Coordinated Minimum Wage Policies: Impacts on EU-Level Income Inequality

2.1 Income Inequality at the EU Level

Most research on income inequality in the EU area is limited to country-level analysis, essentially because tax-benefit systems, which represent the primary policy tool to counter inequality, are in the remit of Member States (European Commission 2021). Moreover, reforms of tax-benefit systems take place mainly at the national level as they generally reflect national preferences.

However, as the mobility of the EU population has risen over the last decade (European Commission 2020a), it is reasonable to assume that EU citizens consider their income levels in comparison to EU-level incomes. In this context, the perception of inequality may go beyond national considerations. Likewise, an integrated European economic space requires that policies should aim, at least in the medium run, at pushing inequality in the Union down. Especially EU policies that might have different effects on income inequality across EU countries are also likely to affect overall EU-level inequality. In this regard, Salverda (2021) delineates a broad range of both national and EU policies with the perspective of a reduction of EU-wide inequality.

This is why some studies have recently estimated EU-level income inequality, following a research strand pioneered by Atkinson (1998). From an empirical viewpoint, these estimates have been carried out with harmonised survey data or with administrative income data. For the former, many studies have documented pan-European inequality trends since the early 2000 (Benczúr, Cseres-Gergeley, and Harasztosi 2017; Brandolini 2007; Darvas 2016; Dauderstädt and Keltek 2014; Eurofound 2017; Heidenreich 2016). More recently, Filauro and Parolin (2019) also evaluated pan-European inequality in market incomes and in disposable incomes to discuss the redistributive role of the EU welfare states and compare it with that in the US. In turn, Brandolini and Rosolia (2021) estimated EU-level income inequality and discussed the macroregional trends (across EU areas) driving the overall patterns, while Filauro, Parolin, and Valetto (2025) analyzed the within-country and between-country dynamics in market income behind the overall reduction in EU inequality observed between 2007 and 2019. For the latter, Blanchet, Chancel, and Gethin (2020) have carried out an admirable reconciliation of survey and administrative income data with national account statistics within the Distributional National Accounts (DINA) framework to discuss EU market income distribution and the EU tax-benefit redistributive power in comparison to the US.

Three main points can be highlighted from a broad overview of these studies. First, disposable incomes in the EU are as unequal as in the most unequal countries of the EU. Secondly, 20–30 % of income inequality is explained by inequality between EU countries, as opposed to the US where the overwhelming source of inequality is within US States – around 99 % as estimated by Filauro and Parolin (2019). Third, in the process shaping inequality, capital and labour incomes determine a very unequal market income distribution in the EU. However, the overall mitigation of tax-benefit systems on market income inequality is over 20 % at the EU level, as computed with EU-SILC data (Filauro and Fischer 2021). The reduction in inequality when moving from market to disposable income is due to the high degree of progressivity of tax-benefit systems in countries where the EU highest market incomes are concentrated, i.e. Nordic countries, Germany and France.

Moreover, EU-level income inequality can be considered as an indicator relevant in itself as its levels may influence trust in the EU institutions and intra-EU mobility decisions. Indeed, one of the predominant economic motives to trigger mobility decisions is presumed to be the level of wage inequality across countries, in particular the wage premium for the same job performed in a different country. Although more focused on the degree of convergence in average income levels, a measure of between-country inequality may indirectly indicate diverging income levels and a higher propensity of cross-country mobility.

2.2 The Impact of Minimum Wage Policies on Income Inequality

There is a consolidated line of research on the impact of minimum wages on income-related outcomes, such as poverty or inequality, at the national level. The three factors that determine minimum wage (MW) increases to reduce income inequality, in the absence of employment effects, are: (1) the level of compliance, (2) the level at which the minimum wage is increased, and (3) the household characteristics of MW earners. Hypothesising full compliance, previous empirical studies have assessed the inequality impact of minimum wages at the national level, mainly with microsimulation techniques. There are some studies that contend that minimum wage policies are not the optimal policy tool to reduce poverty and counter wage inequality (Burkhauser 2015). However, an empirical relation between the introduction or the increase of minimum wage levels and a subsequent wage inequality reduction has been documented in a number of studies. For example, with regard to wage inequality, Keese (1998) and Lucifora, McKnight, and Salverda (2005) show that minimum wages reduce wage inequalities in Europe. More recently, Garnero, Kampelmann, and Rycx (2015) find that the presence of a statutory minimum wage reduces wage inequality significantly, as measured by the Gini coefficient and with a Theil decomposition in a sample of 18 European countries.

