Invasive species impose substantial economic and ecological costs globally, yet little
is known about how to design efficient contracts for private removal efforts under conditions
of moral hazard. We develop a spatially-explicit bioeconomic model that integrates
optimal control theory with contract design to examine two-part compensation schemes
that pay contractors for both time spent searching and species captured. Our theoretical
framework demonstrates that when effort has both observable (time) and unobservable
(search intensity) dimensions, pure piece-rate contracts may fail to incentivize adequate
effort in low-productivity areas or when "cobra effect" constraints limit bounty payments.
We test these predictions using comprehensive data from Florida’s Python Elimination
Program, which employs novel two-part contracts to remove invasive Burmese pythons
from the Everglades ecosystem. Exploiting within-parcel variation in hourly compensation
rates over time, we find that a 10% increase in hourly payments generates approximately
20% more search effort, with effects operating primarily through the intensive
margin (effort per hunter) rather than hunter participation. The responsiveness varies
systematically with ecological productivity, consistent with our theoretical prediction that
time-based payments become more important when piece-rate incentives are weak. Our
results demonstrate that spatially-differentiated contract design can significantly improve
cost-effectiveness compared to uniform compensation schemes, with important implications
for invasive species management, conservation policy, and other environmental contexts
where effort quality is difficult to observe.
