The impact of information on behavior under an ambient-based policy for regulating nonpoint source pollution

Stemming from Segerson [1988], literature on nonpoint source pollution shows that ambient-based regulatory policies can induce polluters in a common watershed to comply with an exogenously determined pollution standard. This study uses laboratory economic experiments in a spatially heterogeneous setting to test the effectiveness of an ambient tax/subsidy policy in a setting with realistic in-stream nutrient transport dynamics when varying levels of sensor information on ambient pollution are available to the agents and the regulator. We find that increasing the frequency of ambient monitoring improves the spatial allocation of emissions reductions. In particular, with more frequent monitoring, the ambient-based policy induces firms further from the monitoring point to reduce emissions significantly more than downstream firms. Overall, the results suggest that enhanced temporal resolution of monitoring leads to efficiency gains.