1. family and parenting
2. children

REDUCING INEQUALITY
Learning Lessons For The Post-2015 Agenda
India Case Study
1
REDUCING INEQUALITY
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2
Acknowledgements
From Thomas Chandy, Chief Executive Officer
Save the Children India
Coming at a time, when inequality is increasingly being discussed as a crucial element
to be included in the post-2015 framework of world development, this report takes a
comprehensive look at the various dimensions of social and economic inequality in India
and attempts to understand the factors responsible for it.
The successful and timely completion of this study was possible with the financial and
managerial support of Save the Children UK. I would like to express my gratitude to the
Save the Children UK team, in particular to Alison Holder, Jessica Espey, Nuria Molina
and Sara Godfrey.
I express my gratitude to Jayanti Ghosh, C.P Chandrashekhar, Amitayu Sengupta, Malini
Chakravarty, Smitha Francis, Deepanwita Dutta at Economic Research Foundation
for conducting the study with the required academic rigour and attention to detail.
At Save the Children India Office, I would like to thank Shireen Vakil Miller for giving
leadership to this project. Deepali Nath, Prasann Thatte, Shailey Hingorani and Resmi
Bhaskaran gave important inputs into the report at various stages and the Media and
Communications Team ensured its publication in a professional manner. During the
process of finalizing the report, we also received valuable feedback from a number of
external experts, including Mr. Joaquin Gonzalez-Aleman, Chief of Social Policy, Planning,
Monitoring and Evaluation at UNICEF Delhi.
I hope that this research report will provide new evidence to the civil society in India to
demand more attention and engagement of our policy-makers towards addressing the
root causes of inequality and to push for a more inclusive policy-making.
Contents
Executive Summary
6
I INTRODUCTION
11
Inequalities in India
11
Social Inequalities
12
Economic Inequalities
14
Methodology14
2 Evidences on Inequalities in India
15
Inequalities amongst Children: Gender
15
Inequalities in Income and Consumption
16
Inequalities in Calorie Intake
20
Inequalities in Health Outcome Indicators
27
Child Labour
33
Inequalities in Educational Outcomes
36
Inequalities in Acces to Some Basic Household Facilities
40
3 Understanding the Determinants of Inequalities
44
Trends in Employment and Wage Shares of Income
45
Trends in Wage Shares of Income 47
Impact of Macroeconomic Policy Choices and their Interactions
54
Impact of Social Policies on inequality
61
Liberalisation, Public Distribution System and Exclusion of the Poor
62
Health and Education
66
Health Expenditure by the Centre and States
69
The Integrated Child Development Services (ICDS)
70
Education73
Government Expenditure as share of GDP
74
Child Protection
80
4 Conclusion and Recommendations
Policy Recommendations
83
85
References88
REDUCING INEQUALITY
EXECUTIVE SUMMARY
Introduction
Rising inequality has emerged as one of the
most important problems confronting societies
across the world. Within the Asian region, South
Asia has experienced rapid increases in income/
consumption inequality during the recent period
of its rapid growth. This is quite evident in case
of India, the largest economy in the region with
over a billion people.
This study attempts to arrive at a holistic
understanding of inequalities in India and how it
affects children, recognise the factors that create
and affect the inequalities, and suggest strategies
to rectify the problem.
Inequalities in India are observed in terms of
income, health, education and other dimensions
of human development as well as between
the states, rural and urban areas and different
social groups. Besides economic factors, there
are certain sociological factors that affect
inequalities in India. This report considers the
two most prevalent social inequalities: caste and
gender. This study attempts to cover the changes
in the various parameters over time, mainly
from 1993-94 onwards till the present, in order
to get a sense of the impact of the economic
liberalisation programme that India embarked
upon in the early 1990s.
6
Evidence of
Inequality amongst
Children
The latest Census data indicates that although
there was an increase in the overall sex ratio
from 933 in 2001 to 940 in 2011, the child sex
ratio deteriorated. Among the states, the lowest
child sex ratio has been observed in the states
of Haryana (830), Punjab (846) and Jammu and
Kashmir (859).
There is evidence to suggest that the poorer
sections of India were actually further
marginalised under the neoliberal economic
regime introduced in India in the early 1990s.
Poorer states like Bihar, Uttar Pradesh and
Orissa witnessed only a marginal improvement
in terms of per capita NSDP (Net State
Domestic Product), whereas the richer states
like Gujarat, Maharashtra, etc witnessed
substantial rises. States that witnessed greater
rise in per capita NSDP during the period 199394 to 2004-05 also witnessed higher rise in
state-level Gini coefficients. This implies that the
states that experienced more ‘growth’ actually
had worsening inequalities. Significantly, within
States, the rural-urban divide worsened. Urban
consumption levels were double that of rural
consumption levels. The social factor of caste
plays a major role in determining household
Monthly Per Capita Expenditure (MPCE) levels.
The Social Category “Others” had higher
MPCEs across both rural and urban sectors in
India compared to the other categories, viz. the
Scheduled Castes (SC), Scheduled Tribes (ST)
and Other backward Classes (OBC).
Inequality is observed in terms of health
indicators as well. In 2011, the Birth Rates (CBR)
were higher (23.3) in rural areas as compared
to urban areas (17.6). Similar high levels of
differences in terms of rural-urban divide
were seen in Infant Mortality Rates as well. .In
2011, IMR for rural areas was 48 per 1000, l as
compared to 29 for urban areas. . Among the
social groups, infant mortality rates substantially
declined for the SC category over the period 93
to 2006, although they remain higher than for
any other social group.
One of the big challenges for children above
the age of 5 is the problem of child labour.
NSSO data shows that children belonging to
Scheduled Castes or Scheduled Tribes are
more likely to be engaged in ‘gainful economic
activities’ than children belonging to the Social
Category ‘Others’. There is a large section of
the population belonging to age group 5-14,
who are counted as Nowhere Children (NWC),
thus called as they are neither counted as child
labourers, nor are enrolled in any schools. It is
often argued that this section should be counted
as part of child labour as more often than not,
they are engaged in some form of work.
In education, Gross Enrollment Ratio (GER) and
Gender parity Index (GPI) show improvements
over time, even for SC and ST children. However,
school dropout rates continue to remain very
high, especially in the elementary and secondary
levels. Dropout rates at the elementary level
for girls (65.2%) were higher than that of boys
(58.2%) in 2009-10. Moreover, the dropout
rates were found to be much higher for the
disadvantaged classes (SC and ST categories).
executive summary
Per capita Calorie intake figures for 2009-10
reveal that national average for per capita calorie
intake for the rural region in 2009-10 was 2020
calories, while that for the urban region was
1946 calories. Significantly, in both cases, the
minimum calorie requirement (2400Cal in the
rural regions and 2100Cal in the urban regions)
was not met in a single state of India in 2009-10.
Tamil Nadu was the only state that witnessed
a rise in calorie intake between 1993-94 and
2009-10. While consumption expenditures in
both rural and urban regions rose, this was not
reflected in a commensurate rise in expenditure
on food. This suggests that rising costs of other
essential commodities, or services like health
and education forced the population to lower
the proportion of food expenditure, thereby
lowering calorie intake.
Rural-urban inequalities exist within the country
with regard to access to safe drinking water
and improved sanitation facilities. According to
the latest Census figures (2011), more than half
(65%) of urban India gets water within their
homes while, only 35% of the rural population
gets drinking water in their homes; again 69%
of households in rural areas are without any
sanitation facilities compared to the 19% in
urban areas.
Understanding the
Determinants of
Inequality
While there were many deep-rooted forms of
economic and social inequalities in India well
before the process of economic liberalisation,
the latter has exacerbated the problem.
The report shows that while India witnessed
rapid output growth especially from 200304 onwards, it was not manifested in rapidly
growing employment in productive sectors
or in the expansion of decent work. In fact,
income generating opportunities have been
getting severely limited for both rural and
urban households, whether headed by males
or females. More than half of all India’s workers
remain self-employed and there has been a
significant rise in casualisation of the workforce
in both rural and urban sectors. All casual and
self-employed, and a significant proportion of
7
REDUCING INEQUALITY
regular workers, are unsupported by any form of
social security.
