Chapter 3. Invest in people and places left behind, providing equal opportunities

This chapter is structured in two main parts. First, it outlines trends in key opportunity and future prosperity outcomes. This includes trends in children’s well-being, and particularly its evolution over the past decade, educational outcomes and opportunities as they relate socioeconomic background, health outcomes, social mobility, and trends in regional disparities and inclusive communities. Second, the chapter discusses key dynamics and policies to enhance opportunities and foundations for future prosperity.

This chapter emphasises the importance of inclusive education systems that provide people with the skills and opportunities to flourish throughout life, and the importance of early childhood education and intervention to mitigate the accumulation of inequalities later in life. It also highlights the centrality of reducing regional disparities and place-based policies in the inclusive growth agenda: enhancing innovation and knowledge diffusion across regions, providing affordable housing and enhancing mobility and connectivity are key components of this regional approach. It concludes by discussing policies that create vibrant communities that can foster people’s well-being.

The Inclusive Growth Framework for Policy Action on Inclusive Growth consolidates some of the key policy recommendations to sustain and more equitably share the gains of economic growth from related OECD work, around broad principles to invest in people and places left behind through:

(i) targeted quality childcare, early education and life-long acquisition of skills;

(ii) effective access to quality healthcare, education, justice, housing, infrastructures; and

(iii) optimal natural resource management for sustainable growth.


Trends in key opportunity and future prosperity outcomes

Trends in child well-being

Child poverty is on the rise in most OECD countries. Children are paying a high price for the large and often rising inequalities in different dimensions of well-being. The proportion of children in poverty has grown in almost two-thirds of OECD countries (Figure 3.1) due to the great recession and despite measures that were often taken to mitigate the effects on families' standard of living (Adema et al., 2014; Ali et al., 2014).

Figure 3.1. Child income poverty rates on the rise in most OECD countries since 2007
Share (%) of children (0-17) with an equivalised post-tax-and-transfer income of less than 50% of the national annual median equivalised post-tax-and-transfer income, 2007a, and 2014-15b or nearest available year

Note: a) 2008 for Germany, Israel, New Zealand; Norway; 2009 for Chile, Japan; b) 2013 for Brazil, China; 2015 for Chile, Finland, Israel, the Netherlands, the United Kingdom. c) The OECD-24 average is the unweighted mean average for the 24 OECD countries with data available for 2007.

Source: OECD Income Distribution Database.


Family living arrangements influence the risk of child poverty. On average, one in three single-parent families live in relative poverty; which is three times higher than the poverty rate among two-parent families. A growing proportion of children experience a period of poverty because the share of single-parent families is increasing: 15.8% of children were living with a single-parent in 2007 and 17.2% in 2016 (OECD, 2017a).

Continued parental employment is the most durable protection against the risk of poverty. On average across the OECD, 66% of jobless single-parent families are income poor and this rate is divided by three when the parent has a job; also on average 62% of families with two parents are income poor when none of the parents work, but the proportion drops to 4% when the two parents work. However, about one in ten children live in a jobless family, and this proportion increased sharply in countries hard hit by the economic recession, including France (+3%), Ireland (+4.1%), Greece (+7%), Italy (+5%), Portugal (+3%), Slovenia (+3%), and Spain (+8%) (OECD, 2017a; OECD, 2017i).

Child well-being goes beyond material conditions. Raising children out of income poverty is just one aspect of ensuring that children can lead happy, healthy and productive lives. Housing conditions, the neighbourhood and environment in which children live, their health, safety, education, leisure time and personal relationships, as well as their subjective well-being and mental health, are all essential factors that contribute to the quality children’s lives (OECD 2009, 2015, 2017a; Richardson and Ali, 2014). For instance, almost one third of children (32%) in low-income families live in overcrowded households while less than 18% of them are in this situation in higher-income families (OECD, 2017a).

Poorer children are unhappier. While strongly conditioning children’s aspirations and educational outcomes (section below), the economic and social background of families affects the general level of satisfaction that children experience with their lives. Indeed, 15 year-olds adolescents from the most socio-economically disadvantaged families are both less likely to report high life satisfaction (32% compared to 37% for children from more privileged families) and more likely to report low levels of satisfaction (14% compared to 9% for adolescents from more favoured families). Data for selected OECD countries suggest that 20-40% of children aged 11 to 15 have multiple recurrent psychosomatic health complaints, which are more prevalent in girls than boys and increase with age (OECD, 2015a; OECD, 2015b).

Figure 3.2. Change in self-reported overweight (including obesity) among 15-year-olds

Source: OECD (2017b), Health at a Glance 2017,

Income poverty affects children's nutritional practices and health outcomes, giving rise to child obesity. In Europe, around 16% of income poor children do not have either fruits and vegetables at least once a day or one meal with meat, chicken or fish (or vegetarian equivalent) at least once a day, while the proportion is four times lower in higher-income families (OECD, 2017a). Equally significant is the risk of “overweight” and “obesity” that is markedly dependent on family affluence: 22% of adolescents aged 11 to 15 in low family affluence are being classified as ‘overweight’ or ‘obese’ while the proportion is only 15% among children in high family affluence (Inchley et al, 2016; OECD, 2017a; OECD, 2017b). In addition, the prevalence of child overweight (including obesity) has increased by 28% in the last decade, from 12% in 2001-02 to 16% in 2013-14 (Figure 3.2). Such rise in the childhood obesity is a great concern for OECD countries because it is a strong predictor of adult obesity (WHO, 2016a) and therefore is associated with a higher risk of experiencing later in life cardiovascular, endocrine, or pulmonary diseases. At a shorter horizon, child obesity often affects mental health through the development of poor self-esteem, eating disorders, and depression (Inchley et al., 2016). Obesity is associated with poorer educational attainment (Devaux et al, 2011).

Childhood and adolescence are crucial periods for good mental health. A large number of children suffer from mental health diseases, especially among low-income households. Many mental illnesses have an onset in childhood or adolescence, and around one in four young people have a mental disorder (Figure 3.3). Data for selected OECD countries suggest that 20-40% of children aged 11 to 15 have multiple recurrent psychosomatic health complaints, which are more prevalent in girls than boys and increase with age (OECD, 2015a). Good mental health in early childhood and even infancy has also been associated with better long-term mental, physical and social outcomes (McDaid, Hewlett and Park, 2017). Mental well-being is generally lower among children in poorer families than among children in richer families (McDaid, Hewlett and Park, 2017). Children and adolescents experiencing mental ill-health are more likely to leave school early, have poorer education outcomes, and consequently have greater difficulty accessing the labour market.

Figure 3.3. People aged 15-24 with a mental disorder
OECD countries, % of the total youth population, late 2000s and mid-1990s

Note: National health surveys. Australia: National Health Survey 2001 and 2007/08; Austria: Health Interview Survey 2006/07; Belgium: Health Interview Survey 1997, 2001 and 2008; Denmark: National Health Interview Survey 1994, 2000 and 2005; Netherlands: POLS Health Survey 2001-03 and 2007-09; Norway: Level of Living and Health Survey 1998, 2002 and 2008; Sweden: Survey on Living Conditions 1994/95, 1999/2000 and 2004/05; Switzerland: Health Survey 2002 and 2007; United Kingdom: Health Survey of England 1995, 2001 and 2006; United States: National Health Interview Survey 1997, 2002 and 2008.

Source: OECD (2012), Sick on the Job? Myths and Realities about Mental Health and Work,

Trends in educational outcomes and opportunities

Home background influences success in education and schooling can either reinforce or mitigate that influence. In 2006, on average across OECD countries, 14% of the variation in students’ science performance could be explained by students’ socio-economic status. A one-unit change in the PISA index of economic, social and cultural status (ESCS) – which corresponds to the difference between students with average socio-economic status and disadvantaged students – was associated with a difference in science performance of 39 score points.

In the last decade, educational opportunities have not increased much (as measured through the strength of socio-economic gradient). By 2015, the degree to which students’ socio-economic status predicted performance in science decreased to 13 score points, while the difference in performance between students who were one unit apart on the ESCS index decreased to 38 score points (OECD, 2016a, 2016b, 2016c; OECD, 2015c). Over the period 2006-15, the strength of the gradient decreased by more than 3% points in eight countries that also managed to maintain their average performance: Brazil, Bulgaria, Chile, Denmark, Germany, Slovenia, Thailand and the United States. In these countries, students’ socio-economic status became a less reliable predictor of achievement as there was no significant change in performance (Figure 3.4).

Figure 3.4. Change between 2006 and 2015 in the strength of the socio-economic gradient

Notes: Only countries and economies with available data are shown.

Changes in both equity and performance between 2006 and 2015 that are statistically significant are indicated in a darker tone (see AnnexA3).

The average three-year trend is the average rate of change, per three-year period, between the earliest vailable measurement in PISA and PISA 2015. For countries and economies with more than one available measurement, the average three-year trend is calculated with a linear regression model. This model takes into account that Costa Rica, Georgia, Malta and Moldova conducted the PISA 2009 assessment in 2010 as part of PISA 2009+.

Source: OECD, PISA 2015 Database, Table I.6.17


Improving performance and equity of the school system at the same time is possible. In some OECD countries where educational opportunities have increased without offsetting improvements: between PISA 2006 and PISA 2015, in Chile, Denmark, Mexico, Slovenia, Turkey, the United Kingdom and the United States, the average impact of students’ socio-economic status on performance weakened by more than 4 score points while mean science achievement did not decline (Figure 3.5).

Figure 3.5. Change between 2006 and 2015 in the slope of the socio-economic gradient

Notes: Only countries and economies with available data are shown.

Changes in both equity and performance between 2006 and 2015 that are statistically significant are indicated in a darker tone (see AnnexA3).

