Germany inflation approaching 2%
07 May 2025 - Written by ML
Highlights
March consumer price index data for Germany registers 121.2 for year on year rate of 2.1% (Statistisches Bundesamt (Destatis), 2025).
That continues its approach to the ECB guidance level of 2%.
| Inflation Measures — March 2025 | |
| Source: German CPI, raw & seasonally adjusted1 | |
| Measure | March 2025 |
|---|---|
| CPI level | 121.2 |
| Month-on-Month (raw) | +0.33% |
| Year-on-Year (raw) | +2.19% |
| CPI (seasonally adjusted) | 121.2 |
| Month-on-Month (sa) | +0.16% |
| 3-Month Annualized | +1.48% |
| 3-Month Rolling Annual (%) | +2.26% |
| Note: “sa” = seasonally adjusted; “raw” = unadjusted. | |
| 1 Seasonally adjusted month-on-month (0.16%) is much smaller than raw (0.33%), and the 3-month annualized pace (1.48%) suggests easing inflation. | |
Inflation computations
the month on month raw change in inflation takes CPI this month, divide by CPI last month, subtract 1, then multiply by 100. A value of, say, 0.33 means prices rose 0.33 % from Feb to Mar.
the Year-on-Year Raw Change compares CPI today with CPI exactly one year ago, subtract 1, then × 100. A rate of 2.19 means prices are 2.19 % higher than in March 2024.
the Seasonally Adjusted CPI Level attempts to remove seasonal swings in prices such as from winter heating or summer fruit. To compute that, raw CPI is fed into a model that strips out the seasonal effect. The hoped-for result is a series that allows a clearer sense of price movement free of seasonality. Without adjustment, the series could show large CPI jumps every January (as winter fuel prices rise) and falls every August—patterns (with the harvest) that repeat every year but obscure real inflation trends.
Seasonality is removed by decomposing the CPI series into its trend, seasonal and irregular components using the X-13ARIMA-function that:
Outlier adjustment down-weights one-off spikes or dips to remove distortions in data;
ARIMA modeling fits autoregressive (AR), integrated (I), and moving-average (MA) components to capture the series’ own momentum.
Seasonal estimation runs a regression on 12 monthly “dummies” (plus ARIMA filters) to pin down the average effect of each month.
Decomposition splits the series into
- T (Trend-cycle)
- S (Seasonal)
- I (Irregular)
- T (Trend-cycle)
Recombination discards S and re-forms
cpi_sa = T + Iso the seasonally adjusted CPI has only the long-run trend and the random noise. Stripped of calendar noise, the
mom_sa,r3m_ann,yoy_12m_rollreflects truer underlying price pressure.
the Month-on-Month Seasonally Adjusted Change is computed exactly like the raw MoM, but uses
cpi_sainstead of raw CPI. It shows the month-to-month rise in prices after removing all regular seasonal ups and downs.the Three-Month Annualized Rate takes the growth from January to March, raises that ratio to the 4th power (because there are 4 quarters in a year), subtracts 1, then × 100. It answers: “If that quarter’s pace ran all year, what would annual inflation be?”
the Three-Month Rolling Average of Year-on-Year takes the last three YoY rates (e.g. Jan, Feb, Mar) and averages them. This smooths out any one-month blip in the annual inflation rate.