Similarly, other studies find that the erosion of minimum wages is correlated with considerable increases in overall inequality (Beramendi and Rueda 2014; Checchi and Garcia-Peñalosa 2008). Jaumotte and Osorio Buitron (2015) estimate a 2.4 % increase in the Gini coefficient of disposable incomes in the Netherlands due to a decrease of 16.5 % in the minimum wage level over the period 1980–2010. In Romania, Militaru et al. (2019) using 2013 survey data, find that household disposable incomes become less unequal when the minimum wage increases. In Ireland, Redmond, Doorley, and McGuinness (2021) found that although wage inequality is reduced by minimum wage increases, the effect on household income distribution is limited because minimum wage workers are spread throughout the income distribution of households. Dustmann et al. 2022 find that minimum wages introduced in Germany in 2015 improved the wages of low-wage workers without significantly lowering their employment prospects. The ILO Global Wage Report (2021), through a microsimulation exercise, assesses the inequality-reducing impact of expanding both the coverage and level of the minimum wage.^[4] The findings indicate that, regardless of the inequality index used, increasing the minimum wage reduces income inequality across all EU countries analysed.

Finally, Grünberger et al. (2022) find that an increase in the minimum wage is expected to reduce wage inequality, depending on the share of workers affected and the amount of wage increase (Tables 1 and 2). They find that countries such as Czechia, Germany, Spain, Luxembourg, Poland, Slovakia and Estonia would record the highest reduction in wage inequality – around 20 % for a minimum wage rise equal to 60 % of the median wage. The degree to which this increase translates into a reduction in income inequality at the country level is mediated by household composition and tax-benefit interaction.

However, at the EU level, the impact of minimum wage rises on overall inequality depends on how much it triggers an upward shift of EU low-income households in the EU distribution. In other words, households which may be low-income in the national distribution and can benefit from a minimum wage increase, may well not be low-income households in the EU distribution. For example, households with minimum-wage earners in Luxembourg may be in the bottom of the national distribution but they are much higher up in the EU-level income distribution. Thus, the final impact of national increases of minimum wages on EU-level income distribution depends on the combination of within- and between-country inequality.

To date, no study has adopted microsimulation techniques to evaluate the impact of EU policies on the income distribution at the EU level. Thus, we contribute to this strand of research by using EUROMOD, a unique microsimulation model widely used for cross-country analysis of the impact of fiscal reforms on inequality, in a supranational framework to study the impact of EU-promoted policies, such as minimum wage policies, on EU-level inequality.

3.1 Adjusting Gross Wages

We use information on individual wages and incomes from the EU Survey on Income and Living Conditions (EU-SILC). We analyse three hypothetical minimum wage (HMW) scenarios which are calculated as ratios of country-specific median gross wages. HMW levels are calculated as 50 %, 55 % and 60 % ratios of median gross wages, following the general suggestion in the EU Directive on Minimum wages and the recent debate on potential MW thresholds in national debates (Eurofound 2023a, Chapter 3). We use median wage statistics of year 2019 from Eurostat (for more details, see Grünberger et al. 2022). We choose 2019 to insulate our analysis from the pandemic-related labour market turbulence occurred in 2020 and 2021.

