Combating inequalities: what role for universal social protection?

Shahra Razavi

Umberto Cattaneo

Helmut Schwarzer

Andrea Visentin

Abstract

The primary aim of this study is to provide evidence regarding the impact of social protection benefits, taxes and social security contributions in reducing income inequalities. The study employs a well-established methodology to estimate the partial redistributive effect of contributory and non-contributory pensions, family benefits, unemployment benefits, sickness and employment injury benefits, disability benefits, social security contributions, as well as income and property taxes. The partial redistributive effect corresponds to the percentage decrease in the Gini coefficient that is attributable to each social protection benefit and tax. The main data input is microdata from the Luxembourg Income Study (LIS). The evidence presented shows that social protection benefits, and its financing through taxes and social security contributions, are effective policy measures for reducing income inequalities. On average countries that spend more on social protection are those that experience larger reductions in income inequality. The paper concludes with practical recommendations on how to finance and design social protection systems that reduce inequalities, as well as ideas for future research in this area.

Executive Summary

The issue of inequality is one of the most topical, wide-ranging – and arguably contested – areas of research and policy, regarded by many as a key challenge of our times. Inequality can be broadly understood as a societal state characterized by hierarchical distinctions, whereby individuals are categorized based on factors such as income, wealth, age, gender, ethnicity, and disability, among other defining traits. When inequality re-emerged as a global policy concern in the 2000s, the initial response from mainstream policy institutions was to focus attention on ‘equality of opportunity’ rather than on income and wealth inequality—referred to as ‘equality of outcome’. However, in view of the interconnections between the two, Atkinson’s response that “if we are concerned about equality of opportunity tomorrow, we need to be concerned about inequality of outcome today” (Atkinson 2015) had considerable resonance.

Interest in the issue of inequality has been growing because, even with the long-term movement toward greater income equality (Piketty 2022) especially in the advanced industrialized countries between 1914 and 1980, there has been an upsurge in income inequality since 1980. In OECD countries, the average incomes of the top 10 per cent reached almost ten times those of the bottom 10 per cent, compared to a ratio of 7 to 1 in the 1980s (OECD 2015). Despite some important reductions in income inequality in some of the most unequal countries of Latin America (most notably Brazil, Ecuador and the Plurinational State of Bolivia), Latin America continues to have some of the highest levels of income inequality in the world, though levels of inequality seem to be even higher in Middle East and North Africa (MENA) and sub-Saharan Africa (Chancel et al. 2022). High income inequality is deemed toxic not only due to its tendency to trigger crises and financial meltdowns (UNRISD 2022) but also for its potential to subvert regulatory and accountability institutions and corrode societal norms and the quality of democracy (Saith 2011).

Based on data from 77 countries, we find that between 2013 and 2022, there was a slight decline in overall income inequality, which may have been in part at least driven by the social protection response to the COVID-19 pandemic. Despite this positive trend, the overall levels of income inequality persist at alarmingly high rates: the portion of total income held by households in the lower 50th percentile is 25 per cent compared to 30 per cent held by those earning within the 90th percentile.

Several factors have contributed to the high level of income inequality we see today. Looking at the share of total income that is attributed to labour earnings compared to the share that goes to profits, stagnation of the labour income share is clear, and it hinders the reduction of income inequalities and the capacity of workers and jobseekers to find gainful employment. It also constrains the ability of governments to generate revenues from social security contributions. In 2022, the labour income share stagnated at 53.8 per cent. Reducing the functional distribution of income (i.e. inequality between labour and capital)—or primary distribution—is therefore essential if countries are to reduce overall inequalities, including in terms of intergenerational social mobility.

In addition, labour market informality exacerbates income inequalities and restrains access to social insurance for workers who lack sufficient contributory capacity. Low intergenerational social mobility is another factor that reinforces inequalities with the causality running in both directions. Countries with higher levels of income inequality tend to have lower levels of intergenerational mobility, a relationship known as the “Great Gatsby Curve” (Gini 1912). Wealth inequalities are increasing in many high-income countries and are also reinforcing and exacerbating income inequalities. This phenomenon was accelerated during the COVID-19 crisis. While national income fell, the value of private wealth increased and this increase was particularly stark among billionaires.

Mainstream economic theories that posit a trade-off between equality and growth, have influenced many governments worldwide, and played a critical role in creating today's high levels of income inequality. The alleged trade-off between equality/equity and growth/efficiency, however, is not supported by empirical evidence. Countries with high levels of income inequality (that is, an unequally distributed “social pie”) are also those with relatively lower GDP per capita (that is, a smaller “social pie”). The strong and negative correlation between income inequality and GDP per capita questions the so-called “big trade-off” between equality and efficiency (Okun 1975). Countries that spend a larger proportion of their GDP on social protection are those where inequalities are lowest. There is a strong and positive correlation1 between GDP per capita and social protection expenditure (excluding health). There is also a positive, though less pronounced, correlation between GDP per capita and government health expenditure.2

The evidence presented in this working paper shows that social protection is an effective tool to reduce income inequalities. The largest reductions in income inequality (measured in terms of individual income) are observed for contributory pensions. In 18 out of 35 countries with available microdata from the Luxembourg Income Study, mostly high- and high-middle-income countries, such pensions reduce the Gini coefficient of income inequality by more than 15 per cent and in the cases of Czechia, Poland, Serbia, and Hungary by at least 30 per cent. It should be noted that this result emerges from a cross-sectional point of view, that is, it does not take into account long-term perspectives and the financing side of contributory pensions, which could significantly reduce the progressive effect of public pensions.

In 25 out of 35 countries with available data, non-contributory pensions are behind a reduction in income inequality below 4 per cent. Only in Denmark, Georgia and Switzerland do such pensions have an equalizing effect on income inequality that is above 15 per cent. Family benefits together with unemployment benefits, sickness and employment injury benefits and disability benefits are behind lower reductions in income inequality when compared to pensions. This is not surprising, given the generally smaller size of most short-term benefits compared to pensions. On average, countries that spend a larger percentage of total gross income on a given social protection benefit are also those that achieve a larger reduction in income inequality. However, the design of social protection benefits is relevant in explaining this outcome: certain countries spend a lower amount of their total gross income than others on a given benefit but obtain a greater income redistribution with such investment.

In 23 out of 25 countries with available data, personal income taxes also lead to a reduction in overall income inequality. However, such reductions are much lower than those observed for social protection benefits. In 14 out of 25 countries, the Gini coefficient is reduced by less than 5 per cent after income taxes are taken into consideration. Social insurance contributions play a key role in financing social security. These contributions enable the payment of contributory social protection benefits, which substantially reduce income inequality. However, single-rate social security contributions can be regressive and increase income inequality. Wealth taxes, which are not widely used, have the potential to reduce income inequality.

The positive impacts of social protection systems in reducing income inequality, both vertically and horizontally (explored here in terms of gender), reinforce the case for establishing and sustaining universal social protection systems based on three principles that are laid out in international social security standards. These three principles are: (1) focus on ensuring universal coverage of social protection systems anchored in legislation, covering the full life cycle and providing adequate benefits; (2) pursue a two-dimensional strategy, combining contributory social insurance mechanisms with tax-financed provisions; and (3) explore all available fiscal space options for extending social protection to those who are currently excluded, regardless of their employment status. However, reducing income inequalities cannot be left to social protection systems alone. It requires a wide range of integrated public policies—from access to quality education and skills training, to wage policies and formalization strategies, macroeconomic policies that create employment and livelihoods, and investment in quality public services—to reduce the primary distribution of income and make labour markets more equitable.

Introduction

Rising inequalities is a key global concern and tackling it a priority of many agencies in the multilateral system. The ILO Centenary Declaration for the Future of Work (ILO 2019) emphasizes the need to tackle income inequality as does the 2030 Agenda for Sustainable Development (under SDG 10). Moreover, combating inequality also underpins SDG 1 (on poverty eradication), SDG 5 (on gender equality) and SDG 8 (on achieving decent work for all) (ILO 2020). The International Labour Conference in its 109th Session in 2021 also recognized that inequality is complex, multifaceted and has many forms and components, concluding that there is a need to address the different dimensions of inequality in the world of work (ILO 2021c). Later, in March 2023, the ILO Governing Body identified inequality as one of the thematic policy domains that will frame the discussions with social partners to shape actions and advocacy messages within the newly formed Global Coalition for Social Justice (ILO 2023e).

In the same vein, the issue of inequality is one of the most topical, wide-ranging – and arguably, contested – areas of research and policy. Inequalities include both vertical inequalities, that is, between rich and poor households, as well as horizontal inequalities, that is, between multifarious groups in society, for example those differentiated by gender and racial/ethnic identity. These social inequalities, defined as disadvantages related to group status, intersect with, and compound inequality, resulting in entrenched structures of stratification that limit the life choices potentially available to so many people while undermining social inclusion and trust (ILO 2021c). High levels of income inequality are deemed toxic not only due to their tendency to trigger crises and financial meltdowns (UNRISD 2022) but also given their potential to subvert regulatory and accountability institutions, corrode societal norms and the quality of democracy (Saith 2011). The discussion of inequality and its drivers is foregrounded by a globalized context marked by significant inequalities between countries that can in turn exacerbate within-country inequalities, though the analysis of these interlinkages is beyond the scope of this paper.

As inequality re-emerged as a policy concern in the early 2000s, the initial response from mainstream policy institutions (e.g. World Bank 2006) was to focus attention on equality of opportunity rather than directly on inequality of outcome, most notably incomes. In view of the interconnections between the two, the World Bank 2006 report provoked considerable unease. ‘’If we are concerned about equality of opportunity tomorrow’’, argued a leading economist in the area, ‘’we need to be concerned about inequality of outcome today” (Atkinson 2015). Feminists concurred with this view, with outcome significantly broadened to include occupations, activities and responsibilities, as well as the distribution of income and wealth (Phillips 2004) paving the way for gendered responsibilities for unpaid work to enter the equation. Amartya Sen’s capabilities approach further challenged the opportunity/outcome distinction in more fundamental ways, underlining the point that substantive opportunities (the “freedom to be and do”) are actually the outcomes that people value (Sen 2001).

By the end of the twentieth century, concerns about poverty and to some extent inequality became more pronounced, reasserting the need to counteract the rationale of neoliberal and trickledown economics and its consequences and introduce policies that addressed the structural determinants of poverty and inequality (UNRISD 2016). However, this shift was not accompanied by a commensurate transformation of macroeconomic and social policy. Instead, social policy was often palliative. It neglected to address structural and systemic hurdles and deficiencies linked to chronic underdevelopment and pervasive poverty. Instead of building universal and comprehensive social protection systems, in tandem with employment and labour market policies, many developing countries pursued limited “safety nets”. These typically relied on conditional cash transfer programmes that are narrowly targeted and critiqued for being exclusionary and deepening social tensions (Kidd and Wylde 2011; Brown, Ravallion, and van de Walle 2018).

The COVID-19 pandemic brought to the forefront the pervasive nature of inequality in our societies, underscoring the pressing need for action (ILO 2021c). The pandemic resulted in widespread job losses that were disproportionally represented among individuals in low-paying jobs, especially informal self-employment. Many were women, who were forced to leave the labour force with lack of childcare often acting as a major trigger (ILO 2023g). In response to the global crisis, an unprecedented effort in the realm of social protection was initiated, leading to expectations that some of these measures might become permanent, thereby significantly reducing poverty and inequalities. The ILO’s Social Protection Monitor reported that over 1,900 measures were put into action by 211 countries and territories between January 2020 and September 2023 (ILO 2023d). However, the majority of these measures were rolled back at the pandemic's end, as many countries opted for austerity measures, heightening concerns that the new wave of fiscal austerity might further exacerbate inequalities (Ortiz and Cummins 2022).

