2025 Theses Doctoral

Essays in Environmental Economics

Papp, Anna

This dissertation examines environmental questions related to difficult-to-measure populations and pollutants.

The three chapters combine novel sources and applications of data with econometric and machine learning tools to investigate interactions between the environment and society for understudied segments of the labor force and complex pollutants. Leveraging large consumer transaction data and both public and original surveys, the first chapter shows that gig economy platforms enable consumers to adapt to climate change while shifting climate-related damages to the rapidly expanding yet hard-to-measure population of gig economy workers.

The following two chapters develop alternative ways of measuring plastics in the environment that allow robust causal inference related to the origins and regulation of plastic pollution. Using citizen science data from shoreline cleanups, the second chapter demonstrates that plastic bag bans and taxes in the US reduce plastic bag litter in the environment.

Finally, the third chapter proposes a new method that combines crowdsourced data collection, machine learning on satellite data, and sampling to create an unbiased measure of the area of open-air plastic waste sites. Together, these chapters study the externalities of consumption related to previously difficult-to-measure populations and pollutants.