A Lorenz curve is a simple, well-used way of representing inequality in an economy. The graph is a typical example. If there was a completely equitable distribution of income, then this would be represented by the 45 degree line on this diagram. The Gini Coefficient is derived from the same information used to create a Lorenz Curve. The co-efficient indicates the gap between two percentages: the percentage of population, and the percentage of income received by each percentage of the population. In order to calculate this you divide the area between the Lorenz Curve and the 45° line by the total area below the 45° line eg.
Area between the Lorenz Curve and the 45° line ÷ Total area below the 45° line
If the income distribution is equal, this coefficient will have a value of 0. At the other extreme, if all income accrues to just one person, then the Gini coefficient is 1 – data is sometimes shown in percentages therefore 100% represents full inequality. Both extremes do not occur in reality – the norm is for coefficients to be somewhere between these two values. A Gini coefficient of 0.3 therefore indicates a more equal distribution of income than say a coefficient of 0.5. The smaller coefficient would be indicated by a slimmer segment on the Lorenz curve. In 2020 New Zealand has a gini-coefficient of 0.32 (32%) – see below.
Income distribution in New Zealand Although the median net worth of New Zealand households has increased between 2015 and 2021, there has been no significant change in the distribution of wealth over this period. The top 10 percent of New Zealand households continues to hold approximately 50 percent of New Zealand’s total household net worth.
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In Norway, people right across the income distribution have high living standards. In the UK, US and Germany, the rich fare well but the poorest rank low vs other countries. From the graph below Norway does very well in equal distribution of income. The top 10% rank second for living standards as do the median (50%). The poorest 5% in Norway are the most affluent compared to other countries. Therefore in looking at all the percentiles Norway is a good place to live no matter what your income is.
Gini Coefficient The Gini coefficient is the best known measure to convey an impression of the overall level of inequality in a country. It ranges from 0 where everyone is equal to 1 where one person owns the whole income of a country. However there are two shortcomings:
There is no intuitive understanding of what a Gini coefficient implies. Although it might say that one country is has more equal distribution how big are the differences really? It gives a single figure for an entire country but it tells us nothing about which parts of society are causing the inequality. Is it the higher incomes being much greater than the rest of the population or is it the middle income group pulling away from the lower income group.
Comparing the very rich to the very poor does not tell us all that much about the everyday experience of ordinary people and societies they live in. Therefore by calculating ratios based on the income of the 10th, 50th and 90th percentiles we get a clearer picture of inequality. These two rations of 90:50 and 50:10 enable us to see the distance between the lowest-ranked wage earners and middle-class, and between the middle class and upper middle class.
Nordic countries – most equal in disposable income The graph below shows the two ratios for disposable income in Denmark, Norway, USA and Italy for 2018. Nordic countries Gini coefficient are characterised by the short distance from the middle class to the upper class, and from middle class to bottom. Although they still have inequality it is evident that affluence is largely shared compared to other countries.
Source: Equality in the Nordic World -2021
Noridic countries – disposable income 90th percentile make 1.5 times more than 50th percentile 50th percentile make 1.8 times more than 10th percentile
USA 90th percentile make 2.3 times more than 50th percentile 50th percentile make 2.7 times more than 10th percentile
Universal Welfare State. There are three elements to this definition: 1. Rights and unconditional benefits: if you are unemployed, sick or old you receive benefits to compensate for income loss. You also have access to free education, medical treatment and care homes for the elderly. 2. Benefits are paid for via general taxes therefore individuals don’t have job-based insurance or health programmes. All citizens are members of the same health coverage programme which is run by the government. 3. Universalism – no matter what your income because you belong to the same job-based insurance programme all citizens will be treated the same from a manual worker to a business manager/doctor. This means the number of deeply impoverished people is very small in the Nordic countries.
Nordic countries – equality kicks in before welfare support. The welfare state and government taxation are important mechanisms for redistributing money from the higher incomes to the lower incomes. Below are figures for the rations of gross income – people’s income before taxation and welfare payments. Therefore at a gross income level Nordic countries have a more equal pay before government intervention.