The enduring impacts of the pandemic, coupled with austerity measures, have been further aggravated by geopolitical tensions and conflicts as well as the ongoing climate crisis (ILO 2021d; ILO 2022b; ILO 2023b; ILO 2023c). These crises are becoming more frequent and severe, often intersecting and compounding one another, disproportionately affecting the well-being and livelihoods of individuals and halting progress in reducing income inequalities within countries and potentially worsening inequalities between countries (ILO 2023a). Recent evidence reveals that in 2020, the world experienced the most significant increase in global income inequality and poverty since at least 1990. The COVID-19 pandemic led to a 0.7-point rise in the global Gini index and pushed an additional 90 million people into extreme poverty (defined by a daily income of US$2.15) compared to what would have occurred without the pandemic (Mahler et al. 2022). These findings are mainly attributable to job losses and a decrease in monthly wages, which saw a real-term decline of 0.9 per cent in the first half of 2022 (ILO 2022a). Global inflation and the cost-of-living crisis that underpinned the decline in real incomes of workers were, at least in part, due to corporate price-gauging with important implications for the overall distribution between wages and profits (Weber and Wasner 2023). Furthermore, another contributing factor to this heightened income inequality is the fact that a new billionaire emerged every 26 hours during the pandemic, while the fortunes of the world's ten wealthiest individuals doubled over the same period (Ahmed et al. 2022). As it will be shown, while income inequality underwent a slight decrease in the aftermath of the pandemic, largely attributable to extensive social protection measures, there is a looming risk of its resurgence as many countries phase out their social protection responses.

The present contribution provides evidence regarding the impact of social protection benefits, taxes and social security contributions in reducing income inequalities. The main data inputs are the Luxembourg Income Study (LIS) and the Luxembourg Wealth Study (LWS) Databases, in particular the most recent datasets available for individual countries (LIS 2023). We draw on the LIS database because it provides household- and person-level data on labour income, capital income, various social protection benefits, as well as taxes and social security contributions, thus making it well-suited for the aims of this paper. A well-established methodology is used to estimate the partial redistributive effect of contributory and non-contributory pensions, family benefits, unemployment benefits, sickness and employment injury benefits, disability benefits, social security contributions and income and property taxes. The partial redistributive effect corresponds to the percentage decrease in the Gini coefficient that is attributable to each social protection benefit and tax.

How much income inequality?

1.1. Why income inequality?

Before going into how much income inequality there is in the world and what the evolution of income inequality is over time, it is worth outlining how inequality is understood and why we measure inequality using income as the metric. Inequality can be broadly defined as a societal state characterized by hierarchical distinctions, where individuals are categorized based on their characteristics such as income, wealth, social status, gender, ethnicity, age, nationality, geographic location, and other defining traits (Midgley 2020). Unidimensional versus multidimensional measures of inequality are contrasted, but there is no evidence in the literature of a satisfactory definition that integrates the different types of inequality into a single conceptual perspective (Midgley 2020). However, measuring income inequality is considered a good summary measure of inequalities and aptly fits the aim of this paper – measuring the impact of social protection on reducing inequalities among individuals (Wilkinson and Pickett 2009).

It must be noted that income inequality – the extent to which income is unevenly distributed within a population – is measured with data from household surveys, which only collect data on total income at the household level. Because of this factor, it is not possible to determine each household member’s share in how income is allocated within the household and it is therefore impossible to measure inequalities within households. Therefore, to ensure comparability across different countries, the current analysis operates under the assumption that income is equitably distributed among members within a household—admittedly, a heroic Beckerian assumption that has received ample criticism from feminist economists who have documented considerable intrahousehold inequalities in the distribution of resources and well-being (Lise and Seitz 2011). But we make this assumption due to the limitations in the questionnaire used in income and expenditure surveys in many countries, which do not facilitate a detailed individual-level analysis of who has a say in the allocation of different income sources and how income is distributed within households.

Following our methodology, it would also be possible to assess horizontal income inequalities, for example by dividing the population into different groups based on certain characteristics, such as race/ethnicity, location or household composition (for example, single-parent versus dual-parent households), which we briefly consider. However, the focus of this paper will be on vertical income inequality and the effects of social protection benefits and taxes on it.

1.2. Income inequality has decreased in most countries, even if modestly

Since the 1980s, evidence of rising inequality has become increasingly apparent across many countries, triggering heightened attention to the issue on the global policy agenda. This period witnessed significant increases in income and wealth disparities, as documented by numerous scholars, including Thomas Piketty and his colleagues (Piketty 2022). Their research, while not always based on the most optimal data (Giles 2014; Sutch 2017) provides a comprehensive overview of the growing economic divides. It also underlines the need to expand general government revenue through taxation, preferably with progressive wealth and corporate taxes, as essential instrument to tackle very high levels of inequality found in developing countries (Razavi et al. 2022). The phenomenon of rising inequality has been observed in both developed and developing countries, driven by factors such as financialization, deregulation, technological change, the decline in trade union membership and collective bargaining coverage and policy choices favoring capital over labor. Despite its growing significance, inequality was notably neglected from the Millennium Development Goals (MDGs), which primarily focused on poverty and other social indicators.

The omission of inequality from the MDGs highlighted a gap in the global development agenda, which was subsequently addressed in the formulation of the Sustainable Development Goals (SDGs). The SDGs, adopted in 2015, explicitly include goals aimed at reducing inequality within and among countries, acknowledging the multifaceted impacts of economic disparities on social cohesion, political stability, and overall development. Fukuda-Parr (2019) and Fukuda-Parr and McNeill (2019) have provided detailed analyses of the politics and knowledge of how inequality was incorporated into the ambitious and transformative 2030 Agenda, but also ‘the slippage in ambition when targets and indicators were selected’, emphasizing both the importance of the shift in global policy focus from the MDGs to the SDGs, but also the compromises and dilution in how ambitious goals like the one on inequality were to be achieved through the choice of targets and indicators.3 Nevertheless, this recognition and inclusion of inequality in the SDGs marks a significant step towards addressing the challenges posed by economic disparities, reflecting a broader and more inclusive approach to global development.

Despite not being included in the SDG monitoring framework,4 one of the most popular indicators for measuring income inequality is the so-called “Gini coefficient”.5 It summarizes the extent of inequality in a single number. It can theoretically take any value between zero (perfect equality, that is, everybody has the same income within a defined population) and one (perfect inequality, that is, all income goes to a single person) (Luebker 2010).6 Figure 1 presents average Gini coefficient estimations based on income variables for regions and countries grouped by income levels for two comparable time periods, 2013–2017 and 2018–2022. Comparable income estimates are those collected through household surveys that have common characteristics within a given country, including with regard to the sampling frame, questionnaire, the methodological construction of the income variable and deflation of prices (Castaneda Aguilar et al. 2019; World Bank 2023).

Figure 1 shows that between the 2013–2017 and 2018–2022 the global Gini coefficient has decreased from 39.1 per cent to 37.9 per cent, corresponding to a reduction of 1.2 percentage points (pp).7 Over the same period and without exception across all regions and countries grouped by income,8 inequality has decreased. It is worth noting that in Asia and the Pacific a reduction of 1.7 percentage points in the Gini coefficient was observed between the two time frames, followed by Africa (1.4 pp), Americas (1.0 pp) and Europe and Central Asia (0.4 pp). When looking at the latest period (that is, 2018–2022), income inequality is highest in the Americas with a Gini coefficient of 44.4 per cent, followed by Africa (43.1 per cent), Asia and the Pacific (36.7 per cent) and Europe and Central Asia (33.1 per cent).

Across national income groups, low-income countries – represented in figure 1 by Gambia, Malawi, Mozambique and Uganda – experienced the largest decrease in inequality, or 2.3 pp of Gini coefficient. While in upper-middle-income countries the decrease was almost halved at 1.5 pp, in lower-middle-income countries it was 1.0 pp and in high-income countries 0.8 pp. When looking at the latest period, income inequality is highest in low-income countries with a Gini coefficient of 44.3 per cent, followed by upper-middle-income countries (39.5 per cent), lower-middle-income countries (36.2 per cent) and high-income countries (34.9 per cent).

Figure 1. Gini coefficient by region and income level, 2013–2022

Note: 77 countries representing 55 per cent of the global population. Averages for the 2013–2017 period are weighted with the 2017 population, while averages for the 2018–2022 period are weighted using the 2022 population. Percentage of population covered by each average: Africa (12.2 per cent), Americas (91.3 per cent), Asia and the Pacific (54.5per cent), Europe and Central Asia (92.4 per cent), low-income countries (14.0 per cent), lower-middle-income countries (28.7 per cent), upper-middle-income countries (92.3 per cent) and high-income countries (77.6 per cent). Country-level data are available in table A1 in the appendix. The data coverage for the Arab States is insufficient to produce a regional estimate.

Source: Authors’ calculations based on the World Bank PIP (2023).

For six countries, household survey data made it possible to track the yearly evolution of income inequality before and after the COVID-19 pandemic and during the cost-of-living crisis. Across all countries in figure 2, the Gini coefficient has decreased between 2013 and 2022. The largest decrease was experienced in El Salvador, which managed to decrease the Gini coefficient by 4.6 pp from 43.4 per cent to 38.8 per cent, followed by Paraguay (2.8 pp), Indonesia9 (2.5 pp), Costa Rica (2.0 pp), Brazil (1.4 pp) and Ecuador (1.4 pp).

Figure 2. Gini coefficient in selected countries, 2013–2022

Source: Authors’ calculations based on the World Bank PIP (2023) and for Brazil IBGEl PNAD Contínua (2022).

These moderate reductions in income inequality may have been possible owing to the global response in the area of social protection, which has at least partially countered the “disequalizing effects” of the COVID-19 pandemic (Subramanian 2023) and of the cost-of-living crisis. More than 1,900 measures were implemented in response to the pandemic by 211 countries and territories between January 2020 and September 2023 (ILO 2023d). Similarly, in response to the cost-of-living crisis countries and territories have adopted 356 measures since September 2021, most of them involving subsidizing or reducing the cost of necessities/utilities and increasing benefit levels (ILO 2023d). Yet, 182 of the 343 known cash benefit schemes in the world, representing more than half of all schemes for which we have data, do not have any clear indexation rule for benefits, leaving beneficiaries vulnerable to rising rates of inflation (ILO 2021d).

Nevertheless, the majority of these social protection measures were temporary, such as cash benefits to workers and their families, benefits to the poor or subsidies that were terminated after the emergency situation as part of austerity measures affecting an increasing number of countries (Kentikelenis and Stubbs 2023). It is important to highlight that while these short-term solutions may have temporarily reduced income inequality to some extent, overall inequality levels persist at alarmingly high rates. This becomes evident when examining household income distribution, which serves as a supplementary measure to the Gini coefficient (Chancel et al. 2022).

1.3. However, large disparities between top 10 per cent and bottom 50 per cent earners persist

Two additional key indicators are used to assess the level of income inequality within each country: the portion of disposable income10 held by households earning less than the 50th percentile (bottom 50 per cent) and the portion of disposable income held by households earning at, or above, the 90th percentile (richest 10 per cent). If all incomes were split equally (that is, in a hypothetical situation of perfect income equality) the bottom 50 per cent would capture 50 per cent of the national income in each country and the top 10 per cent would capture exactly 10 per cent of the national income. The evidence presented (figure 3) confirms that income inequality is stark or pervasive.