At the same time, having employed parents
does not seem to ensure equal socio-economic
development outcomes for children even in
households with some employment, because of
the inequities in the labour market. Critically, the
unorganised sector employment accounts for
the overwhelmingly dominant share (more than
94 per cent) of all workers. However, its share
of national income has been falling sharply even
through the recent period of rapid economic
growth. As a result, the per-employee NDP of
the organised and unorganised sectors have
diverged dramatically, which accelerates sharply
from 1999-2000 onwards. Within the organised
sector, the inequalities are evidenced by the
fact that while there has been stagnation in
organised sector real wages per worker on the
one hand, there has been a dramatic increase
in non-wage salaries and incomes accruing
to persons earning profits, rents and financial
incomes on the other. The trend in real wage
stagnation in organised manufacturing can be
considered indicative of what has happened to
the incomes of a large category of households
dependent on casual, irregular and informal
work in agriculture and non-agriculture.
This labour market inequality has worsened
under deflationary macroeconomic policies..
In post-liberalisation India, while central
government expenditure as a proportion of
GDP has shown a clear declining trend, state
governments’ expenditure to GDP ratio has
stagnated, except for a brief duration in the early
2000s. Share of developmental expenditures
as proportion of total expenditure showed a
decline for both Central and State Governments
until 2004-05 after which there was a slight rise.
However, astonishingly, they are still lower than
the level of the early 1990s.
This expenditure squeeze was perhaps partly
because the period of high growth was not
sufficiently exploited to generate fiscal resources
8
for the necessary expansion in public spending.
While there was improvement in the tax-toGDP ratio on account of increased corporate
tax collections and the service tax mobilisation,
it was not because of increase in tax rates, but
due to the fact that the corporate sector has
been increasing its share of national income.
The systematic withdrawal of the State from
social welfare activities has undermined the
previous progress towards universal access
and has resulted in increased inequality and
exclusion.
In the realm of food-based interventions in
India, for instance, reduction of fiscal subsidies
and the attendant move from a universal
Public Distribution System (PDS) to a targeted
system in the 1990s has resulted in widespread
exclusion of poor and needy households
from the PDS. Moreover, the introduction of
targeting has adversely affected its functioning
and endangering the economic viability of the
PDS network, leading to a situation where the
delivery system itself has collapsed in several
states. The revival of the PDS in some states in
the last couple of years has positively impacted
access to the PDS and food security situation
in these states. However, in the official circles,
the view that the public distribution scheme
should be replaced with a system of coupons
or cash transfers has been gaining ground. This
needs further discussion as it can have severe
implications in terms of increasing inequality in
access to food, both across different segments
of the population as well as across States.
In both health and education, government
expenditure continues to be woefully
inadequate. With respect to health expenditure,
such a pattern of financing has resulted in a rise
in household expenditure on health care as a
proportion of total household consumption,
at least until 2004-05, especially in rural areas.
Low public financing and the resultant high
out-of-pocket expenditures are the two major
factors that affect equity in health financing and
Policy
Recommendations
Child Protection, which has traditionally been
a neglected area, has witnessed some increase
in Central government expenditure with the
initiation of the Integrated Child Protection
Scheme (ICPS). However, even at present the
budget allocated remains much below that
required for fulfilling the objectives of the
scheme.
• In particular, public investments in
agriculture, agricultural research and
rural infrastructure have to be increased
significantly.
One of the positive moves in the period of
liberalisation has been the initiation of the
employment guarantee programme, MGNREGA.
Studies show that MGNREGA, where successful,
has helped to reduce both economic and
social inequalities. Increased spending in the
initial period resulted in a sizeable rise in the
number of rural households getting work under
MGNREGA. However, with the economic crisis
hitting India, Central government funding for the
programme has reduced drastically. As a result,
the enormous potential of MGNERGA has to
reduce inequality is to be realized.
While mapping of inequalities are necessary,
understanding inequality outcomes necessitate
an immediate focus on process indicators.
Macroeconomic policies have a direct link to
development and reduction of inequalities, and
must be designed to encourage employment
creation directly and indirectly.
executive summary
financial risk protection. In the area of education,
even though there has been some increase in
public spending as percentage of GDP in the
last two decades, it continues to remain much
below the target set by the Report of the
Education Commission (1964-66) or even that
set by the UPA-I government in the mid-2000s.
Lack of adequate government spending on
education has given rise to processes that have
the potential to exacerbate inequality. Among
various such processes, the significant ones
relate to dilution of quality norms in education
and increasing reliance on private education
even for schooling. The increasing role of private
institutions in education has constrained access,
especially among the less well-off sections of the
population.
Some of the fiscal policy choices that reduce
inequalities are the following:
• The low level of capital expenditure has to
be increased significantly to create domestic
productive and infrastructural capacities.
• Public expenditure in the social sectors has
to increase substantially to increase both
availability and access to basic public goods
and services.
• Tax exemptions for capital gains should
be removed, both from the point of view
of reducing income and asset inequalities
and for increasing revenue mobilisation
domestically. This would also make the tax
structure significantly more progressive.
There is a need to remove the deflationary
bias of monetary policies by moving away
from a single-minded focus on interest rate
management and including financial policies that
reduce vulnerability to crisis. This would involve:
• directed credit and other ways such as
guarantees for encouraging banks to lend to
more employment-generating sectors
• a focus on financial inclusion of small
producers in informal activities;
9
REDUCING INEQUALITY
• creation of specific packages for sectors
such as agriculture and small-scale
enterprises.
• creation of specific packages for regions
identified as priority areas for addressing
regional disparity issues; etc.
• Dynamic management of capital flows to
reduce the possibility of financial booms and
busts and to ensure that current account
deficits are financed with stable and nondebt creating forms of foreign capital inflows.
Education
• Increase public funding on to at least 6 per
cent of GDP and the Union government
should shoulder the major part of the
responsibility of garnering resources to
finance RTE Act.
• Bring in measures to regulate the private
education sector.
Health
• Increase public funding to 5 per cent of GDP
and universalise basic health services.
• Spending on child health and nutrition needs
to be increased and the ANMs, AWWs
and AWHs need to be paid adequate
remuneration and their employment
regularised.
• Bring in measures to regulate the private
medical sector.
The Public Distribution System
• Expand and revamp universal PDS. Cash
transfers must be additions to public
provision, not substitutes.
• Improve domestic food supply through
measures like remunerative crop prices,
credit to small farmers, etc.
10
Water and Sanitation
• Investment should be prioritised in as much
as the regions lagging behind the most
should be targeted first.
I INTRODUCTION
Inequalities in India
Rising inequality has emerged as one of the most
important problems across the world. At the
global level, recent findings show that inequality
has been growing since the late decades of
the 20th century. Income (or consumption)
inequality has been increasing in countries
that account for more than 80% of the world’s
population. The growing gaps between the rich
and the poor raise serious questions on the
adequacy of current development models and
generate feelings of injustice. The recent UNUWIDER study finds that in most countries the
Gini index (see box 1 below) ranges from 0.35
to 0.45 percent for income inequality. In Asian
region, out of the 36 countries with available
data for the 2000s, 13 had a Gini coefficient
at or greater than 0.4 (Asian Development
Outlook 2012), while the average for the 36
countries was 0.37. Inequality has worsened
in the previous two decades in 11 of these
countries.
Within the Asian region, South Asia used to
be described as one of the less unequal in the
developing world, particularly in contrast with
Latin America and more recently with China.
However, it has experienced rapid increases
in income/consumption inequality during the
recent period of its rapid growth. This is quite
evident in case of India, the largest economy in
the region with over a billion people.
The Gini index or Gini coefficient is
a measure of inequality of income or
wealth. It is defined mathematically based
on the Lorenz curve. A Lorenz curve
plots the cumulative percentages of total
income received, against the cumulative
percentages of recipients, starting with the
poorest household. For the construction
of a Lorenz curve, first all the households
in a country are ranked by their income
level, from the poorest to the richest.
Then all of these households are divided
into deciles. Each decile represents 10%,
or one tenth, of all households and the
income of each decile is calculated and
expressed as a percentage of GDP. Next
the income shares received by these
deciles are plotted until the total of 100
per cent of the population. Joining all the
points, starting with the 0 percent share
of income received by 0 percent of the
population, the Lorenz curve is obtained
for a particular country.
The Gini index measures the area between
the Lorenz curve and a hypothetical
line of absolute equality, expressed as a
percentage of the maximum area under
the line. Thus a Gini index of 0 represents
perfect equality, while an index of 1 implies
perfect inequality. In reality, neither perfect
equality, nor perfect inequality is possible.
Thus Gini indexes are always greater than
0 but less than 1. The deeper a country’s
Lorenz curve, the less equal its income
distribution.
11
REDUCING INEQUALITY
This study attempts to arrive at a holistic
understanding of inequalities in India and how it
affects children, recognise the factors that create
and affect the inequalities, and suggest strategies
to rectify the problem.