Source: Equality in the Nordic World -2021
Noridic countries – gross income 90th percentile make 1.5 times more than 50th percentile 50th percentile make 1.8 times more than 10th percentile
USA 90th percentile make 2.3 times more than 50th percentile 50th percentile make 2.7 times more than 10th percentile
This equality comes about mainly due to centralised wage negotiations. In Nordics countries collective bargaining normally takes place for entire sectors between unions representing employees and the employer associations representing businesses. The deals struck by the two parties then apply to all non union members. By 2015 the percentage of workers covered by collective bargaining were as follows: Sweden – 90% Denmark – 84% Norway – 67% US – 12%
Although this compress may compress wages people in the same occupation generally make the same although there has been an allowance for individual top-ups based on performance and qualifications.
Source: Equality in the Nordic World by Carsten Jensen – 2021
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The Lorenz curve is a useful tool used by those interested in statistics and economics to give a picture of income distribution. Its plots the % of household income on the vertical scale against the % of households on the horizontal. See opposite
The Gini Coefficient is derived from the same information used to create a Lorenz Curve. The co-efficient indicates the gap between two percentages: the percentage of population, and the percentage of income received by each percentage of the population. In order to calculate this you divide the area between the Lorenz Curve and the 45° line by the total area below the 45° line eg.
Area between the Lorenz Curve and the 45° line ÷ Total area below the 45° line
Below is a graphic from the World Inequality Report 2022 published by the World Inequality Lab. Useful figures especially with the top 1% and 10% of world population and the distribution of wealth, income and carbon emissions. Much can be done about inequality and that it is always a political choice, with better policy design inevitably leading to fairer development pathways.
Source: IMF Blog
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Most secondary school economics syllabus include the topic of inequality and the gini-coefficient which has now become more prevalent in the minds of government policymakers. The gini-coefficient is derived from the same information used to create a Lorenz Curve. The co-efficient indicates the gap between two percentages: the percentage of population, and the percentage of income received by each percentage of the population. The resulting number ranges between:
0 = perfect equality where say, 1% of the population = 1% of income, and
1 = maximum inequality where all the income of the economy is acquired by a single recipient.
The global Gini increased from 0.60 in 1820 to 0.72 in 1910, again 0.72 in 2000 and 0.67 in 2020 (see Figure 2.3). The decline in inequality was prevalent after the 2008 financial crisis. In all cases, global indicators indicate very high inequality levels in 2020 (close to those observed around 1900-1910, and substantially larger than those observed in 1820).
Source: World Inequality Report 2022
The graph below (Figure 2.1) gives the basic breakdown of the shares of world income going to the global top 10%, middle 40% and bottom 50% groups between 1820 and 2020. The main points are:
Global inequality has always been prevalent
Top 10% income approximately 50-60% of total income between 1820 and 2020
Bottom 50% share remained between 5-15%
Source: World Inequality Report 2022
Share of National Income by Country
Note that South Africa has the most unequal distribution of income whilst New Zealand is 142 out of 167 countries.
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One of the main areas of concern from the COVID-19 is the increasing level of inequality. Low-skilled workers have lost jobs as the pandemic has been the catalyst for rapid automation which could make jobs obsolete. Policies need to focus not just on redistribution but also predistribution – see image.
Predistribution – government policies aimed at narrowing differences in market incomes at their source, e.g. education, health Redistribution – public intervention through transfer payments and taxes related to unemployment, disability, sickness etc.
Source: IMF – Tackling Inequality on all fronts. March 2022
In order to tackle inequality a mix of these two policies is required to try and achieve a level playing field before people enter the labour market. Countries that spend more on social security an have a more redistributive tax system tend to be more successful on average in reducing inequality. Fiscal policy seems to be the most effective policy instrument to achieve this.
