There is significant interest from governments, companies and third-sector organisations in improving social mobility. For a professional firm this could mean endeavouring to develop a more diverse workforce, while governments could see social mobility as a means of achieving fairness and maximising the productivity of the country’s labour market. But what does social mobility mean?
There is a frequent distinction between ‘equal outcomes’ where, for example, everyone has the same income and wealth, and ‘equal opportunity’, where every person has an equal chance at success, but outcomes will vary.
It is this latter objective of ‘equal opportunity’ that equates to relative social mobility. Relative social mobility measures how far a child moves up or down the social ladder in comparison with their parents. The ladder, in this analogy, reflects the distribution of factors such as wealth, income or educational attainment in a society.
Absolute vs relative mobility
There are two types of intergenerational social mobility: absolute mobility that measures whether (and by how much) living standards have increased or the extent to which people do better than their parents, and relative mobility that refers to the extent to which an individual’s chances depend on their parents’ education, class or income. Social mobility can be measured in terms of education, occupational status, individual earnings or household income.
Source: OECD, 2017
In comparison, absolute social mobility is based on a child’s outcomes in comparison with their parents’ situation. Absolute social mobility does not consider the position of the child in comparison with their peers. Globally, there have been important strides in improving absolute mobility – with extreme poverty falling in every region since the late 1980s (see Figure 2.1). The fall in extreme poverty means that overall quality of life for many of the youngest generation has improved compared with that of their parents.
Figure 2.1: Share of population living in extreme poverty, by world region 
In parallel to the falls in extreme poverty, economic growth has expanded over the same period. In 1987, world GDP was almost $34 trillion and this has more than doubled in real terms to over $80 trillion in 2017 (both figures adjusted to 2010 USD values). This marks an impressive global economic expansion, but the spoils of this success have not been shared equally among countries or within them.
Figure 2.2: World GDP growth from 1987 to 2016, at constant 2010 values of USD
Furthermore, although quality of life can be said to have increased for large parts of the world, many are still denied the opportunities for living well. And at a level down from a ‘bird’s eye’, ‘absolute’ view of the world, where some countries are now richer than they were and others remain poor, there are still entrenched inequalities within countries, advanced and emerging, which stop people from living fulfilled lives.
Figure 2.3: Global income growth and inequality, 1980–2016
Data from the World Inequality Report show that, globally, real income grew by about 60% between 1980 and 2016. Starting from a low base, there were real increases in the bottom 50% of the distribution – with a near doubling of real income. But income growth has still concentrated disproportionately in the top 1% of earners. More developed countries have experienced a particularly acute disparity in income gain. Between 1980 and 2016, real income growth was only 5% for the bottom half of the income distribution in the US and Canada, while the top 0.1% enjoyed income growth of 320% over the same period. Other measures have supported the growing rate of inequality. In Asia, for example, the International Monetary Fund (IMF) found that income inequality, measured by the gini coefficient, rose in 15 countries from 1990 to 2013 (IMF 2016).
2.1 Dimensions of social mobility
i. Life-course mobility
Absolute and relative social mobility both compare a child’s socio-economic outcomes to their parents’. This provides an inter-generational view of social mobility. Individuals can also move up or down a social ladder during their lifetime; this is called intra-generational or life-course mobility.
The Resolution Foundation, a UK-based think tank that works to improve the living standards of low- to middle-income people, tracked how low-paid employees’ incomes changed over a 10-year period. The Foundation identified three main groups from the cohort of low-paid employees:
- Stuck – employees who were in low-paid work in every year of the study
- Escapers – those who exited low pay by the final three years of the decade
- Cyclers – people who achieved higher wages at some point, but were not consistently out of low pay by the end of the decade.
