Development of GDP

Situation in the euro area and the EU

In the 1st quarter of 2024, seasonally adjusted GDP increased by 0.3% quarter-on-quarter in both the euro area and the EU. For comparison, in the 4th quarter of 2023, GDP had been stable in both the euro area and the EU.

Situation in the EU countries

Based on the latest quarter-on-quarter rates of change, GDP increased in the 1st quarter of 2024 in 23 countries, remained stable in 1 and decreased in 3. Malta (up 1.3%) and Cyprus (up 1.2%) recorded the largest increases of GDP. The largest decrease was observed in Denmark (down 1.4%).

Situation in non-EU countries

Compared with the previous quarter, GDP expanded in the 1st quarter of 2024 in China (up 1.6%), Switzerland (up 0.5%), the United States (up 0.3%) and Norway (up 0.2%), while it contracted in Japan by 0.5% and in Iceland by 0.9%.

(*) See latest estimates for more data.

Industrial production

In May 2024, seasonally adjusted industrial production decreased month-on-month by 0.6% in the euro area and by 0.8% in the EU. In the previous month, it had been stable in the euro area and increased by 0.5% in the EU.

Production in construction

In May 2024, seasonally adjusted production in construction decreased month-on-month by 0.9% in the euro area and by 1.0% in the EU. In the previous month, it had decreased by 0.4% in the euro area and been unchanged in the EU.

Retail trade

In May 2024, the seasonally adjusted volume of sales in retail trade increased month-on-month by 0.1% in both the euro area and the EU, following on from decreases of 0.2% in the previous month in both the euro area and 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 2.5% in June 2024, down from 2.6% in the previous month. In the EU, annual inflation was 2.6% in June 2024, which was also a decrease from the rate in the previous month (2.7%).

Situation in the EU countries

The highest estimated annual inflation rates (based on the HICP) in June 2024 were recorded in Belgium (up 5.4%) and Romania (up 5.3%). The lowest inflation rates were recorded in Finland (up 0.5%), Italy (up 0.9%) and Lithuania (up 1.0%).

Situation in non-EU countries

In June 2024, Iceland recorded the highest annual inflation rate (up 5.0%), followed by Norway (up 2.3%), the United States (up 1.8%), Switzerland (up 1.3%) and China (up 0.2%). The annual inflation rate was 2.8% in Japan in May 2024.

Total unemployment

Situation in the euro area and the EU

In May 2024, the seasonally adjusted unemployment rate was 6.4% in the euro area, unchanged from the previous month. In the EU, the rate remained at 6.0% as in the previous two months; the rate in the EU has been 6.0% or 6.1% since June 2022.

Situation in the EU countries

In May 2024, the lowest unemployment rates were recorded in Czechia (2.7%), Poland (3.0%), Malta, Slovenia (both 3.2%) and Germany (3.3%). The highest rates were in Spain (11.7%) and Greece (10.6%).

Situation in non-EU countries

Among the non-EU countries, the unemployment rate in May 2024 increased in the United States (to 4.0%), while it was stable in Japan (at 2.6%) and decreased in Norway (to 4.1%). The unemployment rate was 4.1% in Switzerland in March 2024 and 3.5% in Iceland in February 2024.

Youth unemployment

In May 2024, the youth unemployment rate (for people aged 15–24 years) was 14.2% in the euro area, unchanged from the previous month. In the EU, the rate was 14.4%, down from 14.5% in the previous month.

Economic sentiment indicator

Situation in the euro area and the EU

In June 2024, the economic sentiment indicator decreased by 0.2 points to 95.9 points in the euro area and by 0.2 points to 96.4 points in the EU. The decrease in the euro area resulted from decreases in confidence among retail, construction, services and industrial managers outweighing an increase in confidence among consumers.

Situation in the EU countries

In June 2024, the economic sentiment indicator showed a mixed development among the EU countries, increasing in 14, unchanged in 2 and decreasing in 10 (Ireland, no data available). The strongest increase was in Slovakia (up 8.0 points), while the strongest decrease was in Austria (down 4.6 points). The index level of the economic sentiment indicator (with a long-term average = 100) varied from 83.6 in Estonia to 110.6 in Greece.

Employment expectations indicator

The employment expectations indicator decreased in the euro area in June 2024, down 1.6 points. This was due to more pessimistic employment plans among retail trade managers as well as less optimistic plans among construction and services managers outweighing less pessimistic plans among industrial managers. In the EU, the situation was similar: more pessimistic employment plans among retail trade and construction managers and less optimistic plans among services managers outweighed less pessimistic plans in industry such that the overall index decreased by 0.8 points. In June 2024, the index level (with a long-term average = 100) of the indicator was 99.7 in the euro area and 100.4 in the EU.

€-coin

The €-coin decreased marginally to 0.16 in June 2024 from 0.18 in May 2024 (according to the latest release of the National Bank of Italy on 28 June 2024). The indicator continued to be affected by the weakness of industry, which was offset by an improvement in the confidence of households and services enterprises.

Business climate indicator

The business climate indicator for the euro area decreased from -0.40 points in May 2024 to -0.46 points in June 2024.

Coincident indicators

The growth cycle coincident indicator (GCCI) was 0.97 in June 2024, indicating a slowdown phase for the euro area economy. In the same month, the business cycle coincident indicator (BCCI) was 0.03, 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 0.23% month-on-month in June 2024, to 96.00 points. This followed an increase of 0.50% in May 2024. The Euro-Indikator was 0.72% higher in June 2024 than in June 2023.

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.