Globally there has been a reduction in inequality between the first period (2013–2017) and the second period (2018–2022) (figure 3). During this time frame, the portion of total income held by households in the lower 50th percentile (that is, the bottom 50 per cent) of the income distribution increased from 24.0 per cent to 24.9 per cent, while the share of income held by households earning above the 90th percentile (that is, the top 10 per cent) experienced a slight decrease from 30.3 per cent to 29.9 per cent. However, it is noteworthy that when looking at the latest period, the top 10 per cent of earners still controls more income than the bottom 50 per cent (or in terms of percentage points, a difference of 5.0 pp).

Regional dynamics concerning the household income distribution show moderate reductions in inequality between the two time periods, consistent with the analysis of Gini coefficient. It is worth noting that in the Americas, the top 10 per cent of earners still command a much larger share of income (34.2 per cent) than the poorest 50 per cent (20.9 per cent). This pattern is also seen in Africa and to a lesser extent in Asia and the Pacific. In contrast, in Europe and Central Asia the share of income held by the top 10 per cent (25.9 per cent) is slightly lower than the share of income held by the bottom 50 per cent (27.8 per cent). When we examine income distribution across different country income groups, low-income countries exhibit the highest income inequality, with the top 10 per cent of income earners controlling on average 35.8 per cent of total income, while the bottom 50 per cent of earners only hold 21.7 per cent, resulting in a significant 14.1 percentage point gap. This gap is halved in upper-middle-income countries (7.2 pp), decreases further in lower-middle-income countries (3.2 pp) and nearly disappears in high-income countries (0.2 pp). Nevertheless, the fact that 50 per cent of the population in some countries receives the same income share as the richest 10 per cent remains a challenging issue. In the following analysis, underlying factors of this situation are explored.

Figure 3. Share of income held by the bottom 50 per cent and top 10 per cent of earners by region and national income group, 2013–2022

Note: 77 countries representing 55 per cent of the global population. Averages for the 2013–2017 period are weighted with the 2017 population, while averages for the 2018–2022 period are weighted using the 2022 population. Percentage of population covered by each average: Africa (12.2 per cent), Americas (91.3 per cent), Arab States (5.2 per cent), Asia and the Pacific (54.5 per cent), Europe and Central Asia (92.4 per cent), low-income countries (14.0 per cent), lower-middle-income countries (28.7 per cent), upper-middle-income countries (92.3 per cent) and high-income countries (77.6 per cent). Country-level data are available in table A1 in the appendix. The data coverage for the Arab States is insufficient to produce a regional estimate.

Source: Authors’ calculations based on the World Bank PIP (2023).

The main causes of income inequality

2.1. Stagnating labour income share

High-income inequality is closely linked with the proportion of labour income in total income. Evidence shows that there is a strong association between the income inequality and the share of labour income in total income. Capital ownership is typically concentrated among those at the top of the income distribution and hence a higher share of capital income in total income leads to more income inequality (Dao et al. 2017). In 2020, the labour income share, only represented 53.8 per cent of the total income generated in the world (figure 4). The regional picture is mostly in line with the global one. For instance, the Americas had the largest share of income allocated to labour in 2020 (57.6 per cent), followed by Europe and Central Asia (55.7 per cent) and Asia and the Pacific (52.3 per cent). In Africa the labour income share was at 48.7 per cent in 2020, up from 44.5 in 2004. During the same period, the Arab States saw the most significant increase in labour income share among regions, rising approximately 7 percentage points to reach 36.6 per cent in 2020, potentially driven by growth in non-oil sectors and smooth energy transitions (IMF 2023).

The estimates in figure 4 show that except for the Arab States, labour income mostly stagnated between 2004 and 2020. There are several possible explanations for this trend, including the impact of technological changes, financialization, the enhanced exercise of market power by large firms in concentrated product markets, the decline in unionization rates and the consequent erosion of the bargaining power of workers, as well as persistent gender pay gaps (ILO, OECD, and ISSA 2023). ILO evidence further shows that real wages have declined owing to inflation and that wages are not keeping up with labour productivity: thus, in 2022 the gap between productivity growth and wage growth reached its widest point since the start of the twenty-first century, with productivity growth being 12.6 percentage points above wage growth (ILO 2022a). This creates a situation in which income is increasing but capital owners reap more benefits from such increases than labour owners.11 The labour income share has also stagnated because employment rates are not reverting to pre-pandemic levels, as weak economic conditions, lingering health problems and population ageing weigh on people’s return to the labour market (ILOSTAT 2023). With fewer people entering employment, there is an ensuing curb in labour income being generated. In addition, evidence from 36 mostly high-income countries suggests that automation-oriented technological progress could also be contributing to the decline in the labour income share (ILO 2024a).

2.1.1. Social security contributions in a changing labour market

The labour share of income constitutes the resource pool from which workers make their contributions into social security systems. These contributions into social security systems, along with employer contributions and taxes, are crucial for sustaining social security systems that, depending on their design, can smooth income across the life cycle and reduce income inequalities (ILO, OECD, and ISSA 2023).

ILO evidence shows that social contributions are one of the main sources of financing for social protection policy and have remained a stable source of financing in the twenty-first century, despite the stagnation and decline in the labour share of income (Cetrangolo and Calligaro 2023). Furthermore, unlike what is sometimes claimed (Levy 2008; UNDP 2021), there are no automatic employment or formalization gains associated with reducing social security contribution rates (Cetrangolo and Calligaro 2023). By contrast, appropriate and simplified mechanisms for collecting taxes and social contributions from certain types of enterprises and workers, such as monotax approaches, can promote the transition from the informal to the formal economy and increase revenue mobilization for social protection (see box 1).

Figure 4. Total income from wage and salaried work and self-employment as a percentage of GDP, 2004–2020

Source: Authors’ calculations based on ILOSTAT (2023).

Box 1. Monotaxes

In many countries, gaps in social protection coverage are often associated with high levels of informality that hold back decent work and socio-economic development. More than 50 per cent of the global employed population – some 2 billion men and women – make their living in the informal economy, mostly but not exclusively in developing countries. The majority of these workers are self-employed and do not have access to social protection, which makes them especially vulnerable to shocks (ILO 2023f).

There are many barriers to formalization. These obstacles include, among others, exclusion from legal coverage, lack of information regarding the benefits of registering for social security, costs associated with formalization and complex and burdensome administrative procedures (ILO 2021b). In order to simplify the latter, some governments have adopted unified payments mechanisms of taxes and social security contributions for some categories of micro and small enterprises (MSMEs) and own-account workers to pay one (monthly) flat payment instead of various instalments. These mechanisms are known as monotax schemes.

The level of contributions usually differs according to the category concerned. While participation in monotax mechanisms is typically voluntary, simpler procedures and, in some cases, subsidized contribution rates render this mechanism attractive to eligible categories of self-employed workers and microenterprises. The subsidization of monotax schemes aims to provide incentives for the formalization of enterprises, under the assumption that as these enterprises grow, they will be able to pay the regular level of tax and social security contributions at a later stage.

One of the major advantages of these mechanisms is that they facilitate the payment of social security contributions and taxes, while taking into consideration the limited administrative capacities of micro-entrepreneurs and micro and small enterprises (MSMEs), which can constitute a considerable barrier to formalization. Monotax mechanisms reduce the need to keep accounting records and facilitate the declaration of incomes and effecting of payments to different social security and tax subsystems.

Table B1 shows that monotax schemes are common in Latin America. Brazil was the first country to introduce the monotax schemes with the SIMPLES Nacional mechanism. This scheme has contributed to an increase in registration and more effective tax collection. Between its introduction in 2007 and 2012, the number of micro and small enterprises (MSMEs) registered nearly doubled from 2.5 million to 4.4 million. Studies also confirm that 32 per cent of entrepreneurs report that SIMPLES Nacional reduced their total tax burden. Tax revenues significantly improved, rising from 8.3 billion Brazilian Reals to 46.5 billion Brazilian Reals in the same period as more small firms joined the formal sector (ILO 2014). Similarly, in the Democratic Republic of the Congo, the monotax reform allowed the National Institute of Social Security to raise its revenues from 284 billion Congolese Francs in the 18 months prior to the reform to 327 billion Congolese Francs in the 18 months that followed it (that is, an increase in revenues of 15.1 per cent) (ILO 2021a; ILO 2018; ISSA 2017).

By contrast, evidence shows that monotax schemes, if not adequately designed, could lead to lower than expected increase in government revenues. In Colombia, a monotax scheme was introduced in 2016 and reformed in 2019. Evidence shows that affiliation outside the capital city of Bogota is still low. For example, in the municipality of Cúcuta, the large majority of shoemakers are not aware of the monotax scheme and even when its existence and the associated benefits are explained, they do not show eagerness to affiliate to the system, preferring instead to continue operating in the informal economy. One of the potential reasons for this is the application of the monotax rate on revenues without consideration of costs incurred by the small entrepreneurs. This feature made the monotax system in Colombia particularly disadvantageous during the COVID-19 crisis, when revenues of many small and medium enterprises were often below the costs during extended periods (Acosta Carrillo et al. 2022).

Table B1. Examples of monotax schemes by year of introduction

Country	Scheme name	Year of introduction
Argentina	Monotributo	2004
Brazil	Monotributo nivel Federal, régimen SIMPLES	1996 (first law), 2007 (current law)
Colombia	Régimen Simple de Tributación – RST	2016
Congo Democratic Republic	Guichet unique de dépôt des déclarations	2015
France	Régime de l’autoentrepreneur	2009
Honduras	Monotributo, Régimen Simplificada, Impuesto a las Ventas	2003
Uruguay	Monotributo	2001

Source: Authors’ elaboration.

2.2. Labour market informality

The relationship between income inequality and informality is complex and can vary across different countries and contexts. However, when looking at the global picture, empirical evidence shows that countries with a higher proportion of informal employment in total employment are also those where income inequality is higher. The correlation between income equality and the informality rate is strong and negative at minus 40 per cent (figure 5).

Of course, correlation does not imply causation. The theoretical and empirical literature encountered challenges in analysing the relationship between inequality and informality as evidence points at the causality working in both directions. Some argue that high levels of income inequality can contribute to the growth of the informal sector. In societies with significant income disparities, individuals may turn to informal economic activities as a survival strategy, particularly if they face barriers to entering the formal economy (Dell’Anno 2021). Informality may reduce inequality by providing employment and livelihoods to those who might otherwise have remained unemployed or outside the labour force, especially young people and women from poorer households (UNECA 2018).

By contrast, over time, informality itself can be a driver of income inequality. Jobs in the informal sector often lack the benefits and protections associated with formal employment, leading to a widening gap in income between formal and informal workers. ILO evidence supports this finding as informal wage workers earn far less than formal wage workers. Globally, the earnings of workers in informal wage employment are 56 per cent of the earnings of wage workers in the formal economy (ILO 2023f).

Given the lower earnings of workers in the informal economy, they may lack sufficient contributory capacity to affiliate to social insurance mechanisms. Some groups of informal wage workers and some self-employed workers who have limited contributory capacity and no employer, may require subsidies to be able to affiliate to social insurance. One of these groups is that of unpaid contributing family workers, who are considered informal workers and in most cases have very low or no contributory capacity. Achieving universal social protection for all requires a combination of contributory and non-contributory (tax-financed) social protection mechanisms. Recommendation No. 202 sets out that access to essential healthcare and basic income security over the life cycle should be guaranteed as part of nationally defined social protection floors and that higher levels of protection should be progressively achieved by national social security systems in line with Convention No. 102 and other ILO instruments (ILO 2021b).

Figure 5. Income equality and proportion of informal employment in total employment, latest available year

Note: 124 countries.

Source: Authors’ calculations based on World Bank PIP (2023) and ILOSTAT (2023).

2.3. Low intergenerational social mobility

The stagnation of labour income share in total income over the past 15 years and high rates of informality reinforce each other and impair intergenerational social mobility, thereby contributing to the current high levels of income inequality. Equality of opportunity and equality of outcome are often correlated.