The average three-year trend is the average rate of change, per three-year period, between the earliest available measurement in PISA and PISA 2015. For countries and economies with more than one available measurement, the average three-year trend is calculated with a linear regression model. This model takes into account that Costa Rica, Georgia, Malta and Moldova conducted the PISA 2009 assessment in 2010 as part of PISA 2009+

Source: OECD, PISA 2015 Database, Table I.6.17.


Trends in health outcomes disparities

While longevity differences between countries have narrowed, within countries, inequalities in longevity remain large. Inequality in life expectancy between countries has narrowed over the last decade, although gains in longevity have been mediocre (i.e. less than one year) in Mexico, the United States and Germany, as compared to an average of 2 years gained among OECD and key partner countries, and 1.8 years among OECD countries. Within OECD countries, inequalities in longevity remain large however. Across 25 OECD countries with available data, in 2001, the gap in life expectancy at the age of 30 between high and low-educated people was around 7 years for men and 4 years for women (Murtin et al., 2017; OECD, 2017a).

Longevity gaps differ markedly across countries. High-educated men aged 30 can expect to live more than 10 years longer than their low-educated counterparts in the Slovak Republic, Estonia, Poland, Hungary, Latvia and the Czech Republic, while the gap is less than 5 years in Turkey, Sweden, Canada, the United Kingdom, Italy, Netherlands and Norway. In the case of women, inequalities in life expectancy are relatively small in Turkey, Greece, Canada, France and Sweden but exceed 8 years in Latvia and Estonia. Inequalities in longevity by education persist even at older ages. At 65 years, the gap in life expectancy between the high and low-educated was, on average across the 23 countries with available data, 3.6 years for men and 2.5 for women (Figure 3.6Figure 3.6). In relative terms, i.e. expressed as a share of the remaining lifespan, gaps in longevity are even larger at 65 than at 25. While differences in average life span (i.e. life expectancy) between education and gender groups are large, they are even wider within groups.

Figure 3.6. Gap in life expectancy at age 30 between highest and lowest education level
OECD countries, by gender, 2015 or latest available year

Source: Murtin et al. (2017) and OECD (2017).


Circulatory problems are the main factor explaining the mortality gap between education groups at older age. For older people, circulatory diseases contribute to 41% of the difference in mortality rates between low and high-educated men, and to around 50% of the gap between low and high educated women. Addressing the risk factors underlying circulatory diseases, in particular smoking, would go a long way towards reducing both average mortality rates and inequalities in longevity across education groups (Figure 3.7). Smoking accounts for up to half of the inequalities in mortality rates in some European countries (OECD, 2017b); also, while its contribution to inequalities in longevity has declined in most countries for men, it has increased for women.

Figure 3.7. Mortality rates by gender, education and cause of death
Population aged 65-89 years around 2011

Source: Murtin et al. (2017).


Figure 3.8. Change of the regional gap in life expectancy
OECD countries, 2000-15

Note: The figure shows the difference between the TL2 regions with the highest and the lowest life expectancy at birth in OECD countries, and the evolution of this difference in 2000-15. Since life expectancy has improved in all regions during this period, the reduction of the regional gap is due to a relative better performance of the region with the lowest value. Conversely, an increase of the regional gap is due to faster improvement of life expectancy in the healthiest region. Nunavut (Canada), Ceuta (Spain) and Melilla (Spain) are not included.

Source: Calculations based on OECD Regional Statistics (database).


The regional gap in life expectancy is striking across OECD countries. On average, citizens in regions with the highest life expectancy live two and a half years longer than citizens in regions with the lowest life expectancy (Figure 3.8). In some countries such as Finland, Japan or Switzerland, regional gaps in life expectancy are very low, and these gaps remained stable or even decreased between 2000 and 2015. In contrast, within country differences in the US or Australia are approximately as large as the difference in national average life expectancy between those countries and Mexico, the OECD country with the lowest life expectancy. Although regional discrepancies in life expectancy have, on average, declined only slightly from 2000 to 2015, some countries have experienced a significant drop in the regional gap in terms of life expectancy. For instance, Finland managed to halve its life expectancy gap; Turkey, Greece and Chile also reduced it by 30%.

Figure 3.9. Health worsens with age
Share of people reporting bad health by age, gender, and education in 24 OECD countries

Note: “Low”, “medium” and “high” levels of education correspond to International Standard Classification of Education (ISCED) codes 0-2, 3-4, and 5-6, respectively.

Source: Figure 2.1 in OECD (2017d), Preventing Ageing Unequally,

Health inequalities widen with age. The proportion of people reporting bad health rises with age: from about one-tenth of the entire population at the age of 20 to more than half at 64 years old (Figure 3.9A); and from about one-tenth of the employed to slightly over one-third, respectively (Figure 3.9B). While there are no significant differences between men and women, there are substantial disparities between education levels (Figure 3.9C; Figure 3.9D). Among the highly educated, less than 10% are in bad health at the age of 25 and about 35% at the age of 64. The figures are close to 20% and 60%, respectively, among people with low levels of education.

Figure 3.10. Employment rates at all ages are lower for individuals in bad health
Employment rate by gender, age and self-reported health in 24 OECD countries

Source: Figure 2.2. (Panel A) in OECD (2017d), Preventing Ageing Unequally,

Disadvantage in education, health and the labour market often compound each other. Individuals in bad health are less likely to work and, at all ages, employment rates are lower among the unhealthy than the healthy (Figure 3.10). For example, among both men and women in good or bad health, age-related employment rate curves are hump-shaped, falling away sharply after the age of 55. In addition, when individuals with poor health do work, they earn lower wages than their healthy peers. Over the whole career, bad health lowers the lifetime earnings of men with low levels of educations by 33% and those of the highly educated by 17%. Earnings trajectory patterns among women are a little different and health effects are less pronounced (at 18 and 13%, respectively) as the risk of health-related non-employment is lower (OECD 2017a; OECD, 2017b; OECD, 2017d).

Improving education, for instance, could have positive knock-on effects on the labour market and health. Inequality-reducing policies in education, labour market or health will generate greater total returns in terms of welfare as they spill over into other areas. Interventions at an early age are also important because, in most aspects of human capital (e.g. education and health), inequalities emerge very early in life and interventions that reduce inequality will complement each other over the life course.

Trends in environmental quality of life

Inter-country inequalities raise equity concerns that are linked to countries’ approaches to mitigate environmental degradation, while intra-country inequalities can inform about parts of population exposed to and responsible for environmental pressures and risks. Distributional questions cut to the heart of both environmental quality of life and resource consumption. The extraction and use of energy and non-energy materials has continued to rise at the global level in recent years, while changing trade patterns and the displacement of resource-intensive production to other countries have contributed to production-based productivity gains in OECD countries accompanied with higher emissions (OECD, 2017f; Figure 3.11). There is a potentially larger negative impact of emissions on some countries (e.g. low-lying islands) and negative health effects (not just CO2 emissions) on those countries/regions where activities have relocated.

Natural resource consumption and its by-products, raise concerns about how the appropriation of rents, access to resources and exposure to potential contamination and pollution are being shared among the population. Demand-based CO2 emission patterns hide behavioural traits linked to the inter-country and intra-country dynamics of inequality. Globally, about half of the CO2 emissions associated with individual lifestyles are estimated to be generated by the top 10% of the global income distribution, who disproportionately live in the least egalitarian OECD countries (Chancel and Piketty, 2015). Related work (Levinson and O’Brien, 2015; Oxfam, 2015) has also suggested that the lifestyles and consumption patterns driven by economic inequality typically imply that the top few earners use more energy and create more waste.

Figure 3.11. CO2 emissions from energy use are still growing worldwide

Source: IEA (2016), “CO2 emissions by product and flow (Edition 2016)”, IEA CO2 Emissions from Fuel Combustion Statistics; OECD (2015d), “Carbon dioxide embodied in international trade”, OECD Structural Analysis Statistics: Input-Output.


Uneven consumption of resources is matched by an unequal distribution of its environmental effects. The effects of environmental degradation are unevenly distributed between and within countries, with those least prepared and able to cope suffering the greatest socio-economic consequences. In terms of climate change, the World Bank estimated that unmitigated climate change could push 100 million people in developing countries into extreme poverty by 2030 (World Bank, 2016). Likewise, the economic risk of climate change is shown to be unequally geographically distributed in the US; implying that temperature rises could induce a transfer of value from the poorer south towards wealthier parts of the US, thereby increasing economic inequality (Hsiang, Solomon et al 2017). Poorer communities are ill-prepared to meet the challenges of climate change, being less able to invest in ex-ante preventative measures or ex-post mitigation (OECD, 2017e).

Taking decisive action on climate change provides an opportunity to generate new jobs and spark economic growth, but it will also result in job losses with specific distributional impacts. According to the IEA’s 66% 2°C scenario, putting the planet on a trajectory that would see a 66% chance of limiting temperature rises to 2°C would lead to around 1 million jobs being lost in the energy sector (against a total of 30 million in the sector) due to the premature closure of assets (IEA, 2017). Though modest at the aggregate level relative to the total number of jobs in the energy sector, associated job losses could be unevenly spread and concentrated in specific localities, leading to geographical dislocations (OECD, 2017b).

Acting on climate change will allow reduce exposure of people to air pollution, which is the single greatest environmental health risk worldwide with specific consequences for some segments of the population. Globally, exposure to outdoor fine particles (PM2.5) and ozone can be attributed to an estimated 4.4 million deaths annually. OECD countries account for an estimated 500 000 of these (GBD, 2015). The annual welfare cost is estimated to be USD 1.7 trillion, equivalent to 3.6% of GDP for the OECD area (Figure 3.12Figure 3.12). Without stronger policy efforts, the cost is projected to reach USD 3.5 trillion in 2060 (equivalent to 5% of GDP in 2060). In non-OECD economies, the costs are projected to increase tenfold and could reach USD 15-22 trillion in 2060 (equivalent to 7-10% of their GDP in 2060; OECD, 2016b).

