Excise duty on diesel (units of national currency per 1000 litres) - Germany - European Commission - Weekly
This series is part of the dataset: Retail diesel prices (EU)
Download Full Dataset (.xlsx)Latest updates. In Germany, the excise duty on diesel (automotive gasoil) was 330.00 units of national currency per 1000 litres on 12 October 2026, the same as on 5 October 2026.
Sample. This weekly time series has a total of 1,088 observations. The series covers the span of time stretching from January 2005 to October 2026.
History. Here's a snapshot of a few summary statistics calculated on the full sample: the excise duty reached a trough of 330.00 national-currency units on 6 June 2022; it hit a maximum of 470.40 national-currency units on 3 January 2005; it was equal on average to 467.30 national-currency units.
Latest values
| Date | Value - Units of national currency per 1000 litres |
|---|---|
| 2026-09-28 | 470.400 |
| 2026-10-05 | 330.000 |
| 2026-10-12 | 330.000 |
Nugget of wisdom. A plus of our data visualization and download service is that we publish rich metadata. Find them below to delve deeper into the properties of the indicators that you are exploring.
Not for investment purposes. Any financial data found on this web site are not intended for investment purposes or other financial decisions. Users should obtain professional advice and do independent analysis before making any financial commitments.
Series Metadata
| Field | Value |
|---|---|
| Description | Excise duty on automotive gasoil |
| Country | Germany |
| Economic concept | Tax |
| Data type | Nominal amount |
| Seasonally adjusted | No |
| Deflation method | Current prices |
| Rescaling | None |
| Measure type | Level |
| Frequency | Weekly |
| Unit | Units of national currency per 1000 litres |
| Source | European Commission (Weekly Oil Bulletin) |
| Source type | International institution |
| Data licence | Reuse allowed under EU legal notice (with attribution) |
| Other information | Not available |
| FSR temporal aggregation code | LW1 |
Series in the same data set
Discover the other time series included in this data set.