The Sámi–Forestry Company Conflict and Its Implications for Multinational Finance and ESG Risk

The Sámi–Forestry Company Conflict and Its Implications for Multinational Finance and ESG Risk DescriptionThis repository supports a study analyzing the intersection of Indigenous governance, carbon emissions, and multinational forestry activity. The focus is on the Sámi people of northern Sweden, whose customary land rights conflict with commercial land use regimes. The study explores how institutional pluralism and ESG risk intersect, drawing on panel data from CO₂ emissions, GDP, and V-Dem institutional indicators. All code and data files are designed for use in Google Colab, ensuring reproducibility and accessibility. This repository contains the data and code supporting the paper titled “Navigating Institutional Pluralism and Indigenous Rights: The Sámi–Forestry Company Conflict and Its Implications for Multinational Finance and ESG Risk.” The study analyzes how Indigenous governance frameworks—particularly Sámi customary land rights—interact with state regulation and multinational forestry operations in northern Sweden. Using a combination of clearcutting permit data, ownership type classification, and institutional indicators, we assess the legal and ESG risk environment associated with contested land use. We apply a difference-in-differences (DiD) methodology and OLS regression to detect structural breaks in forestry activity before and after 2020, a year that marks intensifying legal and political pressure over Indigenous land use. Our analysis highlights how institutional pluralism, regulatory uncertainty, and Indigenous claims generate ESG risk exposures for investors and multinational firms. Included Files Clearcut.xlsx: Source dataset from the Swedish Forest Agency covering annual regeneration felling applications by region and ownership type (1998–2024). OLS.ipynb: Google Colab notebook performing base ordinary least squares regression on clearcutting trends. DiD.ipynb: Difference-in-differences analysis notebook estimating the interaction effect of post-2020 institutional signaling and private land ownership. OLS_DiD.ipynb: Combined model for robustness testing with year and region-owner fixed effects. How to Run Open Google Colab: https://colab.research.google.com Upload all .ipynb and .xlsx files to your Colab environment. Ensure the file path for Clearcut.xlsx in each notebook is correctly set (e.g., /content/Clearcut.xlsx). Run cells sequentially to reproduce regression outputs and visualizations. All analyses are written in Python using pandas, statsmodels, and matplotlib, and can be executed without any local setup. All dependencies are handled within the notebooks.