Wages and labour costs developments in the EU and its Member States

Developments in wage adequacy

Wage adequacy has received growing attention among policy makers in recent years as one aspect of job quality and working conditions. The outlook for real wage growth remains restrained and aggregate developments can hide important differences across workers, for instance based on their sector of activity, occupation or skill level (Section 2.2). Besides, inadequate wages are mentioned as a reason for persisting labour shortages in some sectors . Against this backdrop, promoting adequate wages, a key component of job quality, remains high on the political agenda.

The concept of adequate wages is multi-dimensional. Wage adequacy typically refers to at least two dimensions: one being how wages compare to other wages, and the other being whether wages provide enough purchasing power . As there is no commonly agreed measure to assess either dimension, the section goes through a range of indicators that shed light on various aspects of wage adequacy.

The relative situation of low wage earners has improved since the pandemic

In-work poverty has continued its decreasing trend, highlighting the improving income situation of workers living in low-income households, relative to other workers. In-work poverty represents the share of persons at work who have an equivalised disposable income below 60% of the national median. It reached 8.2% in 2024 from a peak of 9.8% in 2016 and 8.9% in 2021 (Graph 2.7, panel a). Between 2016 and 2024, in-work poverty decreased in around half of the Member States, and notably by more than 1 percentage point in Germany, Greece, Hungary, Italy, Poland, Portugal, Romania and Spain. However, it increased by more than 1 percentage point in Croatia, Luxembourg, Malta, and Slovakia. Overall, beyond the impact of support measures adopted during the pandemic and the energy crisis, these improvements may also reflect a more sustained wage growth among lower-income working households compared to others. At the same time, in-work poverty is also affected by other factors, such as other sources of household income (including the income of other household members and social benefits), the household’s composition (e.g. the number of dependent children), and work intensity of the household .

Also the share of low-wage earners has decreased in the EU. The share of low-wage earners, reflecting the proportion of employees earning two-thirds or less of the median gross hourly earnings in a country, decreased in the EU, from 15.2% in 2018 to 14.7% in 2022 . This indicates that, on average, low hourly wages tended to increase more than other wages, or people moving out of low- paid jobs, and thus to get closer to the median (Graph 2.7, panel b). The situation, however, varies greatly across Member States. The share decreased by more than 2 percentage points in Lithuania, Poland, Portugal, Slovakia and Slovenia. In contrast, it increased by more than 2 percentage points in Belgium, Bulgaria, Greece, Luxembourg, Hungary and Romania, indicating in those countries a compression of the hourly wage distribution at the bottom. However, this may not fully reflect the wages ultimately perceived by workers - due to differences in hours worked during a month.

These developments may somewhat contrast with a widespread perception of an unfair distribution of income. In the Special Eurobarometer survey on Fairness, inequality, and intergenerational mobility held in 2022 , across the EU, 57% of respondents indicated that large differences in people’s incomes are acceptable to properly reward differences in talents and efforts. At the same time, 37% of respondents tended to believe that, by and large, people do not get what they deserve (versus only 35% that believe the opposite). The perception of unfairness was marked in Cyprus (65% of respondents), Greece (60%) or Slovenia (55%), and less in Luxembourg (18%), Denmark (25%) or Finland (26%). Furthermore, based on the 2024 European Working Conditions Survey conducted by Eurofound, 14% of responding men and more than 18% of responding women disagree that they get appropriately paid when considering all their efforts and achievements in their jobs. The share of workers who consider their pay as inappropriate is above 16% in agriculture, education, heath, as well as in commerce and hospitality.

Graph 2.7: Share of in-work poverty and low wage earners

Note:

Countries are sorted according to their GDP per capita in PPP 2023.

Source:

Eurostat [ilc_iwp01 and earn_ses_pub].

Looking more in-depth at the distribution of wages and their ability to prevent material deprivation can provide further insights about wage adequacy. A declining rate of in-work poverty or a decreasing share of low-wage earners is not sufficient to conclude that wages are adequate. It is also key to examine the wage distribution to allow for a better comparison of wages across and within groups of workers. Moreover, the degree of material deprivation of workers can help to better understand to what extent wages provide for a decent living . Boxes 2.1 and 2.2 present those indicators, as well as their pros and cons when it comes to assessing wage adequacy.

