Development of GDP

Situation in the euro area and the EU

In the 3rd quarter of 2025, seasonally adjusted GDP increased, up 0.3% quarter on quarter in the euro area and 0.4% in the EU. For comparison, an increase of 0.1% had been observed in the 2nd quarter in the euro area and 0.3% in the EU.

Situation in the EU countries

Based on the latest quarter-on-quarter rates of change, GDP increased in the 3rd quarter of 2025 in 21 countries, was unchanged in 3 and decreased in 3. Denmark (up 2.3%) recorded the largest increase of GDP, while the decreases were observed in Ireland, Finland (both down 0.3%) and Romania (down 0.2%).

Situation in non-EU countries

Compared with the previous quarter, GDP expanded in the 3rd quarter of 2025 in China (up 1.1%) while it contracted in Iceland (down 0.2%), Japan (down 0.4%) and Switzerland (down 0.5%). In the 2nd quarter, growth of 0.9% was recorded in the United States and Norway (up 0.8%). (*) See latest estimates for more data.

Industrial production

In September 2025, seasonally adjusted industrial production increased month on month by 0.2% in the euro area and by 0.8% in the EU. In the previous month, there had been decreases of 1.1% in the euro area and 0.9% in the EU.

Production in construction

In September 2025, seasonally adjusted production in construction decreased 0.5% in the euro area and was unchanged in the EU compared with the previous month. In the previous month, it had decreased 0.2% in the euro area and 0.8% in the EU.

Retail trade

In October 2025, the seasonally adjusted volume of sales in retail trade was unchanged compared with the previous month in both the euro area and the EU (0.0%), following on from modest increases in the previous month in the euro area (up 0.1%) and the EU (up 0.2).

Inflation

Situation in the euro area and the EU

According to the latest data from Eurostat, the annual inflation rate (based on the HICP) in the euro area was 2.2% in November 2025, up 0.1 points from the previous month. In the EU, the annual inflation rate was 2.5% in October 2025, down 0.1 points from the previous month.

Situation in the EU countries

The highest annual inflation rates (based on the HICP) in November 2025 were recorded in Estonia (4.7%), Croatia (4.3%) and Austria (4.1%). The lowest inflation rate was recorded in Cyprus (0.2%). At the time of writing, November 2025 data are not available for 7 EU countries.

Situation in non-EU countries

In October 2025, the annual inflation rate was 3.9% in Iceland, 3.0% in both Norway and Japan, 0.2% in China and 0.1% in Switzerland. In September 2025, the inflation rate was 3.0% in the United States.

Total unemployment

Situation in the euro area and the EU

In October 2025, the seasonally adjusted unemployment rate was 6.4% in the euro area, the sixth consecutive month in which this rate was recorded. In the EU, the rate was 6.0%, also unchanged in 6 months.

Situation in the EU countries

In October 2025, the lowest unemployment rates were recorded in Malta (3.1%), Czechia and Poland (both 3.2%). The highest rates were in Spain (10.5%), Finland (10.3%), Sweden (9.3%) and Greece (8.6%).

Situation in non-EU countries

The unemployment rate in October 2025 was 4.5% in Norway, 4.0% in Iceland and 2.6% in Japan. In September 2025, the unemployment rate was 5.0% in Switzerland and 4.4% in the United States.

Youth unemployment

In November 2025, the youth unemployment rate (for people aged 15 to 24 years) was 14.8% in the euro area, unchanged from the previous month. In the EU, the rate was 15.2%, also unchanged from the previous month.

Economic sentiment indicator

Situation in the euro area and the EU

In November 2025, the economic sentiment indicator increased slightly, up 0.2 points in both the euro area and the EU: the index level was 97.0 points in the euro area and 96.8 points in the EU. The increase in the euro area resulted from increases in confidence among construction, retail trade and services managers outweighing a decrease among industrial managers; there was no change in consumer confidence.

Situation in the EU countries

In November 2025, the economic sentiment indicator showed a generally positive development among the EU countries, increasing in 18 and decreasing in 9. By far, the strongest increase was in Luxembourg (up 9.5 points), while the strongest decreases were in Czechia (down 3.4 points) and Ireland (down 2.4 points). Apart from these 3 countries, the changes ranged between 2.8 and -1.5 points. The index level of the economic sentiment indicator (with a long-term average = 100) varied from 88.6 points in Denmark to 111.8 points in Malta.

Employment expectations indicator

In November 2025, the employment expectations indicator increased (up 0.8 points compared with the previous month) to 97.8 in the euro area; expectations were up 1.1 points to 98.8 in the EU. The increase in the euro area in November 2025 was due to more optimistic employment plans among construction managers and less pessimistic plans among retail trade managers outweighing more pessimistic plans among industrial managers and less optimistic plans among services managers.

€-coin

The €-coin decreased marginally to 0.48 in November 2025, down from 0.49 in the previous month. The indicator continued to benefit from the good performance of the confidence indicators for the services sector, despite the still weak conditions in manufacturing (according to the latest release of the National Bank of Italy on 3December 2025).

Business climate indicator

The business climate indicator for the euro area decreased to -0.66 points in November 2025 (down from -0.47 points in the previous month).

Coincident indicators

The growth cycle coincident indicator (GCCI) was 0.97 in November 2025, the business cycle coincident indicator (BCCI) was 0.02 and the acceleration cycle coincident indicator (ACCI) was 0.09, indicating a recovery phase for the euro area.

The GCCI, BCCI and ACCI are synthetic indicators which are experimental in nature and calculated for Eurostat’s business cycle clock. The GCCI shows the probability of a slowdown in the economy and signals the peaks and troughs of the growth cycle, the BCCI shows the probability of a recession and signals the peaks and troughs of the business cycle and the ACCI shows the probability of a deceleration in the growth rate and signals the peaks and troughs of the growth rate cycle. The probability is given on a scale from 0 to 1.

