Kuznets curve
The Kuznets curve (
Kuznets ratio and Kuznets curve
The Kuznets ratio is a measurement of the ratio of income going to the highest-earning households (usually defined by the upper 20%) to income going to the lowest-earning households,[4] which is commonly measured by either the lowest 20% or lowest 40% of income. Comparing 20% to 20%, a completely even distribution is expressed as 1; 20% to 40% changes this value to 0.5.
Kuznets curve diagrams show an inverted U curve, although variables along the axes are often mixed and matched, with inequality or the Gini coefficient on the Y axis and economic development, time or per-capita incomes on the X axis.[5]
Explanations
One explanation of such a progression suggests that early in development, investment opportunities for those who have money multiply, while an influx of cheap rural labor to the cities holds down wages. Whereas in mature economies, human capital accrual (an estimate of income that has been achieved but not yet consumed) takes the place of physical capital accrual as the main source of growth; and inequality slows growth by lowering education levels because poorer, disadvantaged people lack finance for their education in imperfect credit-markets.
The Kuznets curve implies that as a
- workers migrated from agriculture to industry; and
- rural workers moved to urban jobs.
In both explanations, inequality will decrease after 50% of the shift force switches over to the higher paying sector.[4]
Evidence
Inequality has risen in most developed countries since the 1960s, so that graphs of inequality over time no longer display a Kuznets curve. Piketty has argued that the decline in inequality over the first half of the 20th century was a once-off effect due to the destruction of large concentrations of wealth by war and economic depression.
The Kuznets curve and development economics
Critics of the Kuznets curve theory argue that its U-shape comes not from progression in the development of individual countries, but rather from historical differences between countries. For instance, many of the middle income countries used in Kuznets' data set were in Latin America, a region with historically high levels of inequality. When controlling for this variable, the U-shape of the curve tends to disappear (e.g. Deininger and Squire, 1998). Regarding the empirical evidence, based on large panels of countries or time series approaches, Fields (2001) considers the Kuznets hypothesis refuted.[7]
The East Asian miracle (EAM) has been used to criticize the validity of the Kuznets curve theory. The rapid economic growth of eight East Asian countries—Japan; the Four Asian Tigers South Korea, Taiwan, Singapore, Hong Kong; Indonesia, Thailand, and Malaysia—between 1965 and 1990, was called the East Asian miracle. The EAM defies the Kuznets curve, which insists growth produces inequality, and that inequality is a necessity for overall growth.[6][8] Manufacturing and export grew quickly and powerfully. Yet, contrary to Kuznets' historical examples, the EAM saw continual increases in life expectancy and decreasing rates of severe poverty.[9] Scholars have sought to understand how the EAM saw the benefits of rapid economic growth distributed broadly among the population.[8] Joseph Stiglitz explains this by the immediate re-investment of initial benefits into land reform (increasing rural productivity, income, and savings), universal education (providing greater equality and what Stiglitz calls an "intellectual infrastructure" for productivity[8]), and industrial policies that distributed income more equally through high and increasing wages and limited the price increases of commodities. These factors increased the average citizen's ability to consume and invest within the economy, further contributing to economic growth. Stiglitz highlights that the high rates of growth provided the resources to promote equality, which acted as a positive-feedback loop to support the high rates of growth.
"[T]he statistical evidence for the 'upwards' side of the 'Inverted-U' between inequality and income per capita seems to have vanished, as many low and low-middle income countries now have a distribution of income similar to that of most middle-income countries (other than those of Latin America and Southern Africa). That is, half of Sub-Saharan Africa and many countries in Asian, including India, China and Vietnam, now have an income distribution similar to that found in North Africa, the Caribbean and the second-tier NICs. And this level is also similar to that of half of the first-tier NICs, the Mediterranean EU and the Anglophone OECD (excluding the US). As a result, about 80% of the world population now live in countries with a Gini around 40."[10]
Palma goes on to note that, among middle-income countries, only those in Latin America and Southern Africa live in an inequality league of their own. Instead of a Kuznets curve, he breaks the population into deciles and examines the relationship between their respective incomes and income inequality. Palma then shows that there are two distributional trends taking place in inequality within a country:
"One is 'centrifugal', and takes place at the two tails of the distribution—leading to an increased diversity across countries in the shares appropriated by the top 10 percent and bottom forty percent. The other is 'centripetal', and takes place in the middle—leading to a remarkable uniformity across countries in the share of income going to the half of the population located between deciles 5 to 9."[10]
Therefore, it is the share of the richest 10% of the population that affects the share of the poorest 40% of the population with the middle to upper-middle staying the same across all countries.