In many developing and developed countries there are big differences between income groups and their access to quality education. Also government spending can compensate lower income groups with better infrastructure – clean water, sanitation and basic health services. These policies can increase intergenerational mobility. Progressive taxation has potential to reduce inequality if countries have relatively low rates in terms of its overall burden. However, no government will have enough money to throw at the inequality problem and invariably there will be an opportunity cost – more money spent on education means less on healthcare etc. While fiscal policy has helped reduce inequality in countries it has come at the cost of very high debt levels which now need to be addressed by policies to bring deficits to sustainable levels.
Social Mobility and Education Education is generally seen as one of the vehicles for increasing social mobility. Research has shown that public expenditure on school education is strongly linked to the degree of income equality. Norway – 97.8% of money spent on school education is part of public expenditure USA – 68.2% of money spent on school education is part of public expenditure. This is likely to have a substantial impact on social differences in access to higher education. America now has lower social mobility than Denmark, France and Germany – see graph below with spending on education, health, and social protection.
In unequal societies, young people from poor families are more likely to drop out of school. More parents struggle with mental health problems, long working hours and debt. Income inequality in the USA is 39 (100 is complete inequality – 1 person owns all the income of the country) Denmark is 25. New Zealand Gini Index is 35 with spending on education, health etc lower than Denmark as a % of GDP.
Source: IMF – Tackling Inequality on all fronts. March 2022
What does Denmark do?
University education is free and childcare is well funded
The biggest boost to social mobility is wealth distribution. The Personal Income Tax Rate in Denmark stands at 55.8%. It averaged 60.66 percent from 1995 until 201
Across the West rising inequality hampers innovation and entrepreneurship. A study of 21 countries showed that as inequality rose the number of patents fell. Reducing inequality is one of 17 of the United Nations Sustainable Development Goals.
Source: IMF – Tackling Inequality on all fronts. March 2022
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The presence of technology in rural China is evidence that it is not just the booming cities that are the sources of growth. Furthermore, it suggests that inequality which has been symbolised by the ‘country versus city’ divide is now starting to decline.
Since the 1980’s China has gone through massive growth but it hasn’t been evenly shared. Income inequality is traditionally measured by using the Gini coefficient.
The Gini Coefficient is derived from the same information used to create a Lorenz Curve. The co-efficient indicates the gap between two percentages: the percentage of population, and the percentage of income received by each percentage of the population. In order to calculate this you divide the area between the Lorenz Curve and the 45° line by the total area below the 45° line eg. Area between the Lorenz Curve and the 45° line ÷ Total area below the 45° line
The resulting number ranges between:
0 = perfect equality where say, 1% of the population = 1% of income, and
100 = maximum inequality where all the income of the economy is acquired by a single recipient.
* The straight line (45° line) shows absolute equality of income. That is, 10% of the households earn 10% of income, 50% of households earn 50% of income.
In 2010 China’s Gini coefficient was 61 which was one of the world’s most unequal countries however officially it has been falling for seven years from 49 in 2008 to 046 in 2015. Rural incomes have grown more quickly that their urban counterparts – in 2009 the average urban income was 3.3 times that of a rural worker but now it is 2.7 times. Many of those living in rural areas actually work in cities but are prevented from living there because of the strict residency system. Also companies have now been looking to the rural areas for cheap labour. However, in 2019 China’s official Gini is 46.5 (see graph), meaning that the expected gap will be 93% (ie, twice the Gini) of China’s average disposable income. Since average disposable income was 30,733 yuan ($4,449) in 2019, the expected gap would be about $4,138.
Source: The Economist – 2nd October 2021. Just how Dickensian is China? Inequality is betterthan it was. But it doesn’t feel that way
Martin Wolf of the Financial Times wrote a piece on ‘Monetary Policy is not the solution to inequality’. In it he mentioned that as well as the traditional means of taxation and government welfare spending, can central banks also assist with reducing the level of inequality in an economy? In maintaining aggregate demand (C+I+G+(X-M)) and stimulating economic growth there runs the risk of higher prices and a business cycle that becomes a volatile series of booms and busts – see previous post.
