The global and national inequality faultlines: the economic dimensions of (in)security

Inequality between nations could be viewed as a major global faultline and although there is evidence that it is slowly being reduced, the gap between countries at the top and bottom remains enormous, with GDP per head of the top 25 high-income countries of the Global North being 52 times that of the bottom 25 countries. Inequality within countries is increasing, with evidence of a growing concentration of income and wealth in the hands of a small number of very rich individuals and senior corporate executives on astronomical salaries and bonuses. The COVID-19 pandemic appears to be reinforcing inequality. These developments are widely considered to be a threat to national and international security. Studies that have sought to find a relationship between inequality and threats to security in the form of terrorism and violent and property crime have found it to be positive. There are, therefore, sound practical reasons why inequality should be reduced, if not moral ones to underpin genuine democracy and human rights.

In the last few years there has been widespread recognition, both in the media and in academic journals, that inequality, of both income and wealth, is growing between and within nations, and that it has a causal relationship to terrorism, war, protest and other manifestations of insecurity. Wilkinson and Pickett (2010) and Piketty (2014) have most prominently highlighted rising inequality: the former emphasising the relationship between inequality and a host of social factors, such as health, education, violence and illiteracy, and the latter focusing on the returns to capital and why they had increased. Piketty's work built on that of his mentor, the late Tony Atkinson, who had been researching the subject for some years prior to, and following, the onset of neoliberal policies (Atkinson, 1975(Atkinson, , 2015. Whether the question is the cause of inequality or what inequality causes, the distribution of income and wealth between and within countries is becoming a major faultline in the economic structure of the world economy. The COVID-19 virus has exposed this faultline not only as a driver of the greater vulnerability of the poorer countries to virus cases and virus deaths, but also as a driver of the further enrichment of the rich and impoverishment of the poor across the globe. In this article, I will examine the data to establish the extent of inequality between and within nations, and how this has changed over the last 60 years, analyse the arguments connecting inequality with the various forms of civil unrest, from protests to terrorism, and, finally, raise the question of whether arguments for a clear reversal of inequality growth on moral and ethical grounds are preferable to those built on the back of a fear of unrest and terrorism.

Inequality between countries
In 1960, the 25 countries with the highest GDP per head had, on average, 32 times that of the 25 with the lowest. In 2019, this multiple had risen to 52. Of the 25 countries with the highest GDP per head in 1960, 20 remained in that group in 2019. Of the bottom 25 in 1960, a group that included China and India, 18 remained in 2019. China moved from 91st to 38th and India from 83rd to 63rd. In 2019, the GDP per head of the top country, Luxembourg, was 534 times that of the bottom country, Burundi; in 1960, the top and bottom countries respectively were Bermuda and Myanmar and the multiple was 218. Taking the average of the countries with over $75000, compared with those with less than $1000, brings the multiple down to 95. Table 1 shows the distribution of countries by GDP per head in the latest year for which data is available. The distribution is heavily skewed towards the lower end, with 84 of the 185 countries covered by the data showing a GDP per head of less than $5000 a year, an average of $2236, compared with the average for the six top countries of $92000 -a multiple of 41. 2 Another way of making these comparisons is to standardise the exchange rate of non-dollar currencies to the dollar by taking a standard basket of goods bought in the US and priced in US dollars and comparing that cost with the cost of the same basket of goods in non-dollar countries. This gives the GDP of non-dollar countries at purchasing power parity (PPP) in US dollars. The multiple of GDP at PPP of the richest over the poorest was 89 in 1990 (the first year for which this was calculated), down to 84 in 2019. The average GDP PPP per capita of the top 25 in 1990 was 34 times that of the average of the bottom 25, and in 2019 this multiple had fallen to 33. Of the bottom 25 countries in 1990, 15 were still in the bottom 25 in 2019, and of the top 25 in 1990, 23 remained there in 2019. Whichever way these data are presented, they demonstrate the extent of the global inequalities at a country level and, at the top and bottom end, their relative rigidity with very few countries having moved out of either group.