Percentage of total income
100
80
lity
ua
60
f
eo
40
Lin
t
olu
s
ab
q
ee
20
0
0
Poorest
20
40
60
Percentage of total poulation
80
100
Richest
The Indian economy faced major challenges of
poverty and inequality even before the period
of economic liberalisation since the early 1990s.
Although the subsequent period of relatively
rapid growth has witnessed a moderate
decline in poverty, it has been associated with
substantial increases in inequalities of income
and wealth as well as in terms of access to food,
water, health care, housing and employment.
For obvious reasons, inequality is interlinked to
poverty. Excessive inequality adversely impacts
the quality of life of people leading to higher
incidence of poverty. Besides, the impacts of
inequality and poverty are very significant for
children because children experience them
differently from adults. Children have special
developmental needs for which they are
dependent on their parents or guardians, due
to which they are particularly vulnerable to
exploitation and abuse. Poverty and inequalities
hinder their chances of acquiring skills, capacities
and confidence needed to reach their full
potential. While the ill-effects of poverty may
not be permanent in adults, the consequences
of not having basic needs fulfilled could be
permanent in children. Thus, childhood poverty
can have implications for development in the
rest of the life cycle of the child and may have
cascading impact on future generations, thereby
aggravating inequality in society.
12
Inequalities in India are observed in terms of
income, health, education and other dimensions
of human development as well as between
the states, rural and urban areas and different
social groups. Besides economic factors, there
are certain sociological factors that affect
inequalities in India. This report considers the
two most prevalent social inequalities; caste and
gender, and also economic inequalities.
Social Inequalities
a. Caste
Indian society since time immemorial has been
characterised by exclusion-linked deprivation.
In India, exclusion revolves around the societal
interrelations and institutions that exclude,
discriminate, isolate, and deprive some groups
on the basis of group identities like caste and
ethnicity. The caste system in India is a complex
system of social exclusion which is unique
to Indian society. Caste- and ethnicity-based
exclusions reflect the inability of individuals and
groups like dalits1, adivasis2 to participate in and
benefit from the social, economic and political
life of the general community. The Indian society
has an official classification of four categories of
castes: the Scheduled Caste (SCs)3, Scheduled
Tribes (STs)4, Other Backward Classes (OBCs)
and others. This kind of exclusion has both
direct and indirect economic effects that
1
2
3
4
Dalits in India are the poor, deprived and socially backward
class who has been involved in a long struggle to abolish
untouchability and caste discrimination.
Adivasis are the ethnic and tribal groups claimed to be
the aboriginal population of India. They comprise a
substantial indigenous minority of the population of India.
The lowest level in the hierarchy, constitute around 16% of
the Indian population, a large percentage of who live in rural
areas and are landless agricultural labourers.
Suffer economic and social deprivation. They comprise
around 8% of India’s population. OBCs and forward castes
together comprise 76% of India’s total population
Thorat5 argues that there are three broad ways
in which caste-based exclusion works:
Through absolute denial of access in markets:
exclusion can be practised in the labour market
through denial of jobs and lower wages for the
same jobs; in the capital market through the
denial of access to capital; in the land market
through denial of sale or purchase or leasing
of land; in input markets through the denial of
sale and purchase of factor inputs as they get
lower prices for the goods that they sell; and
in consumption goods markets through the
denial of sale and purchase of commodities as
they pay higher prices for the goods that they
buy, as compared with the market price or the
price paid by other groups. For example, a study
of 565 villages in eleven Indian states (Action
Aid 2000)6 found that SC workers were denied
casual employment in agriculture in 36 per cent
of the villages. They were not allowed to sell any
goods in around one-third of the villages, and in
nearly half the villages they were not allowed to
sell milk or dairy products. They also received
lower wages for the same work in 25 per cent
of the surveyed villages.
Through differential and reduced access to
social needs supplied by the government or
public institutions, or by private institutions
in education, housing, and health, including
common property resources like water bodies,
grazing land, and other land of common use. In
more than one-third of the villages in the study
quoted above, SC people were denied access to
irrigation water for agriculture. In one-fifth of
the villages, they faced exclusion from common
property resources like grazing land and fishing
ponds.
5
6
Thorat, Caste, Social Exclusion and Poverty Linkages:
Concept, Measurement and Empirical Evidence
Action Aid, 2000, ‘Untouchability in Rural India (by
Ghanshyam Shah, Satish Deshpande, Sukhdeo Thorat,
Harsh Mander and Amita Baviskar and Research and other
Regional Staff, Delhi
Through participation in certain categories
of jobs, because of the notion of purity and
pollution of occupations, and engagements in
so-called unclean occupations. In nearly thirty
per cent of villages surveyed, SC workers were
not allowed to participate in house construction
because their normal occupations were viewed
as “unclean”.
INTRODUCTION
contribute to the form and extent of poverty
and inequality.
The disadvantages created by such forms
of social exclusion can affect income
poverty and also contribute to inequality
and multidimensional poverty7. For instance,
multidimensional poverty among the SC and
ST is alarmingly high with over two-thirds of
SC and over three-fourths of ST population
considered to be multi-dimensionally poor. The
human development indicators for the SCs and
STs in India are very low compared to the non
SC/ST categories. The Census 2001 data showed
that the literacy rate among the SCs was 54.69
per cent and that of the STs was 47.1 per cent
as against the national average of 64.84 per cent.
According to Human Development Report
(2011), the value of the Human Development
Index is 29 per cent lower for SC and 54
per cent lower for ST than the non SC/ST
communities (UNDP 2011).
b.Gender
Another form of social exclusion that is often
observed within the Indian society is gender
discrimination. Due to discriminatory systems
7
It is increasingly being realised that poverty is not
just a lack of adequate income. It is a multidimensional
phenomenon; it is the deprivation of one’s ability to live as
a free and dignified human being, with the full potential to
achieve one’s goals in life. The UN World Summit for Social
Development of 2006 described poverty as follows:
“Poverty has various manifestations, including lack of
income and productive resources sufficient to ensure
sustainable livelihoods; hunger and malnutrition; illhealth; limited or lack of access to education and other
basic services; increased morbidity and mortality from
illness; homelessness and inadequate housing; unsafe
environments; and social discrimination and exclusion. It
is also characterized by a lack of participation in decisionmaking and in civil, social and cultural life.” (Source: UN
DESA Report on the World social Situation 2010, United
Nations, New York, 2009, p.8). This is why recently there
have been efforts to develop broader concepts of poverty
that recognize its multidimensional nature and allow for
interventions that address different dimensions of poverty.
13
REDUCING INEQUALITY
based on cultural biases, it is often found that
women and girls are commonly more vulnerable
to deprivation of basic needs than men and
boys. In order to understand the nature of
gender inequalities that exist in India we need to
examine the status of women, men, gender roles
and relations in the society.
Economic Inequalities
The broader economic inequality in society
reflects in the inequalities that exist amongst
children. Children have little or no role in
the level of family income or expenditure
determinants, but have to bear the
consequences of the inequalities that exist.
Lower household consumption figures for the
poor directly translate into lower consumption
for the children belonging to these households.
Similarly, inequalities in access to basic
requirements by households (for whatever
socio-economic reasons) affect children by
denying them some of their basic needs. Thus
children are the silent victims of the inequalities
that their families face.
Methodology
This study attempts to trace inequalities by
measuring some basic parameters pertaining
to general consumption levels, food intake,
education and health. The analysis also tries
to take into account the various social
factors that determine inequalities in India.
The factors considered here are gender,
rural-urban (Sectors) divide and caste (Social
Categories). The social categories ST, SC and
OBC are special categories in India, as there
are reservations and other special provisions
for these categories as part of various types
of affirmative action in India. The category
‘Others’ is also referred to as General Category
to distinguish it from the categories that have
special reservations.
14
This study attempts to cover the changes in
the various parameters over time, mainly from
1993-94 onwards till present to get a sense of
the effect of economic liberalisation programme
that India embarked upon in the early 1990s.
These include NSSO Figures covering different
time periods (1993-94, 2004-05 and 2009-10)
which are household level statistics.
For parameters relating to health, education,
household amenities etc, different data sources
have been referred to.
Inequalities amongst
Children: Gender
The NSS 66th round reports that there are a
total of 385,565,332 individuals who are under
the age of 18 in India. Uttar Pradesh, which is
one of the largest and most populated states in
India, has the highest number of children under
the age of 18 and accounts for 20 per cent of
the total population. Bihar ranks second with
10 per cent of all children in India. It must also
be noted that both Uttar Pradesh and Bihar are
two of the poorest states in India.
Almost all states and across the different social
categories, there is a higher prevalence of male
children as compared to females. This trend is
also evident across rural and urban India.