Figure 3.12. The OECD annual welfare cost of outdoor air pollution is 3.6% of GDP
OECD and BRIICS, the cost of premature deaths from outdoor air pollution, trillion USD

Note: OECD calculations using methodology adapted from OECD (2014). A standard value-of-statistical-life (VSL) estimate is used to calculate the costs of premature mortalities. The country-specific costs presented here account for differences in income levels and income elasticities across countries (elasticity of 0.8 for high-, 0.9 for middle- and 1 for low-income countries). Nevertheless, the underlying VSL estimate might be less reliable when applied to countries with different standards of living or extrapolated over time. VSL also captures non-market values that are unrelated to expenditures and therefore not an integral part of the calculation of GDP. Consequently the cost estimates are compared with GDP only for illustration.

Source: OECD (2014), The Cost of Air Pollution: Health Impacts of Road Transport.


Exposure to air pollution is not uniform across income groups and varies across countries. A recent meta-analysis of existing work on global air pollution and inequalities showed that generally air pollution is higher in poorer communities – with 8 of the 10 studies analysed illustrating this relationship (Hajat A, et al, 2015). The relationship between exposure to ambient air pollution and low income status was most consistent in North America, Asia and Africa (though data are extremely limited). In Europe, by contrast, there was no clear relationship. This indicates the extent to which the distribution of environmental outcomes may depend on numerous other factors, such as: geography, urban planning, infrastructure design, technology and the level of intra-country inequality.

Access to safe water supply and sanitation is widespread across the OECD, but further progress is needed in emerging economies especially for the most vulnerable households. At the global level, inadequate access to safe water supply and sanitation acts as a large drag on economic growth and well-being, increasing mortality and morbidity, reducing labour productivity and undermining freshwater ecosystems. These effects are typically concentrated in the lower parts of the income distribution in emerging economies and developing countries (OECD, 2017e and OECD, 2012b). Across the OECD area, the share of population whose wastewater is connected to a municipal sewage treatment plant rose from about 60% in the early 1990s to almost 80% today. About 72% benefit from at least secondary treatment (OECD, 2017f). Reductions in health impacts, in terms of disability-adjusted life years (DALYs) due to insufficient access to safe water and sanitation, have been substantial, falling by 90% in Mexico and Turkey since 1990 and by 70% or more in the BRIICS (OECD, 2017a). However, further progress is needed in Indonesia, India and South Africa to increase access to improved sanitation and drinking water facilities (OECD, 2017f). This will become increasingly difficult as increased water demand exacerbates water stress in many river basins in densely populated areas in rapidly developing economies. More river basins are projected to come under severe water stress by 2050, mainly as a result of growing water demands and the number of people living in these stressed river basins is expected to increase sharply, from 1.6 billion in 2000 to 3.9 billion by 2050 (OECD, 2012b). By then, around three-quarters of all people facing severe water stress will live in the BRIICS (OECD, 2012b).

Trends in inclusive places and communities

Across a range of dimensions, well-being outcomes can also vary considerably within and across metropolitan regions, with higher income inequality in cities. Educational attainment can vary by more than 15 percentage points across cities in Canada, France, the Netherlands and the United States (OECD, 2016 Making Cities Work for All). Life expectancy can vary by a staggering 20 years across neighbourhoods in Baltimore (United States) or London (United Kingdom) (OECD, 2016 Making Cities Work for All).

Residential segregation has increased in many OECD countries. Residential segregation –in which individuals with shared characteristics, such as income level, race or ethnicity, are spatially concentrated– has been increasing in many OECD countries over the past decades, although the trends, challenges and drivers differ across countries (OECD, 2016f). For instance, the most income-segregated cities in the Netherlands and France are at comparable levels to the least income-segregated cities in the United States (OECD, 2016f). Even within the same country, income segregation can vary across cities depending on place-specific factors, such as urban size and productivity, the degree of concentration of population in a single centre, and demographic profile (OECD, 2017h). By extension, these disadvantages can weigh on future generations and limit social mobility. Evidence suggests that transport plays a crucial role in this regard: a lack of, or poor access to, transport options is central to limitations on access to jobs, educational institutions, health facilities and social networks, which in turn can generate a “poverty trap” (ITF, 2017).

Healthy communities and their connectedness are strong foundations of future prosperity. At the individual level, social support among friends and family, and time spent socialising as core elements of community relationships. At the next level up, factors such as volunteering, trust in others, housing conditions, environmental quality, and personal safety are all highly relevant for community well-being and social capital. Meanwhile, at the wider societal level, acts of civic engagement (e.g. such as voting) and the functioning of public institutions (e.g. trust in government; having a say in government, and government stakeholder engagement) become important factors to consider.

Social ties have weakened since 2005. Mirroring the increasing distance between people and the public institutions, most of OECD countries saw a weakening of social ties among people. This is shown by the fall in the share of people across OECD countries who feel they have friends or family members to count on in times of need (Figure 3.13).

Social divisions threaten community inclusiveness. Like most well-being outcomes, there are large societal divides in terms of who feels safe in their neighbourhood, who feels supported by friends and family, who has time to spend socialising, who trusts in others, who volunteers, and who votes (OECD, 2015e; 2017j). Younger people are worse-off in terms of voter turnout, while older people are heavily disadvantaged (relative to the middle-aged) in terms of social support, feelings of safety and having a say in government – despite being more likely to vote (Figure 3.14). Relative to the native-born, migrants and low-educated feel less safe and less supported.

Trust is also fragmented among different groups of population. Recent data from the European Union’s Statistics on Income and Living Conditions (Eurostat, 2015), and from the OECD’s Trustlab (Box 3.1) both indicate that trust in others increases with income and education, and is lowest among the unemployed.

Figure 3.13. Social support, voter turnout and trust in government have fallen since 2005

Source: OECD (2017j), How’s Life? 2017; Figures 1.13 and 1.29.


Box 3.1. Using experimental methods to measuring trust and other social preferences

Trust is indispensable for social and economic relations (Arrow, 1972, Putnam, 2000, Guiso et al., 2008). At the same time, citizen’s trust in public institutions is a crucial component for policy reform and the legitimacy and sustainability of any political system (OECD, 2015). However, available measurement instruments of trust so far have mostly been narrowly focused and survey-based, with limited evidence on their validity. The OECD’s Trustlab project is the first internationally comparable instrument that combines behavioural measures of trust and other social preferences with an extensive survey of attitudinal, institutional and social determinants of trust in other people and trust in institutions. The database currently contains data from six countries: France, Korea, Slovenia, the United States, Germany and Italy and is supported by a network of affiliated research institutions and government agencies.

The main determinants of trust in others include beliefs about others’ trustworthiness and other-regarding preferences such as altruism, trustworthiness and willingness-to-cooperate, as well as the quality of institutions and proxies of social capital such as neighbourhood connectedness and volunteering. For trust in institutions, perceived government integrity, government reliability and government responsiveness, as well as neighbourhood connectedness and positive attitudes towards immigrants appear as main drivers.

Source: Murtin et al. (2018).

Figure 3.14. Divided communities in terms of social support, feelings of safety, civic engagement
OECD countries, by gender, education, age and migrant status

Note: The figure shows the percentage difference between groups, relative to the reference group indicated. Social support and feelings of safety are captured on a simple yes/no scale; voter turnout concerns the percentage of votes cast among the population registered to vote in the most recent national elections, while having a say in government refers to the share of people who disagree or strongly disagree with the statement: “people like me don’t have any say in what the government does”.

Source: OECD (2017j), How’s Life? 2017.


Figure 3.15. Trust in others increases with income and education
Mean average, on a scale from 0 (you do not trust any other person) to 10 (most people can be trusted) by socio-demographic characteristics, 2016-17

Note: Data is pooled from four countries that participated in the OECD Trustlab project (Germany, Italy, Slovenia, United States). Sample size is N=1000 per country.

Source: OECD Trustlab, Murtin et al. (2018).


Housing and land use

Access to good-quality affordable housing is important on a number of accounts but good-quality and affordable housing remains a pressing concern. Many households across OECD countries are overburdened by housing costs, although there is considerable variation across OECD countries (Figure 3.16). On average across the OECD, the median housing cost burden for mortgage payers is about 18% of disposable income while this is 23% for tenants. The median housing cost burden is much higher for low-income household, at more than one-third of disposable income across the OECD on average (OECD, 2017h). In addition, significant numbers of people are homeless: while statistics are difficult to compare, OECD countries report that 1 to 10 people in every thousand lack regular access to housing. In addition, many households live in low-quality dwellings: 18% of low-income households live in overcrowded dwellings. Neighbourhood crime and pollution are also problematic for many households throughout the OECD.

Housing affordability is a significant issue especially for low-income residents of metropolitan areas. Across the OECD, housing affordability varies considerably. While households in Australian regions only spend around 15% of their disposable income on housing, residents in Scandinavian countries, Belgium or Israel can spend more than a third of their disposable income on housing (Figure 3.17). In Oslo and Akershus (Norway) or Brussels Capital Region (Belgium), housing expenditure accounts for around 40% and 35% of disposable household income, respectively. Overall, competition for housing is significantly stronger in capital city regions. Residents in such metropolitan areas need to spend relatively more on housing, even when higher income levels in capital regions are taken into account. As a consequence, lower income groups risk getting priced out of capital city regions.

Housing policies need to be carefully designed to avoid adverse distributional impacts. OECD countries use a range of policies to promote access to good quality and affordable housing (Figure 3.18). One common type of policy consists of subsidies to homeowners, who receive considerable public support. In many OECD countries home-buyers can benefit from grants, financial assistance and public guarantees often reserved to young and low-income first-time buyers. Homeowners often benefit from favourable tax treatment of housing, which tends to favour better-off households; in addition, they distort incentives to invest in other tenures and/or assets and actually often put pressure on housing prices.

