Development of GDP

Situation in the euro area and the EU

In the 1st quarter of 2025, seasonally adjusted GDP increased, up 0.3% quarter on quarter in both the euro area and the EU. For comparison, an increase of 0.2% had been observed in the 4th quarter in the euro area and 0.4% in the EU.

Situation in the EU countries

Based on the latest quarter-on-quarter rates of change, GDP increased in the 1st quarter of 2025 in 16 countries, remained stable in 2 and decreased in 3 (1st quarter data aren’t available for 6 countries at the time of writing). Ireland (up 3.2%) recorded the largest increase of GDP. The decreases were observed in Slovenia (down 0.8%), Portugal (down 0.5%) and Hungary (down 0.2%).

Situation in non-EU countries

Compared with the previous quarter, GDP expanded in the 1st quarter of 2025 in China (up 1.2%) and contracted slightly in the United States (down 0.1%) and Japan (down 0.2%). In the 4th quarter of 2024, GDP expanded 0.2% in Switzerland, while it contracted in Norway (down 0.6%) and Iceland (down 1.4%). (*) See latest estimates for more data.

Industrial production

In March 2025, seasonally adjusted industrial production increased month on month by 2.6% in the euro area and by 1.9% in the EU. In the previous month, there had been increases of 1.1% in both the euro area and the EU.

Production in construction

In February 2025, seasonally adjusted production in construction decreased 0.5% in the euro area and 0.4% in the EU compared with the previous month. In the previous month, it had increased 0.6% in the euro area and 0.2% in the EU.

Retail trade

In March 2025, the seasonally adjusted volume of sales in retail trade decreased marginally compared with the previous month in both the euro area and the EU (down 0.1%), following on from an increase of 0.2% in the previous month in the euro area and no change in the EU.

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 both March and April 2025. In the EU, annual inflation was 2.4% in April 2025, down 0.1 points compared with the previous month.

Situation in the EU countries

The highest annual inflation rates (based on the HICP) in April 2025 were recorded in Romania (4.9%) and Estonia (4.4%). The lowest inflation rate was recorded in France (0.9%).

Situation in non-EU countries

In April 2025, the annual inflation rate was 3.9% in Iceland, 2.3% in the United States, 2.1% in Norway, 0.3% in Switzerland and -0.1% in China. In March 2025, the rate was 3.6% in Japan.

Total unemployment

Situation in the euro area and the EU

In March 2025, the seasonally adjusted unemployment rate was 6.2% in the euro area, unchanged from the previous month. In the EU, the rate was 5.8%, also unchanged from the previous month.

Situation in the EU countries

In March 2025, the lowest unemployment rates were recorded in Czechia (2.6%), Poland (2.7%) and Malta (2.8%). The highest rates were in Spain (10.9%), Finland (9.5%), Greece (9.0%), Estonia (8.7%) and Sweden (8.1%).

Situation in non-EU countries

The unemployment rate in March 2025 was 4.4% in Norway, 4.2% in the United States and 2.5% in Japan. In January 2025, the unemployment rate was 3.6% in Iceland, while in December 2024 it was 4.5% in Switzerland.

Youth unemployment

In March 2025, the youth unemployment rate (for people aged 15 to 24 years) was 14.2% in the euro area, down from 14.3% in the previous month. In the EU, the rate was 14.5%, down from 14.6% in the previous month.

Economic sentiment indicator

Situation in the euro area and the EU

In April 2025, the economic sentiment indicator decreased, down 1.4 points in both the euro area and the EU: the index level was 93.6 points in the euro area and 94.4 points in the EU. The decrease in the euro area resulted from decreases in confidence among consumers as well as managers from all sectors: industrial, construction, retail and services.

Situation in the EU countries

In April 2025, the economic sentiment indicator showed a generally downward development among the EU countries, increasing in 7, unchanged in 1 and decreasing in 19. By far, the strongest increase was in Luxembourg (up 4.1 points), while the strongest decreases were in Ireland (down 7.8 points), Czechia (down 4.8 points), Denmark (down 4.2 points) and Belgium (down 3.7 points). The index level of the economic sentiment indicator (with a long-term average = 100) varied from 87.7 points in Belgium to 108.0 points in Malta.

Employment expectations indicator

In April 2025, the employment expectations indicator was unchanged compared with the previous month at 96.5 in the euro area; expectations decreased (down 0.7 points) to 96.9 in the EU. The stability in the euro area in April 2025 was due to less pessimistic employment plans among industrial managers combined with more optimistic plans among services managers balancing less optimistic plans among construction managers combined with more pessimistic plans among retail managers.

€-coin

The €-coin was unchanged in April 2025 (according to the latest release of the National Bank of Italy on 5 May 2025). The indicator benefited from the increase in industrial production but was affected by the deterioration in business and consumer confidence.

Business climate indicator

The business climate indicator for the euro area rose to -0.67 points in April 2025 (up from -0.72 points in the previous month).

Coincident indicators

The growth cycle coincident indicator (GCCI) was 0.97 in April 2025, indicating a slowdown phase for the euro area economy. In the same month, the business cycle coincident indicator (BCCI) was 0.02, confirming the absence of any recessionary signals.

The GCCI and BCCI 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, while the BCCI shows the probability of a recession and signals the peaks and troughs of the business 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 0.24% month on month to 97.27 points in April 2025. This followed a similar increase (up 0.25%) in the previous month. When compared with the same month in the previous year, the Euro-Indikator was 1.50% higher in April 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.
• Unobserved Components (UC): a parametric approach which involves estimating a statistical model and decomposing the series into components, including the trend and cycle.

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.
• Unobserved Components (UC): a parametric approach which involves estimating a statistical model and decomposing the series into components, including the trend and cycle.

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.
• Unobserved Components (UC): a parametric approach which involves estimating a statistical model and decomposing the series into components, including the trend and cycle.

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.
• Unobserved Components (UC): a parametric approach which involves estimating a statistical model and decomposing the series into components, including the trend and cycle.

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.
• Unobserved Components (UC): a parametric approach which involves estimating a statistical model and decomposing the series into components, including the trend and cycle.

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.
• Unobserved Components (UC): a parametric approach which involves estimating a statistical model and decomposing the series into components, including the trend and cycle.

Read more in the methodological note.