The Gini coefficient is a global measure of the distribution of wealth throughout a country, the coefficient ranges from 0 to 100 – with readings closer to 100 hinting that the country in question experiences higher levels of inequality. The Gini coefficient represents income inequality; income inequality can be defined as “the unequal distribution of household or individual income across the various participants in an economy” (Investopedia, 2015). In order to figure out the Gini coefficient we use a simple formula which shows that it “is equal to the area marked A divided by the sum of the areas marked A and B, that is, Gini = A/A+B” (Wikipedia, 2015).
There are many associated benefits with using the Gini coefficient as a measure of income inequality throughout a country. A big advantage of using the Gini coefficient is that it’s a globally recognised instrument in this area of economics, therefore it is able to be used to internationally compare the performances of different countries – this is because it is only a measure of inequality within a country or a certain region and can therefore be easily interpreted. On top of this, the Gini coefficient when used alongside the Lorenz Curve, ‘a graphical representation of wealth distribution’ (Investopedia, 2015), the two measurements manage to give a clear overview of how an economy is performing in terms of wealth and income distribution, which will be beneficial to a Government or a Think-tank so that they can implement regulation within an economy to alleviate the inequality. This simplicity also allows Governments to compare Gini coefficients of past years, so that they are able to observe any changes in the country’s income inequality, thus to see whether the country in question is progressing.
However, this ‘overview’ that the Gini coefficient provides can be construed as being rather vague, that’s to say that there’s no indication of what the breakdown of this inequality distribution is; we don’t know who holds the majority of the income – whether the top 5% have 50% of the income. This is important as it’s essential for nations to have an even level of wealth across the country, for example, in China in 2012 the ‘richest 10% had an average disposable income of $43,890, whereas the poorest 10% had an average disposable income of just $1,254 – this meant the richer decile had a 35x larger disposable income than the poorest decile’ (Euromonitor International, 2015). Furthermore, although it is a measure which can be used to internationally compare countries, there is a flaw as different countries distribute benefits in different ways; either through means such as food stamps or money. If money was used as a benefit, this could count as income towards the Gini coefficient and therefore make it difficult to compare countries using the Gini coefficient and the Lorenz Curve alone.
PART B
In 2011, South Africa recorded the second highest Gini index in the World, behind the Seychelles. South Africa obtained a reading of 65.0, this reading was significantly higher than that of the UK – 38.0, although the UK Gini coefficient was obtained in 2010. The main reason that could be associated with this comparatively high income inequality could be principally due to the post-apartheid reforms leading to major change in South Africa. After 1994 when the African National Congress took chair in parliament, a new regime began to be implemented into the country; allowing a much more diverse society to thrive in South Africa. The inequality in South Africa doesn’t lie mainly between the racial groups, rather within the racial groups. After 1994, the black population – due to their new lease of life – they experienced a resurgence in income. This is highlighted by the statistic, showing that “the black middle class in particular grew from 300,000 in 1993 to 3m in 2012, and blacks' share of the middle class from 11% to 41%.” (theconversation.com, 2015) The poorer population of the black Africans still benefited, however, not to the same extent as the black middle-class, therefore this lead to widening societal and economic disparities; due to the differing opportunities. Furthermore, within the white class, after the new election, the poorer-white class lost their job opportunities due to the influx of black-skilled labour who had better qualifications and therefore had higher occupational mobility. Employers started giving jobs to these skilled-black workers, causing white unemployment to increase and causing further disparities in the white community. Due to political unrest in the country, this was the catalyst for national inequality leading to the supremely high Gini index of South Africa, in comparison to the UK.
