1 Introduction

The gap between rich and poor in Organisation for Economic Co-operation and Development (OECD) and European Union (EU) countries has reached its highest level over the past three decades.Footnote 1 This chapter first presents some comparisons on income inequality trends between European and OECD countries (Sect. 3.2). We focus in the following section on the evolution of the situation in the past decades (Sect. 3.3). During this period, income distributions have been profoundly transformed by the interplay of globalisation , technological change and regulatory reforms leading to profound structural changes in labour markets . In addition, taxes and benefits have tended to redistribute less from the mid-1990s up to the crisis. These factors, along with a number of demographic and social trends, are key to understanding the rise in income inequality in the OECD area and EU countries. Following the approach of identifying policies which are effective in tackling inequality, the OECD proposes a strategy based upon four pillars: women’s participation, employment, skills and education, and redistribution (Sect. 3.4).

2 Level and Trends

2.1 How Unequal Are European Union and OECD Countries?

Differences in levels of income inequality in the EU are significant. Within the EU region, the Gini coefficient —a common measure of income inequality that scores 0 when everybody has identical incomes and 1 when all the income goes to only one person—ranges from 0.25 in Denmark, Slovenia and Slovakia to 0.35 in Lithuania, the United Kingdom and Bulgaria. Income inequality is generally around the EU average among continental European countries (France, Germany) and above the EU average among Mediterranean countries (Greece, Italy, Portugal, Spain). In comparison, the distribution of income is sometimes larger beyond Europe, at 0.40 or above in the United States, Turkey, Mexico and Chile.

Alternative indicators of income inequality suggest similar rankings. The gap between the average incomes of the richest and the poorest 10% of the population was at around 8 for the average of the EU countries, ranging from 5–6 in Nordic and central European countries to almost two times larger (10–11) in English-speaking and Baltic countries (see Fig. 3.1).

Fig. 3.1
figure 1

Level of income inequality , 2013 or latest year

Source: OECD Income Distribution Database (http://oe.cd/idd)

Note: non-OECD EU countries are shown in light blue*The statistical data for Israel are supplied by and under the responsibility of the relevant Israeli authorities. The use of such data by the OECD is without prejudice to the status of the Golan Heights, East Jerusalem and Israeli settlements in the West Bank under the terms of international law

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2.2 Has the Gap Between Rich and Poor Widened?

Over the past three decades, the gap between rich and poor has widened in two-thirds of EU countries and three-quarters of OECD countries for which long-term data series back to the mid-80s are available. Income inequality followed different patterns across European countries. It first started to increase in the 1980s in the United Kingdom. The trends in the 2000s showed a widening gap between rich and poor also in traditionally more egalitarian countries, such as Germany and Sweden where inequality grew faster than any other OECD country, in relative terms. Since the beginning of the crisis in 2007, income inequality in Europe increased most in France and Spain, but also in some central European countries (Estonia, Hungary and Slovakia). In most countries, the top 10% did better than the bottom 10%. In Spain for example, real income of the 10% poorest has been dropping by 13% per year compared to only 1.5% for the richest 10%. In Austria, Denmark and France, real income at the top increased, while it slightly fell at the bottom (see Fig. 3.2).

Fig. 3.2
figure 2

Trends in income inequality , Gini coefficient

Source: OECD Income Distribution Database (http://oe.cd/idd)

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3 Key Drivers of Growing Inequalities

OECD (2011, 2015) provides a detailed account of the various driving forces of growing inequality up to the crisis. It concerns directly the richest EU countries which are OECD members. The single most important direct driver of growing inequality has been greater dispersion in wages and salaries. This is not surprising, since earnings account for three-quarters of total household incomes among the working-age population. With very few exceptions, wages of the 10% best-paid workers have risen relative to those of the 10% least-paid workers. This was due to both growing shares of earnings at the top and declining shares at the bottom. Annual hours worked decreased more among low-wage than among high-wage earners, and the share of non-standard work increased. Labour markets have been undergoing profound transformations due to globalisation (e.g. Freeman 2009; Milanovic 2016), technological change (e.g. Acemoglu 2002) and changes in product and labour market regulations (e.g. Checchi and Garcia-Penalosa 2005). People with skills in high-demand sectors like information technology or finance have seen their earnings rise significantly, while on the other end of the scale, wages of workers with low skills have not kept up. Besides these profound transformations in the labour market, demographic and societal changes and the decrease in redistribution constitute the underlying drivers of inequality.