Historically India has been exhibiting a negative
sex ratio that is unfavourable to women.
Although there have been fluctuations in the
trends since 1971, it hovered around 930
females per 1000 males. The latest Census data
Chart 1: Child sex Ratio and Overall Sex ratio in India:
1961-2011
990
980
Females per 1000 males
970
976
964
962
960
950
940
945
941
930
930
920
927
927
914
910
900
940
933
934
1961
Census Years
Source: Census 2011
1971
1981
1991
Sex ratio 0-6
2001
2011
Overall sex ratio
indicate an increase in the overall sex ratio
from 933 in 2001 to 940 in 2011. While this is a
slight but still encouraging increase, the sex ratio
for children in the age group of 0-6 years has
continued to deteriorate. Chart 1 presents the
sex ratio of the total population and the child
population (0-6 years) over the period 19612011.
Evidences on Inequalities in India
II Evidences on Inequalities
in India
Among the states, the lowest child sex ratio
has been seen in the states of Haryana (830),
Punjab (846) and Jammu and Kashmir (859). The
situation is quite distressing as sharp falls have
been reported from Jammu and Kashmir, Dadra
and Nagar Haveli, Lakshadweep, Maharashtra,
Rajasthan, Manipur, Uttarakhand, Jharkhand,
Madhya Pradesh and Nagaland during 2001-11.
Moreover, North-Eastern States like Sikkim and
Arunachal Pradesh have shown a declining trend.
This deterioration in the child sex ratio can
be decomposed into a decrease in the sex
ratio at birth (associated with the use of
technologies that enable prenatal sex selection)
and an increase in the mortality of girl children
compared with the mortality of boy children
(NFHS 3, 2005-06). It is a commonly accepted
fact that there has been a strong preference for
a boy child (0-6 years) in Indian society. Due
to this and the low status of women in many
regions in India, girl children have generally faced
discrimination. Recognising the extent of the
problem, various policy initiatives have been
adopted. The Pre-Natal Diagnostic Techniques
(Regulation and Prevention of Misuse) Act
prohibiting the use of prenatal diagnostic
techniques for the purpose of prenatal sex
determination was passed as early as 1994 in
recognition of the widespread use of ultrasound
15
REDUCING INEQUALITY
and related technologies to eliminate unwanted
female foetuses. Also, the National Population
Policy of 2000 suggested policy initiatives
directed toward ending discriminatory practices
that adversely affect the health of the girl child
(Ministry of Health and Family Welfare, 2000).
However, a shocking revelation of the NFHS
3 Survey Report raises questions about the
implementation of these laws. According to the
report, in India 24 per cent of all pregnancies
in the five years preceding NFHS-3 received
an ultrasound diagnostic testing that can help
choose or determine the sex of the foetus.
Sex ratios at birth estimated separately for
pregnancies with and without ultrasound testing
provided clear evidence that many families are
using ultrasound tests for sex selection. The
sex ratio of completed pregnancies of women
belonging to the highest wealth quintile (with an
ultrasound test) was found to be much lower
(818) than for pregnancies (with an ultrasound
to women) in any other wealth quintile (854905). This suggests that women in the highest
wealth quintile are more likely than women
in the lower wealth quintiles to be using
ultrasound tests for sex selection.
Moreover, contrary to the popular expectation
Chart 2: Sex ratios of completed pregnancies in the five
years preceding NFHS-3 with and without an ultrasound
test by wealth quintile, NFHS-3, India
Females per 1,000 males
1,000
950
955
935
923
905
900
850
954
859
911
881
854
818
800
Lowest
Second
Middle
Fourth
Highest
Wealth quintile
Ultrasound test
during pregnancy
No ultrasound test
during pregnancy
Source: Gender Equality and Women’s Empowerment in India,
NFHS-3, 2005-06
16
that education will enable women to become
aware and empowered in ways that would help
reduce the preference of a boy child, the NFHS
3 study reveals that pregnancies of women
with 10 or more years of education result in a
somewhat lower sex ratio at birth (830) than
those of women with less or no education at all
(841-878). Thus, more highly educated women
are more likely to use ultrasound techniques to
enable sex selection than less educated women.
Chart 3: Sex ratios of completed pregnancies in the five
years preceding NFHS-3 with and without an ultrasound
test by mother’s education, NFHS-3, India
Females per 1,000 males
1,050
1,000
950
900
850
800
956
943
866
841
878
830
750
None
0-9 years
10+years
Mother’s education
Ultrasound test
during pregnancy
No ultrasound test
during pregnancy
Source: Gender Equality and Women’s Empowerment in India,
NFHS-3, 2005-06
Inequalities in Income
and Consumption
It is argued that the process of economic
liberalisation in India was done on the grounds
that the resulting economic growth would help
a developing nation like India overcome its
challenges of poverty, inequality, etc. The free
market paradigm promised to provide benefits
equally to all sections of society. However, the
experience has been otherwise.
There is evidence to suggest that the poorer
sections of India were actually further
marginalised under the neoliberal economic
regime. As Chart 4 clearly shows, the states
that were comparatively richer (measured in
terms of per capita Net State Domestic Product
45000
40000
35000
30000
25000
20000
15000
10000
5000
0
Per Capita
NSDP 1993-94
Chandigarh
Goa
Delhi
Puducherry
Haryana
Maharashtra
Gujarat
Andaman &...
Punjab
Tamil Nadu
Kerala
Himachal Pradesh
Sikkim
Karnataka
Andhra Pradesh
Arunachal Pradesh
Tripura
West Bengal
Nagaland
Meghalaya
Uttarakhand
Rajasthan
Jammu & Kashmir
Jharkhand
Chhattisgarh
Manipur
Madhya Pradesh
Orissa
Assam
Uttar Pradesh
Bihar
Per Capita
NSDP 2004-05
Source: Gender Equality and Women’s Empowerment in India, NFHS-3, 2005-06
or NSDP) managed to garner a greater share
of the growth as compared to their poorer
counterparts. During the period 1993-94 to
2004-05, the inequalities between the states
actually worsened. Thus states like Bihar,
Uttar Pradesh and Orissa witnessed only a
marginal improvement in terms of per capita
NSDP, whereas the richer states like Gujarat,
Maharashtra witnessed substantial rises.
Throughout the 1980s, the per capita NSDP
in Goa was around 4.5 times that of Bihar. In
the 1990s, however, this difference increased
sharply and continuously, reaching a peak of
nearly 11 times in 1998-99. In the subsequent
and most recent decade, the ratio fell slightly
but stabilized around a high level, at an
average of nearly ten times.
Evidences on Inequalities in India
Chart 4: Per Capita Net State Domestic Products
Clearly, the economic reforms that began
in 1991 were associated with processes
that generated rising horizontal inequality,
which peaked around the close of that
decade. In the 2000s, state per capita income
divergences remained high, but did not keep
increasing.
The growing inequality between states is
better understood by studying the change
in the co-efficient of variation of per capita
real NSDP over time. The Chart below
(tracing data for 24 states) shows that there
was a marked rise during the ‘90s, which
was the initial period of the growth process
under liberalization. During the 2000s, the
differences stabilized, although at the very
high levels.
The extent of the inequality can be gauged by
comparing per capita NSDPs of the richest state (Goa)
as a proportion of per capita NSDP of the poorest
state (Bihar) over time.
Coefficient of Variation of per capita NSDP for 24 States
Ratio of Highest (Goa) to Lowest (Bihar) per capita
NSDP
60.0
12.00
55.0
10.00
50.0
8.00
45.0
6.00
40.0
4.00
35.0
2.00
30.0
SOURCE: Growing Differences in State Per capita Incomes,
C.P. Chandrasekhar and J. Ghosh, Business Line, 14 May 2012
2008-09
2009-10
2003-04
2004-05
2005-06
2006-07
2007-08
2001-02
2002-03
1999-00
2000-01
1997-98
1998-99
1995-96
1996-97
1991-92
1992-93
1993-94
1994-95
1990-91
1987-88
1988-89
1989-90
1985-86
1986-87
1981-82
1982-83
1983-84
1984-85
1980-81
2008-09
2009-10
2003-04
2004-05
2005-06
2006-07
2007-08
2001-02
2002-03
1999-00
2000-01
1997-98
1998-99
1995-96
1996-97
1991-92
1992-93
1993-94
1994-95
1987-88
1988-89
1989-90
1990-91
1985-86
1986-87
1981-82
1982-83
1983-84
1984-85
1980-81
0.00
SOURCE: Growing Differences in State Per capita Incomes,
C.P. Chandrasekhar and J. Ghosh, Business Line, 14 May 2012
17
1
18
The consumption expenditure surveys of NSSO are based
on recall periods, where the respondents are asked about
their expenditures over a certain period of time. Over time,
NSSO has adopted different reference periods to get better
estimates of expenditures. However, data based on different
reference periods over time are often incomparable. Thus,
NSSO follows the practise of reporting different forms of
MPCE, based on different reference periods. The MPCE
URP refers to MPCE based on Usual Reference Period,
which is the oldest reference period and can be most easily
used to compare with historical records.
