ECB HICP Core Inflation — Euro Area Underlying Inflation Dataset (1997–2026)
ECB Dataset · Inflation
Euro Area HICP Core Inflation — Ex Food & Energy (1997–2026)
The underlying inflation signal for the euro area — stripping out volatile food and energy components. Dominated by services inflation (~60% of core), which reflects domestic wages and demand conditions rather than global commodity shocks.
Why core inflation matters more than headline
Core HICP strips out food and energy prices — the two components most influenced by global commodity markets and supply shocks rather than domestic monetary conditions. This makes it a better gauge of the underlying inflation trend that the ECB can actually influence through interest rate policy.
In practice, the ECB watches both headline and core, but core inflation drives the pace of rate decisions. During the 2022–2023 inflation episode, headline HICP peaked at 10.6% (October 2022) while core peaked later at 5.7% (March 2023) — illustrating how energy shocks hit headline first, then feed through into broader prices with a lag. Headline returned below 2% by late 2025, but core remained stubbornly above 2.3%, driven almost entirely by services.
The services inflation problem
Services account for roughly 45% of the HICP basket and approximately 60% of core HICP. Services inflation in the euro area has been persistently elevated at 3–4% since 2023, driven by lagged wage adjustments (European wage negotiations are more centralized and slower than in the US), rising rents in major cities, and structural labor shortages in healthcare and hospitality sectors. This “last mile” of disinflation has been the central challenge for ECB policy since mid-2024.
Core HICP vs US Core CPI — structural divergence
Euro area core inflation has historically been lower and less volatile than US Core CPI. Two structural factors explain this: the absence of owner-occupied housing (shelter) from HICP, which is the largest and stickiest component of US Core CPI, and the greater rigidity of European labor markets, which dampens both wage growth and wage-price spirals.
CSV Data Dictionary
| Column | Type | Description |
|---|---|---|
| date | YYYY-MM-DD | First day of the reference month |
| hicp_core_yoy | float | HICP excluding food & energy, annual rate of change (%) |
Python Code Example
import pandas as pd
from io import StringIO
import requests
# Core HICP — direct from ECB (no API key)
url = "https://data-api.ecb.europa.eu/service/data/ICP/M.U2.N.XEF000.4.ANR"
resp = requests.get(url, params={"format": "csvdata"})
df = pd.read_csv(StringIO(resp.text))
core = df[["TIME_PERIOD", "OBS_VALUE"]].copy()
core.columns = ["date", "hicp_core_yoy"]
core["date"] = pd.to_datetime(core["date"] + "-01")
core = core.sort_values("date").set_index("date")
# Compare headline vs core
url_h = "https://data-api.ecb.europa.eu/service/data/ICP/M.U2.N.000000.4.ANR"
headline = pd.read_csv(StringIO(requests.get(url_h, params={"format": "csvdata"}).text))
headline = headline[["TIME_PERIOD", "OBS_VALUE"]].copy()
headline.columns = ["date", "hicp_headline_yoy"]
headline["date"] = pd.to_datetime(headline["date"] + "-01")
headline = headline.sort_values("date").set_index("date")
combined = pd.concat([headline, core], axis=1).dropna()
combined.plot(title="Euro Area Inflation: Headline vs Core", figsize=(12, 5))Related ECB Datasets
Source & Methodology
Series key: ICP/M.U2.N.XEF000.4.ANR
Definition: HICP All-items excluding energy (COICOP 04.5) and food including alcohol & tobacco (COICOP 01, 02).
License: ECB open data — free reuse with attribution.