| Abstract: |
This paper investigates the design of incentives in a dynamic adverse
selection framework when agents’ production technologies display learning
effects and agents’ rate of learning is private knowledge. In a simple
two-period model with full commitment available to the principal, we show that
whether learning effects are over- or under-exploited crucially depends on
whether learning effects increase or decrease the principal’s uncertainty
about agents’ costs of production. Hence, what drives the over- or
underexploitation of learning effects is whether more efficient agents also
learn faster (so costs diverge through learning effects) or whether it is the
less efficient agents who learn faster (so costs converge). Furthermore, we
show that if divergence in costs through learning effects is strong enough,
learning effects will not be exploited at all, in a sense to be made precise. |