My Research

The European Union’s Emissions Trading System (EU-ETS) is an important tool in the collective fight against the adverse effects of global climate change. As the most well-established cap-and-trade program in the world, it has set the global standard for carbon markets. However, prior studies have provided mixed results regarding the efficiency of these markets (where efficiency is defined in terms of the efficient market hypothesis). The existence of inefficiencies can provide arbitrage opportunities for market participants and undermine the market's credibility.

This essay analyzes the price series of four annual carbon futures contracts to determine if recent (2017-2021) carbon markets were weak-form efficient. I use a variety of methods to gauge relative efficiency, including runs tests, unit root/stationarity tests, an autocorrelation analysis, variance ratio tests, and an analysis that compares the performance of simple technical trading rules relative to baseline strategies. My work is novel in its temporal scope; to the best of my knowledge, it is the first study of informational efficiency in the EU-ETS that includes data from the COVID-19 pandemic. Overall, I find mixed evidence of weak-form efficiency in these futures markets.

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Links between human actions and global climate change are well-documented, as are the links between climate change and the frequency and intensity of extreme weather events. The prior literature in economics and finance has examined the effects of natural disasters on global stock markets, mainly at the market-level or sector-level. 

This essay uses an event study framework to study the effects of tropical cyclones, floods, and severe storms on U.S.-based clean energy and fossil fuel firms. I find that the average abnormal returns (AARs) and cumulative abnormal returns (CARs) for both types of firms are negatively affected by the disasters. An additional regression analysis reveals that changes in the firms' CARs are driven by a number of factors, including the firms' return on asset (ROA) values, environmental ratings, classification (i.e., clean energy vs. fossil fuels), business interface (i.e., consumer-facing vs. non-consumer-facing), and size. Back-of-the-envelope calculations suggest that these disasters were economically significant, a point rarely explored in prior event studies.

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In this essay, I study the same firms and natural disasters as Essay 2, but I use a generalized autoregressive conditional heteroskedasticity (GARCH) framework to analyze the natural disasters' effects on mean returns and conditional variances of returns. Grouping the clean energy and fossil fuel firms into custom stock indices, I find no evidence that the disasters affected the clean energy firms' mean returns. I do, however, find evidence of negative impacts to the fossil fuel firms' mean returns. Comparing these findings with those of Essay 2 provides evidence in support of the theory that price effects of natural disasters can be "diversified away" through stock aggregation, a phenomenon that has been noted in prior studies.

Regarding the conditional variance analysis, I find evidence that returns for both classes of firms are impacted by changes in risk introduced by the disasters. Taken together, the results of this Essay and Essay 2 suggest that the natural disasters studied did have meaningful impacts on the market's return and volatility dynamics.

This essay presents a critical analysis of Clean Development Mechanism (CDM) projects in China and India and assess the feasibility of a national-level emissions trading program in India. I find that foreign investment in CDM projects was disproportionate between the two countries, with China benefitting from substantially more international investment than India. Using information currently known about India's proposed trading system, I compare the proposals with a 10-step guideline developed by the World Bank to highlight both the successes of the policy process so far and areas of the process in need of future attention.