Trying to study environmental politics is like trying to juggle flaming bowling pins while riding a unicycle–it requires the acrobat to be good enough at both juggling (political science) and unicycle riding (environmental science) that they do not immediately crash and burn. My attempt to do so is below. In my dissertation I take three different approaches to answering questions which can contribute to our understanding of the interface between the political forces and the environment. In the first I explore electoral deforestation cycles, where deforestation rates are higher surrounding elections in young democracies.These cycles are most pronounced when the elections are highly competitive, occur in young or weakly institutionalized democracies, and are held in majoritarian systems where politicians can effectively target voters with geographic policies. Here, a set of rules designed to expand political power have the unintended consequence of increased environmental destruction. In the second paper we develop a method for discovering and testing influential concepts and phrases in text. We adapt a neural network with recurrent and convolutional layers designed to make the network’s decisions more interpretable to a different task—to identify phrases and concepts which are highly persuasive to a reader. We then apply this to climate change communication to try to uncover some of the most persuasive concepts both for and against climate change mitigation. In it I evaluate the effects of receiving a formal land title on the behavior of plot owners—usually smallholder farmers—using satellite imagery and machine learning. This case speaks to a substantive question that drives millions of dollars in aid annually—how can we reduce barriers to increasing productivity for the world’s poorest and least food secure regions. It also demonstrates new methods which use existing data to more effectively evaluate future (or past!) interventions. Specifically, I evaluate whether having the boundaries of one’s plot officially demarcated and recorded and the ability to obtain a legal title increase the probability that part of the plot will be converted from annual to perennial crops, whether there will be cropland expansion in the plot, and whether the built-up area in these plots increases. I also test whether land titling results in land-sparing in surrounding areas by increasing productivity on the intensive margin. To do this I develop a set of methods for using satellite imagery to measure changes in land cover based on sub-annual variations in surface reflectance of different wavelengths of light. This allows me to observe outcomes at an annual scale and detect the proportion of plots under different types of landcover. Evidence from a pilot area of analysis shows increased conversion from natural forest to cropland as a result of land formalization.

Improved understanding of the physical impacts to the climate caused by anthropogenic emissions has led to an increased focus on the role of policy on limiting mitigating the cause and the impacts of climate change. The emissions trajectory that society takes will play a major role in determining a wide variety of climate impacts from health to economic growth. This dissertation explores how idealized modeling can be used to inform the potential outcomes of the policies meant to mitigate the negative impacts of climate change and optimize the benefits of emission reduction. Chapter 1 explores the potential trade-offs between increased temperatures and reduced health impacts of considering aerosol emissions in international climate policy. Using an idealized model, it is possible to demonstrate that both health and temperature benefits can result from considering either health or temperature separately. Chapter 2 interrogates whether climate policy in the United States can be used to reduce existing racial inequities in air pollution exposure. The modeling shows that prioritizing by exclusively income or cost in national policy would result in worsening inequities, but that prioritizing by race explicitly has the opposite effect. Using a set of more realistic air quality simulations with randomized emission reduction, it appears that the transportation has a unique potential for air quality equity improvements. Lastly, Chapter 3 focuses on statistical models that use natural variation in annual weather to predict how climate will influence human outcomes. Using an idealized outcome variable and real data of global gross domestic product, it is possible to demonstrate that imperfect measurement networks and the mean shift in climate both work to underestimate future climate impacts.

Objective

Design

Setting

Subjects

Results

Conclusions