In Capital in the Twenty-First Century, Thomas Piketty denies the effectiveness of the Kuznets curve. He points out that in some rich countries, the level of income inequality in 21st century has exceeded that in the second decades of 20th century, proposing the explanation that when the rate of return on capital is greater than the rate of economic growth over the long term, the result is the concentration of wealth.[11]
Kuznets's own caveats
In a biography about Simon Kuznets's scientific methods, economist Robert Fogel noted Kuznets's own reservations about the "fragility of the data" which underpinned the hypothesis. Fogel notes that most of Kuznets's paper was devoted to explicating the conflicting factors at play. Fogel emphasized Kuznets's opinion that "even if the data turned out to be valid, they pertained to an extremely limited period of time and to exceptional historical experiences." Fogel noted that despite these "repeated warnings", Kuznets's caveats were overlooked, and the Kuznets curve was "raised to the level of law" by other economists.[12]
Inequality and trade liberalization
Dobson and Ramlogan's research looked to identify the relationship between inequality and
Environmental Kuznets curve
The environmental Kuznets curve (EKC) is a hypothesized relationship between environmental quality and economic development:[14] various indicators of environmental degradation tend to get worse as modern economic growth occurs until average income reaches a certain point over the course of development.[15][16] The EKC suggests, in sum, that "the solution to pollution is economic growth."
Although subject to continuing debate, there is considerable evidence to support the application of environmental Kuznets curve for various environmental health indicators, such as
Deforestation may follow a Kuznets curve (cf. forest transition curve). Among countries with a per capita GDP of at least $4,600, net deforestation has ceased.[20] Yet it has been argued that wealthier countries are able to maintain forests along with high consumption by 'exporting' deforestation, leading to continuing deforestation on a worldwide scale.[21]
Criticisms
However, the EKC model is debatable when applied to other pollutants, some natural resource use, and biodiversity conservation.
At least one critic argues that the US is still struggling to attain the income level necessary to prioritize certain environmental pollutants such as carbon emissions, which have yet to follow the EKC.
Other critics point out that researchers also disagree about the shape of the curve when longer-term time scales are evaluated. For example, Millimet and Stengos regard the traditional "inverse U" shape as actually being an "N" shape, indicating that pollution increases as a country develops, decreases once the threshold GDP is reached, and then begins increasing as national income continues to increase. While such findings are still being debated, it could prove to be important because it poses the concerning question of whether pollution actually begins to decline for good when an economic threshold is reached or whether the decrease is only in local pollutants and pollution is simply exported to poorer developing countries. Levinson concludes that the environmental Kuznets curve is insufficient to support a pollution policy regardless whether it is laissez-faire or interventionist, although the literature has been used this way by the press.[26]
Arrow et al. argue pollution-income progression of agrarian communities (clean) to industrial economies (pollution intensive) to service economies (cleaner) would appear to be false if pollution increases again at the end due to higher levels of income and consumption of the population at large.[27] A difficulty with this model is that it lacks predictive power because it is highly uncertain how the next phase of economic development will be characterized. [citation needed]
Suri and Chapman argue that the EKC is not applicable on the global scale, as a net pollution reduction may not actually be occurring globally. Wealthy nations have a trend of exporting the activities that create the most pollution, like manufacturing of clothing and furniture, to poorer nations that are still in the process of industrial development (Suri and Chapman, 1998). This could mean that as the world's poor nations develop, they will have nowhere to export their pollution. Thus, this progression of environmental clean-up occurring in conjunction with economic growth cannot be replicated indefinitely because there may be nowhere to export waste and pollution-intensive processes. However,
Stern warns "it is very easy to do bad
Kuznets curves for steel and other metals
Steel production has been shown to follow a Kuznets-type curve in the national development cycles of a range of economies, including the United States, Japan, Republic of Korea and China. This discovery, and the first usage of the term "Kuznets Curve for Steel" and "Metal intensity Kuznets Curve" were by Huw McKay in a 2008 working paper (McKay 2008). This was subsequently developed in McKay (2012). A body of work on "Material Kuznets Curves" focused on non-ferrous metals has also emerged as academic and policy interest in resource intensity increased during the first two decades of the 21st century.[citation needed]
References
- ^ Based on Table TI.1 of the supplement Archived 8 May 2014 at the Wayback Machine to Thomas Piketty's Capital in the Twenty-First Century.