3.1 Changes in Working Conditions

Before the crisis, many OECD countries were facing a paradoxical situation: their employment rates were at record-high levels and yet income inequality was on the rise. Typically, rising employment might be expected to reduce income inequality as the number of people earning no salary or relying on unemployment benefits falls. However, in recent decades the potential for this to happen has been undercut by the gradual decline of the traditional, permanent, nine-to-five job in favour of non-standard work—typically part-time and temporary work and self-employment. More (often low-skilled) people have been given access to the labour market, but at the same time, this has been associated with increased inequalities in wages and, unfortunately, even in household income.

The development of non-standard work is related to technological changes and the associated evolution of labour demand. Most advanced economies have witnessed increasing job polarisation (e.g. Autor and Dorn 2013)—a decline in the share of workers in the middle of the workforce, both in terms of skills and income, and increases in the proportions of workers in high- and low-skill jobs. The share of workers with routine-task jobs, such as accountants, fell from 53% to 41% between 1995 and 2010. At the same time, the employment share for abstract high-skill jobs, such as designers, grew from 28% to 38%, and relatively low-skill non-routine manual jobs, such as drivers, increased from 18% to 21% (OECD 2015). The emergence of this U-shaped workforce is closely matched by developments in non-standard employment. The decline in middle-skill employment went hand in hand with a decrease of standard work contracts; and workers taking on low- and high-skill jobs were increasingly likely to be self-employed, part-timers or temporary workers.

The spread of non-standard work is most visible when comparing its share in new jobs created before and since the onset of the crisis. Between the mid-1990s and the start of the Great Recession , almost half of all job creation was in the form of non-standard work; if the crisis years are included, this figure rises to 60% (Fig. 3.3).

Fig. 3.3
figure 3

Employment growth 1995–2013, by type of employment

Source: OECD (2015), In It Together: Why Less Inequality Benefits All

Note: Working-age (15–64) workers, excluding employers as well as students working part-time. Non-standard workers include workers with a temporary contract, part-timers and own-account self-employed

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Recent OECD findings suggest that non-standard work accounted for around a third of total employment in OECD countries in 2013, shared roughly equally between temporary jobs, permanent part-time jobs and self-employment. In some Eastern European countries, the proportion of non-standard workers is lower than 20%, but in most Southern European countries and Switzerland, it exceeds 40% and in the Netherlands more than half of all workers are in non-standard work, largely because of the high number of part-timers.

Non-standard jobs are not necessarily bad jobs. Non-standard employment is used by employers in need of a flexible workforce that can be adjusted quickly with production, to cut costs during downturns or as a screening device for new hires. Part-time, temporary and self-employment arrangements can be attractive to certain workers who opt for this type of employment to achieve a better work–family life balance, higher life satisfaction or, in the case of self-employment, a greater sense of control.

However, they may be associated with precariousness and poorer labour conditions where non-standard workers are exempted from the same levels of employment protection, safeguards and fringe benefits enjoyed by colleagues on standard work contracts. In addition, OECD (2015) shows that many non-standard workers are worse off on a range of aspects of job quality—lower wage rates, less training and security of employment. However, non-standard work can be a ‘stepping stone’ to more stable employment. In particular, temporary contracts can increase the chances of acquiring a standard job compared with remaining unemployed in the short run, but this is less true on the longer-run and is mainly limited to prime-age and elderly workers.

3.2 Institutional Changes

Labour markets in most OECD countries witnessed both regulatory reforms, such as lower minimum to median wage ratios, lower benefit replacement rates or weaker employment protection legislation and institutional changes, such as lower union density or coverage of collective-bargaining arrangements. These changes had contrasting effects on employment and wage distribution. They helped promote productivity and growth and increase employment opportunities while, at the same time, contributing to wider wage disparities. The combined influence of these factors on overall earnings inequality and household income inequality is less straightforward as employment and wage effects tended to cancel each other out.

