Heterogeneous Agents and Information Nudges in Non-Point Source Water Pollution Management

Non-point source (NPS) water pollution from agricultural runoff is a leading cause of impairment for many water bodies in the United States; however, sources of NPS pollution are difficult to identify because of hidden actions and asymmetric information. Theoretical and experimental research has shown that ambient pollution policies can induce groups to reduce pollution to socially efficient levels, but many of these studies have imposed restrictive assumptions about farmer homogeneity and management choices. In reality, agricultural firms differ in both size and location, and farmers make numerous management decisions that can affect runoff and nutrient loss, including decisions about production intensity and pollution abatement technologies. Researchers have shown that introducing either size or location heterogeneity affects the efficiency of ambient pollution policies, but no research has analyzed policy performance while considering several sources of heterogeneity and multiple management decisions. Furthermore, despite multiple examples in using non-pecuniary incentives to promote environmental conservation, little research has examined how to use information nudges, like social comparisons or information about peer actions, to induce better NPS pollution abatement decisions. In this study, we designed an economic experiment to test the effects of multiple layers of heterogeneity, information nudges, and an extended decision space on the performance of the classic ambient tax/subsidy policy. Experiment participants (n=192) were recruited from a large public university in the U.S. In the experiment, each individual was assigned a firm and asked to make individual decisions that affected the profitability of his/her firm and ambient water pollution of their group. In each round of the experiment, participants selected their production intensity and chose one of two 2 production technologies—a conventional technology or a more expensive technology that generated less pollution. Eight within-subject treatments were tested, including two policy variations (no policy and a tax/subsidy policy) and four size/location variations (homogeneous, location heterogeneity, size heterogeneity, and both location and size heterogeneity). Three between-subject information treatments were also tested, including a no information control. In information treatment 1, we tested how individual decisions were affected by information nudges about decisions that similar individuals had made in past sessions. In information treatment 2, participants were provided with information about the average production and technology adoption rate in their group during the last round. A unique dominant strategy Nash Equilibrium was calculated for both the adoption decision and production decision based on location and size. Our results demonstrate that, without information nudges, more firm heterogeneity reduces the effectiveness of ambient tax/subsidy policies and target pollution levels are achieved less frequently. However, the tax/subsidy policy was effective under different heterogeneity scenarios when information is provided about peer and group decisions in past rounds. Furthermore, information treatment 1 and information treatment 2 generate higher policy efficiency than no information treatment. Lastly, participants are able to find and retain their dominant strategy better in the information 1 treatment, suggesting that providing individually targeted information is more effective than providing information about aggregate group-level decisions. Our findings suggest that traditional ambient pollution policies may be less effective when agents are heterogeneous and make multiple decisions that affect pollution, but information nudges can improve policy performance.Much of the research is in cooperation with industry partners, the USDA, and other State and Federal agencies