Figure 6 compares the relative poverty headcounts of adults12 who were living in households facing financial hardship when they were 14 years old with the poverty headcounts of those of the same age from families in favourable financial circumstances. In a scenario of perfect income equality, poverty headcounts would align along the 45 degree line. This implies that the current poverty status of adults would be unrelated to the financial circumstances of their families when they were 14 years old. Yet, among the 33 European Union countries with available data, disparities in poverty headcounts between those from poorer households and those from affluent families exceed 5 percentage points in 21 countries. Notably, in five countries,13 this difference is at or surpasses 15 percentage points. This means that in these five countries, individuals from poorer households are 15 percentage points more likely to be poor when they grow up compared with those from affluent families.

Figure 7 illustrates income inequality (measured by the Gini coefficient) with the difference in poverty headcounts between adults from poorer and their counterparts from affluent backgrounds. The scatter plot shows that intergenerational social mobility decreases in countries with higher income inequality and, conversely, it increases in countries with lower inequality, a relationship known as the Great Gatsby Curve (ILO 2021c; Durlauf et al. 2022; Nybom 2018; Corak 2013). In other words, when the gap between the rich and the poor is wider, it becomes more difficult for individuals to move up or down the socio-economic ladder across generations. This implies that in more unequal societies, the economic position of parents is a strong predictor of their children's economic status. In fact, providing real equality of opportunity is a radical proposition that demands a serious policy effort to level the playing field – not something that can be done easily when outcomes are highly unequal. In fact, high levels of inequality make it much harder to ensure equal opportunities for the new generation. As mentioned earlier, “if we are concerned about equality of opportunity tomorrow, we need to be concerned about inequality of outcome today” (Atkinson 2015). The persistence of income inequality through generations makes an even stronger case to act against inequalities of outcomes through social protection policies.

However, it is also crucial to understand that the Great Gatsby Curve reflects a statistical correlation and does not suggest a direct cause-and-effect connection. Additionally, restricted intergenerational social mobility may further entrench income inequality, particularly in situations where significant disparities exist in the ownership of wealth.

Figure 6. Poverty headcount of adults (aged 25 to 59 years) by level of financial situation of their households when respondent was 14 years, 2019

Notes: 33 countries. Poverty headcounts are defined by Eurostat as “at-risk-of-poverty rate”. They represent the share of people with an equivalized disposable income (after social transfers) below the at-risk-of-poverty threshold, which is set at 60 per cent of the national median equivalized disposable income after social transfers.

Source: Authors’ calculations based on Eurostat (2023).

Figure 7. Difference between poverty headcounts of adults that were living in families with a bad financial situation when they were 14 years old and those that were living in families with a good financial situation and income inequality (Gini coefficient (%)) and, latest available year and 2019

Note: 33 countries. See note to figure 6.

Source: Authors’ calculations based on World Bank PIP (2023) and Eurostat (2023).

2.4. Widening wealth inequalities

Limited intergenerational social mobility may well reflect wealth14 inequality and both exacerbate income inequality (figure 8). This is not surprising since evidence shows that the wealthy save more than the poor and that they benefit from higher rates of return on their investments. This is also known as the snowballing effect of capital accumulation: the more one possesses today, the more one can accumulate tomorrow (Chancel et al. 2022). The levels of wealth inequality are also increasing over time in some countries. This is especially true in high-income countries, where population growth is curbing and where wealth is transferred along kinship lines through bequests or inter vivos transfers (Pfeffer, Killewald, and Siliunas 2016). Moreover, wealth inequalities across racial/ethnic groups further exacerbate overall wealth inequalities. For instance, in the United States, the wealthiest 10 per cent of the population held 72.1 per cent of national wealth in 1995 (LWS 2023) and 79.4 per cent in 2019 (figure 8). Similarly, Estonia, Finland, Greece, Italy, Slovakia, Spain and the United Kingdom displayed increasing wealth inequality trends (LWS 2023). This phenomenon was accelerated during the COVID-19 crisis, while national income fell, the value of private wealth increased and this increase was particularly extreme among billionaires. For this reason, there is a renewed interest in introducing wealth taxes to finance social protection programmes (Chancel et al. 2022). A remarkable example is Argentina, which, in 2020, introduced an ad-hoc wealth tax in response to the economic troubles caused by the COVID-19 pandemic, to be paid by the 12,000 richest individuals residing in the country. It was expected to generate US$3.5 billion in revenues that would be used to finance healthcare and social protection but also foster small and medium enterprises (SMEs), education and natural gas exploitation (Malax-Echevarria 2021). In May 2021, the government announced that the new levy had collected 223.000 millions of pesos, with an 80 per cent compliance rate (El Cronista 2021).

Figure 8. Share of wealth held by the top 10 per cent and Gini coefficient (%), latest available year

Note: 15 countries. See Table A2 for country-level data.

Source: Authors’ calculations based on LWS (2023) and on World Bank PIP (2023).

2.5. The role of economic ideas

John Maynard Keynes (1936, p. 383) once remarked, ‘the ideas of economists and political philosophers, both when they are right and when they are wrong are more powerful than is commonly understood. Indeed, the world is ruled by little else’. But, as Fukuda Parr and McNeill (2019) rightly ask, which ideas rule?

High levels of current income inequality can be attributed, in part, to government decisions influenced by economic theories. One key proponent of such theories is Arthur Okun (1975), who coined the term "big trade-off" to describe the negative relationship between equality and efficiency. Okun used the metaphor of a "leaky bucket" to illustrate income redistribution: as money moves from the rich to the poor, some resources inevitably seep out. He, along with subsequent theorists, proposed an efficiency-equity trade-off, suggesting that governments must decide whether a larger, unequally distributed “social pie” is preferable to a more equally distributed, albeit smaller, one. Another very influential economist, Simon Kuznets, theorized in the 1950s that some level of inequality was not only inevitable, but also necessary for economic growth in the early stages of development. According to Kuznets, inequality would subsequently decrease once the national economy reached a sufficient size (Kuznets 1955). This relationship came to be known as the “Kuznets curve”, though it has been challenged and refuted multiple times since then.

However, some of these theoretical assumptions have been questioned by empirical evidence. Figure 9 shows that countries with high levels of income inequality (that is, an unequally distributed “social pie”) are also those where GDP per capita is lower (that is, smaller “social pie”). The moderately strong and negative correlation between income inequality and GDP per capita suggests the lack of such a “big trade-off” between equality and efficiency. Econometric studies have long tried to explore the existence of such trade-offs; the results, however, are inconclusive (De Dominicis et al. 2008). The International Monetary Fund has highlighted a key reason for inconclusive findings in various studies, which is that many of them overlook the inequality of opportunity. This omission tends to bias empirical estimates regarding the connection between equity – proxied with the Gini coefficient – and efficiency – proxied by GDP per capita growth. The researchers discovered that less equity negatively affects efficiency, particularly in economies with low equality of opportunity, as indicated by intergenerational mobility measurements (Aiyar and Ebeke 2019). Additionally, an important piece of research published by the IMF has shown that 1) lower inequality is correlated with faster and more durable growth; and that 2) the effects of redistributive policies are in most cases supporting economic growth rather than hindering it (Ostry et al. 2014).

A different line of criticism of the “big trade-off” has come from heterodox economists who have criticized the presumed trade-off between efficiency and equity from a political economy perspective. Certain dominant groups (e.g. men, capitalists, white supremacists), they argue, may support inefficient institutions that protect their relative share of income – even if these inefficiencies mean total income is smaller. This is illustrated by historical under-investment in education and healthcare services that are inclusive of women and people of colour, despite their adverse impact on economic growth and dynamism (Folbre 1994).

Figure 9. GDP per capita and income inequality (Gini coefficient (%)), latest available year

Note: 161 countries.

Source: Authors’ elaboration based on World Bank WDI (2023) and on the World Bank PIP (2023).

The role of social protection in reducing income inequality

3.1. Higher social protection expenditure lowers income inequality

Empirical evidence presented in the previous section has indicated that countries with higher income inequality are also those with lower GDP per capita. While countries with lower GDP per capita often experience higher GDP growth rates (since they start from a lower base), it is evident that economic growth alone does not guarantee improved living standards, nor does it promote economic or social development (OECD 2019).

Generally, countries that allocate a higher proportion of GDP to social protection (excluding health) also exhibit greater income equality (figure 10), with the correlation between the two variables being positive and strong. Similarly, higher government health expenditure as a proportion of GDP is associated with more income equality (figure 11), although the correlation is not as strong as observed for social protection (excluding health).

These correlations underscore that social protection, beyond being a fundamental human right, serves as a potent tool for income redistribution. In the next section, we present evidence on the magnitude of the redistributive effect of taxes, social security contributions and different social protection benefits.

Figure 10. Income equality (100-Gini coefficient (%)) and social protection expenditure (excluding health), latest available year

Note: 159 countries.

Source: Authors’ elaboration based on World Bank PIP (2023) and ILO (2024b).

Figure 11. Income equality (100-Gini coefficient (%)) and domestic general government health expenditure as percentage of GDP, latest available year and 2021

Note: 161 countries.

Source: Authors’ elaboration based on World Bank PIP (2023) and WHO Global Health Observatory (2024).

3.1.1 A methodological overview

This section provides a description of the methodology and the data used to assess the partial redistributive effects achieved by taxes, social security contributions and different social protection benefits. Central to all assessments of welfare state outcomes is the chosen framework for examining the dynamics of income redistribution. In this section, the impact of social protection transfers, taxes and social security contributions on income inequality is calculated using a similar methodology to the one presented in (Caminada et al. 2019; Caminada et al. 2017). The aim of this exercise is to obtain the redistributive effect, namely the reduction in income inequality of each social protection benefit, as well as of different taxes and social security contributions. The Gini coefficient in each country (c) is used as a measure of income inequality and it is expressed as follows:

$G i n i_{c} = 1 + \frac{1}{n_{c}} - [\frac{2}{n_{c}^{2}} μ_{c}] \sum_{i = 1}^{n} (n_{c} - i_{c} + 1) y_{c i}, i_{c} = 1 \dots n_{c} [1]$

Where:

$n_{c}$ is the population living in country c

$μ_{c}$ is the average income of the n persons living in country c

$y_{c i}$ is the income of survey respondent i living in country c

As specified in table 1, based on the variables availabe in the Luxembourg Income Study microdata,15 three distinct income categories are computed to gauge the influence of social protection benefits, taxes and social security contributions on income inequality. Market income comprises earnings from labour, capital, private pensions and private transfers. Gross income is the sum of market income and social protection transfers. Deducting taxes and social security contributions from gross income yields disposable income. This study evaluates the impact of various social protection transfers – contributory and non-contributory pensions, family benefits, unemployment benefits, sickness and employment injury benefits and disability benefits – on income inequality.

Since a household’s income also supports the well-being of children and other household members who have no income of their own, it is important to adjust income for household size. In this working paper, household income is adjusted using the square root of household size. This implies that a household of four persons, for instance, has needs twice as large as one composed of a single person. While this is a useful adjustment, it overlooks inequality within households, and it underestimates the amount of household resources (both money and time) that children need, especially at younger ages. It is not possible to determine each household member’s say in income allocation or his or her share. To ensure comparability across different countries, the current analysis operates under the assumption that income is distributed equitably among members within a household. This assumption stems from the limitations in the questionnaire used in income and expenditure surveys in many countries, which do not facilitate a detailed individual-level analysis of how income sources are distributed among household members and who has a say on those income sources.