With the housing sector coming under close scrutiny by central banks higher interest rates to reduce house prices would also impact AD and raise unemployment. With some lower income groups living from pay check to pay check this would make matters worse. The graph below shows the impact of taxation and welfare spending has on inequality levels – note China and India. You can see those economies that have a more left wing government policy objective.
Source: FT – Monetary Policy is not the solution to inequality.
Rising inequality had led government’s to choose between higher unemployment or increasing levels of debt by expansionary monetary policy from the central bank. Either you allow people to borrow excessive amounts of money to boost AD or the economy slows and unemployment rises. A better solution could be to reduce the incentive to fund housing etc by the accumulation of debt but with equity financing
Unemployment around the world is increasing at an alarming rate and one only needs to look at the USA to see the impact of COVID-19 on the rate. Today the number of people claiming benefit is 35 million which equates to 14.7% of the labour force. This is contrast to 3.5% in February this year. More jobs were lost during March than the whole of the GFC in 2008-2009.
Globally it is estimated that 200 million jobs will be lost in 2020 with about 40% of the global workforce in jobs that face a high risk of becoming obsolete – International Labour Organisation. These job losses worldwide will mean mean increasing inequality as the lower income groups more likely to experience unemployment and financial insecurities and therefore more vulnerable to labour market fluctuations resulting from macroeconomic changes. In reality a lot of people on low incomes live from week to week and when their pay suddenly stops the situation becomes desperate. A lot of the jobs that lower incomes do (in the service sector) have now gone with the closure of bars, restaurants, offices etc. Some still work in essential services like hospitals but are now in the front line and exposed to the virus. Research has shown that pandemics lead to a persistent and significant increase in the net Gini Coefficient measure of inequality – see graph below). Government support in a lot of economies has not protected those that are most vulnerable and COVID-19 could end up being a catalyst to increasing inequality more than other previous pandemic episodes.
What is the Gini Coefficient? The Gini Coefficient is derived from the same information used to create a Lorenz Curve. The co-efficient indicates the gap between two percentages: the percentage of population, and the percentage of income received by each percentage of the population. In order to calculate this you divide the area between the Lorenz Curve and the 45° line by the total area below the 45° line eg.
Area between the Lorenz Curve and the 45° line Total area below the 45° line
The resulting number ranges between:
0 = perfect equality where say, 1% of the population = 1% of income, and
1 = maximum inequality where all the income of the economy is acquired by a single recipient.
The straight line (45° line) shows absolute equality of income. That is, 10% of the households earn 10% of income, 50% of households earn 50% of income.
Around the globe the size of the middle class is diminishing and with it societies are becoming more unequal. The Greek philosopher, Aristotle, 2,400 years ago summarising his analysis of the Greek city states pointed out that democracy depended on the size of a country’s middle class. With a proportionately bigger middle class a democracy tends to work well as it promotes social mobility, encourages aggregate demand which in turn leads to economic growth. Notice in the graph below how the Scandinavian countries have higher social mobility compared to the other extreme of the US and the UK.
Source: FT – How to reform today’s rigged capitalism
Aristotle warned that when inequality – see graph below – reaches a certain point it becomes very damaging to society. He refers to the importance of the middle class in his book Politics:
The best constitution is one controlled by a numerous middle class which stands between the rich and the poor. For those who possess the goods of fortune in moderation find it “easiest to obey the rule of reason” (Politics IV.11.1295b4–6). They are accordingly less apt than the rich or poor to act unjustly toward their fellow citizens.
A constitution based on the middle class is the mean between the extremes of oligarchy (rule by the rich) and democracy (rule by the poor). “That the middle [constitution] is best is evident, for it is the freest from faction: where the middle class is numerous, there least occur factions and divisions among citizens” (IV.11.1296a7–9). The middle constitution is therefore both more stable and more just than oligarchy and democracy.