Wages have played an important role in improving the situation of vulnerable workers

Minimum wages have increased more than the average in most Member States, improving the relative situation of minimum wage earners. Between 2019 and 2024, most Member States where a statutory minimum wage exists showed large increases in the Kaitz indexes, that represent the ratio of the gross minimum wage to the mean or average earnings (Graph 2.8, panel a). Among the 18 Member States for which data is available (for 2024, or for 2023), the ratio of the minimum wage to the average earnings increased in 15 Member States. This reflects sizeable updates aimed at mitigating the effects of the high inflation on the lowest paid (see also Section 2.2). The ratio remained stable in four countries, (Belgium, Hungary, Ireland and Luxembourg) and dropped only in three (Bulgaria, Lithuania and Malta).

Graph 2.8: Kaitz index and wage ratio W20/W50 (for single-person households, working full-time)

Note:

In panel a: The Kaitz index can only be for Member States with statutory minimum wage. In panel b: Member States are sorted according to their GDP per capita in PPP 2023. The wage ratios is calculated for single-person households working full-time.

Source:

Eurostat [earn_avgr2] and own calculations based on EU SILC microdata.

In half of Member States, wage decile ratios also point to declining disparities at the bottom of the wage distribution. The gap between lower and median wages can be assessed using ratios of percentiles to the median of the gross wage distribution computed for full-time single workers . For instance, the ratio of the 2nd decile to the median wage increased in 13 countries (Austria, Cyprus, Denmark, Estonia, Finland, Hungary, Greece, Lithuania, Malta, Portugal, Slovakia, Slovenia and Spain), indicating narrowing disparities. The ratio remained stable in five other countries (Belgium, Germany, Luxembourg, the Netherlands and Latvia). However, it decreased in nine Member States (Bulgaria, Croatia, Czechia, France, Ireland, Italy, Poland, Romania and Sweden) (Graph 2.8, panel b). Among the latter countries, Bulgaria, Croatia, Poland and Romania displayed strong real wage increases: lower-wage earners also benefitted from some increases in real terms, although disparities increased. In contrast, Czechia, France, Italy, Sweden showed expanding disparities between lower- wage earners and the median, while real wages remained below 2019 levels (see also section 2.2). This points to relatively weak average wage growth for lower-middle-wage earners in these countries.

Minimum wage increases have a significant impact on the wages of low-paid workers earning beyond minimum wage. A 1% increase in minimum wages results on average in a 0.3% increase in the wages of low-paid employees, but only large minimum wage increases (at least 15% in nominal terms) have a significant impact . Minimum wage updates can also benefit workers with higher wages, but with a time lag compared to spillover effects on low wages, as collective agreements take some time to translate national minimum wage increases to the whole wage distribution. As a result, increases in minimum wages appear to initially compress the wage distribution, but the extent to which compression persists depends notably on sectors and collective bargaining characteristics . In addition, spill-overs on other low-to-medium wages may have been less marked after 2022 due to high inflation. Firms faced increasing cost pressures (notably in energy- intensive industries) and were less able to increase wages as they would have done before, considering increases in minimum wages.

Wage disparities based on skill levels and occupations vary widely across Member States. Some countries, including Estonia, Ireland, Latvia, or Portugal, exhibit a highly polarised wage structure, hinting at a high wage premia for skills and large differences in wages across occupations . In contrast, a more compressed distribution is observed in Czechia, Denmark, Slovakia or Sweden, with overall lower wage premia for skills. Over time, the wage differentials along skills, thus the skill premia, increased in 10 countries, in particular in Finland, Ireland and Malta. This is consistent with the evidence pointing to the increased labour demand for digital or cognitive skills and an associated wage premium for those workers. This may also hint at specific skill gaps, e.g. linked to the twin transition, or the high labour shortages following the pandemic . Seven countries experienced a decrease in wage polarisation, especially Poland, Romania and Slovakia, despite tight labour markets.