Of the 27 EU Member States, 21 had a statutory minimum wage established by legislation in 2019 (see Table A1). Cyprus has adopted a statutory minimum wage in 2023. In the remaining five countries (Austria, Denmark, Finland, Italy, and Sweden), minimum wage protection is still governed by collective agreements. This analysis considers the impact of hypothetical increases in national minimum wages across all countries, regardless of whether minimum wages are statutory or determined by collective bargaining. The rationale is that such hypothetical increases could be implemented either through regulatory changes or by promoting more adequate minimum wage levels via agreements between social partners, in line with European regulations.^[5]

Table A1 shows the levels of statutory minimum wages and HMWs in EUR. For each individual whose observed wage lies below the HMW, we increase the gross wage to the HMW. In case of part-time workers, the respective share of HMW is imputed, depending on the reported working time. The imputation of hypothetical minimum wages is done based on the hourly wage rate. For that, we convert both the observed wages (expressed in yearly terms in EU-SILC data) and the HMW levels (expressed in monthly terms) to hourly levels. A reliable calculation of hourly wages requires reliable data on both earnings and working time. Grünberger et al. (2022) show that particularly information on working time in EU-SILC data is prone to measurement errors. Working time in SILC is reported as the number of months worked during the year and the usual weekly working hours. The number of months worked is further categorized into months worked part-time and months worked full-time. A complication arises because the number of months worked pertains to the income year (the calendar year preceding the survey), whereas the usual weekly working hours refer to the survey year. This discrepancy creates challenges in accurately recording working time, particularly for individuals whose work patterns change over time.

The noise in the assessment of working time introduces a measurement error into hourly wage data. When the working time reported in SILC exceeds the real time worked by the employee, this leads to an underestimation of the hourly wage. On the other hand, we overestimate hourly wages, if the recorded working time is lower than the real time in employment. This measurement error leads to an increase in the variance of hourly wages as it inflates the ratio of observations with an estimated hourly wage below the minimum wage. Thus, we adopt a set of correction methods to account for potential measurement errors in the calculation of hourly wages.

First, hourly wages identified as negative outliers, using the method outlined in Grünberger et al. (2022), are excluded from upward adjustments to HMW levels. Second, wages of employees who report other income sources, such as self-employment or pension income, are not adjusted. Third, in line with Eurofound (2024), we exclude wage adjustments for workers with less than one year of tenure, those alternating between part-time and full-time contracts between the income and survey years, individuals whose usual weekly working hours contradict their employment status for the income year, and workers under 20 or over 65 years of age.

For eligible workers not falling under the above restrictions, we assign HMW hourly wages and recalculate annual earnings. Notably, we assume full compliance with hypothetical minimum wage legislation for this group. However, wages remain unchanged in countries where the statutory minimum wage exceeds the HMW (see grey cells in Table 1).

Table 1 shows the shares of workers affected by each hypothetical minimum wage increase. In Cyprus, Estonia, Greece, Spain, Ireland, Luxemburg, Poland and Romania more than 20 % of workers would be affected if the minimum wage is set to 60 % of the median wage. In Czechia, Denmark, Germany, Croatia, Hungary, Latvia, Malta, Slovakia and Sweden the share of those affected would be between 10 % and 20 %. In Austria, Belgium, Finland, France, Italy, Netherlands and Slovenia less than 10 % would be affected. As already mentioned above, in Bulgaria and Portugal there would be no effect, as the statutory wage is already higher than 60 % of the median wage.

To illustrate visually how an increase in minimum wage levels might determine a reduction in disposable income inequality, we respectively plot the EU-level distributions of wage and disposable income. We plot these distributions first for the sample of workers only and then for the overall population before and after the most ambitious HMW increase, i.e. 60 % of the median wage. Moreover, we focus on the country position of the HMW earners in the EU-level distribution.

All the distributions presented in this section are representative of the EU population as they are obtained by using cross-sectional EU-SILC weights. To make the wage and income values comparable across countries, we apply purchasing power parity (ppp) rates.^[6] The average monthly gross wage is obtained by dividing yearly employment gross earnings by 12. Given the high heterogeneity in wage setting across countries, we expect EU wages to follow a multimodal distribution. In addition to wage differences between countries, levels of average monthly gross wages depend on working time and vary accordingly. The distribution of average monthly gross wages in the EU after assigning a HMW corresponding to 60 % of the national median income has several distinctive peaks in comparison to the distribution of observed survey data (Figure 1a).^[7] These peaks correspond to distinctive EU areas where workers receiving the HMW increase are located as illustrated in Figure 1b.

