Doctor of Philosophy
Statistics and Actuarial Sciences
In 2015, all United Nations member states adopted the Agenda 2030, which consists of 17 Sustainable Development Goals to create a better world in terms of social, economic, and environmental development by 2030. Numerous countries and governments have initiated measures to achieve these goals, including curbing traditional energy consumption, advancing renewable energy development, cutting carbon emissions, and addressing climate risks. In this thesis, statistical modelling techniques are developed to examine economic and financial challenges encountered in the pursuit of sustainable development.
The first study in this thesis explored the dynamic link between Canada's economic growth and renewable energy use using a panel autoregressive distributed lag model framed within the neoclassical production function. We incorporated an OECD-based indicator to identify Canada's economic phases and used the Pooled Mean Group method to analyse long-term and short-term correlations. The findings show a unidirectional causality going from renewable energy to economic growth only during expansion phases in the short-term, highlighting the need for policies that recognise the nonlinear connection between renewable energy and economic growth.
In our second study, we analysed the US stock market's reaction to both types of physical climate risks (chronic and acute) as well as transition climate risk. Using a multivariate hidden Markov model, we employ two climate variables and one sentiment variable to build an indicator for the chronic risk. Acute and transition risks are deemed to be reflected in the natural disaster and policy news, respectively. We evaluated their effects on stock returns using an event study methodology. Our results indicate that some sectors are more susceptible to climate risks than others. Firms with lower environmental scores face greater exposure, affecting their stock returns negatively. This implies that enhancing environmental performance can boost a company's financial resilience against climate risks.
We modelled the Emission Allowance price dynamics in the EU Emission Trading System in our third study. Capitalising on prior studies, we integrated a Markov-switching mechanism into four stochastic models. Parameters were estimated using change of reference probability measures alongside the EM algorithm. The fitting accuracy and usefulness of our model were assessed through an out-of-sample forecasting and the pricing of European-style call options. Notably, the Markov-switching Geometric Brownian motion model surpassed both the non-Markov switching and other Markov-switching stochastic models in in-sample and out-of-sample performance.
The fourth study in this research work investigated the influence of green bond issuance on an issuer's environmental performance, utilising an interrupted time series with a control group. This study also looked into how companies' financial characteristics and specific green bond data can enhance an issuer's environmental performance, using both the Random Forest and Generalised Additive models. Our findings indicate that the environmental performance of most issuers improves following the issuance of green bonds. Additionally, we discovered that certain company's characteristics as well as the specific features of the green bonds play significant roles in determining the efficacy of green bonds in enhancing a company's environmental performance. These findings are valuable for investors when selecting green bonds.
Summary for Lay Audience
Sustainable development has been instrumental in improving the quality of life for all, especially the present and future generations, emphasising equity and respecting our ecosystem's limits. In 2015, the United Nations (UN) formally adopted the 17 Sustainable Development Goals (SDGs), setting a blueprint for a more sustainable, current, and prosperous future. Numerous countries have responded to the call from the UN and implemented regulations and policies to achieve such SDGs. As sustainable development advances and new regulations and policies emerge, there are financial and economic aspects that warrant investigation.
This thesis investigates the financial and economic consequences of sustainable development. It encompasses four key areas: the link between renewable energy and economic progress, the challenges posed by climate risks, the mechanics of the carbon trading system, and the role of green bonds. Whilst policymakers endorse renewable energy for sustainability, they remain equally focussed on economic progress. We aim to determine if the causal relationship is influenced by economic status. This research is relevant to policymakers and regulators in effecting their policies, enabling the economy adapt to the promotion of renewable energy. Climate-risk considerations are crucial for sustainable development, as extreme weather events lead to significant financial and commodity market losses. Many regulatory authorities urge the integration of climate risk into financial systems. However, the effects of various climate risks on financial markets are not well-understood. We examine these impacts on the US stock market to understand issues pertaining to green investing and safeguarding against climate risk. To deal with global warming, many nations have employed various strategies and one of them is carbon emission trading. Our objective is to build a model that accurately captures the spot price of carbon emission allowances within the European carbon trading market. By studying the spot prices of the allowances, we generate ideas that will assist companies in their risk management and help regulators devise more effective carbon market mechanisms. Moreover, to address environmental challenges, companies issue green bonds to fund eco-friendly projects. Analysing the effectiveness of these bonds in elevating a corporation's environmental performance can guide investors in their financing and investment decisions.
Chen, Yiyang, "Statistical modelling and applications for sustainable-development goals" (2023). Electronic Thesis and Dissertation Repository. 9821.
Available for download on Sunday, November 30, 2025