Their findings of low-pay dynamics in Britain demonstrates what some have called the ‘sticky floor’ for social mobility, where only one in six (17%) of the low paid in 2006 were able to secure consistently higher wages by 2016 (Resolution Foundation 2017). These results also apply beyond the UK. The OECD found that, over a four-year period, about 60% of people in the bottom 20% of earners will remain stuck in the bottom. Unpredictable income change was also more likely to drive upward mobility than any sustainable career progression (OECD 2018a). Clearly, examining intra-generation mobility demonstrates that social mobility is not a static outcome. Analysing outcomes over a life course shows that it is possible for people to repeatedly enter and exit positions of social and economic status.
ii. Educational attainment
Although educational attainment is an outcome, it is also a key factor in understanding the challenge of providing equal opportunities for all. Educational attainment includes how well a child performs in school and what overall level of education they achieve; both of these metrics are strongly related to family background (Wilkinson and Pickett 2010: 103). Families with sufficient resources will often support their children with private education, individual tutoring, and post-secondary education fees – through what has been called an ‘educational arms race’ – in order to give their children the best chance in life.
It is understandable that families seek the best for their children and will use the resources available to them to maximise the chance that their children will succeed in education and the labour market. At the same time, the inequality of family resources used to support children is a challenge for policymakers’ goal of providing an equal opportunity for success to all children.
Social policy literature distinguishes between different societal actors that support the provision of welfare in a country. These actors – or pillars – are the state, the family, civil society, and the individual (Heuer et al. 2016). Each country makes use of a unique combination of these pillars to provide for needs such as childcare, education, health care and income replacement. For example, Sweden has a strong reliance on the state in the provision of income support – such as disability benefit and public pensions – and in the provision of health care. In comparison, the US places more reliance on the individual and market forces to meet social needs, such as through private medical insurance.
Figure 2.4: Pillars of social provision
Evidence from an international review of 34 research studies from the US, UK, Canada, Norway and Mexico consistently found that the level of family resources available to a child affects their cognitive development and educational attainment (Cooper and Stewart 2013). A further UK study found that children from families with higher SEBs had vocabulary that was typically 18 months ahead of their peers with lower socio-economic status (Bradshaw 2011). By the time they reach schooling years, differences in familial background can create challenging inequalities. Some governments have invested more in early childhood programmes to help close this gap, but the role of family support still helps to perpetuate individual advantage.
iii. The gender dimension
There are other dimensions beyond income, wealth or family background that need to be understood in countries that are working to achieve equal opportunities for all. Gender is one of the important dimensions that should be considered in shaping government policy to achieve better social mobility.
Figure 2.5: Global performance of the Gender Gap Index, 2017
The World Economic Forum publishes an annual report on the global gender gap, which benchmarks 144 countries on their progress towards gender parity across four thematic dimensions: economic participation and opportunity; educational attainment; health and survival; and political empowerment (WEF 2017). The 2017 report demonstrated real success for female educational attainment – with 27 countries achieving a score of 1, for perfect parity. Globally, 95% of the educational gap has been closed. A great deal more progress is required in the areas of economic participation and opportunity, where the global gap sits at 42%. This sub-index includes indicators such as wage equality, access to the professions, and labour force participation rates.
Research published by ACCA in partnership with King’s College London shows that, in the UK, it takes women pursing an executive role an additional seven years to reach their goal compared to equally qualified men (ACCA 2018b).
The research showed that the primary divergence in economic outcomes between men and women typically occurs in mid-career (Stage 2), once individuals have reached middle management. After this point, some men enter a fast-track route and reach upper-middle management well in advance of women. Despite this divergence, the careers of women accelerate at a faster rate if they manage to reach the executive level.
Figure 2.6: The two-tournament gender system
Men and women executives do not ascend the organisational hierarchy in parallel. Much earlier in their careers, men enter a fast-track route, arriving at upper middle management and executive level well in advance of women and other men whose careers had plateaued. The careers of executive women do accelerate after middle management but the divergence, particularly at Stage 2, means that women ascend a belated route in comparison to men in the accounting and finance sector.
Economies around the world are negatively affected where women are not afforded an equal opportunity or are fully excluded from economic life. The findings also demonstrate that social mobility can be complicated by additional factors throughout individual career trajectories.
iv. The geographic dimension
The degree of social mobility is often considered at a national scale, but countries can exhibit considerable variation in intergenerational mobility depending on where individuals live. The UK’s Social Mobility Commission (SMC) published State of the Nation 2017 focusing on the geographic variability of social mobility in the UK (SMC 2017). The report ranks all English local authorities into social mobility ‘hotspots’ and ‘coldspots’, and shows a stark geographic divide for social mobility outcomes within the country.