Read more about the methodology in the Statistics Explained article about the business cycle clock.

DZ BANK’s Euro-Indikator

The DZ BANK’s Euro-Indikator decreased 0.10% month on month to 97.80 points in November 2025, following on from a similar increase (up 0.12%) in the previous month. When compared with the same month in the previous year, the Euro-Indikator was 1.20% higher in November 2025.

Trend-cycle estimates

This graph shows the quarterly GDP in current prices for the euro area, together with trend-cycle decompositions.

A trend-cycle decomposition method aims at further decomposing seasonally adjusted data into a trend component and a cyclical component (expressed as the deviation from the trend).

The trend provides information on longer-term movements in the seasonally adjusted series over several years; the cycle is a sequence of smoother fluctuations around the longer-term trend, in part characterised by alternating periods of expansion and contraction.

You can choose to show the estimates using three different filters.

• Hodrick-Prescott (HP): a filter widely used in macroeconomics to fit a smooth curve through a set of points.
• Christiano-Fitzgerald (CF): a well-known approximation to an ideal band pass filter, estimated non-parametrically.
• The Harvey and Trimbur decomposition, which is probably the most well-known model within the Unobserved Components (UC) framework.

Read more in the methodological note.

Trend-cycle estimates

This graph shows the monthly industrial production index for the euro area, together with trend-cycle decompositions.

A trend-cycle decomposition method aims at further decomposing seasonally adjusted data into a trend component and a cyclical component (expressed as the deviation from the trend).

The trend provides information on longer-term movements in the seasonally adjusted series over several years; the cycle is a sequence of smoother fluctuations around the longer-term trend, in part characterised by alternating periods of expansion and contraction.

You can choose to show the estimates using three different filters.

• Hodrick-Prescott (HP): a filter widely used in macroeconomics to fit a smooth curve through a set of points.
• Christiano-Fitzgerald (CF): a well-known approximation to an ideal band pass filter, estimated non-parametrically.
• The Harvey and Trimbur decomposition, which is probably the most well-known model within the Unobserved Components (UC) framework.

Read more in the methodological note.

Trend-cycle estimates

This graph shows the quarterly employment in thousand people for the euro area, together with trend-cycle decompositions.

A trend-cycle decomposition method aims at further decomposing seasonally adjusted data into a trend component and a cyclical component (expressed as the deviation from the trend).

The trend provides information on longer-term movements in the seasonally adjusted series over several years; the cycle is a sequence of smoother fluctuations around the longer-term trend, in part characterised by alternating periods of expansion and contraction.

You can choose to show the estimates using three different filters.

• Hodrick-Prescott (HP): a filter widely used in macroeconomics to fit a smooth curve through a set of points.
• Christiano-Fitzgerald (CF): a well-known approximation to an ideal band pass filter, estimated non-parametrically.
• The Harvey and Trimbur decomposition, which is probably the most well-known model within the Unobserved Components (UC) framework.

Read more in the methodological note.

Trend-cycle estimates

This graph shows the quarterly GDP in current prices for the EU, together with trend-cycle decompositions.

A trend-cycle decomposition method aims at further decomposing seasonally adjusted data into a trend component and a cyclical component (expressed as the deviation from the trend).

The trend provides information on longer-term movements in the seasonally adjusted series over several years; the cycle is a sequence of smoother fluctuations around the longer-term trend, in part characterised by alternating periods of expansion and contraction.

You can choose to show the estimates using three different filters.

• Hodrick-Prescott (HP): a filter widely used in macroeconomics to fit a smooth curve through a set of points.
• Christiano-Fitzgerald (CF): a well-known approximation to an ideal band pass filter, estimated non-parametrically.
• The Harvey and Trimbur decomposition, which is probably the most well-known model within the Unobserved Components (UC) framework.

Read more in the methodological note.

Trend-cycle estimates

This graph shows the monthly industrial production index for the EU, together with trend-cycle decompositions.

A trend-cycle decomposition method aims at further decomposing seasonally adjusted data into a trend component and a cyclical component (expressed as the deviation from the trend).

The trend provides information on longer-term movements in the seasonally adjusted series over several years; the cycle is a sequence of smoother fluctuations around the longer-term trend, in part characterised by alternating periods of expansion and contraction.

You can choose to show the estimates using three different filters:

• Hodrick-Prescott (HP): a filter widely used in macroeconomics to fit a smooth curve through a set of points.
• Christiano-Fitzgerald (CF): a well-known approximation to an ideal band pass filter, estimated non-parametrically.
• The Harvey and Trimbur decomposition, which is probably the most well-known model within the Unobserved Components (UC) framework.

Read more in the methodological note.

Trend-cycle estimates

This graph shows the quarterly employment in thousand people for the EU, together with trend-cycle decompositions.

A trend-cycle decomposition method aims at further decomposing seasonally adjusted data into a trend component and a cyclical component (expressed as the deviation from the trend).

The trend provides information on longer-term movements in the seasonally adjusted series over several years; the cycle is a sequence of smoother fluctuations around the longer-term trend, in part characterised by alternating periods of expansion and contraction.

You can choose to show the estimates using three different filters.

• Hodrick-Prescott (HP): a filter widely used in macroeconomics to fit a smooth curve through a set of points.
• Christiano-Fitzgerald (CF): a well-known approximation to an ideal band pass filter, estimated non-parametrically.
• The Harvey and Trimbur decomposition, which is probably the most well-known model within the Unobserved Components (UC) framework.

Read more in the methodological note.