Abstract

Foreign Direct Investment (FDI) plays a crucial role in global economic development and policy-making and can serve as a key mechanism for policymakers seeking to tackle climate change. While FDI promotes the international transfer of low-carbon technologies, it can also introduce challenges by allowing companies to circumvent stringent emissions regulations. This occurs when firms shift carbon-heavy production to countries with looser environmental rules—a process referred to as carbon leakage—and subsequently export the goods to other markets, making it vital for policymakers to thoroughly assess FDI’s environmental impacts.

A key aspect of accurately estimating the carbon footprint associated with FDI is understanding the ownership dimension—distinguishing between domestic and foreign-owned enterprises. Incorporating ownership data allows for more granular analysis of emission sources and consumption patterns across global value chains (GVCs). Emissions stem not only from the operational activities of foreign-controlled firms but also from assets acquired through FDI, such as new buildings, infrastructure, and machinery. These investments, captured by Gross Fixed Capital Formation (GFCF), significantly contribute to the host country’s economic growth but also generate emissions during both construction and operation. This underscores the need for comprehensive indicators covering both capital formation and ongoing business activities.

Methodological approaches to estimating the carbon footprint of FDI and of multinational enterprise (MNE) activities range from basic models requiring minimal data to advanced frameworks that incorporate detailed information on ownership structures, FDI composition, and international supply chains. More sophisticated models enable a clearer differentiation between emissions attributable to domestic and foreign-owned firms, providing richer insights for policy analysis and enhancing comparability across countries. This increased granularity improves the accuracy of footprint estimates and supports targeted interventions.

Recent research, including Borga et al. (2023), illustrates the complex impact of FDI on host economies. While FDI can drive economic growth, diversify exports, and foster structural transformation, emissions from foreign-owned enterprises add complexity to policy design. Isolating these emissions requires detailed ownership and activity data, which can be achieved through global input-output models that integrate ownership information. This approach enhances policymakers’ ability to craft targeted interventions, such as coordinated strategies and green investment incentives.

The importance of integrating ownership data is highlighted by findings from France and the Netherlands. In France, private emissions data reveal clear differences in emissions intensity between domestic and foreign-owned firms, with foreign multinationals showing higher carbon footprints in certain sectors, guiding sector-specific policies. In the Netherlands, national statistics allow estimation of MNEs’ emission intensities, showing significant contributions in key industries. Incorporating ownership details improves accuracy, uncovering patterns otherwise hidden in aggregate data.

In conclusion, integrating the ownership dimension into carbon footprint estimation is essential for capturing the true environmental impact of FDI and multinational enterprises. This enables policymakers to identify major emission sources, design effective coordinated responses, and encourage sustainable investments. While data gaps and enterprise heterogeneity remain as challenges, ongoing methodological improvements and harmonized data initiatives offer promising pathways forward.