Structural Uncertainty and Pollution Control: Optimal Stringency with Unknown Pollution Sources

We relax the common assumption that regulators know the structural relationship between emissions and ambient air quality with certainty. We find that uncertainty over this relationship can manifest as a unique form of multiplicative uncertainty in the marginal damages from emissions. We show how the optimal stringency of environmental regulation depends on this structural uncertainty. We also show how new information, like the discovery of previously unknown emission sources, can counterintuitively lead to increases in both optimal emissions and ambient pollution levels.