Of course, these are all averages and while they demonstrate the inequalities between countries, they say nothing about inequalities within them. The standard way to express income inequality is by the Gini coefficient, which is a measure of the difference between the actual distribution of income and what would be equal distribution. The higher the value of the coefficient the greater the degree of inequality. Table 2 presents a categorisation of countries according to their average Gini coefficient over the four years before 2018. Of the 71 countries for which there is long-term data for the last three decades, 33 have seen an increase in the coefficient, while 38 have seen a decrease. Data on income distribution is derived from tax returns, for those countries that have a well-functioning tax system, or from household surveys where tax returns capture only a small proportion of the working population. In all cases they are subject to error, especially in the case of household surveys where so much depends on the accurate memory recall of the household respondent, and is often based on consumption rather than income data. The other basic problem with the Gini coefficient is that it is a single number, which cannot indicate the inequalities within and between income groups. Nevertheless, the above-mentioned interventions of Wilkinson and Pickett, and of Piketty, have had a significant impact on raising the importance of inequality and its relation to various social, economic and political outcomes. Wilkinson and Pickett find in a cross-country (and occasionally cross-US state) analysis that inequality is negatively related to, among other factors, different measures of educational attainment, life expectancy, women's status and mutual trust. Inequality is found to be positively related to such factors as health and social problems, school dropout rates, teenage pregnancy, the number of homicides per million, the prison population per 100,000 of the total population, adult and child obesity, and to infant mortality. Of course, these correlations do not necessarily prove causation, but the evidence is overwhelming and the reasoning that explains the correlations certainly make the likely causative process very plausible. It is also possible that inequality and the other variables are co-determined by other factors such as religious or political ideology (which might also be interrelated), but the result would still suggest that more equality would generate better outcomes for the whole of society.
Inequality can not only be represented vertically, as above, but also horizontally (Stewart, 2004), as in the case of race or gender discrimination, where people whose only difference is race or gender receive different incomes. Wilkinson and Pickett capture elements of horizontal inequality when they find that inequality is negatively associated with women's status. They also find that inequality is negatively associated with mutual trust, a relationship that could interrelate with racial discrimination.
The most recent comprehensive account of income inequality in historical perspective can be found in Piketty (2014). The received wisdom, based on the work of Kuznets (1955), was that as capitalism developed, the share of income going to the owners of capital would increase, and then, as the political and economic power of the workers increased, their share would start to rise so that, over time, the curve plotting the relationship between inequality and time would form an inverted U shape. This may well have reflected the consequences of the political settlement following the second world war, including the development of the welfare state, the progressive taxation system and the strengthened bargaining power of well-organised trades unions. However, since the end of the consensus and the rise of neoliberalism, which can be dated from the later 1970s, the evidence suggests that the Kuznets curve no longer holds as a principle of the relationship between inequality and growth, and that, as Piketty argues, 'there is no natural, spontaneous process to prevent destabilizing, inegalitarian forces from prevailing permanently' (Piketty, 2014:21). His book documents the increasing share of income going to capital, to highly paid executives, to the top 20% and to the top 1%. Capital and its owning and managing class have received most of the benefits of the economic growth in the last four decades, while wage growth, with the exception of the top decile of management, has been suppressed and, since the financial crisis of 2008-9, has been negative in real terms. 3 Inequality can also be represented by looking at both ends of the distribution. At the top end, for example, it was recently reported that the top 1% of the population owns 45% of the world's wealth (Credit Suisse, 2019) and that the richest five people (all men) own as much wealth as the bottom 50% of the world population (Buchheit, 2017). This increasing inequality is not only a feature of late capitalism but can also be found in the emerging economies, where Piketty shows that since 1980 the share of the top percentile of labour income had steadily risen two to threefold by 2010. In China, for example, in the mid-1980s this share stood at 4%, and by 2010 had risen to 11% (Piketty, 2014). In terms of the wealth share of the top percentile, the emerging economies were rapidly approaching the world average: in 2019, the top percentile owned 39% of the wealth compared with 32% in 2000. In China in 2019, the top percentile owned just over 30% of wealth compared with just over 20% in 2000 (Credit Suisse, 2019).
