An Investigation Into the Kuznets Curve

In the 1950s, the American economist and statistician Simon Kuznets, as a result of his work on economic growth and income distribution, developed the Kuznets curve: a model which posits that as an economy develops, inequality first increases and then decreases. It was first proposed in a 1955 seminal paper. This hypothesis is expressed on a graph of inequality plotted against income (or GDP) per capita and forms an inverted U-shaped curve, as is shown by the diagram below. This article aims to examine the justifications for this hypothesis, why it might be flawed, as well as the lessons one can learn from it.

The Kuznets Curve

Initially, when an economy is in its early stages of development, and income per capita is low, asset owners experience rising incomes as well as increasing investment opportunities, both of which perpetuate their increasing wealth. Simultaneously, there is more migration into urban areas from rural ones as workers seek higher wages and living standards. This large influx of workers into cities depresses wages. As a result, a discrepancy forms between the wealth of the asset-rich and the asset-poor, meaning inequality increases as the economy initially develops.

When an economy is more developed, and income per capita is higher, the Kuznets curve posits that inequality decreases. This is due to industrialization – namely the establishment of a welfare state as well as democratisation – which causes the redistribution of income. Workers also gain the ability to invest in both their own human capital and the wider economy. This higher investment leads to an increase in aggregate demand and thus economic growth, which in turn increases income per capita.

This hypothesis seems reasonable to the average observer: after all, there appears to be a negative correlation between the level of development of an economy and its Gini coefficient for income inequality. The empirical validity of the Kuznets curve has, for many years, been investigated, but findings are mixed, and one can arrive at different conclusions on whether the curve is true depending on which country one chooses to investigate. For example, in England during the late 19th and early 20th century, its Gini coefficient rose from 0.400 (1823) to 0.627 (1871), but then fell back down to 0.443 (1901). This rise and subsequent fall of income inequality match England’s pattern of industrialisation and are in accordance with the Kuznets curve theory. Conversely, certain European countries do not fall in line with Kuznets’ hypothesis. The Netherlands and Norway have ‘monotonically declining inequality [figures] from the mid-nineteenth century.’ The same is true of certain East Asian countries.

As mentioned above, scrutinising whether or not the evidence fits Kuznets’ theory and criticisms of the curve’s explanation leads one to question its validity. The East Asian Miracle (EAM) is clear evidence that contradicts Kuznets curve theory. The EAM refers to the period of intense economic growth of seven East Asian countries – Japan, South Korea, Taiwan and Singapore, which together have been termed the Four Asian Tigers, as well as Indonesia, Thailand, and Malaysia – between 1965 and 1990. According to the Kuznets hypothesis, the rapid growth of manufacturing and export industries and the increase in income per capita which was experienced in the aforementioned countries should have been accompanied by rising inequality. However, the exact opposite happened; the growth led to increases in life expectancy and living quality, and the number of people living in absolute poverty decreased. The countries in question became more equal. Why? An explanation can be found in the work of the economist Joseph Stiglitz: he argues that this relationship between income per capita and inequality during the EAM can be explained by the immediate reinvestment of the initial benefits of growth into land reform. This increased the productivity and income of rural workers, whilst the introduction of both universal education and interventionist policies raised the wages of the lowest-paid, thereby improving inequality. Ultimately, these actions and policies enacted by the governments of the EAM countries bolstered the ability of the average citizen to invest and consume, which further perpetuated economic growth. This example of the EAM further demonstrates that the relationship predicted by the Kuznets curve is not necessarily true: inequality does not always accompany growth.

 Interestingly enough, Kuznets himself expressed reservations about the ‘fragility of data’ that backed up his hypothesis. This data has also been a source of criticism for many and has led some economists to the conclusion that the inverted U-shape of the curve is actually due to dissimilar processes of economic development and historical differences between countries, rather than the general inequality-income relationship that Kuznet postulates. Kuznets’ own data used to develop the curve, for example, was primarily from countries in Latin America, and many of these countries have had historically high levels of inequality. This weak empirical evidence has therefore led some economists to object to his hypothesis.

How can one generalise the development-inequality relationship of countries into one graph, given the rich historical, cultural, political and socio-economic history of differing countries? Can one really apply a blanket model of the inequality-growth relationship, like the Kuznets Curve theory, to all economies, given that they differ to such a great extent? One could argue that this would be disingenuous in both the empirical and investigatory sense. However, the Kuznets curve remains a useful model in the investigation of the relationship between growth and inequality. Its description of this relationship remains true for some economies and countries, and lessons can be learned from its criticisms. Some of these lessons might help us approach developing and tackling inequality in a different way.

 Let us consider the inverse of the growth-inequality relationship we’ve been discussing so far: rather than investigating how growth affects inequality, let us think about how inequality affects growth. Inequality undermines education opportunities for children from poor socio-economic backgrounds, which decreases social mobility and hampers skills development, all of which are contrary to the innovation that is necessary to expand the productive capacity of an economy. This is one example of how inequality inhibits growth. Referencing the EAM, and how the aforementioned countries in East Asia were able to simultaneously increase economic growth and improve inequality, can provide information as to how other countries can mimic this. Conversely, finding out why other countries’ development followed the trend predicted by the Kuznets curve can aid us in remedying it in the future.

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