- ^ Piketty, Thomas (2013). Capital in the Twenty-First Century. Belknap. p. 24.
- New School for Social Research: "...his discovery of the inverted U-shaped relation between income inequality and economic growth..."
- ^ a b Kuznets, Simon. 1955. Economic Growth and Income Inequality. American Economic Review 45 (March): 1–28.
- .
- ^ .
- ^ Fields G (2001). Distribution and Development, A New Look at the Developing World. Russel Sage Foundation, New York, and The MIT Press, Cambridge, Massachusetts, and London.
- ^ .
- ^ (course lectures).
- ^ a b Palma, J. G. (26 January 2011). "Homogeneous middles vs. heterogeneous tails, and the end of the 'Inverted-U': the share of the rich is what it's all about". Cambridge Working Papers in Economics.
- ISBN 978-0674430006.
- S2CID 142683345.
- ^ S2CID 154528726.
- S2CID 220721520.
- ^ Shafik, Nemat. 1994. Economic development and environmental quality: an econometric analysis. Oxford Economic Papers 46 (October): 757–773
- doi:10.3386/w3914.
- S2CID 199855869.
- ^ John Tierney (20 April 2009). "The Richer-Is-Greener Curve". The New York Times.
- ^ "Don't Be Very Worried". The Wall St. Journal. 23 May 2006. Archived from the original on 15 June 2006.
{{cite news}}
: CS1 maint: bot: original URL status unknown (link) - ^ Returning forests analyzed with the forest identity, 2006, by Pekka E. Kauppi (Department of Biological and Environmental Sciences, University of Helsinki), Jesse H. Ausubel (Program for the Human Environment, The Rockefeller University), Jingyun Fang (Department of Ecology, Peking University), Alexander S. Mather (Department of Geography and Environment, University of Aberdeen), Roger A. Sedjo (Resources for the Future), and Paul E. Waggoner (Connecticut Agricultural Experiment Station)
- ^ "Developing countries often outsource deforestation, study finds". Stanford News. 24 November 2010. Retrieved 18 June 2015.
- .
- ^ "Google Public Data US Energy". Energy Information Administration. Retrieved 17 December 2011.
- ^ a b c Yandle B, Vijayaraghavan M, Bhattarai M (2002). "The Environmental Kuznets Curve: A Primer". The Property and Environment Research Center. Archived from the original on 30 December 2008. Retrieved 16 June 2008.
- ISBN 978-4-431-55919-1.
- ^ CiteSeerX 10.1.1.92.2062.
- PMID 17756719.
- ^ Koilo, Viktoriia. 2019. "Evidence of the Environmental Kuznets Curve: Unleashing the Opportunity of Industry 4.0 in Emerging Economies" Journal of Risk and Financial Management 12, no. 3: 122. https://doi.org/10.3390/jrfm12030122
- ^ David I. Stern. "The Environmental Kuznets Curve" (PDF). International Society for Ecological Economics Internet Encyclopedia of Ecological Economics. Archived from the original (PDF) on 20 July 2011. Retrieved 17 March 2019.
Bibliography
- Brenner, Y.S., Hartmut Kaelble, and Mark Thomas (1991): Income Distribution in Historical Perspective. Cambridge University Press.
- Deininger K, Squire L (1998). "New Ways of Looking at Old Issues: Inequality and Growth". Journal of Development Economics. 57 (2): 259–287. .
- Fields G (2001). Distribution and Development, A New Look at the Developing World. Russel Sage Foundation, New York, and The MIT Press, Cambridge, Massachusetts, and London.
- Palma, JG (2011). "Homogeneous middles vs. heterogeneous tails, and the end of the 'Inverted-U': it's all about the share of the rich". Development and Change. 42: 87–153. .
- McKay, Huw (2008) ‘Metal intensity in comparative historical perspective: China, North Asia, the United States and the Kuznets curve’, Global Dynamic Systems Centre working papers, no. 6, September.
- McKay, Huw (2012) ‘Metal intensity in comparative historical perspective: China, North Asia, the United States ’, chapter 2 in Ligang Song and Haimin Lu (eds) The Chinese Steel Industry’s Transformation: Structural Change, Performance and Demand on Resources, Edward Elgar: Cheltenham UK.
- Van Zanden, J. L. (1995). "Tracing the Beginning of the Kuznets Curve: Western Europe during the Early Modern Period". The Economic History Review. 48 (4): 643–664. JSTOR 2598128.