At the bottom end of the distribution are the bottom two deciles. Of the 87 countries for which recent data is available, the bottom 10% in 23 countries received an income share of less than 2%, in 28 countries between 2% and 3%, in 30 countries between 3% and 4%, and in six between 4% and 5%. The shares of the bottom 20% show a similar picture: of the 94 countries for which there is recent data, 11 show the bottom 20% receiving less than 5% of income, 80 show them receiving less than 10%, while three have them receiving 10% or marginally above. Finally, for 19 countries for which recent data is available, between 14% and 70% of their populations were living in extreme poverty at less than $1.90 PPP per day (WDI online).
Further contributing to the increasing gap between the upper and lower band of the income distribution has been the low growth followed by the stagnation of wages. These developments have been aided by legislation to limit the effectiveness of trades unions and the 'simplification' of the taxation system, which has effectively abolished progressive taxation. Stagnation leading to falling real wages in many countries of the Global North after the 2008-9 financial crisis has further contributed to rising inequality. The increasing precarity of work (Standing, 2011), as the fourth industrial revolution reduces demand for labour and increases competition for jobs, exerts a further downward pressure on wages. This is not simply a result of purely economic factors but of political power derived from economic power. The concentration of income and wealth in the hands of a small percentage of the population is mirrored by the concentration of power over production in the hands of a small number of global corporates, such that the top 50 global, mainly financial, corporations control, through a web of ownerships, 75% of world capital (Vitali et al, 2011). The global corporates exert considerable pressure on governments to pursue policies that favour them. The 'revolving door' of politics and business through which politicians join the boards of corporates and corporate executives are seconded to government, has cemented corporate power (Lawrence, 2018). Increased inequality is a consequence of the accumulation of economic and political power concentrated in the hands of a few wealthy individuals and corporations with enormous influence on government policies.
The COVID-19 pandemic has accentuated inequalities both between and within countries. First, while the stronger and larger economies have the ability to mitigate the effects of the lockdown and other restrictive policies to suppress the virus, such as paying the wages and salaries of workers who otherwise would be unemployed, poorer economies do not have such borrowing capacities to compensate those affected by the virus containment measures. Nonetheless, unemployment has risen and those receiving government aid are not getting their lost income fully compensated. This is affecting the retail and hospitality sectors of the economy and reducing effective demand, thus affecting overall output and its growth. Predictions are that the G20 economies will have shrunk by 3.8% in 2020 (the Eurozone by 7.5%, the USA by 3.7% and the UK by 11.2%) and that 2021 will see them grow by 4.7% (the Eurozone by 3.6%, the USA by 3.2% and the UK by 4.2%). The economic decline of 2020 will not be reversed quickly, and neither will its consequences for inequality.
However, COVID-19 has not adversely affected everybody. The obvious beneficiaries from the pandemic have been food and drinks retailers, pharmaceutical manufacturers and suppliers of personal protective equipment. Less obvious has been the effect on the stock markets and, especially, on the profits of hedge fund managers, who make their money hedging their bets against the movements of markets, and have made much more betting on the course of COVID-19 and the discovery of a vaccine. Some fund managers have reportedly profited to the tune of several billions of US dollars as a result of this money market activity (Neate and Jolly, 2020). It is this kind of speculative activity that can yield high returns and set benchmarks for the returns to capital investment in productive activities reflecting the dominance of economies by powerful financial institutions, as noted above.
The consequences of COVID-19 for the Global South are likely to be severe. First, those countries that have economic activities that are part of global value chains will suffer from the downturn in production around the world consequent upon falling demand. Secondly, the indebtedness of developing countries, which was increasing prior to the point where it had reached a high of 170% of GDP in 2019, will increase during and after the pandemic, as budget deficits grow because of necessary increases in government expenditure to deal with the pandemic and falls in government revenue because of the fall in output (Kose et al. 2020). Thirdly, oil-producing countries have suffered from the sharp drop in the oil price accelerating as the pandemic took hold. Fourthly, it is not clear whether those countries that depend on the exports of primary products will see those prices rising again for some time. The one exception is gold, a commodity that usually increases in price whenever there is a crisis. The unequal position of countries of the Global South is further exemplified by early monopolisation by the rich countries of the distribution of the COVID-19 vaccines, thus exacerbating the weaker position of the former and their prospects for economic recovery. The effect of all of these factors is likely to be an increase in inequality between countries, to accompany the increases in inequality within them.