Figure 2.7: Hotspots and coldspots in UK social mobility
Using 16 social mobility indicators, the SMC demonstrated that London accounts for nearly two-thirds of all social mobility hotspots. Out of a total of 32 London local authority areas, 29 are hotspots and there are no coldspots (SMC 2017). This regional variation is not limited to the UK. A study from the US found that social mobility varies substantially across different areas of the US, where areas with less segregation and less income inequality had better social mobility outcomes (Chetty et al. 2014). It is therefore important that governments not only consider top-line indicators of social mobility in their country, but also work to understand how particular areas within the nation are performing on different indicators of mobility.
2.2 Factors impeding social mobility
There are additional, often invisible, factors that can create barriers to accessing opportunities. This section explores two societal factors that may affect the levels of social mobility. The first, income inequality, has been well discussed in academic literature (Wilkinson and Pickett 2010; Corak 2013), whereas the second factor – perceived corruption in a country – has not received equal attention. The analysis below combines OECD intergenerational social mobility data with Transparency International’s Perceptions of Corruption Index, demonstrating a correlation between high levels of perceived corruption with low levels of social mobility in a country.
i. Income inequality and social mobility (Great Gatsby Curve)
There is evidence that inequality can exacerbate low levels of social mobility. The Great Gatsby Curve (see Figure 2.8), devised by economist Miles Corak, demonstrates that intergenerational mobility is worse in countries with high levels of income inequality, for a number of reasons. For example, low incomes for the less-well-off means that they may be able to access fewer opportunities. It may also mean that they have less influence in shaping policies that might benefit those on lower incomes (Corak 2013).
Figure 2.8: The Great Gatsby Curve
ii. Perceptions of corruption and social mobility
Combining Transparency International’s Corruption Perceptions Index data and the OECD’s intergenerational social mobility data demonstrates a relationship between perceived corruption and the degree of social mobility in a country (Transparency International 2017; OECD 2018a ). The OECD’s mobility data compares the relative earnings of sons with those of their fathers, while Transparency International produces a longitudinal dataset from a survey of individuals’ perceptions of corruption in a country. Such data were matched across 20 countries – with representation in North and South America, Europe, Asia, sub-Saharan Africa and Oceania. The results, both from 2017, show that as perceived corruption rises there is a corresponding drop in intergenerational social mobility.
Figure 2.9: Graph plotting intergenerational social mobility (OECD) against perceived corruption (Transparency International)
The prevalence of nepotism in a country, a type of corrupt behaviour, would understandably contribute to a fall in intergenerational social mobility in a country. Elite families or groups will be better placed to pass on their privilege to the next generation when a society’s norms do not impose clear rules for fair competition. In addition, countries with public sectors that do not operate with impartiality towards their citizens are capable of dispersing the benefits of public services unfairly, reinforcing lower levels of social mobility.
Fair access to opportunities requires a competitive, rules-based society with good governance. Meritocratic hiring into the civil service, through open applications that are transparent and challengeable, is an important prerequisite for developing an effective and trusted public service. Of course, applying a system of rules is not sufficient for achieving equal opportunity, as some systems can in fact help entrench advantage for those with higher SEBs. For example, the use of school catchment areas, where students are only drawn from the school’s immediate vicinity, can limit access to high-performing public schools for lower-income students who live outside the school’s neighbourhood.
Finally, as the analysis relies on perceived levels of corruption, this subjective view could be linked to the level of trust in a society. Under this assumption, the causation would operate in the other direction: countries with limited social mobility exhibit lower levels of trust. Ultimately, it is most likely that there are many factors interacting to create the correlation between social mobility and corruption, but it is clearly important to tackle corruption in order to improve social mobility outcomes.
 Extreme poverty is defined as living with per capita household consumption below 1.90 international dollars per day (in 2011 PPP prices). International dollars are adjusted for inflation and for price differences across countries.
 The intergenerational social mobility data (comparing fathers’ and sons’ incomes) can be downloaded through the final data link on page 22 of OECD 2018a.