A comparison across the major states of India
Chart 5: Change in Per Capita NSDP and Gini
Coefficients, 1993-94 to 2004-05
7000
0.45
0.4
0.35
0.3
0.25
0.2
0.15
0.1
0.05
0
6000
5000
4000
9000
2000
1000
Gujarat
Haryana
Kerala
Himachal Pradesh
Tamil Nadu
Maharashtra
Andhra Pradesh
West Bengal
Punjab
Karnataka
Orissa
Rajasthan
Jammu & Kashmir
Uttar Pradesh
Madhya Pradesh
Bihar
Assam
0
total Gini 2004 - 05
total Gini 1993 - 94
per capita NSDP change 1993-94 and 2004-05
Source: Per capita NSDP Figures from RBI Handbook of Statistics.
Gini coefficients from Vakulabharanam and Motiram (2012)
reveals that the states that witnessed greater
rise in per capita NSDP during the period
1993-94 to 2004-05 also witnessed some of the
highest rise in state level Gini coefficients. This
implies that the states that experienced more
‘growth’ actually had worsening inequalities. This
should be juxtaposed with the evidence that
many of the better performers in terms of per
capita NSDP already had higher Ginis during
1993-94 when compared to the some of the
poorer states.
Chart 6: Change in Per Capita NSDP and Gini
Coefficients, 2004-05 to 2009-10
12000
0.5
0.45
0.4
0.35
0.3
0.25
0.2
0.15
0.1
0.05
0
10000
8000
6000
4000
2000
Gini total 2004 - 05
Gini total 2009 - 10
Gujarat
Maharashtra
Haryana
Tamil Nadu
Kerala
Andhra Pradesh
Punjab
Karnataka
West Bengal
Himachal Pradesh
Orissa
Rajasthan
Madhya Pradesh
Bihar
Jammu & Kashmir
0
Uttar Pradesh
The NSSO statistics reveal that inequality was
prevalent not only between states, but within
the respective states as well.Vakulabharanam
and Motiram (2012) in their study provide
evidence that in terms of consumption
expenditures, the inequalities within the
states also worsened. Analyzing the NSSO
consumption expenditure surveys for the 50th
Round (1993-94), 61st Round (2004-05) and the
66th Round (2009-10), the authors report that
inequality has increased in both rural and urban
India. The analysis takes into consideration the
Monthly Per capita Consumption Expenditure_
Usual Reference Period (MPCE URP) as
reported by the NSSO surveys1. Inequality is
measured by the Gini Coefficient of MPCE
URP distribution as reported by the different
NSSO rounds. At a more detailed level, during
the period 1993-94 to 2004-05, urban inequality
increased for all states, whereas rural inequalities
increased for a larger number of states. During
the period 2004-05 to 2009-10, some states
witnessed slight decrease in inequalities in rural
regions, while almost all states saw a rise in
inequality in the urban regions (Chart 5).
Assam
REDUCING INEQUALITY
Per capita NSDP does not capture the
actual distribution amongst the population
as it assumes equal shares for all. The easiest
method of measuring actual distribution
is by analysing differences in consumption
expenditures, as given by the National Sample
Survey Organization (NSSO) periodic sample
survey reporting. While analysing this data, it
is important to bear in mind that household
consumption data tend to understate the extent
of inequality by underestimating the tails of the
distribution (excluding the very rich and the
very poor) and because the poor are more likely
to consume as much or even more than their
income while the rich are more able to save.
per capita NSDP change 2004-05 and 2009-10
Source: Per capita NSDP Figures from RBI Handbook of
Statistics. Gini coefficients from Vakulavaranam and Motiram
(2012)
The inequalities in consumption have been
expressed not just in spatial differences (across
states, between rural and urban areas, between
“dynamic” and “backward” regions) but also
in terms in significantly increased vertical
inequalities. Chart 7 below provides some
evidence of how the gaps between average
consumption of different categories of the
population have changed over time.
Chart 7: Average Consumption by Rural-Urban Deciles
16.00
12.30
12.00
11.38
10.45
10.33
10.00
9.14
8.00
6.96
7.14
6.00
5.68
5.06
5.63
5.94
4.00
0.00
Chart 8: Share of Rural Decile Groups in Increased Rural
Consumption between 1993-94 and 2009-10
50.0
45.0
40.0
35.0
30.0
25.0
20.0
15.0
10.0
5.0
0.0
36.4
14.6
3.0
3.8
4.6
5.5
6.2
1
2
3
4
5
7.0
6
8.5
7
10.5
8
9
10
Chart 9: Share of Urban Decile Groups in Increased
Urban Consumption between 1993-94 and 2009-10
50.0
45.0
40.0
35.0
30.0
25.0
20.0
15.0
10.0
5.0
0.0
45.0
16.4
8.4
1.6
2.3
3.3
4.6
0.9
1
2
3
4
5
11.2
6.3
6
7
8
9
10
14.32
14.00
2.00
However, even this does not give a full idea of
the increasing disparities. It is well known that
NSSO data underestimate the consumption
of the richest groups, which is also reflected
in the growing discrepancy between aggregate
consumption as emerging from the NSSO and
aggregate private final consumption expenditure
as given by the national accounts data. But even
if we examine only the increased consumption
according to the NSSO estimates, it has been
distributed very unequally. Charts 8 and 9
provide the share of the decile groups in
rural and urban areas respectively, of the total
increased consumption between 1993-94 and
2009-10.
Evidences on Inequalities in India
The rise in Ginis have been less over the period
2004-05 to 2009-10, as states with higher per
capita NSDP rise showed lower increases in
inequality. In fact, some states like West Bengal,
Punjab and Tamil Nadu show minor decreases
in Gini coefficients during this period. However,
it must be kept in mind that the two time
periods being compared are not equal. While
the period under consideration in the first case
is more than a decade, in the second case it is
barely 5 years, because of which, much of these
changes are bound to be much less compared
to the former. However, it is quite clear that the
unequal growth (in terms of per capita NSDP)
continues unabated as there is very little change
in the positions of the states in terms of their
ranking in this regard. The states that were
the poorest to start within 1993-94 continue
to have some of the lowest growth while the
richer states are benefiting more, and thus
the horizontal inequality has only continued
to widen even after two decades of economic
liberalisation.
1.50 1.62 1.91 1.96
Urban to rural
average
consumption
1983
Urban top to
bottom decile
1993-94
Rural top to
bottom decile
2004-05
Urban top to
rural bottom
decile
2009-10
Note: Price adjusted to CPI, agricultural labourers for rural and
industrial workers for urban.
They show that in rural India, more than 36
per cent of the total increased consumption
over this period of relatively high growth
was appropriated by the top ten per cent of
the population, while the bottom decile only
received 3 per cent and the bottom forty per
cent of rural households together only managed
to get slightly more than 15 per cent. In urban
areas, the inequality in consumption gains was
even worse: the top ten per cent managed
to garner 45 per cent of the total increased
19
REDUCING INEQUALITY
consumption expenditure, while the bottom
ten per cent got less than one per cent, and the
bottom forty per cent as a group only received
8 per cent of the additional consumption (all in
constant 1993-94 prices terms).
Chart 10: MPCE by Social Categories, 2009-10
3000
2500
2000
1500
1000
500
0
Rural India Mean
MPCE
Chart 11a: Per capita Calorie Intake Rural, 2009-10
Urban India Mean
MPCE
All India mean
MPCE
Source: NSSO 66th Round (Unit Level Analysis)
The social factor of caste plays a major role
in determining household MPCE levels. As is
evident from Chart 10 the Social Category
‘Others” has higher MPCEs across both rural
and urban sectors in India compared to the
other categories. It is interesting to note that
the rural urban divide in MPCEs is a very strong
factor as the MPCE level of even the SCs and
STs in the urban sector exceed the MPCE
of the social category ‘Others’ in the rural
sector. However, the presence of caste based
differentiation in even the urban sector reveals
that the socio-economic factor of caste is not
limited to the backward rural society, but is very
much present in the so called more advanced
urban society of India as well.
