Natural, Social and Financial Capitals

Using comprehensive data from Italian provinces, we establish financial development as a key transmission mechanism affecting biodiversity outcomes. Through instrumental variable approaches addressing endogeneity concerns, we demonstrate that financial inclusion consistently exhibits negative relationships with all biodiversity indicators. We provide empirical support for the Environmental Kuznets Curve in biodiversity contexts, revealing an inverted U-shaped relationship between economic development and ecosystem degradation. Economic growth initially causes biodiversity deterioration, which later eases as development progresses, though our evidence shows the turning point occurs at relatively high income levels.

Our analysis reveals an important tension in sustainable finance: social capital that facilitates financial development and economic growth may simultaneously contribute to natural capital depletion. This finding poses some possible challenges for private capital mobilization and suggests that effective biodiversity finance instruments must account for these complex interdependencies. The methodology leverages scalable satellite technologies to measure biodiversity at granular provincial levels, examining differential impacts across economic sectors and taxonomic groups including amphibians, birds, mammals, plants, and reptiles.

Addressing the $700 billion annual biodiversity finance gap requires robust, comparable, and scalable metrics to build investor confidence and enable effective risk pricing. Therefore, this paper additionally contributes to biodiversity finance by developing and validating four distinct biodiversity measurement approaches using satellite and geospatial data, demonstrating their potential for standardized investment applications. Our metrics, Mean Species Abundance, Biodiversity Intactness Index, Deviation from Potential Natural Vegetation, and a composite Principal Component Analysis measure, capture fundamentally different information than traditional climate indicators, with correlations to CO2 emissions ranging only from 0.22 to 0.27. This finding has critical implications for financial risk assessment, suggesting that climate-focused metrics alone provide incomplete pictures of material biodiversity risks facing businesses and investors.

These empirical results offer practical insights for mainstream investors seeking to integrate biodiversity metrics into investment decisions, price biodiversity-related risks, and design financial instruments that genuinely reduce corporate impacts. By providing comparable, transparent metrics derived from objective geospatial data, this research addresses critical infrastructure needs for developing credible biodiversity markets and mobilizing private finance to bridge funding gaps.