Short-term interest rate (per cent) - Italy - OECD - Monthly
This series is part of the dataset: OECD interest rates
Download Full Dataset (.xlsx)Latest updates. In Italy, the short-term interest rate stood at 2.64 per cent in September 2026, compared to 2.51 in the previous month.
Sample. In the monthly series shown in the plot, there are a total of 576 records. The span of time covered by the series goes from October 1978 to September 2026.
History. Check out some descriptive statistics calculated on the entire sample: the interest rate had a mean of 6.35 per cent; it reached its lowest level of -0.58 per cent in December 2021; it recorded its highest level of 20.51 per cent in June 1982.
Latest values
| Date | Value - Percentage points |
|---|---|
| 2026-07-31 | 2.42539 |
| 2026-08-31 | 2.51314 |
| 2026-09-30 | 2.63505 |
Suggestion. We categorize time series into worksheets and datasets to make our users' life easier. By scrolling down, you will discover how we structured further information related to the statistics provided here.
Not for investment purposes. Any financial data distributed on this web site are not intended for investment purposes or other financial decisions. Users should obtain expert advice and do independent analysis before taking any financial risk.
Series Metadata
| Field | Value |
|---|---|
| Description | Short-term interest rate |
| Country | Italy |
| Economic concept | Interest rate |
| Data type | Annual interest rate |
| Seasonally adjusted | No |
| Deflation method | Not applicable |
| Rescaling | None |
| Measure type | Level |
| Frequency | Monthly |
| Unit | Percentage points |
| Source | OECD |
| Source type | International organization |
| Data licence | Redistributable with citation |
| Other information | Short-term interest rates are the rates at which short-term borrowings are effected between financial institutions or the rate at which short-term government paper is issued or traded in the market. |
| FSR temporal aggregation code | LM1 |
Series in the same data set
Discover the other time series included in this data set.