Euro Area HICP Index Level: Monthly Data Since 1996
ECB Dataset · Inflation
The HICP index level (base 2025=100): the building block for computing inflation rates over any custom period, deflating nominal European data, and constructing real (inflation-adjusted) time series for euro area assets.
Using the HICP index for real-value calculations
While the annual rate of change (headline HICP) captures the flow of inflation, the index level captures the stock: the cumulative effect of price changes since the base year (2025=100). In August 2026 the index stood at 103.7, meaning the euro area price level has risen about 3.7% since the 2025 average; measured from the start of the series in 1996 (55.1), it has close to doubled.
For researchers and analysts, the index level is the more useful series: divide any nominal euro-denominated time series by this index (and multiply by 100) to obtain real, inflation-adjusted values. Underlying series: the ECB Data Portal series for Euro Area HICP Index Level. This is how Eco3min computes datasets like the Real Deposit Facility Rate (DFR minus HICP).
Methodological note
Eurostat began a major methodological revision of the HICP in February 2026, including changes to weights, classifications, and seasonal adjustment. The ECB moved the series from the legacy ICP dataflow, frozen at December 2025, to the new HICP dataflow (data provider code 4D0), and the index was rebased from 2015=100 to 2025=100. This dataset follows the new dataflow: the full history since 1996 is expressed on the 2025 base, so earlier levels quoted on the 2015 base are not directly comparable.
CSV Data Dictionary
| Column | Type | Description |
|---|---|---|
| date | YYYY-MM-DD | First day of the reference month |
| hicp_index | float | HICP all-items index level (2025=100) |
Python Code Example
import pandas as pd
from io import StringIO
import requests
url = "https://data-api.ecb.europa.eu/service/data/HICP/M.U2.N.000000.4D0.INX"
resp = requests.get(url, params={"format": "csvdata"})
raw = pd.read_csv(StringIO(resp.text))
df = raw[["TIME_PERIOD", "OBS_VALUE"]].copy()
df.columns = ["date", "hicp_index"]
df["date"] = pd.to_datetime(df["date"] + "-01")
df = df.sort_values("date").set_index("date")
df.plot(title="Euro Area HICP Index (2025=100)", figsize=(12, 5))Related ECB Datasets
Source & Methodology
Source: ECB / Eurostat, HICP All-items index
Series key: HICP/M.U2.N.000000.4D0.INX
Data terms: ECB copyright notice: the ECB is cited as the source, the data are reproduced accurately and any modification is stated; no Creative Commons licence.
Cite This Dataset
Last updated — 5 November 2026
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Source terms. This series is produced by the European Central Bank (ECB Data Portal) and redistributed here under the ECB's copyright terms: free use provided the ECB is cited as the source, the data are reproduced accurately, and any modification (such as a spread or a real rate computed by Eco3min) is stated explicitly. Eco3min cannot sub-license it under Creative Commons: anyone reusing this file remains bound by the ECB terms, not by CC BY. Full terms.