Figure 3.16. Regional differences in housing costs
Housing expenditure as a share of household disposable income, 2014 or latest available year

Note: Each diamond in the figure represents the value in a large region (TL2). The graph presents the data sorted by range of regional disparity within country from the larger to the smaller.

Source: OECD Regional Statistics (database).


Figure 3.17. Households' housing cost burden (mortgage and rent cost)
Share of disposable income, 2014 or latest year available
Median of the mortgage burden (principal repayment and interest payments) or rent burden (private market and subsidized rent) as a share of disposable income, in percent

Note: For detailed notes and national sources, see the OECD (2017) Affordable Housing Database.

Source: OECD (2017h), Affordable Housing Database.


Housing allowances may distort rental prices. Housing support is also delivered through income-related housing-cost subsidies, generally known as housing allowances, and reporting countries spent up to 1.4% of GDP on housing allowances in 2015. Almost all OECD countries use this policy instrument. Housing allowances are usually means-tested, but eligibility conditions and payment rates vary considerably across countries. Housing allowances have weaknesses: they may be less effective in providing access to good-quality rental housing, especially for vulnerable households, and may have perverse effects on rental prices.

Social rental housing is also often in place in many OECD countries. Most OECD countries support the provision of social rental housing. Direct provision exists in many countries – mostly delivered by local authorities or NGOs and funded in part by the central governments. Low-income households are the majority of tenants in many countries – especially in countries affected by shortages of social rental housing. Central government support for the provision of social rental housing ranges goes up to 0.5% of GDP in reporting countries but the amount of public funding has been decreasing in many countries. In 2015 social housing constituted less than 5% of the total housing stock in the average OECD country (OECD, 2017h).

National housing policies need to be flexible and cities need to be given more freedom and resources to respond to their particular circumstances. Regions, cities, and villages have particular housing needs that require a flexible and localised response. Local governments can integrate housing policy objectives within their urban planning responsibilities to support sustainable urban development. Local governments influence public and private housing markets through their planning and development control decisions, have strong connections to the local community, and are well positioned to facilitate a whole of government approach to housing outcomes. Local authorities can formulate ‘local housing strategies’ incorporating an analysis of local housing supply, expected demand, socio-demographic and market trends as well as recommendations for planning processes, land use plans and development regulations.

Figure 3.18. Housing allowances, social housing and support for home-ownership
Overview of housing policy instruments, by number of reporting countries adopting each policy type 1, 2

Note: The list of policy types refers to those surveyed through the 2016 Questionnaire on Affordable and Social Housing, which gathered information from 35 countries. No information is available for Belgium, Denmark, Iceland, Israel, Italy and Turkey.

Source: OECD Questionnaire on Social and Affordable Housing, 2016.


Local governments play an essential role in ensuring equitable access to an adequate supply of affordable and good quality housing as well as for reducing segregation of communities. In many OECD countries local governments build and manage public rental housing, either directly or through municipal public housing companies. Furthermore, local governments can require from developers that a share of newly built housing is made available to low-income residents at below market rents. Decisions on where to locate public and social housing can also contribute to inclusion by promoting mixed-income neighbourhoods and preventing the risks linked with spatial segregation by income. Local governments can use land use regulations and the building approval process. If land use regulations prevent housing supply from adjusting to growing demand, house prices will rise. Recent evidence suggests that this mechanism is responsible for rising house prices in many large and growing cities in OECD countries (e.g., Glaeser and Gyourko, 2017, and Hilber and Vermeulen, 2016). In cities and regions with fast-growing populations, land use regulations need to permit sufficient housing construction to meet growing demand for housing while preventing the negative externalities of urban sprawl, for example, by encouraging the densification of the existing housing stock (OECD, 2017h).

One challenge for housing policy is to address residential segregation, which reflects and contributes to socioeconomic and racial inequalities. Poor people living in areas with highly concentrated poverty experience inadequate schools, limited job prospects, and disadvantaged peer groups, all of which contribute to social exclusion. Although people have the legal right to live wherever they want, segregation has continued through discrimination (e.g., in the private housing market), historical housing policies (e.g., governments’ placement of social housing in undesirable locations, zoning and planning restrictions), and economic factors (e.g., the affordability of quality housing). National and local policies to address spatial segregation have been put in place in many countries. Some European countries, the US and Chile used tenure diversification, sometimes combined with demolition programmes, as part of wider urban renewal policies integrating economic and social elements. The effectiveness and unintended consequences of these programmes, as well as their integration with social elements, should be further explored (Salvi et al, 2017).

Policies that ease geographic mobility and improve regional connectivity can help individuals to connect to jobs, services and opportunities. In the 29 OECD countries studied, 24 million people changed their region of residence each year during 2011-13. There is a lot of variation within regional migration rates – with the highest rates seen in Gümüshane (Turkey) and North Aegean (Greece) and la Plama (Spain) the lowest rates in Agri (Turkey), the Northern Territory-Outback (Australia) and the Northwest Territories (Canada) (Figure 3.19). In aggregate terms, the net migration rate in the predominantly urban regions of 26 OECD countries is much higher than in intermediate and predominantly rural ones. While predominantly urban areas grew by 6 persons per year (10 000 population in total) in 2011-13, intermediate and predominantly rural areas declined by 2 and 10 persons per year, respectively (Figure 3.20). Distance to labour markets and services seems to explain migration within OECD countries; with the exception of Turkey, the United States, and Sweden, remote rural regions – i.e. regions which are far in driving distance from urban agglomerations – show higher net negative flows than the rural average. Adopting a territorial development strategy based on the functional linkages between urban and rural areas helps to foster better integration between them.

Transport systems help reduce social exclusion by improving individuals’ access to jobs, educational institutions, health facilities and social networks. Extensive public transport coverage is a prerequisite for good accessibility, but in reality, coverage and access are not necessarily related due to low frequencies, low station density and inadequate networks (Figure 3.21). Accessibility to opportunities by public transport varies greatly by cities of different sizes, with European cities generally offering higher accessibility than North American and developing cities. Reducing the accessibility gap in regions and cities requires significant investment in infrastructure and improved services. It is particularly important to identify accessibility limitations faced by vulnerable groups. Lower-income populations tend to suffer more from restricted transport options, have lower quality transport services available to them and travel under worse conditions (safety, security, reliability, and comfort). This in turn generates a “poverty trap”. Other factors, such as age, and disability can also limit peoples’ access to activities and services. Within functional urban areas, more effective and reliable public transport infrastructure can contribute to improve labour market outcomes of minority groups residing in poorly connected areas of cities.

Improved data and analysis can help to develop transport that focuses on creating access, while land-use policies can foster urban accessibility. Coherent pricing policies for each transport mode can support sustainable mobility and social inclusion goals; for example, by ensuring that externalities created by private vehicles are reflected in the pricing framework. Transport-oriented development (TOD) refers to the principle of building high density housing and office space primarily along public-transport corridors and hubs. In cities that are planned along this principle, residents without private cars can access a much larger share of the available jobs than in cities where housing and office space is built without considering public transport. Likewise, TOD proposes mixed-use policies which improve the accessibility of cities. They encourage the construction of residential buildings and commercial facilities, such as office and retail space, within the same neighbourhood. This reduces the average distances residents need to travel for commuting and activities of daily life, such as shopping. Transport-oriented development reduces the need for driving, contributing to lower congestion and decreasing air pollution and carbon emissions, which benefits all residents of a city. Urban renewal and transit-oriented development strategies can be readjusted by measuring their performance in terms of equity and social inclusion and can be used to mobilize increases in land value to deliver objectives for social inclusion

Figure 3.19. Maximum and minimum annual regional migration rate, average 2011-13 (left)
Net flows across TL3 regions, % of total population

Source: OECD Regional Statistics and Indicators (Database).


Figure 3.20. Annual regional migration rate per typology of region, average 2011-13 (right)
Net flows across TL3 regions per 10 000 population

Source: OECD Regional Statistics and Indicators (Database).


The impact of urban planning policies that intend to counter segregation has been mixed so far, suggesting that interventions will have to be carefully designed to increase social capital. While several evaluations found no improvements in social cohesion after changes in the housing stock increased the social mix (Van Bergeijk, 2008, Van Kempen and Bolt, 2009), other authors have found that community connectedness and interactions were stronger in walkable rather than in car-dependent suburban neighbourhoods, as well as in communities that feature good public transport connections and vibrant public spaces (Leyden, 2003; Schreiber and Carius, 2016). Furthermore, the recent relocation of refugees from the Calais “Jungle” in France to temporary refugee-centres has been found to significantly reduce the vote share increase for the far-right in recipient municipalities, suggesting that actual contact with people from another background can improve attitudes towards diversity (Vertier, 2017).

Figure 3.21. Public transport accessibility in cities
Public transport coverage and average accessibility by public transport

Source: International Transport Forum (2017).


Policies to enhance opportunities and foundations for future prosperity

Improving the life of every child

Effective interventions can protect children’s mental wellbeing, or mitigate the impact of mental illness during childhood and adolescence. Infant, child and adolescent mental health promotion and disorder prevention are amongst the areas that have received the most attention from OECD countries in recent years (McDaid, Hewlett and Park, 2017). Education systems can also play a key role in identifying and supporting children with mental health issues at an early stage, including through investments in preventive mental health programmes in schools to develop resilience, and mental health competence training in the teacher-training curriculum (OECD, 2017i; OECD, 2012; OECD, 2009). Timely access to support for young people with mental ill-health is also critical. Although in-school mental health services are common in OECD countries, they lack the capacity to provide timely support to all students in need. The availability of psychological support in schools, and high-quality and easily accessible children’s and adolescents’ mental health services could stand to be improved in most if not all OECD countries.