Figure 1:

Gross wage distribution of EU workers before and after the HMW rise (panel a); gross wage distribution of HMW earners by region (panel b). Note: The distributions are based on kernel density estimates, probability density functions. The EU-wide distribution was corrected with purchasing power parities.

The first peak, at around 800 ppp-adjusted EUR, corresponds to the HMW earned by workers living in Central and Eastern European (CEE) countries. The other peaks correspond to the HMW increase earned by workers living in Mediterranean (MED) as well as in Northern and Western European (NWE) countries.^[8] More specifically, 7.8 million workers in NWE countries would receive the HMW increase, followed by 5.7 million workers in CEE countries and 5.3 million workers in MED countries. The ppp-adjusted wages of MW earners in CEE countries are similar to those in MED ones, although the former are much more concentrated around 800 ppp-adjusted EUR per month due to a low incidence of part-time work in CEE countries.

3.2 Calculating Disposable Income

We analyse the impact of HMW scenarios on EU-level inequality for different income concepts. The first income concept analysed is disposable income as a proxy for household living conditions. Next, we analyse market income, comprising only capital and labour income sources, and gross income, comprising also social benefits. In this way, we can assess the redistributive role of EU tax-benefit systems in conjunction with the impact of HMW levels. The different income concepts of interest are described in Table B1.

For calculating changes in taxes and benefits related to each HMW scenario, we use the static microsimulation model EUROMOD. This model provides a comparative framework for EU countries that enables researchers to conduct cross-country analysis.^[9] EUROMOD takes into account the interaction between gross wage and taxes and benefits in each EU Member State. After increasing wages according to the HMW scenario, at the new level of earnings, EUROMOD calculates taxes, social insurance contributions and benefits, and consequently the disposable income of workers and their household members. For the simulations presented in this study we have used EUROMOD version I2.0+, which refers to the tax-transfer system as of 30 June 2019. This version is based on microdata coming from EU-SILC surveys from 2017. Given that the income reference period of EU-SILC 2017 data is the year 2016, uprating factors are used to bring the income values from the income reference period to 2019. We use 2019 income values to insulate our analysis from the pandemic-related labour market turbulences that affected the income distribution in 2020 and 2021 (Eurofound 2023b).

The model provides only static results and does not account for behavioral reactions of the labour market that may occur in response to policy changes. For example, minimum wage increases may trigger job losses or induce workers to change their labour supply, which in turn would affect individuals’ incomes. However, Grünberger et al. (2022) predict little impact of the minimum wage increase on employment and labour supply.

When moving from gross wages to disposable incomes, applying tax-benefits rules in force, the EU workers’ distribution appears more compressed (Figure 2a).^[10] The baseline distribution appears to have more workers with a disposable income below 600 ppp-EUR than the distribution of the HMW scenario. Instead, the HMW scenario distribution has more observations around 800 ppp26-EUR and 1,500 ppp-EUR than the baseline distribution. Figure 2b helps to identify the geographical location of workers that experience an increase in disposable income as a result of the HMW rise as it includes only workers affected by the HMW increase.

Figure 2:

Disposable income distribution of EU workers before and after the HMW increase (panel a); disposable income distribution of HMW earners by region (panel b). Note: The distributions are based on kernel density estimates, probability density functions. The EU-level distribution was corrected with purchasing power parities.

Two findings emerge from the comparison of the distribution of disposable income with the distribution of gross wages, as in Figure 1b. First, while disposable income of MW workers is higher in MED than in CEE countries (Figure 2b), gross wages were, all in all, of a similar level (Figure 1b). Secondly, the peak observed in the distribution of gross wages for the MW earners in NWE countries almost fades out in the distribution of disposable income. Both findings suggest that in MED and NWE countries, minimum wage earners are benefitting to a larger extent from the tax-benefit system than in CEE countries.^[11] Indeed, prior research documents that tax-transfer systems are generally more redistributive for low-wage workers in MED and NWE countries than in CEE ones (European Commission 2020b).

