Our planet is currently living through mass extinction. Monitored wildlife populations have declined by 69% since 1970 (WWF, 2020). This profound loss of life has become increasingly important for policymakers, with billions of dollars committed to financing programs to restore nature, protect species, and reverse the depletion of local environments (Bromley, 2024). However, the economic, financial, and environmental tradeoffs policymakers face when planning to implement their preferred solutions are poorly understood. When governments expand habitat protections, where will housing affordability worsen, where will residents benefit, and can speculation destabilize markets?
Our paper “Biodiversity Protection Policy and Housing Markets: Supply, Demand, and Speculation” aims to help fill part of this gap, showing the expected impact of biodiversity policy on local housing markets. To estimate the expected impact of regulatory policy, we utilize a unique measure of exposure to biodiversity policy risk, as well as an unexpected policy shift that differentially affected high-exposure counties.
Overview
To measure a county’s exposure, we use the presence of endangered species weighted by the amount of protection the species enjoy. We exploit an increase in policy risk from the Biden administration’s proposed “30×30” plan, which aimed to significantly increase the amount of protected land by 2030. Comparing high-exposure counties to low-exposure counties before and after the announcement isolates how anticipated conservation regulation affects housing markets.
Key Findings
- Prices rise in highly exposed places. Following the policy announcement, house prices increase by 0.6% for each standard deviation increase in exposure (about $990 for homes in our sample) and for the top tercile of exposure we find prices increase by 2.3% on average, increasing to 3.7% by the end of our sample.
Percent Difference in House Price Between Exposed and Unexposed Counties
- Much of this increase is driven by demand. While we find some evidence that supply restrictions play a role, the largest increase in price occurs in nature deprived areas with a large amount of land available for building on, suggesting amenity demand is an important channel. Therefore well targeted policy can preserve species while also benefiting residents.
- Impacts are not uniform—and may be negative in nature-dependent economies. Areas whose economies are heavily reliant on nature such as mining, forestry and oil extraction see a much smaller increase in prices and potentially a negative impact.
Percent Difference in House Price Between Exposed and Unexposed Counties - Speculation amplifies market movements and may increase volatility. Loan application and origination growth is strongest for investment (not owner-occupied) purposes, and land values rise more than property values, consistent with speculative dynamics. In a volatile policy environment, this can generate boom-bust cycles in highly exposed markets.
Conclusion
As governments commit themselves to protect biodiversity, understanding the impact of policy becomes increasingly important. Our findings suggest several policy recommendations. Policymakers should prioritize areas where the benefits of protecting species and satisfying individuals’ demand for natural amenities are largest while being wary of housing affordability issues in supply constrained areas. Policymakers should also work to reduce harm in economies dependent on nature intensive industries by pairing conservation efforts with transition planning. Finally, policy should be designed to dampen speculation by improving clarity and credibility of timelines, and monitoring investor activity in high-exposure markets.