Next we come on to the industrial powerhouse of China; China has experienced various waves in inequality throughout its economic history, in the 50s, 60s and 90s. In 2010 China had a marginally higher Gini coefficient of 42.1, which is directly comparable to the UK’s Gini coefficient of 38.0 The most relevant of these peaks in income inequality in China is that of the 1990s which was supposedly due to embargoes with other trading nations being dropped and that of greater economic integration; as a result of globalisation. The increased trade with the western world lead to huge disparities in inland and coastal communities in China; this is due to the majority of industry taking place in the main cities such as Beijing. Furthermore, there were urban-rural disparities growing due to the increased openness of China, this peaked in 2009, in the middle of China’s most recent and strongest periods of economic growth. The urban-rural inequality at its peak showed that the urban proportion of the country were earning more than 3 times as much as rural dwellers, an income ratio existed of “3.33:1” (National Bureau of Statistics of China, 2015), also (Rosling, 2010) claims, in the documentary “The Joy of Stats”, that in 2019 Shanghai had a GDP similar to that of Italy, whereas rural Guizhou had a GDP bearing resemblance that of Ghana – this just highlights the regional disparities within China. It seems to be that the reason that China seem to have a comparatively higher Gini coefficient and a thusly more unequal society is due to its own success and strong economic growth, the economic growth has been concentrated in the industrious areas, leaving the agricultural areas in China behind in its wake.
Thirdly we have Brazil, in Latin America there have been high levels of inequality for some time, but as a growing and emerging economy Brazil has been able to reduce the levels of income inequality. The Gini coefficient has reduced from 63.3 in 1989 to 56.7 in 2010 (Monga Bay, 2015), still this remains higher than that of the UK at 38.0. In my opinion, there is a main factor which means that Brazil still have a relatively high Gini coefficient. In 2010 Brazil had the 10th highest (Monga Bay, 2015) Gini coefficient, and I think this is due to the low education levels in the country. In 2010 Brazil obtained literacy rates of circa 90%, this isn’t high enough for a developing economy and this comparatively low literacy rate has an adverse effect on income and wealth disparity and limits the opportunities of those in lower classes as it effects their social and occupational immobility. Having lower mobility means that the lower class citizens have limited ability to close up the income gap, i.e. the better education available to all, the higher qualifications and therefore occupational immobility the country’s population has and therefore all are able to access the higher paid jobs.
PART C
High income and income inequality are both economic factors which can lead to a multitude of economic and societal outcomes, including that of there being a positive correlation between a higher Gini coefficient of a country and the crime indices of a country and violence case studies.
Using the countries which I used when comparing their respective Gini coefficients, I aim to show how and why more unequal countries end up having higher crime rates. Firstly, South Africa (65.0) have an incredibly high index of 77.94 (Numbeo, 2015), coincidentally the fourth highest in the world, whereas the United Kingdom (38.0) had a moderate crime index of 42.92. Economic inequality can be a huge factor which can affect the way we think and perceive society, those who experience a lesser income can quite often feel aggrieved at the “injustice” and this could lead to “social competition and so encourage violence or may curtail opportunities for some, giving rise to a sense of hopelessness which incites fear, violence and murder” (Shaw, 2015).
China, who over recent years have seen an increase in their Gini coefficient – from 27.7 to 42.6 over a 20-year period (Fig. 1). Throughout the 80s and 90s China saw the largest increase in its Gini coefficient which coincided with the massacre in Tiananmen Square in 1989, which is a strong example of increased crime and violence. There were new economic reforms brought into action and this then created a “two-tier system where some prices were fixed while others were allowed to fluctuate” (Wikipedia, 2015). These economic reforms lead to a consumer price index increase of 30%, “leading to panic among salaried workers that they could no longer afford staple goods” (Wikipedia, 2015). The increase in the general price level meant that people’s money didn’t go as far, so social cuts were forced into play; job security and social benefits promises had diminished. These economic reforms lead to a lot of the lower and working classes venting their anger and having the students gathering in Tiananmen Square. On the 3rd June, the protests reached their peak and this then lead to a series of deaths over the ensuing two days. This again is an example of income and wealth inequality leading to a case of violence and increased crime.
However, despite the UK having a lower Gini coefficient than the other countries, we have still experienced huge moments of violence; the 2011 riots. Although, the exact cause of the riots isn’t known, there was speculation that one of the leading contributing factors to the riots was down to socio-economic reasons, which have an overall effect on inequality in the country. The policies implemented by the chancellor incited hatred and a lack of trust in the proletariat segment of the nation. These low levels of trust and increased ire materialised into the infamous 2011 riots. Experiences of social inferiority can leave certain individuals feeling less inclined to conform socially and leads to aggressive behaviour and higher crime rates. There are usually lower crime rates in more developed countries, i.e. those with higher Gini coefficients, because they have larger capacities to prevent violence and create safe communities.