Finally, we look at the distribution of equivalised household disposable income in the EU calculated as the total household income divided by the modified-OECD equivalence.^[12] Furthermore, to better identify the impact of HMWs on the working-age population in comparison to the full population, we consider three types of households: (1) households with at least one person earning the hypothetical minimum wage; (2) households with at least one employee; and (3) all households, irrespective of the occupational status of its members (Figure 3).

Figure 3:

Disposable income of EU households. Three subpopulations. Note: The distributions are based on kernel density estimates, probability density functions. The EU-level distribution was corrected with purchasing power parities.

Compared to the shift of the distribution of individual disposable income for workers-only after the HMW rise (Figure 2a), the shift in the equivalent household disposable income for households with at least one employee is visibly less pronounced (Figure 3b). This is because HMW earners are disseminated among households and their income is pooled with the income of other household members. The increase in the HMW appears to have a more visible impact on equalized disposable household income for households with at least one MW earner (Figure 3a). The impact of a HMW increase becomes less visible when considering the full-population income distribution due to the inclusion of pensioner households in the sample (Figure 3c). In fact, although the increase of the HMW to 60 % of the median wage would affect about 19 million workers, its impact on the household income distribution of the whole EU population seems relatively small. In Section 4 we estimate the impact of HWM increases on inequality measures for these different populations to complement the graphical evaluation.

3.3 Measures of Inequality

The primary measure of inequality used in this study is the Gini coefficient. First, the reduction in EU-level income inequality after the HMW rise is measured using the Gini coefficient, although generalised entropy (GE) indices are computed for sensitivity analysis. Second, we compute the relative contribution of within-country and between-country inequality by exploiting the property of decomposition in non-overlapping groups respected by GE indices. As such, the Mean Logarithmic Deviation (GE0) and the Theil index (GE1) are computed at the EU level and are decomposed as follows:

where:

where v _m is country m’s share of the total income; G E α W Y m is the inequality within country m and α represents the sensitivity of the index to differences in income shares along the income distribution.^[13] In turn, G E α B Y is the between-country inequality, in which each individual is assigned the mean income of his/her country. We decompose the within- and between-contributions by country of current residence as reported in EU-SILC data. As such, the between-country component of the decomposition should be interpreted as inequality between the mean incomes of individuals residing in the different EU countries.

Tests of statistical significance are carried out to evaluate the differences between the post and pre-reforms inequality indices.^[14] Negative and zero income values, which are negligible for disposable income and do not exceed 4.5 % for gross income and 9.5 % for market income, are not considered in this testing procedure.

Some caveats should be considered when interpreting this simulation exercise. First and foremost, a limitation refers to the assumption of no employment effects and, secondly, to the assumption of no spillover effects. About the first caveat, there is a large number of studies that have recently documented empirically the employment effects consequential to minimum wage increases in many advanced economies. In general, research on the employment effects of minimum wages has not determined a consensual view as the variation of estimated employment effects across studies is very large (Neumark and Munguía Corella 2021). Thus, we are confident that employment effects due to rises in minimum wage floors, as hypothesised in this study, should not be exaggerated. Grünberger et al. (2022) have analysed possible negative employment effects using “own-wage elasticity” applied to wage increases for minimum wage earners and labor supply effects at the intensive margin using labor supply elasticities for similar HMW increases. Overall, they find relatively small impacts of simulated MW increases on employment and labor supply, never substantially exceeding 0.5 % of total employment even for the largest HMW increase and with much lower increases on labour supply at the intensive margins (% hours offered max +0.2 %). A large-scale and influential review of studies documenting the employment effects of minimum wage increases finds that the weight of the evidence indicates overall modest employment effects (Dube 2019).