Social policies can help foster equal opportunities for children by:

  • Addressing family poverty and its effects on child material deprivation and family climate. Poverty can affect child outcomes through different channels. Inadequate economic resources first reduce households' ability to purchase or produce important “inputs” for child development, such as nutritious meals, educational resources, leisure activities, or high-quality formal childcare. Low-income families also often live in neighbourhoods with a lower provision of transportation or care services, more difficult access to good schools, and sometimes a greater exposure to crime. Financial strain also damages the family climate and affects family relationships, including interactions between parents and children, which in turn can affect children’s outcomes. Better policies helping low-income families to reconcile work and family are also crucial to improve the quality of parental time and of child-parent interactions.

  • Addressing the multiple needs of disadvantaged children. Integrated service delivery has the potential to improve service-use outcomes for families with multiple needs (OECD, 2015e). Successful initiatives share common traits, such as case management and a community-based single-entry point to services, although existing programmes vary greatly across countries in scope and design. Another strategy is home-based services (e.g. mobile family support teams), which help reach families that have difficulties in receiving services or are unable to access co-located services (e.g. in rural areas). Integrated home services also enable providers to assess and treat the full range of problems adults and children face. Programme effectiveness depends crucially on how different services work together and how well local, regional and national authorities facilitate the integration of service delivery.

  • Adapting social protection systems to changes in family living arrangements. The growing heterogeneity of family living arrangements creates inequities between children, as the policy support they receive often depends on the legal recognition of their parents' partnership status. Many countries should consider increasing support for children with non-married parents in the event that their parents separate or die. Tax and benefit systems, as well as child support regimes, also need to ensure that all children have access to the same supports regardless of their parents’ legal partnership status.

  • Investing in children early on. Early interventions, in response to emerging signals of need, must be delivered before disadvantages become entrenched. This can also limit future costs to individuals, society and the state. Policies supporting the early development of cognitive (e.g. language and numeracy) skills, social (e.g. self-confidence, self-control, pro-social behaviour) skills, and physical health can have long-lasting positive effects on educational attainment, employment and income.

Providing strong educational opportunities

Inclusive education systems that provide people with the life-time skills and opportunities are the main foundations of future prosperity. By focusing on early childhood education and targeting disadvantaged children and schools, such systems can foster inclusive growth and social cohesion by focusing on mitigating inequalities early on in people’s lives. Evidence shows that intervening early on in children’s lives is one of the most effective ways to prevent the accumulation of inequalities later on in life (OECD, 2017a). Inclusive education systems must also provide continuous learning and skill development opportunities for adults throughout their lifecycle and remove barriers to adult education by targeting financial assistance to those most in need.

Public investment in education, especially for disadvantaged children and young individuals, need to be prioritised to build equitable and inclusive societies. In 2016, public social spending was 21% of GDP on average across OECD countries. In recent years, public social spending-to-GDP ratios have been highest in France, at 32% of GDP, followed by Finland (over 30%). Social spending-to-GDP ratios have fallen in a few OECD countries, including Hungary, Luxembourg, Latvia and Ireland, but have only slightly increased or have remained stable in most. Most OECD countries spend far less on education as a percentage of GDP, especially post-secondary education, than on pensions or healthcare. On average, public expenditure on primary, secondary and post-secondary education as a percentage of GDP was 3.4%. Given the substantial returns to education countries should consider increase their spending on education focusing on programmes targeted on disadvantaged children and youth (Box 3.2).

Box 3.2. Financing Tertiary Education

The returns to tertiary education are significant (OECD, 2015b). In general terms, countries can provide direct support for tertiary education (e.g. tuition reductions, increases in scholarship, grants, subsidised loans) or through the tax system. Non-tax approaches to providing support for skills investments (e.g. tertiary education, including scholarships, reduced tuition, and income-contingent loans) may be more beneficial for low-income students. Higher tuition levels reduce enrolment, and tuition reductions or increases in scholarship and grant spending has positive distributional and efficiency consequences (Kane, 2006). Fee reductions or scholarship and grant provision is more effective at raising enrolment and completion rates compared to tax-based subsidies. It is also better targeted towards those on lower incomes, and finally it is more likely to raise the enrolment rates of those on lower incomes compared to skills tax expenditures (STEs), which are often less beneficial to those on lower incomes due to a lack of taxable income or to the administrative burden of applying for STEs.

Income contingent loans can be another attractive option. While on average, a skills investment will pay for itself, many students make skills investments that may just break even or may not breakeven at all. This can be the case even if the investment did have positive expected returns. Loans that feature income contingent repayment offer insurance for the student against these risks. Support to students through income-contingent loans has been found to be particularly effective, in terms of ensuring access to education for low-income students, sharing the financial burden between government and students, distributing the risk of human capital investments, and balancing equity and efficiency considerations.

Access to quality early childhood education, to schools with highly qualified teachers and to adult education and training must be warranted to all individuals. The cognitive, social and emotional skills developed during the first years of life set the stage for future potential (OECD, 2015f). Early learning deficiencies can be overcome, but inadequate learning environments and lack of support can hamper educational development and have lasting impacts on individuals later in life (OECD, 2015f). Children from less privileged socio-economic backgrounds are far less likely to benefit from high-quality home learning environments and early childhood education and care services (ECEC) than their more affluent peers. As a consequence, targeted policies need to be considered to ensure high quality learning opportunities for children from disadvantaged backgrounds. These include remove barriers to ECEC, ensure provision of quality of ECEC, and support family and community-based interventions.

Disadvantaged schools should be further supported. Disadvantaged schools are typically most in need of high-quality resources and support, but in most countries, they are more likely to suffer from financial constraints and a lack of staff. Disadvantaged schools also tend to have a disproportionately high number of students considered to be low performers and at risk of dropping out (OECD, 2016c). Allocation of adequate resources to disadvantaged schools is essential in ensuring that all students receive the high-quality education and training they need to fully participate in society (OECD, 2016c). Providing such schools with additional financial and human resources is essential. School budgets should prioritise spending, as well as investing in high-quality human resources such as school leaders and teachers, who play a critical role in reducing educational inequality in their schools. Monetary or professional-level incentives can also be used to attract effective school leaders and teachers to disadvantaged schools. Targeted support should be given to school leaders and teachers in disadvantaged schools, and efforts need to be made to connect them to other school leaders and teachers, which can help them share knowledge and provide assistance to each other (OECD, 2012c; OECD, 2016c).

Young people need support to move on with education and employment. Fifteen percent of the OECD youth population were not in employment, education or training (NEET) in 2015 – about 40 million young people. More than two-thirds of them were not actively looking for work. Job and income uncertainty can keep young people from reaching other traditional markers of adulthood, leaving them disenchanted and discouraged. NEET youth have lower levels of life satisfaction and trust in others compared to non-NEET youth. They also show less interest in politics and are more likely to feel that it is the government’s responsibility to provide for citizens, with rising inequalities when regions fail to catch up (Figure 3.22). Being NEET can also have serious long-term effects on health, fertility and crime, and eventually endanger social cohesion.

Poor health and poor school performance have strong bearings on the risk of joblessness in young adulthood: 15-29 year-olds suffering from poor health are four times more likely than their peers to be not in employment, education or training (NEET), while not having completed upper secondary education more than doubles the risk of becoming NEET later (OECD, 2016c; OECD, 2016f).

School leavers and young people with patchy employment records often fail to qualify for insurance-based income support. Only around 30% of all unemployed young people receive unemployment benefits, while over 40% of all jobseekers aged 30 and over are covered. Consequently, social safety nets are less effective in fighting poverty among young people: 40% of young people who would have incomes below the poverty line are kept out of poverty by public transfers, compared to 50% of adults aged 30 and over. Roughly every eighth young person lives in poverty, and youth poverty rates are higher than those of the elderly (OECD, 2016c; OECD, 2016f).

Comprehensive support is needed to ensure that all young people complete their upper-secondary schooling. Because low educational attainment is such an important risk factor for NEETs, fighting early school leaving is essential. This typically involves actions such as monitoring school attendance to spot warning signs of drop-out; addressing pupils’ social or health problems; and offering after-school programmes to engage pupils and strengthen their motivation.

Figure 3.22. NEET rates are substantially higher among young people with low education
NEET rates as percentages, 25 to 29 year-olds, by level of education, 2013-14

Note: Data refer to 2014, except for Australia, Chile, Germany, Israel, Korea, Mexico, New Zealand and Turkey (2013). No data were available for Japan “Low-education” denotes lower-secondary school and lower (Levels 0-2 in the International Standard Classification of Education [ISCED]); “medium education” refers to upper- or post-secondary education (ISCED Levels 3-4); and “high education” means higher, or tertiary, education (ISCED Levels 5-6).

Source: OECD (2016f), Society at a Glance,

An effective school-to-work transition also requires specific policy interventions. Those who experience a period of unemployment early in their careers are more prone to become unemployed later in life (Schmillen and Umkehrer, 2013; Möller and Umkehrer, 2014) and have been shown to earn less (Umkehrer, 2015). To prevent unemployment at young ages a number of measures have proved particularly effective:

  • Provide work experience early. Working a moderate number of hours (below 15 a week) has been shown to lower the risk of early school leaving, possibly because it helps develop important life skills such as conscientiousness and motivation, and can steer students towards a career path. There are also benefits for university students, especially if they work moderate hours (less than half-time) in a job related to their field of study (Quintini and Martin, 2014). For example, many Swedish municipalities and county councils, as well as the city of New York, run summer internship programmes for 16-18 year-olds. These programmes have been shown to help young people to accumulate more work experience later and increase earnings in young adulthood, especially for the most disadvantaged young people. They also seem to protect young people against adverse outcomes such as incarceration lower mortality (Alam et al., 2013, Gelber et al., 2016).