20
reference period for food items which obviously
give different estimates of calorie intake, as the
recall periods for some of the items are different
between the 2 schedules. Here, the findings of
Schedule 1 are reported as they are comparable
with previous rounds. Calorie intake Figures are
reported in terms of Kilo Calories (Kcal or Cal).
Punjab
Rajasthan
Haryana
Uarakhand
Orissa
Uar Pradesh
Maharashtra
Andhra Pradesh
All india
Gujarat
Assam
Kerala
Madhya Pradesh
Bihar
West Bengal
Chhasgarh
Tamil Nadu
Karnataka
Jharkhand
2223
2191
2180
2179
2126
2064
2051
2047
2020
1982
1974
1964
1939
1931
1927
1926
1925
1903
1900
0
500
1000
1500
2000
2500
3000
Table 1a: Fall in Rural Calorie Intake
Rural
States
Change in Calorie Intake
Haryana
-311
West Bengal
-284
Rajasthan
-279
Uttar Pradesh
-243
Madhya Pradesh
-225
Punjab
-195
Bihar
-184
Karnataka
-170
All India
-133
Orissa
-73
Inequalities in
Calorie Intake
Gujarat
-12
Assam
-9
Andhra Pradesh
-5
Kerala
-1
Food intake is one of the most important
measures of well being and hence forms a very
important parameter for judging standard of
living for any population. This study only takes
into account Calorie (kilo calories) intake.
The NSSO 66 round has a two Schedules of
consumption Survey for 2009-10 with different
Tamil nadu
Maharashtra
41
112
Based on Nutritional Intake in India, NSSO Report No. 540 &
405. The States of Jharkhand, Chhattisgarh and Uttarakhand
were only formed in 1999-2000 out of Bihar, Madhya Pradesh
and Uttar Pradesh respectively and hence separate estimates for
these states for the 1993-94 rounds are not available
Comparison with 1993-94 levels reveals that
barring Tamil Nadu and Maharashtra, all states
have witnessed a fall in Calorie intake in the
rural sectors. Punjab, Rajasthan and Haryana,
the top three states in terms of calorie intake in
2009-10 have witnessed some of the sharpest
falls. The national average of Calorie intake
decline of 133Cal is exceeded by most major
states. It is interesting to note that Orissa, which
is one of the poorest states, actually shows
lower than average decline in Calorie intake.
Gujarat, which has lower than average Calorie
intake levels in 2009-10 also shows lower than
average decline in Calorie intake from 1993-94.
Chart 11b: Per capita Calorie Intake Urban, 2009-10 Table
1b: Fall in Urban Calorie Intake from 1993-94
Orissa
Punjab
Jharkhand
Rajasthan
Bihar
Assam
Karnataka
Uarakhand
Gujarat
Andhra Pradesh
Tamil nadu
Chhasgarh
All india
Kerala
Harayana
Uar Pradesh
Maharashtra
Madhya Pradesh
West Bengal
2096
2062
2046
2014
2013
2003
1987
1984
1983
1975
1963
1949
1946
1941
1940
1923
1901
1854
1851
1700 1750 1800 1850 1900 1950 2000 2050 2100 2150
Table 1b: Fall in Urban Calorie Intake from 1993-94
Urban
States
Change in Calorie Intake
West Bengal
Madhya Pradesh
Haryana
Uttar Pradesh
Bihar
Rajasthan
Orissa
All India
Assam
Maharashtra
Gujarat
Karnataka
Punjab
Kerala
Andhra Pradesh
Tamil nadu
-280
-228
-200
-191
-175
-170
-165
-125
-105
-88
-44
-39
-27
-25
-17
41
Based on Nutritional Intake in India, NSSO Report No. 540 &
405.
Evidences on Inequalities in India
In the rural sector, Punjab has the highest
per capita Calorie intake of 2223 Cal while
Jharkhand had the lowest of 1900 Cal. It is
interesting to note that some of the poorer
states like Orissa and Uttar Pradesh had Calorie
intakes higher than the national average while
comparatively richer states like Gujarat and
Tamil Nadu had lower than the national average
rate of Calorie intake.
The States of Jharkhand, Chhatisgarh and Uttarakhand were only
formed in 1999-2000 out of Bihar, Madhya Pradesh and Uttar
Pradesh respectively and hence separate estimates for these
states for the 1993-94 rounds are not available
For the urban regions, Orissa shows the highest
per capita Calorie intake of 2096Cal, while
West Bengal shows the least intake of 1851 Cal.
Majority of the states rank above the national
average of 1946Cal. Interestingly, Haryana, which
has one of highest Calorie intake levels in the
rural sector, report very low Calorie intake level
in the urban Sector. In contrast, Tamil Nadu,
that showed lower than average Calorie intake
for the rural sector, shows higher than average
Calorie intake for the urban sector.
As in the rural sector, even the urban sector
shows a fall in Calorie intake compared to 199394. Tamil Nadu is an exception in this regard
and is one state that stands out from the rest as
Calorie per capita Calorie intake shows a rise in
both rural and urban sectors for this state. West
Bengal shows the maximum decline in urban
Calorie intake with a fall of 280 Cal, which is
more than double the national average decline.
It is interesting to note that for most states, the
rural Calorie intake levels are higher than urban
Calorie intake levels. This is in accordance with
Calorie requirements norms, as rural Calorie
21
REDUCING INEQUALITY
requirements are higher than urban Calorie
requirements. However, in most cases, the
minimum Calorie requirement (2400 Cal in the
rural regions and 2100 Cal in the urban regions)
is not met in any state. In 1993-94, Punjab
Haryana and Rajasthan had over 2400 Cal intake
for the rural regions while Rajasthan, Haryana
and West Bengal were some of the states that
had over 2100Cal Calorie intake for the urban
regions. However, by 2009, all states have come
under the minimum requirement levels, mainly
due to the uniform decline in Calorie intake
witnessed in India over a long period.
While per capita Calorie intake gives a general
idea of Calorie availability, the NSSO also
provides data on calorie consumption per
consumer unit, which is a better measure of
levels of nutrition. Consumer unit is a unit used
as an indicator of the energy requirement of a
group of persons of different sexes and ages.
Taking the calorie requirement of an average
male in the age group 20-39 in the rural sector
doing sedentary work as the norm, the average
Chart 11c: Rural Calorie per consumer unit per diem
Himachal Pradesh
Lakshadweep
Jammu Kashmir
Punjab
A&N Islands
Tripura
Rajasthan
Orissa
Haryana
Uarakhand
Chandigarh
Pondicherry
Uar Pradesh
Maharashtra
Andhra Pradesh
Mizoram
Kerala
All India
Gujarat
Arunachal Pradesh
Daman & Diu
Sikkim
Assam
Tamil Nadu
Madhya Pradesh
West Bengal
Karnataka
Chhasgarh
Bihar
Goa
Manipur
Jharkhand
Nagaland
Delhi
D&N Haveli
Meghalaya
3020
3005
2867
2729
2727
2724
2703
2696
2695
2675
2662
2620
2557
2547
2520
2511
2496
2489
2431
2425
2419
2417
2408
2382
2372
2362
2357
2357
2352
2350
3244
2335
2307
2261
2063
2049
0
500
1000
1500
2000
2500
3000
3500
Based on Nutritional Intake in India, NSSO Report No. 540 &
405. The States of Jharkhand, Chhatisgarh and Uttarakhand were
only formed in 1999-2000 out of Bihar, Madhya Pradesh and
Uttar Pradesh respectively and hence separate estimates for
these states for the 1993-94 rounds are not available
22
calorie requirements of males and females of
other age groups are expressed as a ratio to
this norm. Defining each household in terms of
consumer units, taking into account the age and
sex composition of the members of the family
helps give a measure of the calorie requirement
of the household. The nominal requirement for 1
consumer unit is 2700Kcal per day.
Table1c: Change in Rural calorie intake, 2009-10
State
Delhi
Lakshadweep
Haryana
Rajasthan
Meghalaya
West Bengal
Nagaland
Uttar Pradesh
Madhya Pradesh
Manipur
Daman & Diu
Jammu Kashmir
Bihar
Punjab
Karnataka
Arunachal Pradesh
All India
Mizoram
Orissa
Andhra Pradesh
Gujarat
Assam
Chandigarh
Tamil Nadu
Kerala
D&N Haveli
Goa
Himachal Pradesh
Maharashtra
Sikkim
Pondicherry
Tripura
Rural
Change in Calorie Intake
-845
-516
-414
-387
-381
-371
-360
-342
-325
-320
-302
-287
-285
-278
-218
-195
-194
-65
-44
-39
-39
2
9
35
45
75
80
104
120
136
170
374
For the rural sector, the national average of
2489 Kcal per consumer Unit is way below
the basic requirement of 2700Kcal per diem.
