Building upon a previous attempt, the study simulates a closure of the South China Sea to maritime trade and estimates welfare changes for economies around the world. Heightened tensions in the region have increased the risk of outright conflict between major powers to the highest level in decades, so the author interacts trade distance data with country-country trade data in both a CES model and multi-industry model to offer refined estimates of gains from trade in the region. The results estimate het- erogeneous and severe welfare declines for many countries, though to a more modest degree than those of previous estimates. A multi-industry approach accounting for heterogeneity in price and trade elasticity is shown to magnify implied gains from trade than does a CES model. Analysis suggests both models offer distinct geopolit- ical incentive structures that may lend explanatory value for nations’ grand strategic moves.

This thesis investigates how the current structure of economic incentives – particularly the omission of non-market ecosystem services from financial and economic decision-making – shapes forest management outcomes across the United States. Drawing on economic theory and utilizing panel data from 2001 to 2023 covering all fifty U.S. states, the analysis examines how political alignment, market conditions, and regulatory intensity influence patterns of annual tree cover growth and loss. A fixed-effects regression framework is used to isolate the effects of commodity price fluctuations, partisan preferences, and institutional restrictions on forest outcomes.

The results reveal that neither lumber nor gasoline prices significantly predict forest loss in aggregate. However, from the data, we learn that the influence of both economic and political factors is strongly conditional on regulatory context. In states with weak forest regulation, Republican political alignment is associated with significantly higher forest loss, while in states with strong regulation, this effect disappears. Similarly, market responsiveness to timber prices is greater in weakly regulated jurisdictions, indicating that institutional design can also buffer ecological outcomes from short-term economic pressures.

The findings in this paper highlight the importance of developing regulatory institutions to promote environmental sustainability. When ecological benefits such as carbon storage and biodiversity remain unpriced, private decision-making often fails to align with long-term societal goals. Strengthening regulatory safeguards and explicitly integrating non-market values into economic planning are two critical steps toward ensuring that U.S. forests remain resilient, productive, and ecologically valuable in the long run.

This paper employs a quasi-experimental event study design that analyzes the equity market reactions to severe weather events in electricity-generating firms via average cumulative abnormal returns and dynamic average treatment effects on the treated (ATT). It uses a novel treatment identification strategy by assembling a treatment zone of severe weather events using individually reported storm locations. Treatment is assigned to power plants within 100 miles of the path of the power-outage inducing storm, then traced to firms for the treatment group via ownership data. The findings are as follows: [1] The average cumulative abnormal returns for both the treatment group firms and the control group firms were significant, at -1.57% and -1.09%, respectively, indicating a negative equity market reaction to severe weather events. [2] The treated renewable firms (-2.38%) earned significantly lower cumulative abnormal returns as compared to the control group of renewable firms. [3] Asymmetrically, the control group fossil fuel firms earned significant lower cumulative abnormal returns (-2.43%) as compared to the fossil fuel treatment group. [4] The ATT for event-day 20 was significant across all observations, renewable firms, and fossil fuel firms, indicating significant positive abnormal return ATTs for the treatment group of 0.24%, 0.11%, and 0.37%, respectively. Findings [1] and [2] support the hypotheses of the study that treated groups would underperform control groups and that renewable energy firms would outperform fossil fuel firms. Findings [3] and [4] oppose the hypotheses of the study but could be explained by extrapolatory beliefs and stimulatory effects of emergency stimulus efforts to restore the grid.