Equation 1 is then used to decompose the Gini coefficient of disposable income into the Gini coefficient of market income, and to assess the redistributive effects of transfers, social security contributions and taxes. Thus, $y_{c i}$ , the disposable income of survey respondent $i$ living in country $c$ , can be rewritten as:

$y_{c i} = y_{c i}^{m k} + \sum_{b = 1}^{n} B_{b c i} - \sum_{t = 1}^{s} T_{t c i} [2]$

Where:

$y_{c i}^{m k}$ is the market income earned by survey respondent $i$ living in country $c$

$B_{b c i}$ is the social protection benefit $b$ by survey respondent $i$ living in country $c$ . With benefit $b$ being contributory and non-contributory pensions, family benefits, unemployment benefits, sickness and employment injury benefits and disability benefits.

$T_{t c i}$ is the tax or social security contribution $t$ paid by survey respondent $i$ living in country $c$

Table 1. The income redistribution framework

Source: Authors’ illustration.

Equation 2 makes it possible to calculate income inequality with, and without, a certain benefit or tax and consequently to estimate the partial redistributive effect of that tax or transfer. However, it must be noted that such an approach ignores the behavioural changes that can be generated by the introduction of a given social protection benefit, for example a reduction in labour supply of persons aged above 65 years, when a non-contributory old-age pension is typically introduced. However, to date models that include all behavioural links are beyond the scope of existing empirical literature on decomposition of income inequality (Caminada et al. 2017). Moreover, disentangling the inequality by income source could be affected by the order in which social protection benefits are added to the market income. To correct for this, each social protection benefit ( $B_{b c i})$ is considered as the first programme to be added to the market income ( $y_{c i}^{m k})$ and a Gini coefficient $G i n i_{m k c + B_{b c}}$ is estimated. Each social protection transfer ( $B_{b c i})$ is then subtracted from the gross income $y_{c i}^{g r o s s}$ and Gini coefficient $G i n i_{g r o s s c - B_{b c}}$ is estimated. In turn, the two effects are averaged [7]. This methodology, which is an adaptation of a methodology widely employed in the empirical literature (Caminada et al. 2017; Caminada et al. 2019), is detailed in Steps 1-3 below.

Step 1: Calculate the percentage change in the Gini coefficient based on market income for each benefit $B_{b c}$

$G i n i_{m k c} ∙ (1 + % c h a n g e G i n i_{m k c + B b c}) = G i n i_{m k c + B b c} [3]$

$% c h a n g e G i n i_{m k c + B b c} = \frac{G i n i_{m k c + B b c} - G i n i_{m k c}}{G i n i_{m k c}} ∙ 100 [4]$

Step 2: Calculate the percentage change in the Gini coefficient based on gross income for each benefit $B_{b c}$

$G i n i_{g r o s s c - B b c} ∙ (1 + % c h a n g e G i n i_{g r o s s c - B b c}) = G i n i_{g r o s s c} [5]$

$% c h a n g e G i n i_{g r o s s c - B b c} = \frac{G i n i_{g r o s s c} - G i n i_{g r o s s c - B b c}}{G i n i_{g r o s s c - B b c}} ∙ 100 [6]$

Step 3: Compute the mean between equation 4 and 6. This mean represents the average partial redistributive effect of benefit $B_{b c}$ [7].

$% c h a n g e G i n i_{B b c} = \frac{% c h a n g e G i n i_{m k + B b c} + % c h a n g e G i n i_{g r o s s c - B b c}}{2} [7]$

Similarly, for taxes and social security contributions $T_{t c}$ , steps 1-3 can be rewritten as follows:

Step 4: Calculate the percentage change in the Gini coefficient based on market income for each tax $T_{t c}$

$G i n i_{m k c} ∙ (1 + % c h a n g e G i n i_{m k - T t c}) = G i n i_{m k c - T t c} [8]$

$% c h a n g e G i n i_{m k c - T t c} = \frac{G i n i_{m k c - T t c} - G i n i_{m k c}}{G i n i_{m k c}} ∙ 100 [9]$

Step 5: Calculate the percentage change in the Gini coefficient based on disposable income for each tax $T_{t c}$

$G i n i_{d i s p c + T t c} ∙ (1 + % c h a n g e G i n i_{d i s p c + T t c}) = G i n i_{d i s p c} [10]$

$% c h a n g e G i n i_{d i s p c + T t c} = \frac{G i n i_{d i s p c} - G i n i_{d i s p c + T t c}}{G i n i_{d i s p c + T t c}} ∙ 100 [11]$

Step 6: Compute the mean between equation 9 and 11. This mean represents the average partial redistributive effect of each tax $T_{t c}$ [12].

$% c h a n g e G i n i_{T t c} = \frac{% c h a n g e G i n i_{m k - T t c} + % c h a n g e G i n i_{d i s p c + T t c}}{2} [12]$

The survey microdata used for estimating the partial redistributive effect of social protection benefits and taxes come from the Luxembourg Income Study (LIS) Cross-National Data Centre in Luxembourg. The LIS provides the largest available income database of harmonized microdata collected throughout the world, in 53 countries.16 Harmonized into a common framework, LIS datasets contain household and individual-level information on labour income, capital income, as well as a detailed account of social protection and private transfers, taxes and social security contributions (LIS 2023). The disadvantage of the LIS database is its limited coverage of developing countries, though efforts have been and are being made to expand the scope. The LIS contains data from household surveys, which only collect data on total income at the household level. Because of this factor, it is not possible to determine each household member’s share in how income is allocated within the household and it is therefore impossible to measure inequalities within households. Therefore, to ensure comparability across different countries, the current analysis operates under the assumption that income is equitably distributed among members within a household—admittedly, a heroic Beckerian assumption that has received ample criticism from feminist economists who have documented considerable intrahousehold inequalities in the distribution of resources and well-being.

3.2. Contributory pensions have the largest effect in reducing income inequality compared to other social protection benefits

This section reviews country-level evidence regarding the partial redistributive effects of individual social protection benefits. Figure 12 showcases the outcomes derived from the estimation outlined in equation 7. Simply put, it shows the size of the impact of each social protection benefit on income inequality, measured as the percentage change in the Gini coefficient after introducing each social protection benefit. The following partial redistributive effects, based on the LIS household income component, are estimated: contributory pensions, non-contributory pensions, family benefits, unemployment benefits, sickness and employment injury benefits and disability benefits. For a detailed description of the variables see Table A3 in the Appendix.

Figure 12.1 shows that the largest reductions in income inequality are observed for contributory pensions.17 In 18 out of 35 countries with available data, such pensions reduce the Gini coefficient by more than 15 per cent and in Czechia, Poland, Serbia, and Hungary by at least 30 per cent. This result is not surprising: contributory pensions are often the most important social protection benefit, in terms of both duration and size of the benefit itself. Non-contributory pensions also produce a substantial reduction in income inequality but to a lesser extent. In 25 out of 35 countries with available data, non-contributory pensions are responsible for a reduction in income inequality below 4 per cent. Only in Denmark, Georgia and Switzerland do such pensions contribute to a reduction in income inequality that is above 15 per cent (figure 12.2).

Family benefits are responsible for lower reductions in income inequality compared to pensions. Figure 12.3 shows that reductions in the Gini coefficient are at the highest level in Poland with 9.1 per cent but remain well below 5 per cent in 38 out of 41 countries with available data. Similarly, of the 36 countries with available data on unemployment benefits (figure 12.4), only in four countries – Finland, France, Ireland and Austria – do such benefits contribute to reducing income inequality by more than 4 per cent. The income redistribution achieved through sickness and employment injury benefits (figure 12.5), with disability benefits (figure 12.6) and with social assistance programs (figure 12.7) is also limited. For example, in the case of disability benefits, reductions in the Gini coefficient are around 2 per cent or more in Belgium, Iceland, Ireland, Lithuania, Spain and the United Kingdom, while with sickness and employment injury benefits (figure 12.5), inequality reductions remain below 1 per cent in all countries except in Denmark (1.1 per cent), Sweden (1.8 per cent) and in Norway (4.2 per cent).

The right part of figure 12 shows the percentage of expenditure on a given benefit as proprotion of total gross income from surveys. It further corroborates the findings by showing that, on average, countries that spend more on a given benefit are also those that obtain a larger reduction in income inequality as a result of such a benefit. However, there are exceptions both, a closer look at the estimates of figures 12 reveals that there is not a one-to-one relationship between public expenditure on a given social protection benefit and the reduction in income inequality generated by such expenditure. For example, Mexico spends only 2.3 per cent of total gross income on non-contributory pensions and this expenditure produces a reduction in income inequality of 2.8 per cent (figure 12.2), but spends 7.8 per cent of total gross income on contributory pensions generating a reduction of income inequality of 2.3 per cent (figure 12.1). When comparing countries, Greece spends more on contributory pensions than Belgium, but it achieves a lower reduction in income inequality with such pensions. These results are not only driven by the underlying income distribution in each country, but they are also explained by the design of each pension system and by the management of public finances in each country.18

Figure 12. Partial redistributive effects of individual social protection benefits measured as percentage changes in the Gini coefficient, latest available year

Public contributory pensions, 35 countries

Public non-contributory pensions , 35 countries

Family benefits , 41 countries

Unemployment benefits , 35 countries

Sickness and employment injury benefits , 27 countries

Disability benefits , 22 countries

Social assistance , 44 countries

Note: Social assistance includes general assistance, housing benefits, public in-kind benefits.

Source: Authors’ calculations based on LIS (2023).

3.3. Personal income taxes have the largest effect in reducing income inequality compared to other taxes

This section reviews country-level evidence regarding the partial redistributive effects of social security contributions,19 personal income taxes20 and wealth taxes.21 Figure 13 showcases the outcomes derived from the estimation outlined in equation 12. In all the 25 countries with available data – except in Ireland and in the Occupied Palestinian Territory – income taxes lead to a reduction in overall income inequality (figure 13.1). However, such reductions are much lower than the ones observed for social protection benefits. In 14 out of 25 countries, the Gini coefficient is reduced by less than 5 per cent after income taxes are taken into consideration. Only in Germany, Finland and Israel do income taxes generate a reduction in income inequality higher than 10 per cent.

Social security contributions play a key role in financing social protection and attempts to reduce social security contributions rates could dampen the reduction in financing gaps and undermine the capacity of governments to comply with payment schedules of social security benefits (Cetrangolo and Calligaro 2023). However, when the payment of social security contributions is factored in, certain countries display an increase in income inequality, which is potentially due to the “single-rate” nature of social security contribution rates (figure 13.2). These increases in income inequality are more than offset by the reduction of income inequality that is generated through the payment of contributory social protection benefits. It should be noted that Switzerland, whose social security system is heavily reliant on a private sector second pillar, displays the highest increase in the Gini coefficient induced by social security contributions. At the other extreme, the largest reduction in income inequality is generated in Colombia (2.5 per cent).

With increasing wealth inequalities,22 the debate on progressive wealth taxation23 is gaining momentum. However, progressive wealth taxes remain an exception to the rule rather than the norm across the world. Property taxes – and their equivalent in various countries, such as the taxe foncière in France – are by far the largest component of total wealth tax revenue: they typically account for 80–100 per cent of total tax revenue on individual wealth (Chancel et al. 2022). The flat-rate nature of property taxes, in sharp contrast to modern progressive income and wealth taxes, is one of the main reasons why their redistributive effect is almost nil (figure 13.3), meaning that they turn out to be regressive.