  • Offer career guidance to help ensure that students make the right choices. Quality career guidance can boost education and training completion rates by improving the match between young people and their chosen path. It can strengthen social mobility by informing young people of career paths that their family and social networks may not suggest, and encouraging them to choose paths more likely to lead to stable employment. Career guidance is of special importance to young people who consider VET programmes –including apprenticeships– as they affect students’ career prospects more directly than general secondary programmes. Young people’s participation in career guidance is easiest to ensure in the case of school-based career counselling. The involvement of employers or outside specialists helps make information more comprehensive and truer to the realities of the labour market.

  • Supply good-quality practical training. Good-quality practical training can help smooth school-to-work transitions by making educational programmes attractive to young people while providing them with skills that are valued in the labour market. To ensure quality and relevance, training should be partly company-based, ideally in the form of apprenticeships. But succeeding in vocational programmes can be challenging for the most disadvantaged, who may lack foundation skills or motivation. Pre-apprenticeship programmes can help prepare young people with skills gaps for participation in standard vocational education programmes by helping them to brush up on patchy literacy or numeracy skills, build motivation, familiarise them with the work routine, and even give them short spells of work experience.

  • Support jobless young people with targeted interventions. While many young NEETs need only some support to find a job, those without upper secondary education and those with health problems or disabilities need more intensive help. The most promising programmes combine schooling and practical training with counselling, psychological support, and housing assistance to build cognitive, vocational and social skills simultaneously. Social skills have been shown to be malleable through adolescence and early adulthood, and to hugely impact a wide range of life outcomes including delinquency, labour market attachment and earnings, as well as family stability (e.g. Kautz etl., 2014). And indeed, intensive programmes that combine training with accommodation, mentoring and social support have been shown to have positive long-term effects on labour market participation, earnings, and reduced criminal activity (Schochet et al, 2008).

It is essential to reduce barriers to participation in adult education. Removing financial, situational and time-related barriers to participation in learning programmes is absolutely essential, especially for the socio-economically disadvantaged. Co-financing and tax incentives are particularly effective. A variety of co-financing arrangements policymakers are one option to consider, including Individual Learning Accounts (ILA), accounts set up exclusively for adult-learning purposes, vouchers and training allowances and training leave. In addition, tax-based mechanisms such as tax allowances and tax credits that reduce the tax liability on at least part of an individual’s spending directly related to skills training costs can remove cost barriers and act as an incentive for participating in adult learning (OECD, 2017k). Such tax incentives can increase the returns to skills by making the costs of skills acquisition deductible for personal tax purposes. To remove time and situational barriers, innovative and effective adult learning programmes, such as online, distance and family-based learning programmes can be used. In addition, providing courses on a part-time basis, on evenings and weekends, can help increase flexibility and encourage participation in adult education (OECD, 2016c).

Invest in health outcomes for all groups in the population

Within the health service delivery system, universal access to quality healthcare services is encouraged. Policies could address the needs of socially disadvantaged and vulnerable population groups (e.g. poor, elderly and pregnant women, among others).

Despite significant governments’ efforts to protect vulnerable populations from excessive cost-sharing, unmet needs across these groups are still large. In New Zealand, for example, very low cost access (VLCA) practices serving disadvantaged populations receive government subsidies if they remove patient fees (Paris et al., 2010). In Canada and France, subsidies are provided for the poor to obtain complementary or supplementary private health insurance. Further, whilst patients from OECD countries often have to pay out-of-pocket for pharmaceuticals, dental care and eye care, the poor, children and elderly populations are commonly exempted from such charges. Nevertheless, unmet care needs are still higher among the poor, with 14% of low income adults reporting unmet care needs due to cost compared with 25% amongst other adults, amongst the 10 OECD countries with comparable data (OECD 2017b).

Ensuring access requires an adequate distribution of health professionals throughout a country as well as harnessing new technologies. Concentration of doctors and other health professionals in one region and shortages in others can lead to inequities in access such as longer travel or waiting times. In many OECD countries, remote and sparsely populated areas, as well as deprived rural and urban regions, have insufficient health professionals. This often reflects the difficulty in recruiting and retaining doctors in such localities. A range of policy levers can be used to influence the choice of practice location of doctors. For example, Japan established in 1973 the Jichi Medical University specifically to educate physicians for service in rural communities, which has contributed to improving access in underserved rural regions (Ikegami, 2014). More broadly, key policy options include: (1) using financial incentives for doctors to work in underserved areas; (2) increasing enrolments in medical education programmes of students coming from specific social or geographic backgrounds; (3) regulating the choice of practice location of doctors (e.g. for new medical graduates or foreign-trained doctors); and (4) re-organising service delivery to improve working conditions in underserved areas (OECD 2017b). Better exploiting information and communication technologies can also improve access in remote areas, for example through greater use of telemedicine and other innovative models of service delivery.

Alongside policies to improve access to health services, a priority is to address the major causes of ill-health and premature deaths amongst disadvantaged populations. This includes tackling preventable major risk factors, such as obesity and smoking. The prevalence of these risk factors varies across socioeconomic categories and may be disproportionately prevalent amongst poorer and less educated populations. For example, less-educated women are two to three times more likely to be overweight than those with a higher level of education in about half of the eight countries for which data are available (Figure 3.23). Disparities are smaller for men, although they are growing. Greater efforts targeting modifiable behavioural risk factors among disadvantaged groups can play an important role in promoting healthier lifestyles, offering individuals better choices, and reducing health inequalities.

Figure 3.23. Less educated women are more likely to be overweight
Education-related inequality in being overweight for women, 2014 or latest year available

Note: Overweight defined as BMI≥25kg/m². Education level is categorised into three groups (primary, secondary, tertiary education). On the Y-axis, the relative index of inequality measures the inequality of being overweight by education level.

Source: OECD analysis of national health survey data.


A comprehensive policy package, tailored to local contexts and engaging across all stakeholders and across all sectors is suggested to tackle obesity, especially among disadvantaged individuals and households. New health care initiatives implemented in some OECD countries over the last few years include interventions in the primary care setting (e.g. prescribing physical activity) and communication policies which promote healthy diets (OECD, 2017c). For instance, informative food labelling can help people make healthier choices. Policies outside the health sector include pricing and fiscal measures, school-based and worksite interventions, reformulation of products, changes in portion sizes, and transport policies (e.g. subsidies for active commuting as an alternative to cars).

Design of health policies must specifically take into account low-income groups. For example, communication policies that promote healthy diets by improving health literacy and empowering consumers (e.g. mass media campaigns to increase awareness of healthier food consumption) designed to target specific disadvantaged population groups. A number of OECD countries (e.g. Belgium, Chile, Finland, France, Hungary, and Mexico) increasingly implemented taxation policies in the past few years to increase the price of potentially unhealthy products such as foods high in salt, sugar or fat, or sugary drinks. Taxation policies financially affect low-income people disproportionally more than high-income people. But at the same time, these low-income individuals also are more likely to be obese. Additional evidence is however needed to establish the efficacy of these policies in reaching specific health outcomes.

Reducing alcohol consumption requires a range of policy interventions. Policies aiming to reduce alcohol consumption include fiscal measures (e.g. taxation and minimum unit pricing for alcohol), regulatory measures (e.g. regulation about point of sales, location and hours, age limits, drink-driving enforcement, advertising regulation), and health promotion and health care policies (e.g. treatment of alcohol dependence) (OECD, 2015a). Regulations of alcohol advertising have been implemented in many OECD countries but the forms of media included in these regulations (e.g. printed newspapers, billboard, and internet) and law enforcement vary considerably across countries. Norway may have the strictest regulation of alcohol marketing in the OECD. Among recent policy initiatives to limit harmful drinking, minimum unit pricing was implemented in Scotland in 2012. Minimum unit pricing, devised to increase the price of cheap alcohol, is likely to change the consumption among low-income heavy drinkers whereas high-income heavy drinkers may continue to afford to maintain harmful drinking patterns (OECD, 2015a).

A variety of policies exist to tackle smoking. Policies aiming to tackle smoking range from taxation to regulation (e.g. regulation about age limit, smoking-free areas, advertising bans and plain packaging), through mass media campaigns to warn about the dangers of smoking, and health care policies to help smokers to quit. All OECD countries have implemented anti-tobacco programmes and policies, although the types and the intensity of policies vary by country (OECD, 2015b). New anti-tobacco initiatives have been recently implemented in some countries. Australia and France have adopted plain cigarette packaging. Regarding tobacco taxation –a highly cost-effective policy to reduce smoking rates– 26 OECD countries applied taxation rates at 70% in 2014 (WHO, 2016a). France announced a gradual price increase to EUR 10 per cigarette pack by 2020.

Box 3.3. Employment conditions matter for health

Long working hours and limited choice over working hours are harmful to health (Bassanini and Caroli 2014). A review of workplace interventions spanning Canada, Japan, the Netherlands, Sweden, the United Kingdom and the United States found that policies which improved employee control had positive mental health effects (Egan et al 2007). Better educated individuals and their offspring are healthier, independent of income and employment-related effects. A large part of this difference has been attributed to healthier lifestyles. Poor housing conditions (e.g. cold and damp, inadequate safety) and certain neighbourhood characteristics such as the risk of crime have frequently been shown to adversely affect health (Gibson et al 2011). Households with low-incomes and many ethnic minorities are more likely to experience these inadequate living conditions. Air pollution also varies greatly across different neighbourhoods. Across a number of OECD countries, policies targeting better housing infrastructure (home visits, removal of hazards) and rental assistance policies, have had positive health effects (Bambra et al 2010).