The problem that the concentration of wealth poses is that unless that wealth is invested in productive activity, which generates employment and thus increases demand for all products with consequent positive effects on unemployment and the earnings of the labour force, there will be a crisis of overproduction, a slump and mass unemployment. Wade (2014) refers to IMF research, which finds that higher inequality is associated with lower growth and redistribution, though higher taxation on higher incomes does not lead to lower growth as the benefits to growth of redistribution outweigh the costs to those who have to pay higher taxes. Since we have always known that people on low or middle incomes tend to spend almost all of any additional income they receive, while those on higher incomes would not have spent very much of the income they lose through taxation, these are not surprising findings, but very powerful ones for those making the case for attacking inequality.
As we know from the history of the twentieth-century, scenarios created by levels of inequality that increase unemployment and impoverish large sections of the population lead to civil disturbances and even to war. The Great Depression of the 1930s is a striking example of how this kind of inequality had an effect on security, through the growth of fascist movements in Europe culminating in a civil war in Spain, which became a prelude to Nazi Germany's invasions of Czechoslovakia, Poland and France, and the resulting six-year second world war.

Inequality and security
While there has been a growth in concern about inequality, this does not mean that it is generally accepted that inequality is a problem. Indeed, for a neoliberal economist it cannot be a problem, but only an efficient outcome of economic market mechanisms. These will, over time, become self-equilibrating, as those at the bottom end of the distribution increase their effort by raising their level of education and skills to gain higher returns. However, there is enough evidence that the mechanisms of the market result in cumulative inequalities: those higher in the distribution of income are more able to retain and also improve their position, while those at the lower end are in a constant battle to prevent themselves from falling further.
For Wilkinson and Pickett, a more equal society is a better one in many different aspects of life that are measurable. For Piketty, inequality is a threat to social justice achieved by getting 'patrimonial' capitalism back under democratic control. Neither directly raise a relationship between inequality and security, although Wilkinson and Pickett get close, correlating inequality positively with violence in the form of homicides, children's experience of conflict and people's view of their own ability to win a fist fight. However, there have been several attempts to consider the relationship between inequality and various forms of conflict, including terrorism.
A concern for ruling classes throughout the world must be the potentially destabilising effects of inequality, resulting in more than simply their governing parties losing elections. Civil wars, revolutions and terrorist incidents are possible outcomes of inequality. There are many studies that have looked for a relationship between inequality and social and political instability as evidenced, for example, by revolts and terror attacks. Survey data has been used to show that, while controlling for other possible causal variables, inequality has a positive relationship with a preference for revolution (Macculloch, 2005), although what people say and what they would actually do when faced with a potential revolutionary situation is another matter. Indeed, when the evidence is collected for revolutions that have occurred, the relation with inequality is not always in the same direction and, as Macculloch observes, some analyses have found a U-shaped relationship where revolts take place in high and low inequality countries.
Studies into the relationship between inequality and terrorism have shown inequality is positively related to the number of terrorists acts. One study found that controlling for various factors that could cause such attacks, such as types of regime (no relationship to terrorism), civil war (a positive relationship), population size (positive) and levels of economic development (no relationship), an increase in the Gini coefficient by one unit results in a 7.4% increase in the number of domestic terrorist attacks (Krieger and Meierrieks, 2018). The same study tested for endogeneity, that is, that terrorism could lead to income inequality as more state resources were spent on suppressing terrorism and, thus, less available for redistributive measures, and they found that this did not affect the robustness of their findings. Their results suggested mechanisms through which inequality is transmitted to terrorism, the most important being the quality of institutions. For example, they find that inequality results in poor institutional quality and, therefore, for example, more corruption and a poorer level of human rights. They also include a horizontal equality control variable, ethnic discrimination, and find that it is associated with increased domestic terrorism. They suggest that, added to these indirect ways in which inequality affects terrorism, there may be direct ways, as the relative deprivation of the lower income groups results in increasing discontent spilling over into terrorist attacks.
