Open Collections

Peters, Allen Leo

University of British Columbia

This dissertation consists of three essays concerning the interaction of firms with the environment, with a focus on the maritime shipping and agricultural sectors. Each essay quantifies aspects of firm behavior that are relevant to environmental policy. In the first essay, I quantify the impacts of potential emissions regulations on the time path of carbon dioxide emissions from the maritime shipping industry. In particular, I explore the equilibrium interactions between travel speed, price, and capital turnover. To quantitatively assess these mechanisms and their time horizons, I construct a dynamic model of the dry bulk shipping industry with endogenous entry, exit, and travel speed, as well as fleet heterogeneity across age and size. Using a rich dataset on the global fleet and its operation, I structurally estimate the model and use it to simulate the dynamic effects of potential emissions policies. I find that a fuel tax has a persistent impact, while the effect of a speed limit diminishes considerably over time due to endogenous fleet growth. Counterintuitively, rather than hastening the exit of older ships, both policies initially suppress exits. In the second essay, we develop a methodology for obtaining accurate and timely estimates of carbon dioxide emissions from maritime shipping. We leverage a combination of ship tracking data, technical characteristics, and fuel consumption reports. Our approach incorporates both engineering-based calculations and machine learning to significantly improve upon industry-standard emissions calculation-based estimates. In the third essay, I develop a methodology for estimating context-specific time preferences of firms, which are particularly relevant for environmental policy. I structurally estimate the discount rate of farm operators in Canada using a dynamic discrete choice model of crop rotation decisions. My estimation strategy leverages the finite temporal dependence of expected yields on crop history and builds on a recent identification result for dynamic discrete choice models. My estimates suggest a strong present bias, in contrast to common modeling assumptions. Together, these essays apply cutting-edge analytical techniques to provide insights into the effects of regulations on emissions, through their impacts on firm behavior.

Text

2024-07-08

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/88599

Economics

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/4.0/