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How to Make Loss Aversion Disappear and Reverse

One of the most robust empirical findings in the behavioral sciences is loss
aversion—the finding that losses loom larger than gains.  We offer a new
psychological explanation of the origins of loss aversion in which loss
aversion emerges from differences in the distribution of gains and losses
people experience.  In 4 experiments, we tested this proposition by
manipulating the range of gains and losses that individuals saw during the
process of eliciting their loss aversion.  We were able to find loss
aversion, loss neutrality, and even the reverse of loss aversion.

The average laboratory samples a population of 7,300 Amazon Mechanical Turk

Using capture-recapture analysis we estimate the effective size of the
active Amazon Mechanical Turk (MTurk) population that a typical laboratory
can access to be about 7,300 workers. We also estimate that the time taken
for half of the workers to leave the MTurk pool and be replaced is about 7
months. Each laboratory has its own population pool which overlaps, often
extensively, with the hundreds of other laboratories using MTurk. Our
estimate is based on a sample of 114,460 completed sessions from 33,408
unique participants and 689 sessions across seven laboratories in the US,
Europe, and Australia from January 2012 to March 2015.