Women and third country nationals are more likely to remain in low-paid jobs. In 2023, women's gross hourly earnings remained on average 12.0% below those of men in the EU . The gender pay gap has decreased compared to 2019, for the EU (from 14.1%), as well as in 21 EU countries. However, the gap tends to increase with age (as a result of the career interruptions women may experience during their working life), and is on average higher in the private sector than in the public sector. Furthermore, in 2023, the persistence in low-paid jobs for at least 4 years ranged from less than 2% in Finland, Denmark and Sweden and more than 10% in Latvia, Estonia, Hungary, Malta, Cyprus, Portugal, Lithuania, Ireland, Bulgaria . In a majority of countries, women are more likely to experience low pay for multiple years compared to men, with wider gender differences in Cyprus, Czechia, Estonia, Latvia, Lithuania and Malta. The persistence of low-paid jobs is significantly higher among migrants than native employees, except notably in Sweden.

Box 2.1: The relative situation of lower and middle wage earners along the wage distribution.

The Kaitz indexes provide insights about the fairness of the statutory minimum wages (where they exist). They are calculated by dividing the gross statutory minimum wage by the median or the average wage for full-time employees. The Kaitz index is published by Eurostat based on country declarations, but there are sizeable delays for the indicator referring to the median. Other data sources (e.g. the OECD) can provide more up-to-date information, but with notable differences in concepts and estimates compared to Eurostat. Furthermore, the Kaitz index cannot be calculated for Member States without a statutory minimum wage. Finally, the indicator does not provide information on the share of workers earning minimum or close-to-minimum wages.

Other ratios can compare wages at different points of the earnings distribution. Common decile ratios used in the literature include the ratio of the 90th to the 10th or of the 80th to the 20th percentiles of the wage distribution. Other common ratios are expressed in relation to the median wage. At the EU level, such ratios can be estimated using the EU Structure of Earnings Survey (SES) or the yearly EU-SILC micro data. In this section, ratios of the 10th, 20th and 30th percentiles to the median are considered to reflect the relative wage of low or lower-middle wage earners. Those percentiles, including the median, are determined using the variable ‘Employee cash or near cash income’, from the User Database of EU-SILC, see also Box 2.2.

Some indicators exist but are not presented in the chapter because they are difficult to interpret or present a perspective that is outside the scope of this chapter.

The Gini coefficient is commonly used to summarise the extent of income inequalities, but is sensitive to changes in the middle of the distribution . A higher (lower) Gini coefficient indicates a more (less) unequal distribution. Nonetheless, it is very sensitive to changes in the middle of the wage distribution and less so to changes at the extremes, which is where wage inequality is often more marked (Hey and Lambert, 1980). In addition, the Gini coefficient can produce similar estimates in the presence of different distribution patterns (Atkinson, 2009).

The mean log deviation, the Theil index and the coefficient of variation are other possible metrics, although difficult to interpret. The mean log deviation and the Theil index are used by some international organisations (see for instance World Bank, 2024; International Labour Organisation, 2024a). They belong to entropy measures that are also used in physics to measure randomness. They have the key advantage of being easily decomposable into a between and within groups component, e.g. groups of countries or of workers (Shorrocks, 1980). At the same time, both indicators (that can only take positive values, with zero representing an equal distribution) do not have an upper bound. Therefore, they can also be difficult to interpret. Similarly, the coefficient of variation, defined as the ratio of the standard deviation of a distribution to the mean, has also been used to gauge the extent to which wages deviate from the average wage, and can be decomposed into between- and within-country components (see for instance, European Commission: Directorate-General for Employment, Social Affairs and Inclusion, 2023a; Zwysen, 2024). It also faces similar caveats.

Additionally, wage ratios focusing on the extreme segments of the distribution focus on a very low proportion of workers and often are affected by highest wage earners. This is for instance the case for the income of the top 1% of the wage distribution. The Palma ratio is also a common indicator computed by dividing the total wages accumulated by the top 10% by the total wages accumulated by the bottom 40% of the wage distribution (International Labour Organisation, 2017). It however reflects in part the situation of some workers at the top of the wage distribution.