Reducing health inequalities also requires developing policies that address the wider social determinants of health. Income, unemployment, education and other socioeconomic factors, as well as lifestyle choices and a person’s living environment can all affect an individual’s health (James et al, 2017). Low income and poverty, particularly when persistent, have clear detrimental effects on health by, for example, causing people to have unhealthy diets. Progressive policies on taxation, benefits and minimum wages are therefore likely to contribute to improved health outcomes. Policies providing more targeted material support can be complementary. For example, studies of the Supplemental Nutrition Assistance Program, which provides food vouchers to low-income families in the United States, find evidence of positive impacts on birth outcomes and child health (US Executive Office of the President 2015). Being unemployed also adversely affects health. For example a meta-analysis of studies using individual data found that unemployment is associated with a 63% higher risk of mortality after controlling for age and other control factors (Roelfs et al 2011).

Policies enhancing environmental justice

Policies aimed at reducing environmental inequalities need to take a holistic perspective to address the social drivers of environmental footprints. Meeting the targets set out in the Paris Agreement will call for a rapid acceleration of the phase out and reform of inefficient fossil fuel subsidies and efforts to broaden the carbon pricing base. Targeted measures can compensate for any potentially regressive impacts of climate policy or removal of fossil fuel subsidies on poor households. There remains a risk that though the effects of new environmental levies (or the removal of subsidies) would affect those higher up the income distribution harder in absolute terms, the poorest groups in society may feel the reduction in spending power more. In that light, it is key to ensure that a portion of the revenue raised from environmental taxation or the removal of subsidies is recycled to support those same groups. Recent OECD work has provided evidence of the need for revenue recycling with respect to addressing inequality. It found that between 1995-2011, in those OECD countries without an explicit mechanism to redistribute environmentally related tax revenues, energy tax revenues (% of GDP) were shown to have a positive, although modest, relationship with income inequality. In contrast, in countries where energy tax revenues are, at least partially, used to reduce tax burden on income and labour, there is a negative relationship between energy taxes and inequality in income sources (OECD, 2016d).

Governments ought to seek out potential policy complementarities between promoting greater resource efficiency and equity. To improve resource efficiency, policies need to target the entire life-cycle of any given material resource (OECD, 2016e). To date, policy instruments have generally been applied further downstream in the product lifecycle rather than upstream (OECD, 2016e). For example, the number of countries reporting the use of economic instruments such as landfill taxes increased significantly in the past 15 years, which has led to a move away from landfill towards energy recovery. Despite this and other downstream successes, further efforts are needed upstream to encourage waste prevention in the first place. Such efforts could include policies that encourage greener product designs and measures to change consumer behaviour. These prevention efforts would naturally have socio-economic distributional implications, as their focus would be on those consuming the greatest quantities of material resources, who typically come from the upper end of the income distribution (in the wealthiest countries). Ultimately, efforts to improve resource efficiency will only be successful if governments can embed the objective into key existing policies areas from innovation, to investment, trade, education and skill development. Notably, several of these policy areas are also crucial for determining the shape and extent of socio-economic inequalities, suggesting that cross-cutting actions could be undertaken to address both issues. For instance, efforts to foster ‘green’ skills and entrepreneurship to promote resource efficiency could also be targeted at population groups lower down the income distribution.

There are several barriers to a just transition to a low-carbon economy but past industrial transitions can help policy makers chart a course. At present there are several barriers to the transition to a low-carbon economy that need to be overcome. For firms, these barriers include the administrative costs of closure, severance payments for workers and the irretrievability of sunk costs in capital intensive industries. There are also barriers which impact government action, such as the geographical concentration of industries and the role of state owned enterprises – particularly in emerging economies and developing countries (OECD, 2017e). For guidance in overcoming these barriers, lessons can be learnt from previous industrial transitions, where governments have deployed all manner of measures to support both workers and companies. From the perspective of workers, past experience indicates the value of a combination of: public support to promote job creation in depressed areas; active labour market policies (in terms of training and counselling); and closure aid to help with severance pay (OECD, 2017e). For businesses, several measures can help, including: investment aid; loan guarantees coupled with commitments to reduce capacity; and financing instruments and other measures to promote diversification and modernisation (OECD, 2017e).

Policies tailored to combat the deterioration of environmental quality of life should be designed with their social impact in mind. Whilst everyone in our societies stands to benefit from a reduction in air pollution, reductions are likely to be particularly beneficial to low income groups (i.e. North America, Asia and Africa) where exposure is characterised by the distribution of income (Hajat A., et al, 2015). First and foremost, prevention measures are key. These can include strategies to reduce harmful emissions by replacing dirty fuels with cleaner ones and encourage the development of cleaner industries (OECD, 2017e). OECD work has found that policies that provide incentives across a broad spectrum of firms and consumers, such as emission or energy taxes tend to be more cost-efficient than those that target a specific product, fuel or technology, such as subsidies for electric cars. Such policies are particularly cost-efficient when they are spatially heterogeneous, allowing for more stringent measures in densely populated areas or for emission sources located upwind from urban areas (OECD, 2017e). Mitigation measures also have a key role to play in addressing residual pollution. For instance education about the risks of air pollution, and the provision of up-to-date information on pollution levels, can significantly reduce health impacts, particularly amongst populations at higher risk. More broadly, the effectiveness of the healthcare system can play an important role in reducing the negative effects of illness on individual well-being and limit the impact on labour productivity (OECD 2016d).

Access to water remains a policy priority in developing countries and emerging economies, whilst financing is a key concern in the OECD area. In developing and emerging economies, promoting wider access to crucial water supply and sanitation services, particularly in rural areas and to the poorest communities, remains key. Much can be gleaned from the advance of OECD countries like Mexico in increasing population coverage in recent years. In Mexico, efforts by initiatives such as the Social Infrastructure Fund, which supports local and state governments in developing basic social infrastructure (including drinking water and sanitation), have seen access to drinking water increase from covering less the 80% of the population in the early 1990s to around 95% today. From 2000, coverage of water treatment has grown from just over 20% to approaching 60% (INEGI and CONAGUA). In OECD countries, the main challenge is often to renew and upgrade existing infrastructure. This is particularly vital in light of climate change, which makes water demand and availability more uncertain, and, in some instances, also increases rainwater run-off in urban environments. The financing of water services remains an important challenge. An important first step towards addressing this challenge is to combine revenues from water tariffs, transfers from public budgets and transfers from the international community (i.e. the 3Ts). Well-designed tariffs for water supply and sanitation services should cover the operation, maintenance and renewal costs of infrastructure and a progressive proportion of capital costs (OECD, 2017e). Sometimes it may raise affordability issues for lower-income groups, but these are best addressed through targeted social measures outside the water bill.

Reducing disparities in regional opportunities and urban segregation

Regional catching up in productivity is associated with the presence or the proximity to a well-governed city and to a dynamic tradable sector. Two characteristics stand out in distinguishing regions that narrowed the gap to their country’s most productive regions and those falling further behind (OECD, 2016c). First, well-functioning cities are important, not only through economic activity in the city itself but also for rural areas in the city’s proximity. Second, regions catching up in terms of productivity have a larger share and growth rate of the tradable sector in their economies.

Strategically diversifying regional economies supports productivity growth. For traded goods and services, sector-clustered firms are an important source for productivity growth and innovative activity. In some regions, firms specialising in sectors related to a single category of goods or services can play an important economic role. In Europe, the largest specialisation in such a traded clusters accounts for more than 40% of the workforce in the region (OECD, forthcoming). Other regions are more diversified with the largest concentration of traded sectoral clusters that employ less than 5% of the workforce, whereas others employ more than 40% of the workforce. Highly specialised regions have higher per capita GDP levels than regions where economic activity is distributed more diversified across many clusters. In contrast, per capita GDP growth is higher in more diversified regions. This implies that specialisation is increasing when regions become richer, but this effect can limit the future growth potential of regions.

Strategic investments are key to unlock the growth potential of regions. Public investment, as a percentage of government spending, has, however, dropped from 9.5% to 7.7% over the past two decades (OECD, 2016b). Subnational governments remain responsible for the majority of public investment (59%), but boosting their capacity to implement projects is often not a high priority. Investments that facilitate the diffusion of innovation and good practices across sectors and firms within and beyond a region are an opportunity to increase productivity, as the frontier keeps pulling further away from other firms (Andrews et al., 2015). While in many countries policies seek to reduce gaps across regions, they should avoid stifling growth in the highest-productivity regions.

Enabling regional catching up and promoting regional development policies that build economic potential in lagging regions is vital for future prosperity. Such regional development policies should focus on innovation and knowledge diffusion to boost productivity growth, and focus on developing the tradeable sector, whilst enacting policies to mitigate the adjustment costs of trade shocks. Providing affordable housing is a major part of the inclusive growth agenda and should be central to regional development strategies. Finally, encouraging geographical mobility and connectivity across regions is important for social inclusion and productivity growth.

Support for innovation and knowledge diffusion can narrow regional gaps and boost aggregate productivity growth. Knowledge diffusion requires working with different types of actors in the region. Industry associations can help firms to learn from each other’s experiences and can coordinate joint research activities of businesses. Governments should aim to set framework conditions that support coordinated efforts by businesses, but avoid room for collusion among competing firms. Effectively links between universities and private businesses can foster and spread innovation, particularly when universities research activities are linked to areas that are of importance for the local economy. These links are mutually beneficial as they can provide grants to universities. Technology centres that aim to connect university research with firm R&D can be catalyst that helps translate abstract research into innovative new products.