We acknowledge the potential risk of employment effects resulting from minimum wage increases, particularly in countries where raising the minimum wage to 60 % of the median would represent a substantial adjustment. Countries with the lowest current minimum wages compared to our most generous scenario include Estonia, Malta, Ireland, Czechia, Latvia, the Netherlands, Croatia, Greece, Belgium, and Slovakia. However, prior research, such as Christl, Köppl-Turyna, and Kucsera (2018), suggests that Eastern European countries, including Czechia, Croatia, and Slovakia, where minimum wage are among the most distant from the most ambitious hypothetical levels, may have more room to raise minimum wages without significantly affecting employment, particularly among young workers. In turn, Germany, due to its size and economic influence, stands out as a country where employment effects from minimum wage increases could have EU-wide implications. In 2021, Germany’s Kaitz ratio was 51 %, and with the October 2022 minimum wage increase to 12 euros per hour, this ratio rose significantly. Nonetheless, a systematic review by Dutsch, Ohlert, and Baumann (2024) documenting the effects of minimum wages in Germany reports mixed findings: while employment reductions were observed following the 2017 minimum wage increase, no significant employment effects were noted for the increases in 2019 and 2020 among firms employing minimum wage workers. Thus, while an increase in the hypothetical minimum wage could potentially trigger employment effects, these studies highlight that the magnitude of such effects remains uncertain and should not be overstated even in countries where the proposed increase would be substantial, as it may depend on factors such as labour market conditions, the scale of the wage adjustment, and workers’ behavioral responses.

In turn, spillover effects may arise subsequently to a MW rise. It may be plausible that wages close to the new MW are affected by spillovers due to efficiency wage and/or reservation wage effects. However, these effects are empirically hard to quantify with household data, as surveyed by Autor, Manning, and Smith (2016) for the case of the US. Spillover effects are expected to be most significant in precisely those countries and scenarios where the direct effects of minimum wage increases are already substantial (see the case of Spain analysed by de Paz-Báñez, Sánchez-López, and Asensio-Coto (2024). Therefore, a consideration of these effects would likely not alter the conclusions of our study but would probably amplify them – both within and between countries.

In light of this uncertainty, this paper opts for a straightforward simulation approach, excluding employment effects and spillover effects while acknowledging the limitations this approach entails. By avoiding the assumption-heavy exercise of predicting employment impacts across EU countries and the subsequent second-round simulations on EU-wide inequality, we remain focus on a simplified, day-after simulation of minimum wage increases without incorporating behavioral responses. These complexities are beyond the scope of this paper and are left for future research.

4.1 Inequality-Reducing Effect of Rising Hypothetical Minimum Wages (HMWs)

Inequality in equivalised disposable household income in the EU as measured by the Gini coefficient is around 33 % in 2019.^[15] Increases in the HMW reduce EU-level inequality under all HMW scenarios. As expected, the higher the increase in the HMW, the larger the reduction in disposable income inequality (Figure 4). In detail, minimum wage floors, correspondent to 50 %, 55 % and 60 % of the national median wage, would reduce the EU-wide Gini coefficient of disposable income relative to the baseline by, respectively, 0.25 %, 0.4 % and 0.63 %.^[16]

Figure 4:

EU-wide income inequality. Gini coefficient, disposable incomes 2019. Note: EUROMOD simulations. The “current” baseline reflects minimum wages in 2019. Simulations respectively for hypothetical minimum wages equal to 50 %, 55 % and 60 % of the national median wage.

Albeit of little magnitude, these inequality changes after the HWM increase are statistically significant (Table 2). It is consequential that for the distribution of working-age EU households, the HMW has a more pronounced beneficial effect in reducing inequality. Zooming in on the two subpopulations of EU households with a minimum wage earner or households with at least one employee, the reduction in disposable income inequality is a bit more pronounced after the HMW increase, for the former more than for the latter distribution. For instance, hypothetical minimum wages set at least at 60 % of the median wage in all EU countries would reduce EU-level inequality by 1.25 % and 0.73 % in the distribution of respectively households with at least one minimum wage earner and households with at least one employee. This reflects the visual intuitions of Figure 3 and, unsurprisingly, highlights that a potential increase in minimum wage levels exerts larger inequality-reducing effect on the population of households more attached to the labour market.