However, there are many states that do have per
consumer unit Calorie consumption above the
nominal requirement. Himachal Pradesh has the
highest per consumer unit Calorie consumption
of 3020 Kcal. Of the major states, Punjab and
Rajasthan have above norm Calorie intake as
well. Some of the poorer states like Orissa and
Comparison of per consumer unit Calorie
intake Figures over time (1993-94 to 2009-10)
based on the 50th and 66th Round NSS Surveys
in these years, it is seen that per consumer unit
calorie intakes have mostly fallen across the
country, with a national average of -194 Kcal.
Delhi has the maximum fall of -845Kcal, while
Tripura shows maximum rise of 374 Kcal. Some
of the better off states like Tamil Nadu and
Maharashtra have shown rise in per consumer
Calorie intakes, while for others like Gujarat and
Punjab, there have been declines. The magnitudes
of declines are much larger than the increases
in some of the states, which explain the overall
decline in the national average.
It is interesting to note that amongst the
states that in 2009-10 have above the nominal
norms of per consumer Calorie intake, barring
Himachal Pradesh, there have been declines in
per consumer Calorie intake in all these states.
Chart 11d: Urban Calorie per consumer unit per diem
2009-10
Urban
Lakshadweep
Tripura
Himachal Pradesh
Jammu Kashmir
Chandigarh
Pondicherry
Sikkim
Orissa
Mizoram
Punjab
Jharkhand
A&N Islands
Kerala
Bihar
Gujarat
Tamil Nadu
Karnataka
Andhra Pradesh
Assam
Uarakhand
Goa
Harayana
All India
Chhasgarh
Arunachal Pradesh
Uar Pradesh
Maharashtra
Manipur
West Bengal
Daman & Diu
D&N Haveli
Nagaland
Madhya Pradesh
Delhi
Meghalaya
2864
2780
2768
2757
2670
2528
2499
2471
2456
2454
2443
2435
2431
2428
2425
2420
2413
2392
2385
2385
2348
2343
2336
2326
2295
2286
2281
2276
2265
2088
1957
500
1000
1500
2000
2500
3000
State
Delhi
Arunachal Pradesh
Meghalaya
Nagaland
West Bengal
Madhya Pradesh
Uttar Pradesh
Rajasthan
A&N Islands
Bihar
Haryana
Daman & Diu
Manipur
Jammu Kashmir
Orissa
Chandigarh
All India
Mizoram
Himachal Pradesh
Assam
Maharashtra
Goa
Karnataka
Gujarat
Punjab
Andhra Pradesh
Kerala
D&N Haveli
Tamil Nadu
Sikkim
Pondicherry
Tripura
Change in Calorie Intake
-807
-639
-565
-307
-292
-291
-272
-248
-247
-224
-224
-221
-213
-193
-193
-169
-157
-151
-146
-123
-96
-66
-57
-56
-41
-30
9
28
65
161
225
292
Based on Nutritional Intake in India, NSSO Report No. 540 &
405. The States of Jharkhand, Chhatisgarh and Uttarakhand were
only formed in 1999-2000 out of Bihar, Madhya Pradesh and
Uttar Pradesh respectively and hence separate estimates for
these states for the 1993-94 rounds are not available
For the urban sector, the All India average is
2385Kcal, which too is much lower than the
nominal requirement. Lakshadweep has the
highest per consumer Calorie intake in urban
India at 2864Kcal, while Meghalaya has the
least at 1957Kcal. Fewer states have higher
than nominal requirement level per consumer
Calorie intake in the urban sector than the rural
sector, although a greater proportion of states
have above national average levels.
2665
2663
2561
2536
0
Table 1d: Change in Urban Calorie Intake
Evidences on Inequalities in India
Uttar Pradesh have above the national average
per consumer unit intake, although lower than
the nominal requirement. Some of the well off
states like Gujarat and Tamil Nadu show lower
than national average per consumer Calorie
figures in the rural areas.
3500
In the urban region, barring Maharashtra, all
the well off states have above national average
per consumer Calorie intake levels. Of the
23
REDUCING INEQUALITY
be noted that the better off states like Gujarat,
Maharashtra or Punjab show lower fall in urban
per consumer Calorie intake figures than
others.
poorer states, Bihar and Orissa have above
national average levels while Madhya Pradesh,
Chhattisgarh and Uttar Pradesh rank much
lower. The fall in the national average of urban
per consumer unit Calorie intake figures is
lower than that for the rural sector.
In terms of change from 1993-94 levels, the
All India average fell by 157Kcal for urban India.
Delhi shows the maximum fall for the urban
sector as it did for the rural sector, while Tripura
shows the maximum rise for the urban sector,
as it did for the rural sector. Barring Tamil Nadu,
none of the well off states shows a rise in urban
per consumer Calorie intakes. However, it must
These findings on calorie intake values point
towards a continuation of what has often been
referred to as the ‘calorie consumption puzzle’
of India. Average calorie intake figures in India
have been consistently falling over time despite
rises in consumption expenditure. On this issue,
contrasting viewpoints have been put forward
by different economists trying to explain the
apparent anomaly.
Chart 12: Average Per Capita Expenditures (Total And Food) Over Time
700
70
600
60
500
63.18
57.03
54.65
51.69
50
400
45.93
38.40
40
300
30
200
20
100
10
0
Average per
capita
expenditure
Average per
capita food
expenditure
Average per
capita
expenditure
1993-94
Average per
capita food
expenditure
Average per
capita
expenditure
2004-05
Average per
capita food
expenditure
0
1993-94
2009-10
2004-05
2009-10
% of consumpon on food items out of
total consumpon expenditure rural
% of consumpon on food items out of total
consumpon expenditure urban
urban
rural
Chart 12 shows while the average per capita expenditures have been rising over time (which can be
read as a rise in disposable incomes), the expenditure on food has not witnessed a commensurate
rise. As a result, the proportions of expenditure on food items out of total expenditures have been
steadily declining for both the rural and the urban sector. The rural sector continues to have a
higher proportion of total expenditure being spent on food, which is understandable given the lower
MPCE figures in rural vis-à-vis urban India.
Chart 13a: Food Expenditure as percentage of Total Expenditure, Rural
60
50
40
72.97
66.45
64.45
65.02
72.44
63.74
71.54
62.17
70.42
61.56
69.42
59.69
67.45
58.15
65.55
55.56
61.74
52.14
47.78
38.11
30
20
10
0
1 Decile 2 Decile 3 Decile 4 Decile 5 Decile 6 Decile 7 Decile 8 Decile 9 Decile 10 Decile
24
2009-10
70
1993-94
Food as % of total expenditure Rural
80
80
70.65
Food as % of total expenditure Urban
70
60
50
62.55
69.54
59.1
67.8
56.4
66.11
54.11
64.23
51.13
62.05
59.43
49.04
46.35
40
55.79
43.38
52.24
39.06 39.21
1993-94
2009-10
30
25.43
20
10
0
1 Decile 2 Decile 3 Decile 4 Decile 5 Decile 6 Decile 7 Decile 8 Decile 9 Decile 10 Decile
Based on NSSO reports over time. Proportions calculated at constant prices as reported in each round. Decile classes as reported in
each round.
Analysis of expenditure breakup by decile
classes show that the fall in food expenditure
as proportion of total expenditure has taken
place across all deciles across rural and urban
areas in India. The upper deciles of urban areas
show some of the sharpest falls, and there are
systemic falls across all decile classes.
The lower deciles of the rural sector, in 1993,
showed a rise in proportion of food expenditure
with increase in income, which shows that
the poorest segment of the rural society tried
to raise food intake levels with income rise.
However, even this segment today shows falling
proportion of food expenditures, like the urban
sector.
The commonality of the trends across both
sectors suggests that there are some common
economic factors driving this trend. The most
plausible explanation is rising costs of other
essential commodities or services like health
and education have forced the population to
lower the proportion of food expenditure,
thereby of lowering Calorie intake. In addition,
there has been the effect of the shift away from
the more calorie-intensive traditional staples
like jowar, ragi and bajra to less calorie-intensive
cereals like wheat and rice.
In terms of different categories of food items,
Shalini Gupta (2012) reports that there has
been a fall in consumption of cereals, pulses and
sugar across both rural and urban sectors in
India, with an increase in consumption of milk
and milk products. Such declines have been
particularly sharp during the period 2004-05 to
2009-10.
