Causes and Consequences of Income Inequality – An Overview

2.1 Globalisation

One of the earliest, and most prominent explanations for the rise of income inequality emphasised the role of globalisation (Borjas, Freeman, and Katz 1992; Revenga 1992). Globalisation has led to the offshoring of many goods and services that used to be produced or completed domestically in the West, which has created downward pressures on the wages of lower skilled workers. According to the ‘market forces hypothesis,’ increasing inequality is a response to the rising demand for skills at the top, in which the spread of globalisation and technological progress have been facilitated through reduced barriers to trade and movement.

Proponents of globalisation as the leading cause of inequality have argued that globalisation has constrained domestic state choices and left governments collectively powerless to address inequality. Detractors admit that globalisation has indeed had deep structural effects on Western economies but its impact on the degree of agency available to domestic governments has been mediated by individual policy choices (Thomas 2016: 346). A key problem with attributing the cause of inequality to globalisation, is that the extent of the inequality increase has varied considerably across countries, even though they have all been exposed to the same effects of globalisation. The US also has the highest inequality amongst rich countries, but it is less reliant on international trade than most other developed countries (Brown 2017: 56). Moreover, a recent meta-analysis by Heimberger (2020) found that globalisation has a “small-to-moderate” inequality-increasing effect, with financial globalisation displaying the largest impact.

2.2 Technology

A related explanation for inequality draws attention to the impact of technology specifically. The advent of the digital age has placed a higher premium on the skills needed for non-routine work and reduced the value placed on lower skilled routine work, as it has enabled machines to replace jobs that could be routinised. This skill-biased technological change (SBTC) has led to major changes in the organisation of work, as many full-time permanent jobs with benefits have given way to part-time flexible work without benefits, that are often centred around the completion of short ‘gigs’ such as a car journey or food delivery. For instance, the Organisation for Economic Co-operation and Development (OECD) estimated in 2015 that since the 1990s, roughly 60% of all job creation has been in the form of non-standard work due to technological changes and that those employed in such jobs are more likely to be poor (Brown 2017: 60).

Relatedly, a prevailing doctrine in economics is ‘marginal productivity theory,’ which holds that people with greater productivity levels will earn higher incomes. This is due to the belief that a person’s productivity is equated to their societal contribution (Stiglitz 2013: 37). Since technology is a leading determinant in the productivity of different skills and SBTC has led to increased productivity, it has also become a justification for inequality. However, it is very difficult to separate any one person’s contribution to society from that of others, as even the most successful businessperson owes their success to the rule of law, good infrastructure, and a state educated workforce (Stiglitz 2013: 97–98).

Further criticisms of the SBTC explanation, are that there was still substantial SBTC when inequality first fell dramatically and then stabilised in the period from 1930 to 1980, and it has failed to explain the perpetuation of both the gender and racial wage gap, “or the dramatic rise in education-related wage gaps for younger versus older workers” (Brown 2017: 67). Although it is difficult to decouple globalisation and technology, as they each have compounding tendencies, it is most likely that globalisation and technology are important explanatory factors for inequality, but predominantly facilitate and underlie the following more determinant institutional factors that happen to be already present, such as reduced tax progressivity, rising executive pay, and union decline. It is to these factors that I now turn.

2.3 Tax Policy

Taxes overwhelmingly comprise the primary source of revenue that governments can use for redistribution, which is fundamental to alleviating income inequality. Redistribution is defended on economic grounds because the marginal utility of money declines as income rises, meaning that the benefit derived from extra income is much higher for the poor than the rich. However, since the late 1970s, a major rethinking surrounding redistributive policy occurred. This precipitated ‘trickle-down economics’ theory achieving prominence amongst American and British policymakers, whereby the benefits from tax cuts on the wealthy would trickle-down to everyone. Subsequently, expert opinion has determined that tax cuts do not actually spur economic growth (CBPP 2017).