Not surprisingly, they find that using the ratio of the Gini coefficients of gross to net income as the redistribution variable, more equal distribution has the opposite effects, such that a one-unit increase in the Gini ratio results in an 85.3% reduction in terrorist acts. They also find that greater equality is associated with better institutions but negatively associated with investment, as redistribution from higher earners, who save more, to lower earners, who save less, will result in less investment and lower rates of growth. Redistributive policies resulting in higher public expenditure may, according to this argument, crowd out private investment leading to lower growth outcomes. This is a classic neoliberal conclusion and contradicts other findings associated with structuralist economic approaches cited above that suggest redistribution is good for growth as it increases consumption demand and, so, stimulates investment.
Distributions of income and wealth across countries' populations may be very different across regions, such that interregional inequality may be the key variable determining the amount of terrorism a country suffers. One study found that, after controlling for other possible explanatory variables such as GDP per head, population size, interpersonal inequality, economic decentralisation and openness to international trade, higher interregional inequality increased the incidence of domestic terrorism (Ezcurra and Palacios, 2016).
One less obvious way that inequality could affect levels of terrorism negatively or positively is through education. Krieger and Mierricks (2018) did not find education to be a significant variable. It might be expected that the higher the level of education, the lower the incidence of terrorism, not least because higher levels of education are associated with higher incomes. However, an argument could also be made that higher levels of education could make a section of the educated more aware of social injustices associated with inequality and, in doing so, result in a higher level of terrorism. One study that attempts to determine the relationship between education and terrorism finds that there is a relationship between the two but that it is curvilinear. As schooling years increase in the least educationally developed countries with between three to six years of schooling, terrorist attacks intensify. Then, as years of schooling increase, concomitant with rises in GDP per head, terrorist attacks decrease (Korotayev et al., 2019). The results are complicated by the authors finding a negative relationship between GDP per head and terrorist intensity but, when control variables such as inequality and unemployment rates are introduced, the relationship becomes positive, suggesting to the authors that if increases in GDP per head do not come with increasing equality and reduced unemployment then discontent with the situation is likely to increase, resulting in more terrorist attacks.
Terrorist attacks are not the only manifestation of a breakdown in security. Income inequality is also associated with neighbourhood property crime (Metz and Burdina, 2018), and with burglary, assault and robbery (Choe, 2008;Kelly, 2000). There is evidence that these associations vary in magnitude across countries, with one study for European countries finding that inequality and crime were significantly associated in Northern and Eastern Europe, while there was little relationship found between the two in Southern and Western Europe.

Critiques of economic models of conflict, terrorism and crime
For an orthodox economist, every action rationally chosen will involve some kind of calculation regarding its costs and benefits (e.g. Collier and Hoeffler, 1998). Terrorists will calculate the marginal cost or benefit of engaging in a terrorist act and criminals will do the same. Motivations for participating in rebellions or civil wars are reduced to greed or grievance with various economic proxies to stand in for these unmeasurable motives (Collier and Hoeffler, 2004). A strong government with well-informed security services will increase the costs of terrorist action, so terrorists will weigh up the risks against the respect they will gain from their peers for carrying out the terrorist act. Political and social factors will be included in the analysis if they can be measured or be inserted as a dummy variable. The studies on the relationship between inequality and terrorism, or other forms of insecurity such as crime, takes a measure of the variable to be explained -the number of terrorist acts or the number of violent crimes -and regresses them against some measure of inequality, usually the Gini coefficient and a set of other possible explanatory variables, which may be associated with terrorism or crime. This kind of neoclassical economic modelling of conflict does not take account of power relations and how far decisions by individuals to engage in civil conflict are determined by the force that leaders can bring to bear on them (Cramer, 2002).
