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I am a doctoral candidate at the London Business School. I am an empirical researcher who works on climate risk and sustainability. I apply econometric and deep learning methods on big and alternative data to address questions around this theme. I have also served as a senior consultant for data science and investment management organisations.

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We compile a dataset comprising seven million residential real estate transactions in the United Kingdom to examine homeowner valuation of dwelling sustainability. Homeowners pay a premium for more energy-efficient dwellings. Exploitation of the spatial, temporal, tenurial, and vintage heterogeneity in the premium shows that homeowners price the energy efficiency of their dwellings following economic principles. We propose a simple valuation model to recover the discount rates used by homeowners, which provide direct measures for rates used to discount investments in sustainable development and climate change mitigation. The rates demonstrate that homeowners accept lower returns for greener dwellings, indicating non-pecuniary incentives.

To study the impact of green-transition regulation on firm value, we analyze stock returns around legislator tweets about climate change. Green stocks significantly outperform brown stocks in the one-to-ten-minute window around pro-transition tweets. The cumulative daily-average green-minus-brown portfolio return around pro-transition tweets is 6.9% higher than around anti-transition ones. For tweets that mention environmental regulations, the spread increases in the weeks before a congressional vote and is stronger before close votes and when Congress is split. Our findings suggest that the green transition impacts the relative performance of green and brown stocks, at least partly, via a regulatory channel.

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Copyright @ Milind Goel (2025)

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