Personal income tax progressivity has declined sharply in the West, as the average top income tax rate for OECD members fell from 62% in 1981 to 35% in 2015 (IMF 2017: 11). However, the decline has been most pronounced in the UK and the US, which had top rates of around 90% in the 1960s and 1970s. Corporate tax rates have also plummeted by roughly one half across the OECD since 1980 (Shaxson 2015: 4). Recent International Monetary Fund (IMF) research found that between 1985 and 1995, redistribution through the tax system had offset 60% of the increase in market inequality but has since failed to respond to the continuing increase in inequality (IMF 2017). Moreover, in a sample of 18 OECD countries encompassing 50 years, Hope and Limberg (2020) found that tax reforms even significantly increased pre-tax income inequality, while having no significant effect on economic growth.

This decline in tax progressivity has been a leading cause of rising income inequality, which has been compounded by the growing problem of tax avoidance. A complex global web of shell corporations has been constructed by international brokers in offshore tax havens that is able to keep wealth hidden from tax collectors. The total hidden amount in tax havens is estimated to be $7.6 trillion US dollars and rising, or roughly 8% of total global household wealth (Zucman 2015: 36). Recent research has revealed that tax havens are overwhelmingly used by the immensely rich (Alstadsæter, Johannesen, and Zucman 2019), thus taxing this wealth would substantially reduce income inequality and increase revenue available for redistribution. The massive reduction in income tax progressivity in the Anglo world, after it had been amongst its leaders in the post-war years, also “probably explains much of the increase in the very highest earned incomes” since 1980 (Piketty 2014: 495–496).

2.4 Executive Pay

The enormous rising pay of executives since the 1980s, has also fuelled income inequality and more specifically the gap between executives and their employees. For example, the gap between Chief Executive Officers (CEO) and their workers at the 500 leading US companies in 2016, was 335 times, which is nearly 10 times larger than in 1980. It is a similar story in the UK, with a pay ratio of 131 for large British firms, which has also risen markedly since 1980 (Dorling 2017).

Piketty (2014: 335) posits that the dramatic reduction in top income tax has had an amplifying effect on top executives pay since it provides them with much greater incentive to seek larger remuneration, as far less is then taken in tax. It is difficult to objectively measure an individual’s contribution to a company and with the onset of trickle-down economics and accompanying business-friendly climate since the 1980s, top executives have found it relatively easy to convince boards of their monetary worth (Gabaix and Landier 2008).

The rise in executive pay in both the UK and US, is far larger than the rest of the OECD. This may partially be explained by the English-speaking ‘superstar’ theory, whereby the global market demand for top CEOs is much higher for native English speakers due to English being the prime language of the global economy (Deaton 2013: 210). Saez and Veall (2005) provide support for the theory in a study of the top 1% of earners from the Canadian province of Quebec, which showed that English speakers were able to increase their income share over twice as much as their French-speaking counterparts from 1980 to 2000. This upsurge of income at the top of the labour market has been accompanied by stagnation or diminishing returns for the middle and lower parts of the labour market, which has been affected by the dramatic decline of union influence throughout the West.

2.5 Union Decline

Trade unions have typically been viewed as an important force for moderating income inequality. They “contribute to wage compression by restricting wage decline among low-wage earners” and restrain wage surges among high-wage earners (Checchi and Visser 2009: 249). The mere presence of unions can also drive up the wages of non-union employees in similar industries, as employers tend to give in to wage demands to keep unions out. Union density has also been proven to be strongly associated with higher redistribution both directly and indirectly, through its influence on left party governments (Haddow 2013: 403).

