Essays on the Econometric Analysis of Energy Markets and Climate Change
This PhD thesis uses econometric techniques to provide new insights into energy markets and climate change. The developed econometric models are applied in five research articles that focus on energy markets, financial economics, climate vulnerability and adaptation strategies, and the impacts of climate change on coastal regions. The first part of the thesis is dedicated to the econometric analysis of the oil market. Crude oil and its derivatives are the world’s most commonly traded commodities. Although the energy landscape is in a state of transition, crude oil has been and will likely remain important in the context of global energy consumption. By focusing on econometric and time series regression models, Chapter 2 examines whether it is possible to generate reliable long-term monthly forecasts of the real price of crude oil and how these can be improved using forecast combination. Chapter 3 investigates the North American oil industry using firm-level data. The relationship between oil prices, oil market volatility, and the cost of debt for oil firms is analyzed empirically using a distributed lag model and a panel data “within-between” approach. The second part of the thesis focuses on climate change vulnerability and adaptation strategies in the context of smallholder farmers in the Indian watersheds, as well as long-term trends in the Australian wave climate. The global climate has changed relative to the pre-industrial period. Moreover, this change already affects ecosystems and livelihoods worldwide. This has severe implications for food production and security, especially for the rain-fed agricultural systems that dominate much of tropical agriculture and are extremely vulnerable to projected climate change. Consequently, Chapters 4 and 5 focus on two research questions related to watershed development programs and factors that affect the adaptation strategies of smallholder farmers in India. Chapter 4 provides a theoretical framework for developing a climate vulnerability index. Chapter 5 is aimed at investigating how smallholder farmers perceive climate change and how they adapt their behavior in response to perceived changes in the climate. Using a binary logistic model, this thesis quantifies the impact of various explanatory variables that affect households’ choices of adaptation strategies. In addition, anthropogenic climate change has caused global mean sea levels to rise substantially over the last century. As a result, local and regional sea level variations and the occurrence of sea level extremes increase climate change related risks for coastal regions. This amplifies the need to understand how waves and extremes change over the long term to assess the impacts of climate change. Therefore, Chapter 6 empirically investigates long-term trends in and extreme values of wave power and height on a local scale along Australia’s east and southeast coasts. A comparison of the distribution of wave power employing the Jensen-Shannon divergence and Laplacian embedding provides new insights into Australia’s wave climate on a local and regional scale in the context of climate change.