Inequality in IndiaDimensions and Trends

Himanshu Rinku Murgai

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GDP has grown at more than 5% since the mid-1980s. The acceleration in growth rates to more than 9% since 2005-06 was short lived with growth rates slowing down in recent years.

While the acceleration in growth rates has been accompanied by increase in consumption inequality as measured by the NSS consumption surveys, these admittedly are gross underestimate of the actual extent of inequality prevailing

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Gini of Consumption Expenditure (MRP) (NSS)

Rural Urban Total

The increase in inequality from NSS consumption surveys is also reflected in other measures of inequality based in NSS consumption surveys

1983 1993-94 2004-05 2009-10 2011-12

Share of Various Groups in Total National Consumption Expenditure

Bottom 20% 9.0 9.2 8.5 8.2 8.1

Bottom 40% 22.2 22.3 20.3 19.9 19.6

Top 20% 39.1 39.7 43.9 44.8 44.7

Top 10% 24.7 25.4 29.2 30.1 29.9

Ratio of Average Consumption of Various GroupsUrban top 10%/Rural bottom 10% 9.53 9.43 12.74 13.86 13.98

Urban top 10%/Urban bottom 10% 6.96 7.14 9.14 10.11 10.06

Urban top 10%/Rural bottom 40% 6.47 6.84 9.40 10.11 10.16

Estimates of Income Inequality from NSSO Consumption Surveys

Evidence of inequality from Survey data: IHDS Survey (2005)Our inequality indices on income are among the worst in the world. Income inequality based on IHDS data increased from 0.53 in 2004-05 to 0.55 in 2011-12

CES MRP EUSIHDS 

consumptionIHDS 

Income

Rural 0.28 0.27 0.36 0.49

Urban 0.36 0.36 0.38 0.48

All‐India 0.35 0.34 0.38 0.53

Gini ratio from different surveys and measures (2005)

However, consistent with the earlier trend of increasing inequality at the national level, the growth pattern across states also confirms increasing regional inequality

Source: Ahluwalia (2011)

And these continue to rise

Distribution of national income by factor shares : Only the private non farm sector has increased its share, mainly organised sector surpluses. Shares of both agriculture and the public sector have declined.

But employment shares show no growth in organised employment and a sharp decline in agricultural wage employment.

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2% 4% 17.0

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31.9

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ag‐wagesnonag wagesself‐emp agriself‐emp nonagriprivate salariesgovt salaries

Innermost:1993‐94, Second ring: 1999‐00, Third ring: 2004‐05, fourth ring: 2009‐10, Outermost: 2011‐12

The gap between organised sector salaries and self-employed/wages started at the end of 1990s and has been growing thereafter.

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ag‐wages nonag wages self‐emp agriself‐emp nonagri private salaries govt salaries

Within the organized manufacturing sector, the growth rate of income has largely been due to increase in managerial incomes. ASI data shows that the workers wages have increased much slower than managerial emoluments

ASI data also shows that the share of wages have gone down considerably with profits share in NVA increasing faster than ever

This is also confirmed from the National Accounts with profits of the organized sector increasing in the last decade

But even more worrying is the fact that this acceleration in GDP growth has also coincided with the worst phase of employment growth with employment growth slowing down to less than 0.1% per annum, the lowest in the post independence history.

Not only did the economy not create sufficient jobs, there was deterioration in quality of existing jobs. Two third of all workers in organized private sector are informal workers.

The slowdown in employment generation appears to be driven by two factors: (1) falling employment among women, partly due to increased educational attendance and also due to rising incomes; (2) falling employment in agriculture: 49 million new workers were added in non-farm sector between 2004-05 and 2011-12 whereas farm sector lost 34 million workers during the same period.

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The increase in Non-farm employment has been among the fastest in recent history. 10 percentage point increase in last 7 years. Fastest so far

For the first time, workforce in agriculture has declined in absolute numbers

But much of the new non-farm jobs are shifts from farm sector with economy not creating new jobs

Also, two third of rural employment generated between 2004-2011 is casual employment

The major driver of non-farm employment is the construction sector with manufacturing adding very little.

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Organised sector hasn’t contributed to employment generation

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Organised Employment

Public Private Total

But even within organised manufacturing, the decline of wage share for manufacturing was partly achieved by increasing the share of contract workers.

Rural areas benefitted from an acceleration in growth rate of wages. Rural real wages increased at more than 6% per annum between 2008 and 2013.

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Real Wages (Rural Men) (2004‐05 prices)

Higher premium to skill/education meant that wages of graduates and above rose faster than others even among regular workers

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Index of Wage rate of Urban Male Regular workers (1993=100)

Urban Male Illiterate Urban Male PrimaryUrban Male Secondary Urban Male Graduate

Changing employment structure has also led to increasing inequality in workers income

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Gini of Workers income

Forbes: In the last decade, corporate wealth has continued to increase faster

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% Share

Net Worth of Local Indian Billionaires (Resident) as a Share of GDP (%)

Source: Walton (2011)

But where did they make money 69 billionaires in 2010, 49 in 2009, 13 in 2004 For simplification, I have divided the sources of growth

in two categories. The first comprises the ‘rent-thick’ sectors that

essentially rely on government permits and contracts for public infrastructure. These include mining, metals, constructions, land, real estate and so on. Telecom too,

The second set consists of knowledge-based industries that rely on research and development primarily in services but also in manufacturing. The IT sector and pharmaceuticals would ideally belong to this category.

