Persons who cannot afford to replace worn-out clothes by some new in Euro area – 20 countries (2023-2025)
Euro area – 20 countries (2023-2025): Persons who cannot afford to replace worn-out clothes by some new was 6.9% in 2025. ▼ Falling
Latest (2025)
6.9%
Change on year
down 1.4%
Rank
6th
of 6 regions
All-time high
9.4%
in 2014
All-time low
6.7%
in 2019
Years of data
12
2014–2025
Persons who cannot afford to replace worn-out clothes by some new in Euro area – 20 countries (2023-2025), 2014–2025
Source: Eurostat. Measured in Percentage.
Analysis
The most recent figure for persons who cannot afford to replace worn-out clothes by some new in Euro area – 20 countries (2023-2025) is 6.9%, measured in 2025.
The figure is down 1.4% on the previous year and down 18.8% over ten years.
Over the whole period, persons who cannot afford to replace worn-out clothes by some new in Euro area – 20 countries (2023-2025) peaked at 9.4% in 2014 and was at its lowest, 6.7%, in 2019.
The long-run direction has been consistently falling across the 12 years of available data.
Persons who cannot afford to replace worn-out clothes by some new in Euro area – 20 countries (2023-2025), year by year
| Year | Percentage | Change |
|---|---|---|
| 2014 | 9.4% | — |
| 2015 | 8.5% | -9.6% |
| 2016 | 7.6% | -10.6% |
| 2017 | 6.9% | -9.2% |
| 2018 | 6.9% | +0.0% |
| 2019 | 6.7% | -2.9% |
| 2020 | 7.3% | +9.0% |
| 2021 | 7.1% | -2.7% |
| 2022 | 7.2% | +1.4% |
| 2023 | 7.3% | +1.4% |
| 2024 | 7.0% | -4.1% |
| 2025 | 6.9% | -1.4% |
Averages by decade
| Decade | Average | Lowest | Highest | Years |
|---|---|---|---|---|
| 2010s | 7.7% | 6.7% | 9.4% | 6 |
| 2020s | 7.1% | 6.9% | 7.3% | 6 |
Countries ranked near Euro area – 20 countries (2023-2025)
More work & labour data for Euro area – 20 countries (2023-2025)
- Employment expectations indicators - monthly data 96.8 Index (2025)
- Population and employment - national accounts - quarterly data 352,767 Thousand persons (2026)
- Employment by main industry (NACE Rev.2) - national accounts 67.24 million Thousand hours worked (2026)
- Labour productivity and unit labour costs - quarterly data 104.36 Index, 2020=100 (2026)
- Population and employment - national accounts - annual data 352,258 Thousand persons (2025)
- Labour productivity and unit labour costs by industry 15.3 Euro (2025)
- Labour productivity and unit labour costs - annual data 51,903 Euro (2025)
- Employment by main industry (NACE Rev.2) - national accounts - annual 267.01 million Thousand hours worked (2025)
- Employment by detailed industry (NACE Rev.2) - national accounts 265.89 million Thousand hours worked (2024)
- Labour input in construction - quarterly data 107.7 Index, 2021=100 (2026)
Frequently asked questions
- What is persons who cannot afford to replace worn-out clothes by some new in Euro area – 20 countries (2023-2025)?
- Persons who cannot afford to replace worn-out clothes by some new in Euro area – 20 countries (2023-2025) was 6.9% in 2025, according to Eurostat.
- What is the highest persons who cannot afford to replace worn-out clothes by some new recorded in Euro area – 20 countries (2023-2025)?
- The highest recorded value was 9.4% in 2014.
- What is the lowest persons who cannot afford to replace worn-out clothes by some new recorded in Euro area – 20 countries (2023-2025)?
- The lowest recorded value was 6.7% in 2019.
- How does Euro area – 20 countries (2023-2025) rank for persons who cannot afford to replace worn-out clothes by some new?
- Euro area – 20 countries (2023-2025) ranks 6th out of 6 regions with data for 2025.
- Is persons who cannot afford to replace worn-out clothes by some new rising or falling in Euro area – 20 countries (2023-2025)?
- Over the last ten years it is down 18.8%. The long-run trend across the full record is falling.
- Where does this Euro area – 20 countries (2023-2025) data come from?
- The figures come from Eurostat, published as part of Persons who cannot afford to replace worn-out clothes by some new (not second-hand) ones by employment status and income quintile. Statizoid updates them automatically from the source API.
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