Biodiversity and natural resource finance

Peter G. Iliev, Jennifer Liang, and Jess Cornaggia

This research aims to explore how biodiversity is reflected in the pricing of local real estate and agricultural land, and how this relationship has evolved over time in the United States. It quantifies the relationship between biodiversity and local asset values – specifically residential and agricultural real estate prices – by combining property-level biodiversity loss metrics (from CSIRO) and county-level species richness data (from NatureServe). It analyses over 63 million US property transactions from CoreLogic over a 21-year period between 2000 and 2021.

Zoey Yiyuan Zhou and Douglas Almond.

The main objective of this research is to provide the first large-scale, empirical assessment of whether nature-based carbon offset projects lead to measurable improvements in biodiversity outcomes. This is frequently claimed to be the case but rarely verified at scale. The dataset compiled for this research includes 29,974 voluntary carbon offset projects (2701 with geospatial data) and 419,267 carbon credit retirements. It’s the largest known dataset of its kind. It links this data with satellite-based biodiversity and land-use metrics, particularly the Human Influence Indexes, which captures habitat disturbance from human activity. and analyses the ecological outcomes of these carbon projects across space and time.

Massimo Guidolin, and Manuela Pedio.

This project investigates the link between biodiversity risk and commodity prices, addressing an underexplored area in financial economics. It examines whether investors demand a premium for commodities with high biodiversity exposure, as biodiversity loss – driven by deforestation for agricultural and energy production – exacerbates climate change in a reinforcing feedback loop. With emerging regulations targeting ecological preservation, such commodities may face significant transition risks. The study leverages innovative data and controls to isolate biodiversity risk from broader environmental risks, offering new insights into its impact on commodity pricing.

G. Andrew Karolyi, William W. Xiong, Hui Xu, and Sean S. Cao.

This research examines the effectiveness of venture capital financing for emerging biodiversity-focused startups, which differ from large public firms where biodiversity projects are secondary initiatives. It explores tools to improve funding outcomes. Social media is highlighted as a potential tool for overcoming challenges these ventures face, such as limited investor bases and the complexity of nature-related business models. The project uses data from platforms like Twitter, LinkedIn and investment sources like Crunchbase and PitchBook to study how social media can help engage investors and reduce information gaps.

Ted Liu, Brook Constantz, Michael Beck, and Galina Hale.

This project quantifies the financial benefits of nature-based solutions to climate adaptation and aims to contribute to existing knowledge on pricing climate risks and identifying cost-effective risk reduction solutions. It focuses on the role that mangroves have on reducing home price declines and price variability following major hurricanes in 2004, 2012, and 2017. The project explores the private financial benefits of mangrove protection and the role of private funding as a key source for financing restoration projects.

Snorre Gjerde, Zacharias Sautner, Alexis Wegerich, and Alexander Wagner.

This project aims to explore how companies perceive and manage nature risks and how they interact with institutional investors on this issue. The survey themes include corporate exposure to nature risks, investor interest in these risks and nature-related disclosures. Distributed through a large asset owner to its portfolio companies, the survey provides early insights into corporate views and actions on emerging nature risks and their alignment with investor perspectives. The findings could assist regulators, investors and academics in shaping policies and models related to nature risks in corporate finance and asset pricing, as well as understanding the impact of investor engagement.

Franklin Allen, Patrick Behr, Riccardo Cosenza, and Eric Nowak.

This project explores how investors respond to firms’ activities in the Voluntary Carbon Market (VCM) using a dataset covering VCM transactions and retirements from 2009 to 2023. Publicly listed firms primarily retire carbon credits linked to rainforest conservation projects, as deforestation is a key driver of climate change and biodiversity loss.

Andre Poyser.

This project explores the impact of financing on biodiversity risks, focusing on endangered species, species richness, species protection, and data coverage. Using data from 13,919 biodiversity projects funded by 114 European agencies, the research distinguishes between public and private financing. The project also highlights the potential of biotechnology-focused projects to attract private investment, as these projects may generate future cash flows through ancillary technological applications.

Arthur Romec, Zacharias Sautner, , Alexander Wagner, and Alexandre Garel.

This project aims to quantify and understand how much firms rely on nature and ecosystem services and to explore the financial implications of that dependence. It constructs scalable, firm-level measures of nature dependence, known as NatureDep scores, for 26,595 listed firms from 115 countries over a 12-year period between 2010 and 2022. These scores combine firm-level revenue data with dependency materiality ratings from the ENCORE database to capture the extent to which a firm’s business activities rely on ecosystem services. The research analyses this data to explore what it means for risk, disclosure and investor behaviour.

Amir Akbari, Man Duy (Marty) Pham, Jing Yu, and Lilian Ng.

This project introduces a new Corporate Biodiversity Risk (CBR) measure to assess biodiversity risk and its financial impacts at the organisation/establishment level. CBR evaluates the proximity of corporate production sites to protected areas in the contiguous US to quantify risk. It uses data from 1990 to 2021.