“The best political community is formed by citizens of the middle class, and that those states are likely to be well-administered in which the middle class is large, and stronger if possible than both the other classes . . . ; for the addition of the middle class turns the scale, and prevents either of the extremes from being dominant.”
Inequality creates barriers to the supply of talent, innovation and finance as wealthy families monopolise educational and workplace opportunities. This is done by the cost of education and the influence of social networks.
It overturns private competition and public investment as powerful corporations force out competitors and suppress wages. Also the government underfund public goods which are essential for social mobility.
Lower wages reduce consumer demand and lead to less buying power which in turn encourages more borrowing and pushes the economy toward financial instability.
The Department of Statistics recently published wealth distribution figures for New Zealand. According to Stats NZ, the median household net worth in the year ended 30 June 2018 was $340,000, up from $289,000 in 2015. The increase was mainly driven by an increase in property values over the last three years.
% of net wealth held by % of Households – 2018
According to the survey, the top ten percent of households hold 53 percent of total wealth in New Zealand, which is unchanged from 2015. The top one percent of households hold 16 percent of total wealth in New Zealand, which is down slightly from 2015. New Zealand’s Gini Coefficient is approximately 0.33.
The Lorenz Curve
The Gini Coefficient is derived from the same information used to create a Lorenz Curve. The co-efficient indicates the gap between two percentages: the percentage of population, and the percentage of income received by each percentage of the population. In order to calculate this you divide the area between the Lorenz Curve and the 45° line by the total area below the 45° line eg. Area between the Lorenz Curve and the 45° line ÷ Total area below the 45° line.
The resulting number ranges between:
0 = perfect equality where say, 1% of the population = 1% of income, and
1 = maximum inequality where all the income of the economy is acquired by a single recipient.
* The straight line (45° line) shows absolute equality of income. That is, 10% of the households earn 10% of income, 50% of households earn 50% of income.
In 2010 China’s Gini coefficient was 0.61 which was one of the world’s most unequal countries however officially it has been falling for seven years from 0.49 in 2008 to 0.46 in 2015. Rural incomes have grown more quickly that their urban counterparts – in 2009 the average urban income was 3.3 times that of a rural worker but now it is 2.7 times. Many of those living in rural areas actually work in cities but are prevented from living there because of the strict residency system. Also companies have now been looking to the rural areas for cheap labour.
But at the top end you would get the impression that inequality of wealth is extremely high – wealth = what you own, as opposed to what you earn. China has more dollar billionaires (596) than the USA (537). Research has shown that 1% of the population control a 1/3 of China’s assets.
The presence of technology in rural China is evidence that it is not just the booming cities that are the sources of growth. Furthermore, it suggests that inequality which has been symbolised by the ‘country versus city’ divide is now starting to decline.
Since the 1980’s China has gone through massive growth but it hasn’t been evenly shared. Income inequality is traditionally measured by using the Gini coefficient.
The Gini Coefficient is derived from the same information used to create a Lorenz Curve. The co-efficient indicates the gap between two percentages: the percentage of population, and the percentage of income received by each percentage of the population. In order to calculate this you divide the area between the Lorenz Curve and the 45° line by the total area below the 45° line eg. Area between the Lorenz Curve and the 45° line ÷ Total area below the 45° line
The resulting number ranges between:
0 = perfect equality where say, 1% of the population = 1% of income, and
1 = maximum inequality where all the income of the economy is acquired by a single recipient.
* The straight line (45° line) shows absolute equality of income. That is, 10% of the households earn 10% of income, 50% of households earn 50% of income.
In 2010 China’s Gini coefficient was 0.61 which was one of the world’s most unequal countries however officially it has been falling for seven years from 0.49 in 2008 to 0.46 in 2015. Rural incomes have grown more quickly that their urban counterparts – in 2009 the average urban income was 3.3 times that of a rural worker but now it is 2.7 times. Many of those living in rural areas actually work in cities but are prevented from living there because of the strict residency system. Also companies have now been looking to the rural areas for cheap labour.