There had broadly existed a ‘social contract’ between labour and business, whereby collective bargaining establishes a wage structure in many industries. However, this contract was abandoned by corporate America in the mid-1970s when large-scale corporate donations influenced policymakers to oppose pro-union reform of labour law, leading to political defeats for unions (Hacker and Pierson 2010: 58–59). The crackdown of strikes culminating in the momentous Air Traffic Controllers’ strike (1981) in the US and coal miner’s strike (1984–85) in the UK, caused labour to become de-politicised, which was self-reinforcing, because as their political power dispersed, policymakers had fewer incentives to protect or strengthen union regulations (Rosenfeld and Western 2011). Consequently, US union density has plummeted from around a third of the workforce in 1960, down to 11.9% last decade, with the steepest decline occurring in the 1980s (Stiglitz 2013: 81).

Although the decline in union density is not as steep cross-nationally, the pattern is still similar. Baccaro and Howell (2011: 529) found that on average the unionisation rate decreased by 0.39% a year since 1974 for the 15 OECD members they surveyed. Increasingly, the decline in the fortunes of labour is being linked with the increase in inequality and the sharpest increases in income inequality have occurred in the two countries with the largest falls in union density – the UK and US. Recent studies have found that the weakening of organised unions accounts for between a third and a fifth of the total rise in income inequality in the US (Rosenfeld and Western 2011), and nearly one half of the increase in both the Gini rate and the top 10%’s income share amongst OECD members (Jaumotte and Buitron 2015).

To illustrate the changing relationship between inequality and unionisation, Figure 1 displays a local polynomial smoother scatter plot of union density by income inequality, for 23 OECD countries, 1980–2018. They are negatively correlated, as countries with higher union density have much lower levels of income inequality. Figure 2 further plots the time trends of both. Income inequality (as measured via the Gini coefficient) has climbed over 0.02 percentage points on average in these countries since 1980, which is roughly a one-tenth rise. Whereas union density has fallen on average from 44 to 35 percentage points, which is over one-fifth.

Figure 1:

Gini coefficient by union density, OECD 1980–2018. Data on Gini coefficients from SWIID (Solt 2020); data on union density from ICTWSS Database (Visser 2019).

Figure 2:

Gini coefficient by union density, 1980–2018. Data on Gini coefficients from SWIID (Solt 2020); data on union density from ICTWSS Database (Visser 2019).

In sum, income inequality is multifaceted and is not the inevitable outcome of irresistible structural forces such as globalisation or technological development. Instead, it has largely been driven by a multitude of political choices. Tridico (2018) finds that the increases in inequality from 1990 to 2013 in 26 OECD countries, was largely owing to increased financialisation, deepening labour flexibility, the weakening of trade unions and welfare state retrenchment. While Huber, Huo, and Stephens (2019) recently reveals that top income shares are unrelated to economic growth and knowledge-intensive production but is closely related to political and policy changes surrounding union density, government partisanship, top income tax rates, and educational investment. Lastly, Hager’s (2020) recent meta-analysis concludes that the “empirical record consistently shows that government policy plays a pivotal role” in shaping income inequality.

These preventable causes that have given rise to inequality have created socio-economic challenges, due to the demonstrably negative outcomes that inequality engenders. What follows is a detailed analysis of the significant mechanisms that income inequality induces, which lead to harmful outcomes.

3.1 Economic

Income inequality is predominantly an economic subject. Therefore, it is understandable that it can engender pervasive economic outcomes. Foremost economically speaking, it has been linked with reduced growth, investment and innovation. Leading international organisations such as the IMF, World Bank and OECD, pushed for neoliberal reforms beginning in the 1980s, although they have recently started to substantially temper their views due to their own research into inequality. A 2016 study by IMF economists, noted that neoliberal policies have delivered benefits through the expansion of global trade and transfers of technology, but the resulting increases in inequality “itself undercut growth, the very thing that the neo-liberal agenda is intent on boosting” (Ostry, Loungani, and Furceri 2016: 41). Cingano’s (2014) OECD cross-national study, found that once a country’s income inequality reaches a certain level it reduces growth. The growth rate in these countries would have been one-fifth higher had income inequality not increased, while the greater equality of the other countries included in the study helped to increase their growth rates.

