“Risk and punishment revisited — Errors in variables and in the lab”
We provide an example for an errors in variables problem which might
be often neglected but which is quite common in lab experimental
practice: In one task, attitude towards risk is measured, in another
task participants behave in a way that can possibly be explained by
their risk attitude. How should we deal with inconsistent behaviour
in the risk task? Ignoring these observations entails two biases:
An errors in variables bias and a selection bias.
We argue that inconsistent observations should be exploited to
address the errors in variables problem, which can easily be done
within a Bayesian framework.
Keywords: Risk, lab experiment, public good, errors in variables, Bayesian inference.
JEL: C91, D43, L41