To understand the dynamics behind this reduction in EU-level inequality it is useful to look at the two components of within- and between-country inequality, which are computed from the inequality decomposition. Previous studies show that within-country inequality is responsible for around 75 % of EU inequality while between-country inequality explains the remaining 25 % (Blanchet, Chancel, and Gethin 2020; Filauro and Parolin 2019).

The inequality reduction after the HMW increase depends first on the change in inequality in each country, which affects the within-country inequality. Second, changes in country-specific average incomes affect between-country inequality.

On the one hand, we expect within-country inequality to decrease because higher minimum wage floors have been shown to reduce gross wage inequality, or at least keep it constant, in all countries (Grünberger et al. 2022). Thus, lower wage inequality should normally result in a lower inequality of equivalised disposable household income. This implies that within-country inequality of equivalised disposable household income in the EU, i.e. the population-weighted average of country-level inequality indices, is also expected to decline as the HMW increases.

On the other hand, the impact of the HMW increase on between-country inequality is less clear-cut. The potential of a HMW increase to reduce between-country inequality depends on the country-specific position of HMW earners and the magnitude of their HMW increase, along the EU distribution. For example, low-pay households in countries such as Germany and Luxembourg, whose income conditions would improve significantly due to higher HMW, might be located in the middle-upper part of the EU income distribution. In other words, if a higher HMW increases the average national income of richer countries more than the average income of poorer EU countries, this might place the latter countries in a worse situation and in this way magnify between-country inequality.

As expected, the reduction in within-country inequalities is significant and increases as the HMW is set at higher levels (Figure 5). Thus, more generous HMWs have the potential to reduce within-country income inequality, triggering in this way a reduction in EU-level inequality.^[17] Between-country inequality also declines under all three HMW scenarios. While the absolute reduction is smaller compared to within-country inequality, the relative reduction is of a similar magnitude (Figure 5 and Table A3).

Figure 5:

EU-level inequality reduction, decomposition by country, disposable income, 2019. Note: EUROMOD simulations. The baseline reflects the distribution of EU disposable incomes in 2019, with the observed minimum wages. Relative reduction in EU-level inequality (%) is simulated for different hypothetical minimum wages. Mean logarithmic deviation (MLD) and Theil indices.

The indicators of between-country inequality measure the income differences between individuals based on the average income in each country. Therefore, a decline in between-country inequality implies some degree of convergence in average incomes across EU countries when the hypothetical minimum wage increases.^[18] Although inequality-reducing, the general impact of a HMW increase on average incomes is small across countries. This effect is in the range of [−20; +20] ppp EUR in terms of average annual disposable income in the most ambitious scenario of HMW equal to 60 % of national median wage, as documented in Table A2. In a simulation exercise applied only to Member States with statutory minimum wages, the reduction in between-country inequality would be lower (Figure C1). In all cases, concerns that a coordinated rise in the minimum wage would significantly alter average incomes across countries are exaggerated.

4.2 Tax-Benefit Interaction with Minimum Wages and Impact on EU-Level Income Inequality

The redistributive effect of tax-benefit systems in the EU, as measured by the inequality reduction from the distribution of market to disposable income, is generally high. Recent estimates from EU-SILC show that the inequality reduction in passing from market incomes, including public pensions, to disposable incomes amounts to slightly over 20 % – a redistributive effect similar to that in France or Germany (Filauro and Fischer 2021). Blanchet, Chancel, and Gethin (2020) assess the redistributive power of tax-benefit systems in Europe with their integrated DINA dataset and find it similar, although they argue that this effect is overestimated with survey data.^[19]

In all cases, the relatively high reduction in inequality attributable to tax-benefit systems is partly a result of the relative position of different EU countries in the EU distribution. Indeed, the largest market incomes in the EU distribution are those recorded in Nordic or high-income countries such as France or Germany. These market incomes are also those more subject to a substantial reduction after taxes due to the progressivity of their national tax systems. This is not the case for the largest market incomes observed in some Eastern European countries that are not at the top of the EU distribution. In fact, the slight progressivity of nearly flat-tax regimes in some Eastern European countries should not impair the overall redistributive effect at play in the EU distribution. Therefore, the compression of EU-level income distribution after taxes and transfers is partly due to national dynamics in the richer EU countries.