When analysing tax revenues as a proportion of total gross income from surveys,24 revenues from wealth taxes are the lowest when compared with income taxes and social security contributions. Similar to what was observed with regard to social protection benefits, governments that are able to generate larger revenues from income taxes are also those which are able to achieve greater reductions in inequality through income taxes (figures 12 and 13). However, a closer look at the information shows that countries with similar income tax revenues as a proportion of total gross income achieve different redistributive impacts due to the different design of their tax systems. For example, in the United States personal income taxes represent 15.0 per cent of total gross income, while in Sweden they represent 19.7 per cent. Despite having a lower tax to total gross income ratio stemming from income taxes, the United States in 2021 was able to reduce income inequality through income taxes by 8.6 per cent, while Sweden only achieved a reduction of inequality of 5.0 per cent in the same year. However, when considering taxes, social security contributions and benefits, Sweden achieves a remarkable income redistribution of 36.3 per cent, while the United States’s tax and social protection system reduces inequality by 28.2 per cent (figure 14). This underscores the importance of looking at both taxes and social expenditure, as shown in figure 14.

Figure 13. Reduction of inequality (percentage change of Gini coefficient) through social security contributions and taxes, latest available year

Personal income taxes, 25 countries

Social security contributions, 22 countries

Wealth taxes, 20 countries

Source: Authors’ calculations based on the Luxembourg Income Study (LIS).

Figure 14. Reduction of inequality (Gini coefficient) through social security transfers and taxes, selected countries, latest available year

Note: Data available for 52 countries.

Source: ILO, 2024b.

3.4. Taxes, social security contributions and social protection benefits reduce gender income inequality

While data on social protection coverage and adequacy of benefits disaggregated by sex have been scarce, the latest World Social Protection Report marks a significant watershed.25 The latest ILO evidence suggests that social protection coverage still shows significant gender inequalities, with the effective coverage of women by at least one social protection benefit lagging behind that of men by 4.5 percentage points (50.1 and 54.6 per cent respectively), especially in middle-income countries. Looking at old-age pensions at the global level, 63.2 per cent of men above statutory retirement age are receiving a contributory pension, whereas this percentage drops to 49.2 per cent for women. This is in large part a reflection of historical gender inequalities in employment patterns and linked to that, of differential responsibilities for the unpaid provision of care for their households: in other words, they reflect gender inequalities that were present at the time that persons above the retirement age today were in working-age. In fact, in most regions and subregions, older women are less likely to receive a contributory pension than men. However, in most regions, women are more likely than men to receive a non-contributory (tax-financed) pension. At the global level 34.2 per cent of women above statutory retirement age receive a tax-financed pension compared to 26.9 per cent of men (ILO 2024b). While tax-financed benefits play an important role in guaranteeing at least a basic level of social security for all as part of a social protection floor, social insurance coverage is also essential, since it can provide more adequate benefits and greater potential for broad risk sharing and redistribution to offset gender inequalities in the labour market compared to other contributory mechanisms.

Despite the low coverage rates, figure 15 shows that, without exception, when taxes and social protection transfers are included, gender income inequality is reduced, though the extent of change varies across countries.

Figure 15. Average women’s personal income as a percentage of men’s before transfers (market income) and after transfers (disposable income), persons aged 25+ years, 2018–2022

Note: 30 countries.

Source: ILO calculations based on the Luxembourg Income Study (LIS) Database.

Figure 16 provides further evidence that social protection transfers are fundamental to help fighting poverty while also tackling income inequalities between genders. This figure shows how impactful social protection transfers can be on the poverty rates of single mothers. Single-parent families are a particularly vulnerable population group and single-mother households make up most of this category. It is very important to show that social protection benefits not only reach the vulnerable populations, but that they are also effective in lifting them out of poverty. Of course, the extent to which the poverty rates are reduced vary widely across countries, emphasizing that there are several factors that can improve or reduce the effectiveness of these transfers. In particular, it is important to note that most of the countries represented below are high-income or upper-middle-income economies due to data availability. It is hence critically important to repeat a similar analysis in low-income and lower-middle-income countries using available household surveys that are not currently included in the LIS.

Figure 16. Poverty rates among single mothers pre- and post-transfers, percentage of single mothers, persons aged 18 years or above, 2018–2022

Note: 30 countries. The poverty line is set at one half of national median equivalent disposable income among all persons aged 25–54 years.

Source: ILO calculations based on the Luxembourg Income Study (LIS) Database.

Conclusion

Before concluding, it is fitting to delineate the existing state of social protection on a global scale. A little over 47 per cent of the world’s population is without any form of social protection benefit. Under-investment in social protection continues to be one of the main reasons for the low coverage rates. Public expenditure on social protection (excluding healthcare) was on average 12.9 per cent of GDP worldwide (around 2023) (ILO 2024b). The ILO estimates the financing gap for extending a Social Protection Floor to all in low-and middle-income countries to be US$1.4 trillion or 3.3 per cent of GDP (2024) (Cattaneo et al. 2024).

The evidence presented in this paper has shown that filling these gaps can significantly reduce income inequalities. Contributory pensions are responsible for the lion’s share of income inequality reductions, followed by non-contributory pensions, family benefits, unemployment benefits, sickness and employment injury benefits, as well as disability benefits. This fact can be attributed to the size and stability of contributory systems and especially contributory pensions, vis-à-vis smaller non-contributory benefits. However, it does not mean that these benefits are less important than contributory pensions: in fact, they are still very relevant to fighting poverty and inequality and to reaching the overall objectives of social protection systems. Furthermore, as already mentioned, the data on which this analysis is based comes mainly from high-income and upper-middle-income countries. This means that in lower-income countries, where contributory systems require more efforts to be established or where they cover a smaller share of the population, non-contributory benefits could have a significant impact on reducing income inequality.

Nevertheless, given the persistently high levels of income inequality and the strong potential of social protection in reducing such inequalities, there is a consensus on the imperative to establish universal social protection systems. This necessity has been further underscored by the compounding health and climate crises, as well as protracted conflict that continue to unfold. But how can universal social protection be established?

Focus on building universal social protection systems

There is a significant body of literature analysing whether welfare regimes that target benefits to people with low incomes produce better redistributive outcomes than welfare regimes grounded in universal approaches. Most studies indicate that levels of inequality are lower in countries with universal approaches (Stampini et al. 2023; Korpi and Palme 2000; Gugushvili and Laenen 2021; ILO 2021d).

One explanation for this outcome is that more universalistic approaches are better able to mobilize support from the general public across all income levels and that, as a result, redistributive budgets are larger in countries where universal approaches prevail. For example, Gaspar et al. (2016) emphasize the importance of a sense of fairness: if citizens believe that sufficient public goods are being provided in return for the taxes they pay and others also pay their fair share, they are more willing to comply. They point to the importance of constitutive institutions, inclusive politics and credible leadership for the building of tax capacity, which would apply also to building universal social protection systems.

However, it would be misleading to assume that there is no role for targeted or means-tested schemes within a broader universal system, though it is critical that means-tested schemes be rights-based, with clear eligibility criteria to ensure that those who are entitled to the benefits actually receive them. Nor are tax-financed and contributory schemes mutually exclusive options. In fact, a systems approach means combining both financing modalities to create a multi-tiered social security system with a view to achieving universal life cycle guarantees. The main objective of social protection policies and programmes should ultimately be to realize the human right to social security. In practice, this requires that the system, entitlements, and eligibility criteria are established under domestic law, and public authorities take responsibility for the administration or supervision of the system, including by ensuring that those who are eligible for the benefits have a right to receive them when needed by making the financial resources available and by establishing effective and accessible complaints and redress mechanisms.

Pursue a two-dimensional strategy, including a focus on work-related provisions

The ILO Social Protection Floors Recommendation, 2012 (No. 202) urges States to pursue and implement policies aimed at securing universal, comprehensive and adequate protection, prioritizing national social protection floors as the fundamental element of their social security systems in order to guarantee at least a basic level of social security to everyone. Importantly, the Recommendation urges governments to go beyond mere ad hoc and fragmented approaches towards establishing universal rights-based systems that are reliable and anchored in national legislation.

The Recommendation also very usefully envisions a two-dimensional strategy (figure 17), urging countries to guarantee at least basic levels of income security and access to essential healthcare for all (the social protection floor as the horizontal dimension) and to progressively secure higher levels of protection for as many persons as possible and as soon as possible (the vertical dimension).

Figure 17. Effective national social security extension strategies: Building comprehensive systems (normative basis: Social Protection Floors Recommendation, 2012 No. 202)

Source: ILO (2012).

Explore all available fiscal space options for extending social protection coverage26

It is widely understood that domestic resource mobilization must remain the foundation for building universal social protection systems, working in tandem with employment policies and investments in essential public services, as a core element of a social contract between states and their citizens. Taxes and social security contributions constitute the lifeline of sustainable and equitable social protection systems that can provide adequate protection to everyone.

However, in a highly globalized world, it is misleading to see domestic resource mobilization efforts disconnected from the global economic and financial architecture within which developing countries are operating. Over the past 20 years, domestic resource mobilization efforts of developing countries have been eroded not only by the extensive informality of enterprises and employment and their smaller tax bases, but also by declining tariff revenue due to trade liberalization, competitive pressures to lower corporate taxes and rising debt service burdens, among others (UNDESA 2024).

Taxes which have greater potential for progressive redistribution, such as personal income tax and corporate tax rates, have been de-prioritised, while regressive indirect taxes, such as value-added tax, are expanding. In addition to lower direct taxes, illicit financial flows by multinational corporations are estimated to deprive developing countries of between USD 50 billion to USD 200 billion a year in fiscal revenues, while other estimates suggest that the combined global revenue losses from cross-border tax abuse by people with undeclared offshore assets and of multinational companies amount to some USD 483 billion a year (UNRISD 2022). The recently concluded agreement on a globally-aligned minimum tax rate of 15 per cent on multinational corporations (OECD 2024), despite some loopholes, could serve to retain domestic resources in the countries where firms are operating. Another proposal, already presented to a finance track meeting of the Group of Twenty (G20), seeks to negotiate an international agreement to impose a two per cent wealth tax on the 2,500 billionaires in the world today (G20 2024).

At the same time, with global interest rates at a four-decades high in inflation-adjusted terms,27 the alarming surge in global public debt, driven by cascading crises, has meant unsustainable debt servicing costs for developing countries (UNCTAD 2024). Twenty-five developing countries allocate more than a fifth of their total revenue to servicing their public external debt alone, crowding out SDG financing, and more than half of all Least Developed Countries and other Low-income countries are assessed as either at high risk or already in debt distress (UNDESA 2024). As a result, numerous countries now find their interest payments on debt exceeding what they spend on social protection. In Latin America and the Caribbean, for example, the rise of interest payments between 2012 and 2021 curtailed spending on key public services and contributed to a decline in public investment (UNECLAC 2023).

Last, but not least, many developing countries have less access to contingency financing during crises, which limits their ability to respond to and recover from shocks and be able uphold the right to social protection at a time of great need. This became evident, once again, during the COVID-19 pandemic. While many high-income countries were able to put in place massive fiscal stimulus measures to protect their population and enterprises, alongside aggressive monetary policies, most developing countries were constrained in their response. The fact that IMF financing through the special drawing rights (SDRs)28 were in proportion to countries’ quotas meant that developing countries received only around one-third of the 2021 SDR allocation. This means that they are effectively in a much weaker position to use their social protection systems as a counter-cyclical measure when they are facing a crisis.

In other words, the solution lies not only in domestic spheres of governance and domestic resource mobilization efforts, but in addressing the disabling global financial and development institutions in ways that can support social protection system-building and the realization of SDG targets on social protection, especially in low-income countries, more effectively. As the UN Special Rapporteur on Extreme Poverty and Human Rights puts it, to achieve the national social protection floors that are recommended by social security standards, “requires international solidarity to allow beneficiary countries to come up with a solid and credible plan to build capacity for strengthened systems and then to gradually increase the mobilization of domestic resources” (De Schutter 2023).