Consumer spending is good for economic growth but rising income inequality shifts more money to the top of the income distribution, where higher income individuals have a much smaller propensity to consume than lower-income individuals. The wealthy save roughly 15–25% of their income, whereas low income individuals spend their entire income on consumer goods and services (Stiglitz 2013: 106). Therefore, greater inequality reduces demand in an economy and is a major contributor to the ‘secular stagnation’ (persistent insufficient demand relative to aggregate private savings) that the largest Western economies have been experiencing since the financial crisis. Inequality also increases the level of debt, as lower-income individuals borrow more to maintain their standard of living, especially in a climate of low interest rates. Combined with deregulation, greater debt increases instability and “was a major contributor to, if not the underlying cause of, the 2008 financial crash” (Brown 2017: 35–36).

Another key economic effect of income inequality is that it leads to reduced welfare spending and public investment. Since a greater share of the income distribution is earned by the very wealthy, governments have less income available to fund education, public amenities, and other services that the poor rely heavily on. This creates social separation, whereby the wealthy opt out in publicly funding services because their private equivalents are of better quality. This causes a cycle of increasing income inequality that is likely to eventually lead to a situation of “private affluence and public squalor” (Marmot 2015: 39).

Lastly, it has been proven that economic instability is a by-product of increasing inequality, which harms innovation. Both countries and American states with the highest inequality have been found to be the least innovative in terms of the amount of Intellectual Property (IP) patents they produce (Dorling 2018: 129–130). Although income inequality is predominantly an economic subject, its effects are so pervasive that it has also been linked to a host of negative health and societal outcomes.

3.2 Health

Wilkinson and Pickett found key associations between income inequality for both physical and mental health. For example, they discovered that on average the life expectancy gap is more than four years between the least and most equitable richest nations (Japan and the US). Since their revelations, overall life expectancy has been reported to be declining in the US (Case and Deaton 2020). It has held or declined every year since 2014, which has led to a cumulative drop of 1.13 years (Andrasfay and Goldman 2021). Marmot (2015) has provided evidence that there exists a social gradient whereby differences in affluence translate into increasing health inequalities, which can be shown even down to the neighbourhood level, as more affluent areas have higher life expectancy on average than deprived areas, and a clear gradient appears where life expectancy increases in line with affluence.

Moreover, Marmot’s famous Whitehall studies, which are large-scale longitudinal studies of Whitehall employees of UK central government, found an inverse-relationship between salary grade and ill-health, whereby low-grade workers were four times as likely as high-grade workers to suffer from ill-health (2015: 11). Health steadily improves with rank and the correlation is little affected by lifestyle controls such as tobacco and alcohol usage. However, the leading factor that seems to make the most difference in ill-health is job stress and a person’s sense of control over their work, including the variety of work and the use and development of skills (Schrecker and Bambra 2015: 54–55).

‘Psychosocial stresses,’ like those appearing in the Whitehall studies, have been found to be more common and frequent amongst low-income individuals, beyond just the workplace (Jensen and van Kersbergen 2017: 24). Wilkinson and Pickett (2019) posit that greater income inequality engenders low self-esteem, chronic stress and depression, stemming from status anxiety. This occurs because more importance is placed on where people fit in a hierarchy with greater inequality. For evidence, they outline a clear relationship of a much higher percentage of the population suffering from mental illness in more unequal countries. Meticulous research has shown that huge inequalities in income result in the poor having feelings of shame across a range of environments. Furthermore, Dickerson and Kemeny’s (2004) meta-analysis of 208 studies found that stress-hormone (cortisol) levels were raised particularly “when people felt that others were making negative judgements about them” (Rowlingson 2011: 24).

