Influence of the Carbon Border Adjustment Mechanism on the imports of Passenger Vehicles to Germany

This dataset accompanies the study “Influence of the Carbon Border Adjustment Mechanism (CBAM) on the Imports of Passenger Vehicles to Germany”, which analyzes the political and economic implications of the EU’s CBAM within the framework of the “Fit for 55” package. The research applies a gravity model to investigate how bilateral trade flows respond to CO₂ pricing, technological efficiency, and institutional governance factors between 2008 and 2024. The empirical results show that CBAM exerts a mild but statistically significant trade-restrictive effect, which intensifies with the CO₂ intensity of exporting countries. This effect is stronger for non-EU nations and weaker in large, densely populated markets that benefit from economies of scale.

The dataset combines information from several authoritative sources:

Car import data from the German Federal Ministry of Transport (annual bilateral import volumes, 2008–2024);

Macroeconomic indicators (GDP per capita, total population, exchange rate, political stability) from the World Bank’s World Development Indicators;

Inflation rates from the International Monetary Fund (IMF);

CO₂ intensity data from the European Commission’s EDGAR database;

Technological efficiency measures from the Global Innovation Index (WIPO), used to construct a custom CBAM impact indicator that accounts for differences in carbon pricing, production efficiency, and embedded emissions;

Additional constructed variables include a dummy for EU membership, bilateral geographic distance (CEPII GeoDist dataset), and derived indicators such as population density ratios (BevRho_ij) and relative inflation and governance differences between trading partners.

All datasets were harmonized by country and year, cleaned for consistency, and merged into a balanced panel structure covering 47 partner countries across 17 years. Variables were log-transformed or z-standardized where appropriate to reduce heteroskedasticity and ensure comparability.

The dataset is provided in Excel (.xlsx) format, consisting of multiple sheets, each representing one of the key variables used in the regression analysis (e.g., GDP, imports, CO₂ intensity, distance, EU membership, etc.).
Each sheet contains country–year data in a wide structure, which can be easily converted into a long (panel) format for econometric replication in software such as Python, Stata, or R.