Imports of goods and services (million units of national currency) - Luxembourg - Eurostat - Quarterly
This series is part of the dataset: Nominal GDP (Eurostat)
Download Full Dataset (.xlsx)Latest updates. In Luxembourg, nominal imports of goods and services were 39,877 million units of national currency in 2026-Q2, compared to 39,048 in the previous quarter. This represents a rise of 2.1 percent.
Sample. There are 126 records overall in the quarterly series presented in the plot above. The series covers the span of time extending from March 1995 to June 2026.
History. Check out a few summary statistics we calculated on the entire sample: imports of goods and services recorded their highest level of 41,541 million units of national currency in June 2024; they reached their minimum of 3,169 in March 1995; they had a mean of 17,596.
Latest values
| Date | Value - Million units of national currency |
|---|---|
| 2025-12-31 | 39,731.6 |
| 2026-03-31 | 39,047.9 |
| 2026-06-30 | 39,877.1 |
Nugget of wisdom. A plus of our data visualization and download service is that we provide rich metadata. Check it below to gain insights on the properties of the indicators that you analyze.
Not for investment purposes. Data series and other information collected and published on this web site are not suitable for investment purposes or other financial decisions. Users should ask for professional advice and do their own independent due diligence before taking any financial risk.
Series Metadata
| Field | Value |
|---|---|
| Description | Imports of goods and services |
| Country | Luxembourg |
| Economic concept | Flow |
| Data type | Nominal aggregate |
| Seasonally adjusted | Yes |
| Deflation method | Current prices |
| Rescaling | None |
| Measure type | Level |
| Frequency | Quarterly |
| Unit | Million units of national currency |
| Source | Eurostat |
| Source type | International organization |
| Data licence | Free reuse with attribution |
| Other information | Not available |
| FSR temporal aggregation code | LQ1 |
Series in the same data set
Discover the other time series included in this data set.