Data
| CPI & Inflation Measures: Last 3 Years | |||||||
| Through March 2025 | |||||||
| Date | CPI | MoM (raw) | YoY (raw) | CPI (SA) | MoM (SA) | 3-Mo Annualised | 3-Mo Avg YoY |
|---|---|---|---|---|---|---|---|
| Apr 2022 | 108.8 | 0.6 | 6.2 | 108.5 | 0.4 | 10.9 | 5.5 |
| May 2022 | 109.8 | 0.9 | 7.0 | 109.5 | 0.9 | 13.1 | 6.4 |
| Jun 2022 | 109.8 | 0.0 | 6.7 | 109.6 | 0.1 | 5.7 | 6.7 |
| Jul 2022 | 110.3 | 0.5 | 6.7 | 110.0 | 0.3 | 5.5 | 6.8 |
| Aug 2022 | 110.7 | 0.4 | 7.0 | 110.5 | 0.5 | 3.6 | 6.8 |
| Sep 2022 | 112.7 | 1.8 | 8.6 | 112.6 | 1.9 | 11.4 | 7.4 |
| Oct 2022 | 113.5 | 0.7 | 8.8 | 113.4 | 0.6 | 12.8 | 8.1 |
| Nov 2022 | 113.7 | 0.2 | 8.8 | 114.0 | 0.6 | 13.4 | 8.7 |
| Dec 2022 | 113.2 | −0.4 | 8.1 | 113.5 | −0.5 | 3.1 | 8.6 |
| Jan 2023 | 114.3 | 1.0 | 8.7 | 114.9 | 1.2 | 5.5 | 8.5 |
| Feb 2023 | 115.2 | 0.8 | 8.7 | 115.4 | 0.5 | 5.0 | 8.5 |
| Mar 2023 | 116.1 | 0.8 | 7.4 | 116.1 | 0.6 | 9.5 | 8.2 |
| Apr 2023 | 116.6 | 0.4 | 7.2 | 116.3 | 0.1 | 4.9 | 7.7 |
| May 2023 | 116.5 | −0.1 | 6.1 | 116.2 | 0.0 | 2.8 | 6.9 |
| Jun 2023 | 116.8 | 0.3 | 6.4 | 116.6 | 0.4 | 1.9 | 6.5 |
| Jul 2023 | 117.1 | 0.3 | 6.2 | 116.8 | 0.1 | 1.8 | 6.2 |
| Aug 2023 | 117.5 | 0.3 | 6.1 | 117.3 | 0.4 | 3.8 | 6.2 |
| Sep 2023 | 117.8 | 0.3 | 4.5 | 117.7 | 0.4 | 3.8 | 5.6 |
| Oct 2023 | 117.8 | 0.0 | 3.8 | 117.7 | −0.1 | 3.0 | 4.8 |
| Nov 2023 | 117.3 | −0.4 | 3.2 | 117.7 | 0.0 | 1.3 | 3.8 |
| Dec 2023 | 117.4 | 0.1 | 3.7 | 117.7 | 0.0 | 0.0 | 3.6 |
| Jan 2024 | 117.6 | 0.2 | 2.9 | 118.2 | 0.4 | 1.8 | 3.3 |
| Feb 2024 | 118.1 | 0.4 | 2.5 | 118.3 | 0.1 | 2.3 | 3.0 |
| Mar 2024 | 118.6 | 0.4 | 2.2 | 118.4 | 0.1 | 2.5 | 2.5 |
| Apr 2024 | 119.2 | 0.5 | 2.2 | 119.0 | 0.5 | 2.7 | 2.3 |
| May 2024 | 119.3 | 0.1 | 2.4 | 119.0 | 0.0 | 2.3 | 2.3 |
| Jun 2024 | 119.4 | 0.1 | 2.2 | 119.2 | 0.2 | 2.7 | 2.3 |
| Jul 2024 | 119.8 | 0.3 | 2.3 | 119.5 | 0.2 | 1.6 | 2.3 |
| Aug 2024 | 119.7 | −0.1 | 1.9 | 119.5 | 0.0 | 1.7 | 2.1 |
| Sep 2024 | 119.7 | 0.0 | 1.6 | 119.7 | 0.1 | 1.4 | 1.9 |
| Oct 2024 | 120.2 | 0.4 | 2.0 | 120.1 | 0.3 | 1.9 | 1.8 |
| Nov 2024 | 119.9 | −0.2 | 2.2 | 120.3 | 0.2 | 2.6 | 2.0 |
| Dec 2024 | 120.5 | 0.5 | 2.6 | 120.8 | 0.4 | 3.9 | 2.3 |
| Jan 2025 | 120.3 | −0.2 | 2.3 | 120.9 | 0.1 | 2.8 | 2.4 |
| Feb 2025 | 120.8 | 0.4 | 2.3 | 121.0 | 0.1 | 2.6 | 2.4 |
| Mar 2025 | 121.2 | 0.3 | 2.2 | 121.2 | 0.2 | 1.5 | 2.3 |
| Note: SA = seasonally adjusted; percent changes computed as 100×(current/lag – 1). | |||||||