidence interval excludes unity, the value used in official guidance by the UK government.
The UK (GDP per capita: 40k) data seems very out-of-sample for Kenya (GDP per capita: 1.8k), Uganda (GDP per capita 0.8k), Rwanda, Liberia, Malawi, DRC, and Morocco. As is often the case with social science research, we should be skeptical of out-of-country and out-of-distribution generalizability.
So I’m not sure whether I should make a huge update in the direction of this data, and I think this uncertainty should be flagged more in your post.
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Taking a step back, I do think it’s plausible that the first doubling of money creates more utility than the second doubling, and this generalizes reasonably well across multiple doublings. Firstly because there’s no strong theoretical reason to prefer unity (prefer a doubling the same degree as disprefer a halving). And anecdotally, this matches my intutions. Certainly I personally feel like the difference between my material well-being now vs my childhood (consumption ~1 OOM more?) is not as different as the consumption between my childhood and that of the median person in Kenya (consumption another ~1 OOM more or so). But of course my own intuitions are pretty out-of-distribution here too!
Hello, thanks for this! Exciting to see more concrete estimates out of QURI!
I think your claims here (and the general conclusion) is a bit stronger than warranted. The analysis you link seems reasonably strong on a quick skim, but it is used for the UK:
The UK (GDP per capita: 40k) data seems very out-of-sample for Kenya (GDP per capita: 1.8k), Uganda (GDP per capita 0.8k), Rwanda, Liberia, Malawi, DRC, and Morocco. As is often the case with social science research, we should be skeptical of out-of-country and out-of-distribution generalizability.
So I’m not sure whether I should make a huge update in the direction of this data, and I think this uncertainty should be flagged more in your post.
___
Taking a step back, I do think it’s plausible that the first doubling of money creates more utility than the second doubling, and this generalizes reasonably well across multiple doublings. Firstly because there’s no strong theoretical reason to prefer unity (prefer a doubling the same degree as disprefer a halving). And anecdotally, this matches my intutions. Certainly I personally feel like the difference between my material well-being now vs my childhood (consumption ~1 OOM more?) is not as different as the consumption between my childhood and that of the median person in Kenya (consumption another ~1 OOM more or so). But of course my own intuitions are pretty out-of-distribution here too!
That’s true!η could easily be something other than 1.5. In London, it was found to be 1.5, in 20 OECD countries, it was found to be about 1.4. James Snowden assumes 1.59.
I could but don’t represent eta with actual uncertainty! This could be an improvement.