3.3 Demographic and Societal Changes

Demographic and societal change—more single and single-parent households, more people with a partner in the same earnings group—also played a role for increasing inequality, but much less than sometimes assumed. Smaller households are less able to benefit from household economies of scale. And the so-called assortative mating (i.e. the degree to which individuals marry within their own income group) concentrates earnings of couples in the same income classes. Both trends did contribute to higher overall inequality. However, these factors accounted for much less than labour market-related factors: the widening dispersion of men’s earnings contributed more than twice that value, while the increase in women’s employment countered the increase towards higher inequality.

On the other hand, when looking beyond wages and including all factors related to higher female labour force participation —higher share of women working full-time and higher relative wages for women—OECD (2015) showed that the general impact of women joining the labour force had an equalising effect on income.

3.4 Weaker Redistribution

Another key factor for rising net income inequality was the weakening of redistribution through tax and benefit systems since the mid-1990s until the late 2000s. Direct taxes and cash transfers are the most direct and immediately effective policy levers that governments can use to redistribute market incomes and reduce income inequality. At the onset of the crisis, public cash transfers and income taxes reduced inequality among the working-age population by an average of about one-quarter across OECD countries, down from about one third in the mid-1990s: in Sweden for instance, redistribution fell from 42% to 27% over this period. This redistributive effect is above the OECD average in most European countries, remaining above 35% in Slovenia, Finland, Denmark, Belgium and Austria, and between 30% and 35% in Luxembourg, Czech Republic, France, Croatia, Hungary, Greece, Slovak Republic and Norway. The weakening of redistribution prior to the crisis was driven chiefly by benefits rather than taxes or, to be more precise, by changes in their receipt patterns and generosity. Fewer numbers of unemployment benefit claimants and reforms to benefit eligibility criteria have been particularly important factors. Although governments spent more on benefits overall, transfers did not become more progressive. In particular, spending on out-of-work benefits shifted towards ‘inactive’ benefits, which resulted in reduced activity rates and thus exacerbated the trend towards higher market income inequality (see Fig. 3.4).

Fig. 3.4
figure 4

Trends in redistribution

Source: OECD Income Distribution Database (http://oe.cd/idd)

Note: Redistribution is measured as the percentage difference between inequality (Gini coefficient) of gross market income (before taxes and transfers) and inequality of disposable income (after taxes and transfers)

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4 What Can Policy Makers Do?

Tackling inequality and promoting equal opportunities for all requires comprehensive policy packages (see also Atkinson 2015), centred around four main areas:

  • Promoting fuller participation of women in the labour market: governments need to pursue policies to eliminate the unequal treatment of men and women in the labour market and to remove barriers to female employment and career advancement. This includes measures to increase the earnings potential of women in low-paying jobs and to address the glass ceiling. In addition to gender gaps in employment participation, women still face a glass ceiling when it comes to reaching the top of their professions. To increase women’s representation in decision-making positions, France, Germany, Italy and Spain have introduced mandatory quotas.

  • Fostering employment opportunities and high-quality jobs: policies need to emphasise access to jobs and labour market integration. The focus must be on policies for the quantity and quality of jobs; jobs that offer career and investment possibilities; jobs that are stepping stones rather than dead ends. Active labour market policies also need to be designed to raise the earnings potential of non-standard workers, particularly youth and low-skilled workers. Addressing labour market segmentation is an important element of enhancing job quality and tackling inequality.

  • Strengthening quality education and skills development during working life: the inability of individuals from poor socio-economic background to access higher education and develop their human capital lies at the heart of the transmission mechanism through which income inequality lowers economic growth. A focus on the early years, as well as on the needs of families with school children, is crucial in addressing socio-economic differences in education. More must be done to provide youth with the skills they need to get a good start in the labour market . With a rapidly changing economy, further efforts should be made, with the active involvement of business and unions, to promote continuous upgrading of skills throughout working life.

  • Designing a better tax and benefits systems for efficient redistribution: adequately designed redistribution via taxes and transfers is a powerful instrument to contribute to more equality and more growth. In recent decades, the effectiveness of redistribution has declined in many countries due to working-age benefits not keeping pace with real wages and taxes becoming less progressive. Policies must ensure that wealthier individuals, but also multinational firms, pay their share of the tax burden. Large and persistent losses of low-income groups underline the need for well-designed income-support policies and counter-cyclical social spending. Government transfers have an important role to play in guaranteeing that low-income households do not fall further back in income distribution , but they need to be paired with measures to re-establish self-sufficiency, prevent long-term benefit dependence and support families’ capacities to compensate for earnings losses.