Yet the world is falling short when it comes to international solidarity. Official Development Assistance (ODA) has remained at levels below the internationally agreed goal of 0.7 per cent of gross national income of the high-income donor countries (in 2023, the average rate was 0.37 per cent). Furthermore, despite some increase in the share of ODA allocated to employment and social protection in the context of the COVID-19 pandemic, ODA allocations to social protection remain very low (Cattaneo et al. 2024). Nor does ODA constitute a guaranteed, stable and long-term source of finance that countries need, given that it is often short-term, pro-cyclical and reflecting the priorities (including geo-political) of donor countries.

In a highly globalized and crises-prone world, domestic policy efforts of countries in building rights-based social protection systems and mobilizing domestic resources need to be complemented by an enabling global financial and development architecture. This latter architecture will be the subject of Member State deliberation at the Fourth International Conference on Financing for Development in Seville (30 June-3 July 2025) aimed at achieving the global sustainable development and climate goals.

Further research on the role of universal social protection systems in reducing inequalities

Beyond its impact on poverty and income inequality, future research should aim to assess the impact of social protection benefits in reducing inequalities in terms of human capabilities, as articulated by Amartya Sen. This is, in effect, what research on multi-dimensional poverty does, and it offers particular advantages in capturing intra-household gender dynamics. It is essential to complement income-based measures of wellbeing, which are typically collected at the household level and neglect intrahousehold inequalities, with a focus on capabilities, which lend themselves to measurement at the individual level. Sen’s capabilities approach emphasizes the importance of assessing what individuals can do and be, highlighting inequalities that can be masked by income measures of wellbeing. Key capabilities that should be examined in this context could include nutritional adequacy, access to healthcare and education, decision-making autonomy and the freedom to participate in social, economic and political life of the community. These capabilities capture a broader range of well-being than income alone and allow for a more nuanced understanding of how social protection benefits affect inequalities within and outside households (Sen 2001). This dual approach—incorporating both income and capability-based assessments—will offer a fuller picture of how social protection benefits reduce inequalities considering also those experienced by individual members within households and can inform more inclusive policy design (Robeyns 2005).

Annex

Table A1. Gini coefficient and income captured the bottom 50 per cent and top 10 per cent of earners in the population, two waves

	Wave 1 (2013–2017)				Wave 2 (2018–2022)
Country	Year	Gini	Bottom 50%	Top 10%	Year	Gini	Bottom 50%	Top 10%
Argentina	2017	41.1	22.0	29.7	2021	42.0	21.7	30.8
Australia	2016	33.7	27.2	25.8	2018	34.3	27.0	26.6
Austria	2017	29.7	29.7	23.0	2020	29.8	29.7	23.1
Belarus	2017	25.4	32.6	21.3	2020	24.4	33.3	20.7
Belgium	2017	27.4	31.5	21.9	2020	26.0	32.5	21.4
Bolivia, Plurinational State of	2017	44.6	20.0	32.0	2021	40.9	22.6	30.3
Brazil	2017	53.3	16.0	42.0	2021	52.9	16.2	41.5
Bulgaria	2017	40.4	23.9	31.9	2020	40.5	24.0	32.6
Canada	2017	33.3	27.4	25.3	2019	31.7	28.4	24.4
Chile	2017	44.4	21.7	36.3	2020	44.9	21.1	35.8
China	2017	39.1	23.8	29.9	2020	37.1	25.3	29.4
Colombia	2017	49.7	18.1	39.0	2021	51.5	17.0	40.2
Costa Rica	2017	48.3	18.5	37.0	2022	47.2	19.0	35.7
Croatia	2017	30.4	29.1	22.9	2020	29.5	29.6	22.3
Cyprus	2017	31.4	29.1	25.5	2020	31.7	29.0	26.3
Czechia	2017	24.9	33.4	21.5	2020	26.2	32.6	22.5
Denmark	2017	28.7	31.0	24.0	2020	27.5	31.6	22.9
Dominican Republic	2017	42.2	22.7	33.5	2021	38.5	24.6	30.2
Ecuador	2017	44.7	20.6	33.8	2022	45.5	20.1	34.3
El Salvador	2017	38.0	24.6	29.1	2022	38.8	23.9	28.7
Estonia	2017	30.4	28.7	22.5	2020	30.7	28.8	23.5
Finland	2017	27.4	31.6	22.6	2020	27.1	31.8	22.6
France	2017	31.6	29.0	25.8	2020	30.7	29.4	24.5
Gambia	2015	35.9	26.2	28.7	2020	38.8	24.4	30.6
Georgia	2017	37.9	24.6	28.9	2021	34.2	27.0	26.2
Germany	2017	31.9	28.7	24.8	2019	31.7	28.8	25.2
Greece	2017	34.4	26.8	25.9	2020	33.6	27.3	25.2
Honduras	2017	49.4	17.3	36.6	2019	48.2	17.6	34.6
Hungary	2017	30.6	29.4	23.9	2020	29.7	29.8	23.3
Indonesia	2017	38.8	24.1	30.2	2022	37.9	25.2	30.7
Iran, Islamic Republic of	2017	40.8	22.9	31.3	2019	40.9	23.0	31.7
Ireland	2017	31.4	29.1	25.4	2020	29.2	30.3	23.8
Israel	2017	38.2	23.7	27.0	2018	38.6	23.6	27.6
Italy	2017	35.9	25.8	26.7	2020	35.2	26.1	26.1
Kazakhstan	2017	27.5	31.4	23.0	2018	27.8	31.3	23.4
Kenya	2015	40.8	23.1	31.6	2021	38.7	25.0	31.8
Kyrgyzstan	2017	27.3	31.7	23.3	2020	29.0	30.4	24.0
Latvia	2017	35.6	25.9	26.9	2020	35.7	26.1	27.5
Lithuania	2017	37.3	25.2	28.4	2020	36.0	26.3	28.5
Luxembourg	2017	34.5	26.4	25.6	2020	33.4	27.1	25.0
North Macedonia, the former Yugoslav Republic of	2017	34.2	26.2	23.8	2019	33.5	26.4	22.9
Malawi	2016	44.7	22.4	38.1	2019	38.5	24.8	31.0
Malaysia	2015	41.1	22.6	31.3	2018	41.2	22.5	31.2
Malta	2017	29.2	30.2	23.3	2020	31.4	28.9	25.1
Mexico	2016	47.7	19.5	37.8	2020	45.4	20.6	35.5
Moldova, Republic of	2017	25.9	32.4	21.7	2021	25.7	32.7	22.1
Mongolia	2016	32.3	28.2	25.6	2018	32.7	27.8	25.7
Montenegro	2017	36.9	24.7	26.0	2018	36.8	24.7	26.0
Mozambique	2014	54.0	17.0	45.5	2019	50.5	18.4	41.2
Netherlands	2017	28.5	30.9	23.3	2020	26.0	32.5	21.6
Norway	2017	27.0	31.7	21.6	2019	27.7	31.3	22.4
Pakistan	2015	31.3	29.5	27.0	2018	29.6	30.5	25.5
Panama	2017	49.9	17.5	37.7	2021	50.9	17.2	39.4
Paraguay	2017	48.5	19.2	39.1	2022	45.1	20.7	35.4
Peru	2017	43.3	21.2	32.3	2021	40.2	23.2	30.6
Philippines	2015	44.6	21.0	34.9	2021	40.7	23.5	32.5
Poland	2017	29.7	29.9	23.5	2019	28.8	30.6	23.1
Portugal	2017	33.8	27.5	26.7	2020	34.7	26.9	26.9
Romania	2017	36.0	24.8	24.9	2020	34.6	26.0	24.2
Russian Federation	2017	37.2	25.3	29.2	2020	36.0	26.3	29.0
Serbia	2017	36.2	25.3	25.6	2020	35.0	26.9	27.1
Seychelles	2013	46.8	21.4	39.9	2018	32.1	27.8	23.9
Slovakia	2017	23.2	33.9	18.4	2019	23.2	34.0	18.8
Slovenia	2017	24.2	33.5	20.4	2020	24.0	33.7	20.5
Spain	2017	34.7	26.4	25.4	2020	34.9	26.0	25.0
Sri Lanka	2016	39.3	24.7	32.6	2019	37.7	25.5	30.8
Sweden	2017	28.8	30.4	22.3	2020	28.9	30.4	22.4
Switzerland	2017	32.7	28.0	25.5	2018	33.1	27.7	25.8
Thailand	2017	36.5	25.5	28.4	2021	35.1	26.3	27.3
Türkiye	2017	41.4	22.7	31.9	2019	41.9	22.2	31.6
Uganda	2016	42.8	22.3	34.2	2019	42.7	22.6	34.5
Ukraine	2017	26.0	32.2	21.7	2020	25.6	32.7	21.8
United Arab Emirates	2013	32.5	26.5	21.4	2018	26.0	31.5	20.0
United Kingdom	2017	32.6	27.8	24.9	2020	32.6	27.8	25.0
United States	2017	41.2	22.3	30.3	2021	39.8	23.5	30.1
Viet Nam	2016	35.3	26.3	27.1	2020	36.8	25.5	28.5
Zimbabwe	2017	44.3	21.0	34.8	2019	50.3	18.0	40.6

Table A2. Share of wealth held by the top 1, 5 and 10 per cent, earliest and latest data points available

	Earliest				Latest
Country	Year	Top 1%	Top 5%	Top 10%	Year	Top 1%	Top 5%	Top 10%
Austria	2011	22.2	48.2	60.5	2017	22.0	44.2	56.1
Canada	1999	16.3	42.2	55.9	2019	14.5	40.1	54.3
Chile	2007	22.9	51.7	64.5	2017	18.8	47.5	61.5
Estonia	2013	20.8	44.6	55.7	2017	23.1	46.3	57.1
Finland	2009	11.9	32.8	45.8	2016	13.8	36.6	49.8
Germany	2002	20.0	44.8	58.6	2017	18.9	43.5	56.7
Greece	2009	8.9	28.1	40.4	2018	10.2	32.0	44.9
Italy	2004	11.6	32.4	44.6	2016	12.3	34.0	46.5
Luxembourg	2010	18.9	44.6	56.0	2018	21.2	43.0	54.3
Slovakia	2010	7.9	26.0	37.5	2017	13.5	32.4	43.2
Slovenia	2014	21.9	40.3	50.7	2017	12.4	34.6	46.3
Spain	2002	13.6	32.9	44.8	2017	21.4	45.3	57.2
United Kingdom	2007	14.6	36.5	49.3	2019	16.1	39.5	52.7
United States	1995	36.9	61.7	72.1	2019	37.8	68.9	79.4

Table A3. Definitions of variable used for the analysis, from the LIS and LWS codebook

