The Nonlinear Library EA - Charity Entrepreneurship Is Overestimating the Value of Saving Lives by 10% by Mikolaj Kniejski
Jun 12, 2024
14:40
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Charity Entrepreneurship Is Overestimating the Value of Saving Lives by 10%, published by Mikolaj Kniejski on June 12, 2024 on The Effective Altruism Forum.
I got this idea after I read a few of CE (Charity Entrepreneurship) cost-effectiveness estimates when I was preparing my application for the CE research training program. Although this is not a major pressing improvement, this definitely is an iterative improvement over the current methodology and I haven't seen anyone else raising this point yet.
CE uses DALYs averted as a measure of impact:
DALYs (Disability-Adjusted Life Years): A measure of disease burden, expressed in years lost to disability or early death. Dying one year before your expected life span causes 1 DALY. DALYs are averted when we save someone from dying early, or when we reduce the number of sick people or the duration of their sickness. DALYs for a disease are the sum of YLLs and YLDs:
.
Years of Life Lost (YLLs): Calculated as the difference between the age at death and the life expectancy. Death is the worst possible outcome, and it gets one DALY per person per year.
Years Lived with Disability (YLDs): Calculated by multiplying the severity of an illness or disability by its duration.
DALYs averted: I like to think of DALYs averted as the difference between DALYs without intervention and DALYs with intervention. This captures the notion of counterfactuality, meaning our estimate should reflect the difference between a world where the intervention happened and one where it didn't.
For example, if an intervention saves a person who would have otherwise died at 30 and the life expectancy is 70, 40 YLLs are averted (without considering temporal discounting and age-weighing). If the intervention reduces a year of severe disability (with a disability weight of 0.5), 0.5 YLDs are averted.
When Charity Entrepreneurship estimates the number of DALYs that an intervention would avert, it uses a pre-made table by GiveWell. This table includes age weighting (which gives years in around 20-30 more value) and applies temporal discounting at 4% per year. CE uses the average values (last column).
Table 1: GiveWell estimates of value of life saved at various ages of death. The table is available here and made using a formula that you can find here.
Age of death
Life expectancy (years)
YLL incorporating discount and age-weighting
Females
Males
Females
Males
Average
0
82.5
80
33.13
33.01
33.07
5
77.95
75.38
36.59
36.46
36.53
15
68.02
65.41
36.99
36.80
36.90
30
53.27
50.51
29.92
29.62
29.77
45
38.72
35.77
20.66
20.17
20.41
60
24.83
21.81
12.22
11.48
11.85
70
16.2
13.58
7.48
6.69
7.09
80
8.9
7.45
3.76
3.27
3.52
90
4.25
3.54
1.53
1.30
1.42
100
2
1.46
0.57
0.42
0.50
CE takes the exact values from the table. When an intervention saves someone who is 30 years old they literally take the value 29.77 DALYs which only includes temporal discounting and age-weighing.
This implicitly assumes that the subject would live a perfectly healthy life to the life expectancy used in the estimation. The full value of e.g. 29.77 DALYs averted was calculated assuming the subject lives healthy to the life expectancy. He is not going to - The subject is almost definitely going to get sick and will fail to realize the full value.
Why This Matters
We want our cost-effectiveness analyses (CEAs) to measure counterfactual impact. The difference between the world where the intervention happened and the one where it didn't should be the key result. If we take the full value of the life saved, we will overestimate the value by the DALYs the subject will incur while being sick. This is crucial when choosing between interventions that improve lives compared to interventions that save lives.
Is CE really making this mistake?
I'm pretty sure they do. Here, I try to show the exact place where it hap...
I got this idea after I read a few of CE (Charity Entrepreneurship) cost-effectiveness estimates when I was preparing my application for the CE research training program. Although this is not a major pressing improvement, this definitely is an iterative improvement over the current methodology and I haven't seen anyone else raising this point yet.
CE uses DALYs averted as a measure of impact:
DALYs (Disability-Adjusted Life Years): A measure of disease burden, expressed in years lost to disability or early death. Dying one year before your expected life span causes 1 DALY. DALYs are averted when we save someone from dying early, or when we reduce the number of sick people or the duration of their sickness. DALYs for a disease are the sum of YLLs and YLDs:
.
Years of Life Lost (YLLs): Calculated as the difference between the age at death and the life expectancy. Death is the worst possible outcome, and it gets one DALY per person per year.
Years Lived with Disability (YLDs): Calculated by multiplying the severity of an illness or disability by its duration.
DALYs averted: I like to think of DALYs averted as the difference between DALYs without intervention and DALYs with intervention. This captures the notion of counterfactuality, meaning our estimate should reflect the difference between a world where the intervention happened and one where it didn't.
For example, if an intervention saves a person who would have otherwise died at 30 and the life expectancy is 70, 40 YLLs are averted (without considering temporal discounting and age-weighing). If the intervention reduces a year of severe disability (with a disability weight of 0.5), 0.5 YLDs are averted.
When Charity Entrepreneurship estimates the number of DALYs that an intervention would avert, it uses a pre-made table by GiveWell. This table includes age weighting (which gives years in around 20-30 more value) and applies temporal discounting at 4% per year. CE uses the average values (last column).
Table 1: GiveWell estimates of value of life saved at various ages of death. The table is available here and made using a formula that you can find here.
Age of death
Life expectancy (years)
YLL incorporating discount and age-weighting
Females
Males
Females
Males
Average
0
82.5
80
33.13
33.01
33.07
5
77.95
75.38
36.59
36.46
36.53
15
68.02
65.41
36.99
36.80
36.90
30
53.27
50.51
29.92
29.62
29.77
45
38.72
35.77
20.66
20.17
20.41
60
24.83
21.81
12.22
11.48
11.85
70
16.2
13.58
7.48
6.69
7.09
80
8.9
7.45
3.76
3.27
3.52
90
4.25
3.54
1.53
1.30
1.42
100
2
1.46
0.57
0.42
0.50
CE takes the exact values from the table. When an intervention saves someone who is 30 years old they literally take the value 29.77 DALYs which only includes temporal discounting and age-weighing.
This implicitly assumes that the subject would live a perfectly healthy life to the life expectancy used in the estimation. The full value of e.g. 29.77 DALYs averted was calculated assuming the subject lives healthy to the life expectancy. He is not going to - The subject is almost definitely going to get sick and will fail to realize the full value.
Why This Matters
We want our cost-effectiveness analyses (CEAs) to measure counterfactual impact. The difference between the world where the intervention happened and the one where it didn't should be the key result. If we take the full value of the life saved, we will overestimate the value by the DALYs the subject will incur while being sick. This is crucial when choosing between interventions that improve lives compared to interventions that save lives.
Is CE really making this mistake?
I'm pretty sure they do. Here, I try to show the exact place where it hap...