In 2004, of the 13 billionaires, two created their wealth in pharmaceuticals and two in IT; the remaining made their fortunes in rent-thick sectors.

In 2010, out of 69 billionaires, 11 created their wealth in pharmaceuticals and six in the IT. In comparison, 18 billionaires made their fortunes in construction and real estate, 15 of them in real estate alone; seven made their fortunes in commodities (metals and oil) and two in telecom. That makes 27 billionaires in rent-thick sectors.

The total wealth of the knowledge-based sectors (IT and pharmaceuticals) is $55 billion, against $132 billion in the rent-thick sectors. Services account for only 20% of the total wealth of the 66 resident Indian billionaires.

All 15 real estate billionaires in India have joined the billionaire club between 2005 and 2010. Incidentally, they have also seen the fastest rate of wealth growth. On the other hand, IT sector billionaires have among the lowest rates of wealth growth.

How do they compare internationally

Per capita income in the US is 45 times that in India at the nominal exchange rate, and almost 15 times in purchasing power parity terms.

Net wealth of the 100 richest Americans is $836 billion; that of 100 richest Indians is $300 billion.

There are eight Indians among the top 100 billionaires of the world. There are none from China.

Of the top 20 billionaires in the US, eight are from the IT sector, three from finance, five from retail and one from media. Of the remaining three, two are from engineering and only one from real estate. In other words, one billionaire out of 20 is from a rent-thick sector. Among the top 20 in India, nine are from such sectors.

How about the other billion That billion, which is still consuming less than Rs50 a day, is

slipping on international rankings in almost all measures of human development.

Our rankings on food, nutrition, gender and poverty issues in the last decade have either remained stagnant or have worsened.

India is not only home to the largest number of billionaires outside the US. It is also home to the largest number of poor, of hungry and malnourished, of child labourers, of people defecating in the open, of those without access to safe drinking water, of illiterates and so on.

India is the last country on international environment index, PISA scores, Global hunger index and so on

It is also among three countries in the world whose global hunger index has worsened

Some measures of wealth inequality based on AIDIS data. Sharp Increase in wealth inequality in last decade.

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1991 2002 2012

Gini of wealth (AIDIS data)

Total Assets Net Worth

Source: Anand and Thampi (2016)

Increasing concentration of wealth among the top. Top 1% now accounts for more than one fourth of total wealth.

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Share of Top groups in total wealth

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Source: Anand and Thampi (2016)

Disparity in asset ownership has worsened by social groups with disadvantaged groups losing out to privileged groups.

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Asset Share/Population Share by Social Groups

1991 2002 2012

Source: Anand and Thampi (2016)

Although the access to outside jobs and increase in non-farm share has also been accompanied by increasing inequality, longitudinal data from

Palanpur also shows that the Jatabs have benefited from this expansion

  Theil L Measure Gini Coefficient1957/8  0.188 0.336 1962/63  0.282 0.390 1974/5  0.169 0.253 1983/4  0.174 0.307 2008/9  0.336 0.427  

Income Inequality in Palanpur

Growing “isolation” of Jatabs has reversed since 1983/4 

Jatabs versus the rest of the village  

Overall Theil L Measure of Inequality 

ELMO Partitioning Index 

Inequality Contribution from “classic” decomposition 

1957/58  0.188 7% 3%

1962/63  0.282 10%  4%

1974/5  0.169 39%  9%

1983/4  0.174 50%  22%

2008/9  0.336 29%  12%

 

Inequality in the Giants Inequality is now centre stage in economics

(Piketty, Occupy etc) Much less known about inequality in emerging

countries But, importantly about the processes that

generate inequality and suitable policies to tackle inequality (revisiting Kuznets?)

The project aims to study inequality in emerging countries as well as industrialized countries

Going beyond the standard metrics to understand nature, dimensions and processes

India Project Hai-Anh Dang (World Bank) Chris Elbers (VU Amsterdam) Himanshu (JNU Delhi) Rinku Murgai (World Bank, Delhi Office) Abhiroop Mukhopadhyay (ISI, Delhi) Roy van der Weide (World Bank, Washington D.C.)

Lead by: Peter Lanjouw (VU Amsterdam) and Finn Tarp (WIDER, Helsinki)

What we plan to do Create a credible time series of inequality

trends in different dimensions (income, wealth, social development indicators and employment outcomes) using existing data

Profile of inequality by regions/sub-regions and by population groups including social and religious groups

combine micro data and macro data to understand processes and outcomes

Situate the findings in the overall framework of growth, poverty, mobility and exclusion