Yet, middle class workers have become more exposed to material deprivation in some countries

An in-depth analysis of worker’s material deprivation provides valuable insights whether wages are sufficient to afford basic goods and services. One can argue that the more adequate wages are, the less workers are materially deprived. Although it is not universally agreed what this implies in terms of ultimate purchasing power, this concept of material deprivation, developed by Eurostat, provides a commonly agreed framework at the EU level . The concept lists goods and services generally required for a household to lead a decent life and integrate meaningfully into society. As such it is relevant to analyse the extent to which individuals (or households) can afford these 13 pre-defined ‘basic’ items . There are a number of caveats though. In particular, the level of deprivation can be affected not only by wage rates but also by work intensity, other sources of incomes and household composition, as well as other factors such as the relative prices of these basic items (e.g. energy) and in which quantity they are needed (see also Box 2.2) .

Developments in the average number of items deprived among workers are assessed, accounting for household composition or work intensity. The situation of two groups of workers is considered: single, full-time workers without children and all workers. This allows, respectively, to look at wage adequacy for a single worker, excluding the effects of second wage earners in the household or other dependent household members (including family benefits), and also the actual average situation of workers. In essence the results are similar for both types of workers . The analysis also provides further insights into the role played by hours worked and gross wages vis-à- vis other sources of income. The section then focuses on the three lower monthly gross wage quintiles in each Member State, as deprivation is expected to generally affect lower-wage workers.

Overall, workers’ material deprivation of basic items depends on GDP per capita, but the distribution of incomes also matters. At EU level in 2023, workers reported on average to be deprived of 1.3 basic items (1.4 for single, full-time workers). Less than 10% of workers lacked 5 or more basic items, i.e. faced social and material deprivation, according to Eurostat’s definition. In countries with a lower GDP per capita, such as Bulgaria, Greece and Romania, workers report on average to be deprived of 2 or more items and the share of socially and materially deprived workers lies above 15%. This underlines the key role of GDP per capita, and ultimately national productivity in determining the standards of living of a country’s workers. At the same time, in some countries with medium GDP per capita, notably Czechia, Estonia and Slovenia, workers have similar or fewer deprivation items (ranging from an average of 0.8 items for single, full-time workers in Slovenia to 1.1 items in Estonia) than countries with a higher GDP per capita such as Denmark and Germany (resp. 1.2 and 1.5 items reported on average). This suggests that the income distribution can also play a significant role in reducing material deprivation, either via wages - notably by ensuring that more workers benefit from economic growth - or via redistribution by the tax-benefit system.

Graph 2.9: Average number of deprivation items for wage earners (single-person households working full-time)

Note:

Analysis takes only those individuals into account who report to be receiving income from work in EU SILC data. For this graph the sample includes only single-person households working full-time. Member States are ranked according to their GDP per capita in PPS 2023.

Source:

Own calculcations based on EU SILC microdata and Eurostat [prc_ppp_ind].

Since 2019 lower-middle and middle wage earners have increasingly struggled to afford basic goods or services, in particular in higher income countries. Between 2019 and 2023 the average number of material deprivation items reported by workers tended to decrease in catching-up countries, consistent with a strong real wage growth. However, it increased in many higher income Member States (Graph 2.9 and Graph A.2.1.2 in the annex) . The worsening in some Member States reflects increases in energy and food prices which led to a growing share of workers being deprived of proper heating or quality food, and a slow recovery in real wages (see Section 2.2). The increase in deprivation was marked for the lower-middle wage earners and the middle wage earners, represented respectively by the 2nd and 3rd wage quintiles, but less for the lowest wage earners (Graph A.2.1.3 in Annex 2.1) . Thus, lower-middle wage groups, that benefitted less from support measures and minimum wage increases than the lowest wage earners, have become more vulnerable . From 2024, the persistence of inflation in some services, which replaced food and energy as drivers of inflation, may also affect workers in those lower-middle wage groups.

Less hours worked is one reason for the increase in deprivation for some workers. Between 2019 and 2023, the number of hours worked declined in most countries. This concerns the hours worked for full-time employees in almost all countries (except in Cyprus and Poland where it slightly increased and in Denmark, Lithuania where it stayed stable), as well as for part-time workers in most higher income Member States. This decline in hours worked, coupled with the strong decreases in real hourly wages experienced over 2022-2023, is likely to have contributed to the increase in workers’ material deprivation. Conversely, in lower income Member States, real hourly wages and working hours of part-time workers tended to increase, except in Romania, which may have helped to reduce the material deprivation of workers.