But at the top end you would get the impression that inequality of wealth is extremely high – wealth = what you own, as opposed to what you earn. China has more dollar billionaires (596) than the USA (537). Research has shown that 1% of the population control a 1/3 of China’s assets.
National income figures, usually GDP at factor cost, are the man figures used to compare living standards. This is because most countries keep and publish detailed national income data.
However, care has to be taken in using national income figures to compare living standards both over time and between countries. It is important to use GDP at constant prices (i.e. real national income) so that a misleading impression is not given because of the effects of inflation. It is also important to take into account differences in population size. A country with a large population is likely to produce more than a country with a small population. However, this output has to be shared out among more people so living standards are not necessarily higher. This is why economist divide output by population and compare real GDP per capita. Even when adjustments have been made for inflation and differences in population size, national income figures as a measure of living standards have to be interpreted cautiously.
A rise in real GDP per capital may have resulted from an increase in the output of capital goods. In the longer run this will increase productive capacity and result in more consumer goods being produced. However, in the short run people may not feel any benefit from more capital goods being made. An increase in weapons will also increase GDP but, again, may not necessarily improve living standards. If more police are employed and crime is reduced, the quality of people’s lives will be improved. However, if more police are employed to keep pace with rising crime, people will be feeling worse off. So economists have to look not only at the amount of goods and services produced but also at the composition of those goods and why the quantity has changed. In addition, the quality of goods and services produced should be examined. The same quantity could be produced this year as last year or five years ago but if the quality of the output has risen, living standards will have improved.
The distribution of income also has to be taken into account. National income may rise but if it is concentrated in the hands of a few, the living standards of the majority may not rise. See graph below from The Economist showing the Gini coefficient of income inequality.
National income figures also fail to take into account some items which affect the quality of people’s lives. A certain amount of economic activity is not declared, either to avoid paying taxes or because it is illegal. If there is an increase in, say, people providing home hairdressing services but not declaring them, people’s living standards may rise, although this increase will not be reflected in the official figures.
Differences in working hours and working conditions are also not taken into account. If output remains constant but working hours fall, people are likely to have a higher quality of life.
National income figures only take into account economic activities for which a payment is made. They do not take into account externalities and non-marketed activities. So, for example, an increase in pollution will reduce living standards while an increase in people decorating the homes of old people, on a voluntary basis, will improve the quality of life of the elderly. Neither of these will be recorded in national income figures.
All of these factors have to be taken into account in using national income figures to make comparisons both over time and between countries. However, some additional factors have to be considered when making international comparisons. Different statistical methods are employed in some countries and the degree of accuracy can vary. Tastes and needs can be different in different countries. For example, people living in a cold climate have to spend more on heating than those in warm countries, merely to enjoy the same standard of living. There is also the problem of selecting a rate of exchange to make the comparison. Exchange rate fluctuate and do not always reflect relative prices in compared using purchasing power parities which compare the cost of a given basket of goods in different countries.
Interesting report from the OECD that was published yesterday. There are a couple of good graphs that can be used for teaching inequality: The increase in inequality from 1985 – 2011; and the impact that inequality has on growth.
The Gini coefficient increased in 16 out of the 21 OECD countries for which long time series are available, rising by more than 5 points in Finland, Israel, New Zealand, Sweden and the United States and falling slightly only in Greece and Turkey (Figure 1).
The OECD estimate that increasing inequality by 3 Gini points (that is 0.03) points would drag down economic growth by 0.35 percentage point per year for 25 years: a cumulated loss in GDP at the end of the period of 8.5 per cent. Figure 2 below shows the that the increasing levels of inequality are estimated to have reduced growth levels in the majority of countries. Those of note are:
New Zealand -15%
Mexico -12%
UK -9%
Finland -9%
Norway -9%
Sweden -8%
Italy -7%
USA -6%
The graph also shows that greater equality prior to the crisis helped increase GDP per capita in Spain, France and Ireland.