For a heterodox economist, it is not necessarily all about rational chosen economic calculation. First of all, there is the problem of how far inequality can be represented by the Gini coefficient. This suggests that there is only one kind of inequality, but how income or wealth is distributed cannot be measured by one number. So, as Cramer (2003) has observed, the kind of equality is important, as is the robustness of the data, which he argues is poor for time series studies as well as for country cross section analyses. Moreover, as the same author also observes, countries with the same kind of income distribution can have very different patterns of civil conflict (Cramer, 2003). As we have seen, the studies referred to above all attempt to control for a whole set of other possible determinants of domestic terrorism or violent crime. While it may then be difficult to disentangle which of the variables actually causes, rather than is associated with, inequality, there have been attempts to tell a story around the results that plausibly explains the associations that have been found.
The more important issue that Cramer (2003) raises is the extent to which the inequalities that are observed are rooted in the social relations of production that result in particular distributional effects. Countries with weak states and a strong corporate presence, with weak trades unions or a large landlord class, or all three characteristics, are likely to exhibit significant inequalities in income and wealth. Conversely, countries with strong states and strong trades unions and farmer associations are likely to inhibit a concentration of income at the upper end of the distribution. As Cramer notes, the way these social relations evolve could be a more precise explanation for any ensuing civil conflict. The roots of conflict are likely to lie more in horizontal, rather than vertical, equality (Stewart, 2004). Examples of such origins are ethnic group rivalries when land is scarce or the beginnings of capitalist agriculture forcing people off the land to become an agricultural working class or part of a fighting force to gain power for a particular set of domestic interests. There are many other explanations for violent outcomes that rest more in the sphere of politics, sociology and anthropology than economics, and all of these, and not simply economic factors, need to be incorporated in any meaningful analysis.
A final point relating to the critique of the orthodox economic analysis of social conflict is that even if it is conclusively shown that inequality is undesirable because of its effects on various aspects of security, are those the only reasons why it needs to be addressed and reduced? Inequality is principally a symptom of the distribution of power, the social relations in which a few dominant people and organisations determine the lives of the majority of the citizens. This set of social relations undermines not only democracy itself, but also ideas of fairness and equity that underpin the freedoms and human rights of all individuals. If the analyses of the effects of inequality discussed in this article have any validity, then redistribution should be a key policy of every government, not only on pragmatic grounds but also on grounds of democratic principles and human rights.

Conclusion
This paper began with an analysis of global inequalities between nations, noting that although many countries have moved up the GDP league table, there are many who have stayed close to where they were five decades ago. The gap in GDP per capita between the bottom and top groups of countries has narrowed, although that is not the case for the top and bottom countries that belong to these groups. The inequality of nations around the globe remains a key feature of the world economy, dominated as it is by the rich and powerful countries of the Global North and, in particular, by the global financial corporates who have been able to exert a strong degree of control over largely compliant governments.
The inequality of people within nations has also grown, with the evidence highlighting that the concentration of wealth is in the hands of a very few, extremely rich, individuals and the high pay of top corporate executives and the upper echelons of corporate management. For the bottom and some sections of the middle class, wages and salaries have been stagnant since the last financial crisis of 2008-9, and an increasing section of the population in many countries of the Global North are in precarious employment exemplified by zero-hour contracts or low minimum wages.
There is increasing evidence that inequality, after controlling for other possible causes, results in threats to security, whether this comes in the form of terrorist attacks or in violent crime. However, inequality levels result from the nature of societies and economies and how they are organised. The nature of the social relations of individual countries can reveal why terrorism and violence are a feature of some societies but not others with similar distributions of income and wealth. The increasing concentration of wealth and power in the hands of a small group of individuals and corporates remains a global faultline that threatens democratic and human rights everywhere.
Notes 1 Peter Lawrence is Emeritus Professor of Development Economics at Keele University. He holds a BA and MA from the University of Sussex and a PhD from the University of Leeds. He has taught and researched in several African countries and published variously on rural and industrial development, macroeconomic policy and development strategy. p.r.lawrence@keele.ac.uk