Q from
@deankarlan
: do people make too much about what nudges can do?
Kahneman: everybody is excited about being right on the direction of the hypothesis, but ignore the magnitude of the effect, which is often quite small, or comes with very high variance
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Replies
Daniel Kahneman: when making predictions beware, because confidence and accuracy are uncorrelated
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Currently thinking about noise in judgement, often quite large even among professionals "Wherever you have human judgement you will have noise"
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Your final judgement shouldn't be given to a human it should be the algorithm, except in very rare circumstances. When people overrule the algorithm, they're usually wrong.
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@dsaava
@deankarlan
Hi (& cc
@RGoyal02
) unfortunately there's no recording, but many of the themes discussed were similar to this interview with
@R_Thaler
and his podcast interview with
@tylercowen
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@poverty_action
@deankarlan
Yes. A perpetual disappointment in public policy research is the small size of many significant +ve effects. We need to keep reminding policy makers of this awkward 'it works!' factoid.
《Muted Eureka!》Archimedes lost the top few inches of his bathwater, not the whole lot.
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@poverty_action
@deankarlan
In line with Kahneman's thoughts, I propose a new approach to assess the economic importance of regressors in a recent CSAE working paper
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