These effects on both mental and physical health can be best illustrated via the ‘absolute income’ and ‘relative income’ hypotheses (Daly, Boyce, and Wood 2015). The relative income hypothesis posits that when an individual’s income is held constant, the relative income of others can affect a person’s health depending on how they view themselves in comparison to those above them (Wilkinson 1996). This pattern also holds when income inequality increases at the societal level, because if such changes lead to increases in chronic stress, it can increase ill-health nationally. Whereas the absolute income hypothesis predicts that health gains from an extra unit of income diminish as an individual’s income rises (Kawachi, Adler, and Dow 2010). A mean preserving transfer from a richer to poorer individual raises the health of the poorer individual more than it lowers the health of the richer person. This occurs because there is an optimum threshold of income required to maintain good health. Thus, when holding total income constant, a more equal distribution of income should improve overall population health. This pattern also applies at the country-wide level, as the “effect of income on health appears substantial as countries move from about $15,000 to 25,000 US dollars per capita,” but appears non-existent beyond that point (Leigh, Jencks, and Smeeding 2009: 386–387).

Income inequality also impacts happiness and wellbeing, as the happiest nations are routinely the ones with low inequality, such as Denmark and Norway. Happiness has been proven to be affected by the law of diminishing returns in economics. It states that higher income incrementally improves happiness but only up to a certain point, as any individual income earned beyond roughly $70,000 US dollars, does not bring about greater happiness (Deaton 2013: 53). The negative physical and mental health outcomes that income inequality provoke, also impact key societal areas such as crime, social mobility and education.

3.3 Social

Rates of violent crime are lower in more equal countries (Hsieh and Pugh 1993; Whitworth 2012). This is largely because more equal countries have less poverty, which leads to less people being desperate about their situation, as lower-income individuals have been shown to commit more crime. Relatedly, according to strain theory, more unequal societies place higher social value in achieving economic success, while providing lower means to achieve it (Merton 1938). This generates strain, which may lead more individuals to pursue crime as a means of attaining financial success. At the opposite end of the income spectrum, the wealthy in more equal countries are also less likely to exploit others and commit fraud or exhibit other anti-social behaviour, partly because they feel less of a need to cut corners to get ahead, or to make money (Dorling 2017: 152–153). Homicides also tend to rise with inequality. Daly (2016) reveals that inequality predicts homicide rates better than any other variable and accounts for around half of the variance in murder rates between countries and American states. Roughly 90% of American homicides are committed by men, and since the majority of homicides occur over status, inequality raises the stakes of disputes over status amongst men.

Studies have also shown that there is a marked negative relationship between income inequality and social mobility. Utilising Intergenerational Earnings Elasticity data from Blanden, Gregg, and Machin (2005), Wilkinson and Pickett (2009) first outline this relationship cross-nationally for eight OECD countries. Corak (2013) famously expanded on this with his ‘Great Gatsby Curve’ for 22 countries using the same measure. I update and expand on these studies in Figure 4 to include all 36 OECD members, utilising the WEF’s inaugural 2020 Social Mobility Index. It clearly shows that social mobility is much lower on average in more unequal countries across the entire OECD.

Figure 4:

Index of social mobility by Gini coefficient. Data on social mobility index from World Economic Forum (2020); data on Gini coefficients from SWIID (Solt 2020).

A primary driver for the negative relationship between inequality and social mobility, derives from the availability of resources during early childhood. Life chances have been shown to be determined in early childhood to a disproportionately large extent (Jensen and van Kersbergen 2017: 29). Children in more equitable regions such as Scandinavia, have better access to resources, as they go to similar schools, receive similar educational opportunities, and have access to a wider range of career options. Whereas in the UK and US, a greater number of jobs at the top are closed off to those at the bottom and affluent parents are far more likely to send their children to private schools and fund other ‘child enrichment’ goods and services (Dorling 2017: 26). Therefore, as income inequality rises, there is a greater disparity in the resources that rich and poor parents can invest in their children’s education, which has been shown to substantially affect “cognitive development and school achievement” (Brown 2017: 33–34).