The Regulation of Nonpoint Emissions in the Laboratory: A Stress Test of the Ambient Tax Mechanism

We investigate the ability of the damage based tax mechanism to induce socially optimal outcomes in a controlled laboratory environment which incorporates important aspects of nonpoint pollution problems. Our experimental setting combines a strictly convex damage function with uncertainty in measuring the ambient level of pollution, indefinitely repeated interactions among heterogeneous polluters, limited information on the regulator's side about the polluters' profit functions, and, in half of the experimental conditions, limited information on the polluters' side about the strategic environment. We additionally investigate whether the relative position of the social optimum in the polluters’ emission space has an impact on the efficiency of the fiscal instrument. In almost all implemented conditions, the observed total pollution level is not significantly different from the socially optimal level but compliance at the individual level is rarely observed. Experimental conditions in which polluters have to dramatically reduce their emissions in order to comply with the fiscal instrument lead to higher efficiency levels than those where compliance implies less dramatic reductions. Our most striking result is that less information on the polluters' side is beneficial from a social point of view as the performance of the damage based tax mechanism is higher the less information polluters have about the strategic environment.