Key Findings from OECD Report
* The gap between rich and poor is now at its highest level in 30 years in most OECD countries.
* This long-term trend increase in income inequality has curbed economic growth significantly.
* While the overall increase in income inequality is also driven by the very rich 1% pulling away, what matters most for growth are families with lower incomes slipping behind.
* This negative effect of inequality on growth is determined not just by the poorest income decile but actually by the bottom 40% of income earners.
* This is because inter alia people from disadvantaged social backgrounds underinvest in their education.
* Tackling inequality through tax and transfer policies does not harm growth, provided these policies are well designed and implemented.
* In particular, redistribution efforts should focus on families with children and youth, as this is where key decisions on human capital investment are made and should promote skills development and learning across people’s lives.
It has long been thought that you need to have some inequality if you are going to encourage growth. However you can go to extremes, as in the case of Margaret Thatcher, who said that inequality is essential to fostering “the spirit of envy” and hailed greed as a “valuable spur to economic activity”. There is some truth in the matter that without the carrot of financial reward risk taking by entrepreneurs would not be as prevalent as would innovation. This all relates to equity efficiency trade-off where you cannot have both at the optimum level – ie you have an opportunity cost. The Free Exchange column in The Economist discussed this issue.
Negatives of Inequality:
* Damages growth as those on low incomes suffer poor health and low productivity
* Reduces public confidence in growth-boosting policies – eg Free Trade
* A response to the problem of inequality has been to make borrowing easier for lower income groups but when the borrowing ends everyone suffers – Sub-Prime crisis.
Duration of Growth
Some researchers have suggested that getting the economy to grow in the first place is much easier than trying to maintain the levels of growth. When growth does slow down after an initial burst it is usually inequality that is the root of the problem.
Inequality and Redistribution
Further research has tried to separate the effects of inequality and redistribution. Governments tax and spend (fiscal policy) to try and reduce the level of inequality. The chart below shows the difference between 2 measures of income – Market Income and Net Income (after taxes and transfer payments). The difference between the two gives a measure of redistribution. Some notable points:
1. USA – does comparatively little redistribution as its Gini is reduced by approximately 10 points.
2. Sweden – cuts the Gini by 23 points
3. Governments in more unequal countries redistribute more
4. Germany are more unequal than the UK with Market Income but has less inequality when redistribution policies are implemented.
5. Economies that redistribute a lot of lower incomes may have shorter growth periods.
6. If the gap between Market and Net Income is 13 points or more further distribution shrinks growth expansion
7. Inequality more associated with low growth – the higher the Gini Coefficient for net income the slower the growth in income per person.
Pope Francis challenged business leaders assembled at the World Economic Forum in Davos to put their wealth at the service of humanity instead of leaving most of the world’s population in poverty and insecurity.
The global economy should grow by 3.2% this year, up from 2.4% in 2013, according to the World Bank. Yet for many, in the developed world and emerging markets alike, the recovery from the worst economic crisis since the 1930s has a phantom-like quality. Many people can’t see an improvement in their quality of life, and the gap between rich and poor is growing.
“Since the global financial crisis, it’s been a race to the bottom in jobs, wages and living standards,” said Philip Jennings, general secretary of UNI Global Union. Central banks have pumped trillions of dollars into the world financial system to stabilize their economies, sending stock markets and real estate prices soaring to the benefit of the wealthy.
The Economist magazine produced a very useful graphic showing the percentage share of income held by the richest 20% and the poorest 20%.
Figures from the World Bank show that by this indicator many of the world’s most unequal countries are in Latin America. In Colombia the incomes of the top fifth are nearly 25 times those of the bottom fifth. Most emerging Asian countries are less unequal: the incomes of the richest 20% of Chinese are about eight times those of the poorest 20%. In Thailand, one of Asia’s most unequal countries, the ratio is 15:1. Qatar’s income per person is among the world’s highest. But income is unequally distributed: the richest Qataris receive over 13 times as much as the poorest.
ECONFIX 