Box 2.2: Measures linked to the affordability of basic goods and services

There is no commonly agreed measure defining whether ages allow for a sufficient purchasing power. Across countries, wages can be compared in terms of their purchasing power, by using purchasing power standards (PPS) to reflect differences in prices. But defining a threshold below which a wage is inadequate for a worker also depends on the consumer basket that he or she can afford. Only a few EU countries (e.g. Ireland or Romania) have assessed poverty lines based on a consumer basket. Across countries, recent initiatives have aimed to agree on common concepts for a lower threshold capturing the decency of wages . The EU project on reference budgets underlined the challenges to develop an EU-wide measure, both in terms of agreeing on a minimum consumer basket and of collecting the relevant data.

The section analyses to what extent workers regard their wage as sufficient to afford basic goods and services. This avoids assuming a common minimum consumer basket to estimate a threshold for wage adequacy. Material deprivation, a concept that is commonly agreed among Member States, refers to individuals' inability to afford items necessary or desirable for an adequate life – but without setting a priori how many of each basic item are needed (Townsend, 1979). Eurostat’s material deprivation indicator is based on 13 questions asking for pre-defined basic items, integrated into the EU-SILC (European Union Statistics on Income and Living Conditions) survey. The indicator, which is reported yearly by Eurostat, indicates the share of persons that cannot afford at least 5 items out of the 13 basic items . However, the data show that people across all income levels and countries may be deprived of some basic items.

The analysis looks at the degree of deprivation of individual basic items, as measured by the average number of deprived items, and looks into the role played by wages. For a given category of workers, the fewer items they are deprived of, the more adequate wages are considered to be. However, material deprivation does not only depend on the individuals’ wages, but also on other factors such as other sources of income (including a second income in the household, or social benefits), or the number of dependent persons in the household. It also depends on work intensity. Therefore, the degrees of deprivation are considered, both for single, full-time workers without children and for all workers. This provides insights about wage adequacy for one person alone, and also considering the actual average situation of all workers. Wages are also expressed in gross terms, instead of net terms. Indicators using net wages would allow to consider the effects of the tax-benefit system, but are more complex, since taxes and benefits are affected by household composition. In addition, ratios expressed in net terms provide a less clear signal on whether the wages paid by employers are adequate (before redistribution by the tax-benefit system). Furthermore, the analysis focuses on the three lowest quintiles of the wage distribution as they capture, respectively, the lower, lower-middle and middle wage earners.

Some caveats apply when using material deprivation to assess wage adequacy. First, as for any survey data, answers are subject to respondents’ interpretation. For instance, a worker declaring not being able to afford heating may be constrained, but not completely deprived of heating. Second, it may also depend on the specific individual needs of the worker (e.g. transports or heating needs depend on the region where the individual lives and works). Third, wages are approximated by the variable cash income from employment from the User Database in EU-SILC . Besides wages and salary, this variable also includes social contributions and income taxes, ‘remuneration for time not worked’, ‘enhanced rates of pay for overtime’ and other components. While this is the closest approximation of gross wages which can be retrieved across Member States using the yearly EU-SILC data, not all types of bonuses are covered. This may slightly affect the definition of wage quintiles used to assess differences across the wage distribution.