Concept	Variable name	Variable description
Adjusted disposable net worth	anw	Adjusted disposable net worth is the sum of non-financial and financial assets, excluding occupational pension assets and social security pension entitlements, minus the value of the total liabilities. In other words, it is disposable net worth of the household, enlarged by the value of the life insurance and voluntary individual pensions.
Gross income	hitotal	Sum of cash and non-cash income from labour, income from capital, income from pensions (including both public and private pensions) and non-pension public social benefits stemming from insurance, universal or assistance schemes (including in-kind social assistance transfers), as well as cash and non-cash private transfers.
Disposable income	dhi	Sum of cash and non-cash income from labour, income from capital, income from pensions (including private and public pensions) and non-pension public social benefits stemming from insurance, universal or assistance schemes (including in-kind social assistance transfers), as well as cash and non-cash private transfers, less the amount of income taxes and social contributions paid.
Market income (sum of hifactor, hi33, hiprivate)	hifactor	Sum of cash and non-cash income from labour and income from capital.
	hi33	Private pensions including: - pensions and other monetary transfers for old-age, disability and survivors, stemming from the employers or occupational organisations through occupational schemes that aim at supplementing the main pension scheme; - monetary payments from personal pension accounts not linked to employment, including annuities from life insurance and other pension-like annuities.
	hiprivate	Cash transfers and value of in-kind goods and services of a private nature that do not involve any institutional arrangement between the individual and the government or the employer. Includes transfers provided by non-profit institutions, other private persons/households, and other bodies in the case of merit-based education transfers. This variable is constructed according to the following formula: hiprivate = hi51 + hi52 + hi53 + amounts that are directly placed at the level of hiprivate.
Personal income taxes	hxitax	Expenditure on income taxes, defined here as compulsory payments to the Government based on current income earned. Includes both the amount withheld at source and the amount directly paid at the moment of the tax adjustment.
Social security contributions	hxscont	Payroll taxes from wage and salary workers for first and second pillars of social insurance: social security, health plans, unemployment insurance, etc. Includes also the employee's contribution which is paid, as a way of social assistance, by the employer.
Wealth taxes	hxptax	Recurrent and non-recurrent taxes on the property and net worth as well as taxes on financial and capital transactions. The examples are taxes on land, buildings, movable properties, taxes on the issue, transfer, purchase and sale of securities, and taxes levied on specific legal transactions such as validation of contracts and the sale of immovable property. Additionally, this variable contains any taxes on the revaluation of capital and non-recurrent taxes on particular items of property. Finally, this variable records the other recurrent taxes such as taxes on owned goods (jewelry, cattle, etc.) and other external signs of wealth.
Public non-contributory pensions	hi31	Pensions and similar monetary transfers for old-age, disability and survivors, stemming from non-contributory public programmes, including: - universal programmes, aimed at covering the whole population or a part of the population selected based on other criteria than previous employment existence or income or assets thresholds. - social assistance programmes targeted towards individuals or households in need. It includes also veteran pensions if they are non-insurance based.
Public contributory pensions	hi32	Public contributory pensions, including: - pensions and other monetary transfers for old-age, disability, and survivors, stemming from the main pension insurance system that covers mainly the active population. The main pension system can be the public one or the mandatory individual accounts one or a mixed between the two when the country's pension system is in transition from a PAYG system to mandatory accounts one, or even the occupational one if it represents the main pension scheme and is not just a supplementary pension to the main one; - pensions and other monetary transfers for permanent full or partial disability or death caused by a work-injury or occupational disease from schemes specifically set up with the purpose of covering work-injury and occupational diseases. Are included all social insurance schemes that cover mainly the active population; however sometimes is possible for (some categories of) inactive people to join (voluntary) the system. Includes all benefits linked to a permanent/long-term exit from the labour market (even if not received for a long-term duration, such as in the case of one-time or short-duration benefits linked to the corresponding old-age, disability and survivors pension schemes). Includes supplements to pensions.
Public Social Benefits (excluding pensions)	hipubsoc	Cash social security transfers (excluding public pensions) stemming from insurance, universal or assistance schemes, and in-kind social assistance transfers. This variable is constructed according to the following formula: hipubsoc = hi41 + hi42 + hi43 + hi44 + hi45 + hi46 + hi47 + amounts that are directly placed at the level of hipubsoc.
Family benefits	hi41	Total family-related benefits, including: - wage replacement benefits from maternity, paternity, or parental leave insurance schemes; - monetary child or family allowance to households with dependent children, from public programmes, which are aimed at covering the whole population or a part of the population; - monetary family-related transfers, received from the state through social programmes targeted towards individuals or households in need, including specific systems which are set up to relieve single parent households; - monetary transfers to a parent, guardian or foster parent to compensate for the time spent staying at home caring for dependent children, stemming from public programmes; - public advance maintenance schemes, which are aimed at covering the whole population or a part of the population selected based on other criteria than previous employment existence or income or assets thresholds, such transfers are paid by social security to compensate for unpaid alimony payments.
Unemployment benefits	hi42	Total unemployment benefits, including: - wage replacement benefits from the unemployment insurance aimed to compensate for the partial or total loss of labour income and to help the job seeker integrate the labour market; - cash benefits from unemployment public programmes, which are aimed at covering the whole population or a part of the population selected based on other criteria than previous employment existence or income or assets thresholds; such transfers maintain or support the income in case of first-time job seekers or aim to integrate inactive persons into the labour market (active labour market policies); - cash benefits from unemployment social programmes targeted towards individuals or households in need.
Sickness and work injury	hi43	Cash benefits from sickness and work-injury insurance schemes that cover mainly the active population. Such transfers replace or supplement employment income during periods of temporary interruptions (or reductions) of employment caused by temporary inability to work due to sickness or injury, or cover the additional costs incurred in such circumstances (e.g. rehabilitation benefits). These systems can be either organised in autonomous social protection schemes or by the employer in the form of continued payment of wages and salaries during the period of sickness. Includes also rehabilitation benefits provided during the period of temporary leave.
Disabilty	hi44	Monetary disability-related transfers from public programmes, which are aimed at covering the whole population or a part of the population. Such transfers cover people in connection with disability, sickness or injury. Includes care allowances for disabled persons who need frequent or constant assistance to help them meet the extra costs of attendance (other than medical care). Includes also other periodic payments not falling under the above headings, such as occasional income support, allowances for intensive care, special bonuses or allowances for tuberculosis patients, etc.
Other Social Assistance (sum of hi45, hi46, hi47)	hi45	Monetary transfers from minimum income guarantee systems/last resort systems, received from the state through social programmes targeted towards individuals or households in need. Such means-tested systems are meant to provide a minimum subsistence level, covering frequently the totality of the population. Includes in-work benefits paid to those in low-paid jobs in order to raise disposable income without creating disincentives to work. Excludes mimimum protection schemes which are covering only specific groups of the population such as the elderly, disabled, dependents of a deceased, or families.
	hi46	Monetary housing-related transfers, received from the state through social programmes targeted towards individuals or households in need. Such means-tested programmes are meant to cover the cost of housing. Includes means-tested near-cash transfers granted by a public authority to tenants, to cover temporarily or on a long-term basis the cost of rent. Includes means-tested near-cash transfers by a public authority to owner-occupiers, to cover their current housing costs; frequently by temporarily paying mortgages and/or interest. Excludes tax subsidies and/or national price subsidies.
	hi47	Value of goods and services received from the state through social programmes targeted to individuals or households in need, including, programmes aimed at helping cover the educational, housing, heating, food, medical and other specific needs of needy individuals or families.

Table A4. Regional and national income grouping

Country, territory and area groupings (ILO)	https://ilostat.ilo.org/methods/concepts-and-definitions/classification-country-groupings/
World Bank Group country classifications by income level for FY24 (July 1, 2023- June 30, 2024)	https://blogs.worldbank.org/en/opendata/new-world-bank-group-country-classifications-income-level-fy24

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Acknowledgements

The working paper was authored by Shahra Razavi, Umberto Cattaneo, Helmut Schwarzer and Andrea Visentin. The working paper benefitted from an ILO internal peer review by Christina Behrendt and from an external peer review by James Heintz (Andrew Glyn Professor of Economics, Department of Economics, University of Massachusetts, Amherst, USA) and Nicola Yeates (Chair of Social Policy, Department of Social Policy and Criminology, Open University, UK).

The paper originated as S. Razavi, Combating Inequality: What Role for Universal Social Protection, The Annual Inequality Lecture, Southern Centre for Inequality Studies, Wits University, South Africa, 18 October 2022. We thank Imraan Valodia (Director of the Southern Centre for Inequality Studies, University of the Witwatersrand, Johannesburg) for extending the invitation.

The authors also wish to acknowledge the following persons (listed in alphabetical order) for their comments, contributions and ideas: Belen Borja and Maurice Starke.

Special thanks are also due to Ana Carolina De Lima Vieira and Meriem Allek for facilitating the production process, Graeme Shepherd for editing the working paper, and Stéphane Pellet Bourgeois for handling the layout.

43.7 per cent. See figure 10.

26.8 per cent. See figure 11.

As Fukuda-Parr and McNeill (2019) show, the lead target (10.1) is for inclusive growth – or the World Bank’s concept of ‘shared prosperity’. Yet it is extreme inequality and its potentially corrosive impact on democracy that has raised alarm in contemporary public debates.

SDG indicator 10.2.1 measures income inequality through the 10.2.1Proportion of people living below 50 per cent of median income, by sex, age and persons with disabilities.

See section 3 for a mathematical definition and (Gini 1912)

In this contribution, the Gini coefficient is multiplied by 100 and then ranges between 0 and 100 to improve readability.

Estimate based on 77 countries (55 per cent of the global population) with comparable surveys included in the analysis.

See Table A4 for regional and national income groups.

In Indonesia, comparable surveys for 2013 and 2014 could not be retrieved. Therefore, the percentage point change is calculated between 2015 and 2022.

Disposable income is defined as the sum of gross household income minus taxes and social security contributions plus transfers.

It must be noted that no information is provided regarding labour related earnings of the self-employed, which constitute a sizeable share of labour income in middle-and low-income countries.

Persons aged between 25 and 59 years.

Bulgaria, Italy, Montenegro, North Macedonia and Romania.

Wealth, or net worth, is the value of assets owned by a household, such as properties or savings, net of outstanding debt. It refers to an amount that has been accumulated over a lifetime or more, as it may be inherited across generations. This accumulated wealth is a source of retirement income, protects against short-term economic shocks and provides security for future generations.

See Appendix Table A3 for details.

LIS microdata accessed at the end of 2023.

Contributory pensions include both public and occupational pensions.

Further research on these aspects goes beyond the scope of this contribution.

Defined as payroll taxes from wage and salary workers for first and second pillars of social insurance.

Defined as compulsory payments to the government based on current income earned.

Defined as recurrent and non-recurrent taxes on the property and net worth, as well as taxes on financial and capital transactions.

See section on wealth inequalities.

Not to be confused with property taxes, which are only a part of wealth taxes. A wealth tax is a levy on the net market value of a taxpayer’s assets. To be more precise, the wealth tax evaluated in this analysis includes “recurrent and non-recurrent taxes on the property and net worth as well as taxes on financial and capital transactions. The examples are taxes on land, buildings, movable properties, taxes on the issue, transfer, purchase and sale of securities, and taxes levied on specific legal transactions such as validation of contracts and the sale of immovable property” (LIS Codebook).

Total gross income from surveys represents the sum of all individual gross incomes reported in the LIS household surveys. For a definition of gross income see Table 1 and Table A3.

The World Social Protection Report 2024-26 (ILO 2024b) provides a useful analysis of social protection from a gender perspective, focusing in particular on pensions for which sex-disaggregated data is available for a larger number of countries.

This section is based on Razavi, 2024 forthcoming.

As pointed out by one of the reviewers of this paper, these high interest rates are themselves a policy decision. Interest rates were raised to combat non-monetary sources of inflation (corporate price gauging) – and it is not clear they are in anyway effective. Hence, coordination of monetary policy with sustainable fiscal policy needs to be an aspect of resource mobilization plan.

The SDRs were created in 1969 as a form of supplementary reserve asset. According to its Articles of Agreement, the IMF allocates SDRs to members under certain conditions. In 2021, the largest-ever allocation of around USD 456 billion was agreed, but allocations are distributed according to country’s quota shares at the IMF which reflect its position in the global economy. A member country’s quota determines its maximum financial commitment to the IMF, its voting power and access to IMF financing. This effectively leaves many developing countries with small SDR allocations from new issuances, while high-income countries do not often use their allocations. There have been calls for reform of the system so a larger share can go to countries that need them (Gallagher et al. 2020).