Macquarie University
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The real effect of the US Green New Deal

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posted on 2024-01-25, 03:06 authored by Xu Chen

The US Green New Deal (GND) is a proposal calling for political action to tackle climate change. Its aim is to adopt policies that support the achievement of carbon-neutral, however, it has encountered significant obstacles in being passed as legislation. Some of this resistance is based on concerns relating to the potential consequences of climate actions on asset values. Utilizing the approach of Barraclough et al. (2013), we use option prices of fossil fuel firms to estimate the probability of the successful passage of the GND through four voting events related to the three versions of the proposal, namely the initial GND proposal in 2019, the Build Back Better Act (BBBA) in 2021, and the Inflation Reduction Act (IRA) in 2022. We find that the passing rates for the four voting events are 46.74%, 49.84%, 48.89%, and 41.16% respectively. We also estimate the proposals’ value effect and news effect on fossil firms. Specifically, we find the average value effect of GND, BBBA, IRA (Senate), and IRA (House) is negatively significant at –17.87% (–1.83 billion USD), –5.10% (551.81 million USD), –15.08% (–2.73 billion USD), and –11.66% (–2.65 billion USD) respectively. The average news effects for GND, BBBA, IRA(Senate), and IRA(House) have an average value of 6.28% (533.48 million USD), 2.27% (254.43 million USD), 7.13% (1.31 billion USD), and 5.23% (1.15 billion USD) respectively. Furthermore, we find that the value effects of the proposal are more pronounced for fossil fuel firms with higher carbon emissions.


Table of Contents

Chapter 1. Introduction -- Chapter 2. Literature review -- Chapter 3. Timeline of the Green New Deal -- Chapter 4. Methodology -- Chapter 5. Data and sample -- Chapter 6. Results -- Chapter 7. Conclusion -- References

Awarding Institution

Macquarie University

Degree Type

Thesis MRes


Master of Research

Department, Centre or School

Department of Applied Finance

Year of Award


Principal Supervisor

Thomas Smith

Additional Supervisor 1

Jianlei Han


Copyright: The Author Copyright disclaimer:




United States


31 pages

Former Identifiers

AMIS ID: 295883

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