Notes

  1. European Commission: Directorate-General for Employment, Social Affairs and Inclusion (2024).
  2. Principle 6 of the European Pillar of Social Rights notably underlines that workers have the right to fair wages that provide for a decent standard of living. See also Impact assessment (SWD(2020) 245 2020 and SWD(2020)) which explains that fairness of the wage in relation to the wage of other workers in the same country (relative) and the sufficiency of the wage in relation to a decent standard of living (absolute) are important.
  3. In-work at-risk-of-poverty rate refers to the percentage of persons in the total population who declared to be at work (employed or self-employed) who are at-risk-of-poverty (i.e. with an equivalised disposable income below the risk-of-poverty threshold, which is set at 60 % of the national median equivalised disposable income (after social transfers)). The equivalised disposable income is the total income of a household, after tax and other deductions, that is available for spending or saving, divided by the number of household members converted into equalised adults; household members are equalised or made equivalent by weighting each according to their age, using the so-called modified OECD equivalence scale.
  4. Based on the structure of earnings survey.
  5. European Commission (2022).
  6. Some authors have also suggested to consider broader aspects of wage-setting when studying wage adequacy, such as the transparency and predictability of wages (including delays in payment), compliance with regulation, social dialogue, or working time (Balestra et al.. 2023; Bronkhorst, 2020; Neugebauer et al., 2017).
  7. Similar to the previous sub-section, in this analysis, low wages are defined as gross wages within the first two deciles of the wage distribution, lower-middle wages as those in the 3rd and 4th deciles, and middle wages as those in the 5th and 6th deciles. Different ratios of percentiles to the median of the gross wage distribution are computed (including W20/W50 and W10/W50), for full-time single workers.
  8. See in particular Eurofound (2025b).
  9. In particular, labour shortages tend to amplify spill-over effects of increases in minimum wages on other wages, while higher initial minimum wage levels would decrease those effects. Other factors, include the existence of bargaining actors on both sides of industry, the union density in the sector, or the percentage of workplaces with worker representation structures.
  10. Stazi (2025).
  11. Jona-Lasinio and Venturini (2024); Kölling (2022); Josten et al. (2024).
  12. The highest gender pay gap was recorded in Latvia (19.0%) and the lowest in Luxembourg (-0.9%), see Eurostat (online data code: sdg_05_20). The gender pay gap comes on top of an overall lower participation in the labour market and fewer hours worked per month for women compared to men.
  13. While numerous factors influence the extent of persistency in low paid jobs, including technological change, labour market conditions, labour policies and institutional factors, the degree of persistence in low-paid jobs mirrors, as expected, the prevalence of low-paid jobs (Dreger et al., 2015; Schnabel, 2021; Stazi, 2025).
  14. It considers the area between the Lorenz curve of an income distribution and a hypothetical line of absolute equality.
  15. Eurostat’s concept of material deprivation is consistent with Townsend (1979).
  16. They consist of seven items linked to the functioning of a household (including, for instance, the ability to keep the home adequately warm), and six personal items (including, for example, replacing worn-out cloths). For more details see Box 2.2. below.
  17. If the individual cannot afford at least 5 out of these 13 basic items, he or she is classified as socially and materially deprived. However, workers across all income groups are deprived of some of these items.
  18. The degree of workers’ material deprivation somewhat varies, with the biggest difference for 2023 in, Finland, Greece, the Netherlands, Malta and Romania .
  19. As approximated by the variable cash income from employment in gross terms in EU SILC.
  20. For single, full-time workers, deprivation increased in all catching-up Member States, as well as in Italy, Portugal and to some extent in Ireland and France. By contrast, it increased from 2019 in the more affluent Member States (see Graph 2.8 for full-time, single workers; the results generally hold when considering all workers, see Graph A.2.1.2 in annex).
  21. For example, in Germany, the lowest wage group (1st quintile) saw an increase by 0.67 items on average while the 2nd quintile saw an increase of 0.73 items. Or for Belgium where the lowest wage group (1st quintile) saw a decrease by 0.11 items while the 2nd quintile saw an increase by 0.26 items.
  22. In addition, a sizeable share of low-wage earners can be second earners in a household. As such, the main wage in the household may have acted as a buffer for some expenses linked to the household, such as energy and food.
  23. At the EU level, the European Refence Budgets Network and the JRC project on “Measuring and monitoring absolute poverty” (ABSPO) aimed to establish a common methodology to define a lower threshold for decent wages i.e. living wages. This approach would imply quantifying a basket of goods and services deemed essential for a decent life. A decent wage would then be determined by a threshold, meaning being able to afford such consumer basket, taking into account the worker's location (International Labour Organisation, 2024b, Menyhert et al., 2025).
  24. They consist of 7 items linked to the functioning of a household (warming home, buying meat, buying furniture, having a car, going to holidays, paying arrears or unexpected expenses), and 6 items linked to the living standard of the individual within the household (buying shoes, clothes, having some leisure activity, spent money on oneself, meeting outside with friends, or accessing internet)
  25. This corresponds to the variable PY010G in EU-SILC.