Crowdsourcing is a form of "peer production" in which work traditionally
performed by an employee is outsourced to an "undefined, generally large group
of people in the form of an open call." We present a model of workers supplying
labor to paid crowdsourcing projects. We also introduce a novel method for
estimating a worker's reservation wage--the smallest wage a worker is willing
to accept for a task and the key parameter in our labor supply model. It shows
that the reservation wages of a sample of workers from Amazon's Mechanical Turk
(AMT) are approximately log normally distributed, with a median wage of
$1.38/hour. At the median wage, the point elasticity of extensive labor supply
is 0.43. We discuss how to use our calibrated model to make predictions in
applied work. Two experimental tests of the model show that many workers
respond rationally to offered incentives. However, a non-trivial fraction of
subjects appear to set earnings targets. These "target earners" consider not
just the offered wage--which is what the rational model predicts--but also
their proximity to earnings goals. Interestingly, a number of workers clearly
prefer earning total amounts evenly divisible by 5, presumably because these
amounts make good targets.