Regions need to focus on tradable activities. Regions with the largest expansion in non-tradable sectors, suffered most since the 2007-08 global financial crisis. On average, employment grew by about 0.7% annually since 2008 in regions that experienced only small shifts in employment to the non-tradable sector before the 2007-08 crisis (Figure 3.24). In contrast, regions where employment shifted strongly towards non-tradable sectors saw employment decline by nearly 1% annually between 2008 and 2014. The lack of resilience is most pronounced for the 10% of regions with the largest shifts towards non-tradable sectors before the crisis. In these regions employment dropped after the crisis with an average decline in employment of 2.9% annually. The result might seem counterintuitive as local sectors can appear less dependent on global trends. But non-tradable activities are not truly disconnected from global shocks. Local sectors are tied to tradable sectors through demand and supply links.

Trade is beneficial at the national level and most regions benefit from it, but in a few regions the downsides dominate. Greater trade integration creates benefits for firms that make use of larger markets for their goods and sources and the ability to source inputs at lower costs. But firms that originally provided these inputs locally can be priced out of the market. Often these shocks are regionally concentrated. Manufacturing in Portugal’s Norte region is highly specialised in textiles and shoe manufacturing. Following accession of the People’s Republic of China to the World Trade Organization and adoption (and subsequent appreciation) of the Euro, Norte lost nearly 170 000 jobs in manufacturing, a decline of 30% in employment in the sector between 2000 and 2015.

Figure 3.24. Regions with strong pre-crisis increases in non-tradable sectors lost more jobs
Annual average employment growth (2008-13) and change in the share of non-tradable workers in total employment in 2007 compared to 2000

Note: Data for 203 territorial level 2 (TL2) regions in 19 OECD countries: Austria, Australia, Belgium, Bulgaria, Czech Republic, Denmark, Finland, Greece, Ireland, Italy, the Netherlands, Portugal, Romania, Slovenia, Slovak Republic, Spain, Sweden, the United Kingdom and the United States. Categories from left to right include 81, 84, 19 and 19 regions.

Source: OECD Regional Statistics [Database].


No single policy can address the concentrated losses following trade shocks. Policy packages need to include training and education programmes to reduce the impact on workers. The changing demand for skills requires workers to adapt to find new opportunities when economic sectors disappear. However, it is unlikely that skill and education policies alone will be enough. Since trade can lead to a decline in the number of firms in a region, it is important to target not only workers but also consider local labour demand. Policies should therefore consider incentives for firm creation or those to attract foreign direct investment into a region. Furthermore, workers should be supported to find jobs in other regions were unemployment rates are lower. Economic and social constraints may prevent workers from seeking jobs in other regions. Providing support and information on how to overcome these constraints helps workers to find jobs elsewhere. Such policies can also benefit workers who remain in the region by reducing the number of people competing for limited job openings.

Good governance arrangements are necessary for cities to pay a double dividend in terms of productivity and inclusiveness. A doubling in the number of municipalities in a (functional) urban area is associated with a productivity penalty of 6%. That penalty is halved when there is a governance body for the metropolitan area (Ahrend et al., 2017). This is one of the reasons why many countries in reforms of their metropolitan governance arrangement (OECD, 2015a). A given level of municipal fragmentation has a greater negative impact on growth in urban regions due to the higher density of interactions than in rural areas (Bartolini, 2015). Fragmentation is also associated with greater levels of segregation by income in metropolitan areas, which in turn influences access to opportunities (Boulant et al., 2016).

Creating vibrant, inclusive communities

Governments should stimulate investment in social capital, civic engagement and other more intangible goods, such as social support networks and trust and cooperative norms. Creating vibrant, inclusive communities goes beyond good quality jobs, productivity growth, affordable housing and well-connected transportation systems. At their heart, vibrant and inclusive communities are also founded on positive social relationships, one of the main pillars of social capital (Scrivens and Smith, 2013). These are not traditionally areas that have garnered close attention in public policy. Yet this presents a vital missed opportunity – both because of their role in supporting higher individual and community well-being, but also because of how these factors influence the effective functioning of both the economy and governments. This ranges from the health impacts of social isolation; to the educational, employment and mental health advantages of having good social support; the improved institutional performance that comes from greater civic engagement; and the benefits to business of operating in a high-trust society where economic interactions run smoothly (Scrivens and Smith, 2013; OECD, 2017l).

Institutional quality and neighbourhood connectedness can increase social capital. Social capital can be strengthened by policies that focus on improving institutional quality (e.g. by reducing corruption) or that increase neighbourhood connectedness (Box 3.4). Most of research on the latter has focused on the role of community diversity in building trust - in terms of inequality and ethnic fractionalization (Rothstein and Uslaner 2005; Algan and Cahuc, 2013). For instance, in the United States, people that live in a racially mixed community or in one with a high degree of income disparity trust other people less (Alesina and La Ferrara, 2002). Similar patterns have been found in other countries (Bjørnskov, 2006; Helliwell and Wang, 2010). There is increasing evidence that residential segregation lowers trust, rather than diversity (de Souza Briggs, 2002; Rothwell, 2011; Uslaner, 2012; Laurence, 2017). OECD countries with large immigrant populations (e.g. Australia, Canada, Luxembourg, New Zealand and Switzerland) are high-trust countries, suggesting that the interplay between diversity and trust may be complex.

Box 3.4. What is social capital and how can it be strengthened?

While there is no single interpretation of ‘social capital’ and the term has been applied to a vast range of situations, four main ways of conceptualising and measuring the concept have been identified: (i) Personal relationships; referring to people’s relationships and the actions taken to create/maintain those relationships (such as spending time with others); (ii) Social network support, referring to the resources – emotional, material, practical, financial, intellectual or professional – available to individuals through their personal networks; (iii) Civic engagement, referring to activities that contribute to civic and community life such as volunteering, political participation, group membership and other forms of community action; and (iv) Trust and cooperative norms, referring to the trust, social norms and shared values that underpin societal functioning and enable mutually beneficial cooperation.

Figure 3.25. Interpersonal trust is associated with a variety of community and institutional factors

Note: This graph reports the simulated change in generalised trust, which is measured on a 0-10 scale, following the increase in selected drivers. Regression coefficients are based on a multivariate analysis of trust in others, controlling for a range of individual, societal and institutional variables. Data is pooled from four countries that participated in the OECD Trustlab project (Germany, Italy, Slovenia, the US). Sample size is N=1000 per country and the sample is representative by age, gender, income and location.

Source: Murtin et al. (2018).


Evidence from OECD’s Trustlab project shows that trust in others, one of the proxies of social capital, goes hand in hand with neighbourhood connectedness, institutional quality (in terms of government responsiveness and integrity), perceived social mobility, attitudes towards immigration and globalization, and a high frequency of volunteering. This mirrors previous research: for instance, frequent interactions with other people in the neighbourhood foster the development of trust in people in general because such trust is inferred from ongoing social experiences, which in turn allow inferences about shared social norms in society at large (Offe, 1999; Glanville and Paxton, 2007).

The link between a person’s community relations and interpersonal trust has been established both in correlational and causal designs (Putnam 2000; Delhey and Newton 2003; Li, Pickles, and Savage 2005; Glanville and Paxton, 2013). Meanwhile, quality of government matters for interpersonal trust since fair and effective institutions enable a person to extend trust to strangers without putting themselves at risk (Gambetta, 1993; Tabellini, 2008; Herrmann et al, 2008; OECD, 2017b)

Governments need to actively promote volunteering and look for collaborative ways for engaging with the society and citizens on volunteer activities. One in three people of working age volunteer through an organisation at least once a year in OECD countries, ranging from 18% in Spain and the Czech Republic, to more than 55% in the United States and Norway. Employed people, and those with a higher level of education and income are more likely to volunteer than those without. When adding up the value of the time people spend on volunteering, it amounts to around 2% of GDP on average in OECD countries (OECD, 2015e). Volunteering also creates a “virtuous circle”, whereby those who help others in the community also gain in terms of their own well-being – including their subjective well-being, skills and earnings potential (Box 3.5).

Box 3.5. Volunteer services are attractive schemes as concerns youth inclusion

Governments have increasingly focused supporting volunteers in their commitment - be it through a validation of the skills acquired in order to unleash potential career benefits, involvement of citizens in political processes, or in providing support to volunteers when they want to solve a social problem. Some of these policies include:

The French “service civique” (volunteer service), which was statutorily institutionalised at the beginning of 2010 as a special form of volunteering. The programme has two objectives: to reinforce “civism” and national cohesion, and also allow young people to participate in a collective project. The government supports volunteers engaged in the “service civique” by paying them a small stipend and their insurance contributions, and by providing advanced trainings. Between 2010 and 2016 around 182,000 young people have done their “service civique”. Over time, this programme has gain in popularity amongst the unemployed and those from disadvantaged background.

Mirroring, in some ways, the French volunteer service, the United Kingdom Government introduced the National Citizen Service as a flagship initiative to support building a “bigger, stronger society” (UK Cabinet Office, 2013). A summer programme for 16 year olds that includes both residential and at-home components, it offers an opportunity for young people to work in teams to design and implement a social action project in their local area. An evaluation published in 2011 indicated that participation in the Citizen Service yielded significant gains to young people’s well-being, when compared to a control group.

The Danish Social Service Act imposes on municipalities the duty to support economically and cooperate with voluntary organisations. They have to develop a policy to support volunteering and review their activity. In effect, about 60-80% of all municipalities in Denmark have a voluntary policy and 55% of all municipalities have established a voluntary council, which functions as a bridge between the municipality and the local voluntary organisations. Voluntary organisations are represented at the voluntary council, which recommends to the municipality what type of activity should be supported (Principi, Jensen and Lamura, 2014).

In order to strengthen the cohesion and foster the solidarity in European society, a European Solidarity Corps has been set up by the European Commission to create a community of young people willing to engage in a wide range of solidarity activities, either by volunteering or gaining occupational experience in helping to resolve challenging situations across the European Union and beyond.


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