If you are not aggregating all-considered views of experts, but rather aggregating models with mutually exclusive assumptions, use the mean of probabilities.
Models can have more or less mutually exclusive assumptions? I guess the less they do, the more it makes sense to rely on the median or geometric mean of odds instead of the mean. In practice, how do you decide? I am asking following a discussion about how to aggregate welfare ranges.
In addition, there is not a strong distinction between all-considered views and the outputs of quantitative models, as the judgements of people are models themselves. Moreover, one should presumably prefer the all-considered views of the modellers over the models, as the former account for more information?
(speculating) The key property you are looking for IMO is to which degree people are looking at different information when making forecasts. Models that parcel reality into neat little mutually exclusive packages are more amenable , while forecasts that obscurely aggregate information from independent sources will work better with geomeans.
In any case, this has little bearing on aggregating welfare IMO. You may want to check out geometric rationality as an account that lends itself more to using geometric aggregation of welfare.
Hi Jaime,
Models can have more or less mutually exclusive assumptions? I guess the less they do, the more it makes sense to rely on the median or geometric mean of odds instead of the mean. In practice, how do you decide? I am asking following a discussion about how to aggregate welfare ranges.
In addition, there is not a strong distinction between all-considered views and the outputs of quantitative models, as the judgements of people are models themselves. Moreover, one should presumably prefer the all-considered views of the modellers over the models, as the former account for more information?
(speculating) The key property you are looking for IMO is to which degree people are looking at different information when making forecasts. Models that parcel reality into neat little mutually exclusive packages are more amenable , while forecasts that obscurely aggregate information from independent sources will work better with geomeans.
In any case, this has little bearing on aggregating welfare IMO. You may want to check out geometric rationality as an account that lends itself more to using geometric aggregation of welfare.