TWO STUDIES IN GREEN FINANCE: HAVE GREEN BONDS BEEN DELIVERING ON THEIR PROMISE TO MAKE THE ENVIRONMENT MORE SUSTAINABLE IN THE FACE OF CLIMATE CHANGE? AND DO ENVIRONMENTAL, SOCIAL AND GOVERNANCE LABELLED FUNDS CREATE A DIFFERENT INVESTMENT ALTERNATIVE OR ARE THEY MORE OF THE SAME?
Fernandes Lopes, Otavio Augusto
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Throughout the 20th century it became clear that anthropogenic activity is the main factor in the rapid climate shift resulting from temperature increases. In capital markets this challenge has been dealt with mainly through the classification of certain assets as green and, more recently, the Environmental Social and Governance (“ESG”) scoring of assets and funds. This doctoral thesis has investigated the impact that green bond issuances in the USA had on greenhouse gas (“GHG”) emissions reported at a facility level to the Environmental Protection Agency (“EPA”). It also compares ESG denominated funds and non ESG denominated funds to define if they are statistically different between them and when compared to the SP500. The analysis concludes that first time green bond issuances are corelated to statistically significant reductions in GHG emissions by the facilities associated with a green bond parent firm even using 99% confidence intervals. It further shows that there is no clear pattern to when green assets related to an issuance are created, making lagged or leading effects of treatment not obvious. The innovative approach, using facility level data, sets the steps for future analysis when more data may be available. The analysis also concludes that ESG labelled exchange traded funds (“ETFs”) are not able to statistically differentiate themselves from non-ESG ETFs nor the SP500 in terms of industry allocation. When analyzing E, S, G and ESG scores we found mixed results. Group average E, S, G and ESG scores were not statistically different under the Wilcoxon Signed-Rank test. However, there was no significant evidence that ESG ETFs and non-ESG ETFs have the same median S, G and ESG scores when using non-averaged data under the Wilcoxon Rank-Sum test, which means that they differentiate enough to be considerate different.