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GINI Index- An indicator to understand whether the growth is homogeneous or not

Prof. Bikramaditya Ghosh

Abstract

Gini Index or measure is actually a deviation measure from perfect equal distribution of resources and expenditure within an economy. So, the higher it is will indicate that it is going towards perfect inequality and the lower it is will indicate the tendency to reach the[1]perfect equality. The Gini index measures the area between the Lorenz curve and a hypothetical line of absolute equality. A Lorenz curve plots the cumulative percentages of total income received against the cumulative number of recipients, starting with the poorest individual or household. The constituents of Gini traditionally are  new income component, tax and benefit component, GDP distribution component, interest rate component, component of concentration ratio (or Index) and last but not the least percentage of inequality.  This study has been done on the basis of World Bank data and OECD data. The study attempts to reveal the true sense of growth in different economies. Growth as a holistic manner means distribution of wealth in a proportionate manner across all the levels.

Study & Methodology

According to Boston Consulting Group’s 15th annual report just 928 households own India’s wealth. Indian households with financial wealth of more than $1 million own 36% of private financial wealth in the country. The share of those with over $1 million in financial assets has gone up from 33% of total private financial wealth in 2009 to 36% in 2014. Their share is projected to go up to 38% by 2019. The BCG 2015 global wealth report doesn’t say how many households in India had financial wealth of more than $1 million. However, their 2014 report said that India had 175,000 millionaire households in 2013[2].Due to the increasing importance of income inequality and poverty issues in policy discussion; the database is now annually updated. [3]Gini measurement methodology[4] is linked to Poverty calculation mechanism used by World Bank. To measure poverty in the developing world as an entity, the World Bank’s “$1 a day” measures apply a common standard, anchored to what “poverty” means in the world’s poorest countries. The original “$1-a-day” line was based on a compilation of national lines for only 22 developing countries, mostly from academic studies in the 1980s (Ravallion, et al., 1991). While this was the best that could be done at the time, the sample was hardly representative of developing countries even in the 1980s. Since then, national poverty lines have been developed for many other countries. On the basis of a new calculation of national lines for 75 developing countries, Ravallion, Chen and Sangraula (RCS) (2009) proposed a new international poverty line of $1.25 a day. This is defined as the average poverty line for the poorest 15 countries in their data set.

Interpretation

According to World Bank data India has a steady kind of Gini Coefficient
from 1978.[5] In 1978 it was at a record high of 35, from where by 1994 it went down to a low of 30. Again between last couple of decades it went up to 33.90. We can say that the movement has constantly been range bound. China on the other hand has quite a high number compared to India. Also it only and steadily went up in China. This means compared to India the growth of China has not been holistic in nature. Countries like US with Gini Index of more than 40, Brazil with more than 56 and Japan with 32 are also an indicator of unequal distribution of wealth. Scandinavian counterparts such as Netherlands, Sweden & Denmark are better off with Gini Coefficients in and around 27. Very surprisingly two most unfamiliar names feature in WB report with low Gini are Afghanistan & Pakistan. Probably the businesses are counted through the UAE for avoiding political turmoil. 20 Countries out of 212 countries were found over the red zone, i.e. over 50 in Gini Index. Not surprisingly 50% of them are from Africa and 25% of them are from Latin America. Seychelles leads the list with Gini Coefficient of 66, closely followed by South Africa at 65. Slovenia, Czech Republic, Belarus, Ukraine are the lowest group of Gini Coefficients with approximately with 24. However all the countries with extremely low Gini Coefficient are countries with a small base effect, which clarifies that India with its large mass, is comparatively in a comfortable position as far as wealth distribution is concerned.

Chart 1.0

Chart 1.1

 

Conclusion

In conclusion we can say in an easy way, that Gini Index clearly demarcates economies with holistic growth. BRAZIL, China or South Africa despite being an integral part of BRICS, do not show homogeneous growth. We can understand the situation with the pace of growth along with the proportionate distribution of wealth post or during growth. India may be growing at a slower pace than its counterparts in the BRICS, but the growth is visible a lot better overall. As in economics we conclude that sustainable growth is more important than sporadic growth, so as an economy we are heading in the correct direction as far as homogeneous growth with such a large base effect. Neither China nor Brazil could control their heterogeneous growth, and that residual impact has clearly been captured in the Gini coefficients.

Citations

[1]      Chen, Shaohua and Martin Ravallion, 2010, “China is Poorer than we thought, but no Less Successful in the Fight against Poverty,” in Debates on the Measurement of Poverty, Sudhir Anand, and Paul Segal, and Joseph Stiglitz, ed. (Oxford, UK: Oxford University Press).
[2]      Shaohua Chen and Martin Ravallion, 2011, “The Developing World is Poorer than we Thought, but no less Successful in the Fight against Poverty,” Quarterly Journal of Economics, Vol. 125, Issue 4, pp. 1577-1625. 
[3]      Martin Ravallion, 2008, “A Global Perspective on Poverty in India,” Economic and Political Weekly October 25, Vol.43, No. 43, pp.31-37. 
[4]      Martin Ravallion, Shaohua Chen, and Prem Sangraula, 2009, “Dollar a Day Revisited,” World Bank Economic Review, Vol. 23 , pp. 163-184. 
[5]      Martin Ravallion, Gaurav Datt, and Dominique van de Walle, 1991, “Quantifying Absolute Poverty in the Developing World,” Review of Income and WealthVol. 37, pp. 345-361.

 

 

 

 

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