One of the most pressing questions in economics is “why are some countries richer than others?” One methodology designed to help answer the question is known as “Development Accounting,” a framework that organizes the determinants of income into two categories: differences in inputs and differences in efficiency. The objective of our work is to study to what extent differences in the levels of pollution can help explain income differences across countries. To do this, we adjusted a factor-only model to allow us to enter PM2.5, a measure of pollution that tracks the concentration of fine particulate matter in the air and looked to see if the model’s predictive power improved. We ultimately find that we can improve the model’s success in predicting GDP by .5 - 6%. Thus, pollution is unlikely to be a major force in understanding cross-country income differences, but it can be used with other economic factors to potentially magnify its impact with other additions in the future.

This research explores the use of transformative urban scenarios and timelines as a planning tool for addressing future sustainability challenges in urban environments. The analysis comes from a set of scenarios that were explored through workshops conducted in 2019 in which Phoenix stakeholders developed timelines toward their visions of Phoenix 60 years into the future. To evaluate the pathways created in these timelines, we employed process tracing methodology to understand which causal mechanisms lead to certain phenomena. Or in other words, it helps us understand how changes happen. We converted the timelines into process tracing diagrams that categorized the relationship between actions, actors, and observable manifestations (OM’s) of change over time. To understand the relationship between these components, we then used a combination of inductive and deductive coding to categorize types of activities, actors, OM’s and sustainability topics and organized them into themes. This helped us to understand how city decision-makers and community leaders think sustainability and resilience transformation can and should occur. This thesis takes a closer look at one particular scenario, Some Like it Hot, which explores resilience to extreme heat. Through coding and analysis, we found trends, correlations, and missing pieces in the participants’ timeline. There are numerous overarching causal mechanisms throughout the scenario timeline. These trends offer insight into which activities and stakeholders are seen as significant drivers of sustainable transformation according to the workshop participants. The file attached is a pdf version of an ArcGIS Story Map completed for this honors thesis. To view the full, interactive thesis deliverable, visit https://storymaps.arcgis.com/stories/14d1e52a9448498e87f20e7566651a13