Our simulations indicate that an increase in HMW would reduce inequality also in EU-level market incomes by around 0.6 %. The overall percentage reduction in market income inequality is similar to that observed for disposable income, although the reduction in Gini points for market income inequality is greater. In turn, this inequality reduction is greater than that recorded for gross incomes (Table A4), due to the withdrawal of benefits after household market incomes rise due to higher HMW. These findings are robust across different inequality indices. Unsurprisingly the inequality reduction is larger for the population of EU households with a stronger attachment to the labour market (Table A5). As in the case of disposable income, the reduction in the Gini coefficient for market and gross incomes increases as the HMW is set at a higher level (Figure 6).

Figure 6:

EU-wide income inequality. Gini coefficient, market (left) and gross income (right), 2019. Note: EUROMOD simulations. The “current” baseline reflects minimum wages in 2019. Simulations respectively for hypothetical minimum wages equal to 50 %, 55 % and 60 % of the national median wage.

The dynamics for the inequality reduction in market and gross incomes follows the same explanation as for disposable incomes (Figure 7). A HMW increase is very likely to bring about a reduction in within-country market inequality. In many EU countries, the increase in market income for low-pay workers is actually higher than after the interaction of taxes and benefits (Grünberger et al. 2022) because benefits can be withdrawn and income taxes may rise after a HMW increase. Therefore, a reduction in market incomes inequality is expected due to a reduction in within-country inequality.

Figure 7:

EU-level inequality reduction, decomposition by country, market (left) and gross income (right), 2019. Note: EUROMOD simulations. The baseline reflects the distribution of EU disposable incomes in 2019, with the observed minimum wages. Relative reduction in EU inequality (%) is simulated for different hypothetical minimum wages. Mean logarithmic deviation (MLD) and Theil indices.

The percentage changes in between-country inequality are generally modest but more noticeable for market income than for disposable income. For both inequality indices analysed, but more clearly for the mean logarithmic deviation, a percentage reduction in between-country inequality is detectable and is of similar magnitude to the percentage change in within-country inequality for the most ambitious Kaitz ratio of 0.6 (Figure 7). This is likely due to the greater potential for increases in lower market incomes in relatively poorer member states with lower minimum wages.^[20]

For gross incomes the impact of a HMW on between-country inequality is ambiguous in principle. This is because the withdrawal of transfers for HMW earners can be more noticeable in Eastern European countries rather than in more redistributive countries such as Germany or Belgium, potentially increasing the differences in average gross incomes across EU countries.^[21]

Similar to market income, the reduction in EU-level inequality for gross incomes can be ascribed to both inequality components with a broadly similar dynamics (compare the right and left panels in Figure 7). There is a small but observable reduction in within-country inequality, reaching an almost 1 % reduction for the Theil index in the most ambitious HMW scenario. Our simulations show that between-country EU inequality also slightly decreases, at least in relative terms, as the HMW increases (Figure 7). In the most generous scenario of Kaitz ration of 0.6 the overall increase in average annual market incomes and gross incomes, after benefits, for all EU countries is contained within the range [−1; +27] ppp EUR (Table A2). Thus, the impact of HMW increases on the between-country inequality in both absolute and relative terms is of relatively moderate intensity. Still, the between-country inequality reduction seems to dominate the within-country reduction in both indices, especially for more ambitious floors of HMW. This is likely due to the composition effect of lower gross-income countries, which stand to gain the most from an increase to the most ambitious scenario, even net of potential social benefit withdrawals.