Evidences on Inequalities in India
Chart 13a: Food Expenditure as percentage of Total Expenditure, Rural
Cereal consumption has always been higher
in the rural sector compared to the urban
sector and still continues to be so. However,
the difference has reduced over time as the
rural sector has been experiencing a sharper
fall in cereal intake over time. Amongst cereals,
the consumption of certain traditional staples
like Jowar and Bajra (as compared to rice and
wheat) has shown considerable fall, especially in
the rural sectors. These traditional cereals were
earlier priced relatively cheaper than rice and
wheat, and formed the staples for some of the
poorest segments of community in India. The
steady decline of cereal consumption coupled
with a sharper fall in the consumption of some
of the options traditionally favoured by the poor
suggests that the consumption of the poorest
segment have been hit more drastically and
hints at the possibility of rise in absolute hunger
amongst the poorer sections of the society.
Similarly, in the case of pulses it is reported
that the urban rural gap in consumption (urban
consumption of pulses have always been higher
than rural consumption) has been increasing,
25
REDUCING INEQUALITY
as the fall in consumption in the rural sector
is much sharper than that in the urban sector.
Consumption of milk in the rural areas actually
declined during the period 1993-94 to 2004-05,
but shows a rise during the periods 2004-05 to
2009-10, while urban consumption of milk has
been always higher over the periods (Shalini
Gupta, 2012). All this indicates that rural food
consumption has been worse hit. Falls from an
already low and often critical level reiterates the
food crisis that the marginalised section of India
is facing across the country, despite economic
growth and rise in consumption expenditures.
The increases in per capita NSDPs fail to
capture the absolute pauperisation of a large
section of society. In fact, calorie availability
figuresdonotrelatedirectlywithMPCE
figuresaswell,asstateswithhigherMPCEsdo
not necessarily imply have higher per capita
calorie consumption, and increases in MPCE
within states over time also are not necessarily
associated with rises in calorie intake.
The problem of low calorie intake is linked to
the broader issue of social policies pertaining to
food security and the Public Distribution System
HUNGER INDEx FOR SELECTED STATES
States
Prevalence of Calorie
Under Nourishment
(Percent)
Proportion of
Underweight Children
Less than 5 years of Age
(Percent)
Under Five Mortality
Rate (Per 100)
Hunger
Index
Rank as Per
Punjab
11.1
24.6
5.2
13.63
1
Kerala
28.6
22.7
1.6
17.63
2
Andhra Pradesh
19.6
32.7
6.3
19.53
3
Assam
14.6
36.4
8.5
19.83
4
Haryana
15.1
39.7
5.2
20.00
5
Tamil Nadu
29.1
30.0
3.5
20.87
6
Rajasthan
14.0
40.4
8.5
20.97
7
West Bengal
18.5
38.5
5.9
20.97
8
Uttar Pradesh
14.5
42.3
9.6
22.13
9
Maharashtra
27.0
36.7
4.7
22.80
10
Karnataka
28.1
37.6
5.5
2373
11
Orissa
21.4
40.9
9.1
23.80
12
Gujarat
23.3
44.7
6.1
24.70
13
Chhattisgarh
23.3
47.6
9.0
26.63
14
Bihar
17.3
56.1
8.5
27.30
15
Jharkhand
19.6
57.1
9.3
28.67
16
Madhya Pradesh
23.4
59.8
9.4
30.87
17
India
20.0
42.5
74
23.30
SOURCE: India Human Development Report, 2011
in India, which are dealt with in detail later.
The India Human Development Report
2011 reports abysmal levels of hunger and
malnutrition in select states across India. The
lowest hunger index is above 10, which is a
26
reflectionofthemagnitudeoftheproblem.
Punjab,whichisoneofthemostaffluentstates
with a very strong agrarian basis is the rural
sector is the best performer with a Hunger
Index of 13.63. The poorer states Like Madhya
In India increased inequality is observed in
terms of health indicators as well. Although the
health indicators like Crude Birth Rate (CBR)
and Crude Death Rate (CDR) have declined
over the period for the country, large disparities
are observed within the regions of the country.
The trend in the CBR shows a slow decline
from 29.5 (1991) to 21.8 (2011). However, CBR
is higher (23.3) in rural areas as against urban
areas (17.6).
Chart 14: Crude Birth Rate: Rural, Urban, Total
70
63.18
57.03
60
54.65
51.69
50
45.93
38.40
40
30
20
10
0
1993-94
2004-05
2009-10
% of consumpon on food items out of total
consumpon expenditure urban
% of consumpon on food items out of
total consumpon expenditure rural
Source: Family Welfare Statistics in India, 2011 & SRS Bulletin,
Volume 47, No. 2
45
42.8
42.8
Chart 15: Per cent Decline in CBR, 2001-2011
40
35
30
16.8
13.4
16.8
15.8
15.8
23.6
19.3
14.5
14.5
19.3
13.2
13.2
15.3
12.1
15.3
12.1
18.7
14.8
11.9
18.7
11.2
14.8
11.9
4.6 4.6
5
5
7.4 7.4
10
6.0 6.0
15
10
14.2
20
11.2
15
14.2
20
25
00
INDIA
INDIA
Inequalities in
Health Outcome
Indicators
30
13.4
25
35
20.9
23.6
40
20.9
45
42.8
It is shocking to note that even states like
Maharashtra or Gujarat in the Western region,
which have some of highest per capita NSDP
and even higher than average MPCEs and rank
amongst the richest states in the country, have
very poor rankings in the Hunger Index. This
proves that economic growth alone cannot
resolve the problems of hunger and the
growth process that India has experienced has
often lead to very high levels poverty amongst
the population, reflecting stark inequalities.
When it comes to state-wise performance,
some of the major states still have high CBR, for
instance, Uttar Pradesh recorded the highest
CBR (27.8) in 2011 followed by Bihar (27.7),
Madhya Pradesh (26.9) and Rajasthan (26.2).
In terms of the rate of decline in CBR, Andhra
Pradesh and Assam’s achievements have been
commendable with the highest rate of decline
over the last decade 2001-2011. On the other
hand, Delhi, which is the richest state in the
country (with per capita NSDP is Rs 108,876)
has recorded a very poor rate of decline over
the last decade.
42.8
Pradesh and Chhattisgarh in the Central Zone
or Bihar and Jharkhand in the East, that show
some of the lowest lower levels of MPCE,
not surprisingly, reflect some of the highest
hunger indices. The gap between the best and
worst performer is also relatively large, which
reflects the high levels of inequality in terms of
hunger that only worsens the problem.
Evidences on Inequalities in India
Inequalities in Health
Outcome Indicators
Source: Family Welfare Statistics 2011 & SRS Bulletin,Vol. 46 no.1
27
Chart 16: CBR in Rural and Urban Regions of some of the major states of India, 2011
28.8
11.5
16.0
15.7
18.1
23.7
27.4
22.5
20.1
17.3
15.8
21.0
14.7
16.8
15.2
26.3
19.0
19.7
17.2
15.4
14.4
13.1
19.5
19.1
22.9
19.0
22.9
26.3
23.3
15
18.3
19.3
17.2
15.5
20
17.6
17.5
17.8
25
22.8
24.0
30
28.8
35
28.4
REDUCING INEQUALITY
Andhra Pradesh and Assam. In these two states,
Andhra Pradesh and Assam, higher CBR has
been reported from the urban region in 2011,
with a small gap between the rural and urban
regions.
The rural urban gap in CBR is found to be
higher in the comparatively poorer states of
Bihar (per capita NSDP in 2010-11 Rs 13,632),
Orissa (per capita NSDP in 2010-11 Rs 25,708),
Jammu and Kashmir and also West Bengal and
Madhya Pradesh; evidently the rural regions
of the states recording higher CBR, excepting
Rural
10
Urban
5
West Bengal
Uƒar Pradesh
Tamilnadu
Rajasthan
Orissa
Punjab
Maharashtra
Kerala
Madhya Pradesh
Karnataka
Jharkhand
Jammu & Kashmir
Haryana
Gujarat
Delhi
Chhasgarh
Bihar
Assam
Andhra Pradesh
INDIA
0
Source: Family Welfare Statistics 2011 & SRS Bulletin,Vol. 46 no.1
their rural counterparts (61.2 and 62.7 years
respectively). Among the states, Kerala has the
highest (74 years) overall life expectancy as
well as for males and females. It is the lowest in
Madhya Pradesh (58 years) where the female
population has lower life expectancy (57.9) than
males (58.1) (Table I in Appendix).
A significant dimension of health is life
expectancy, which has been increasing over the
years. It has increased more for females than
males. According to 2002-06 estimates, life
expectancy at birth for males was 62.6 years as
compared to 64.2 years for females. Also the
urban male (67.1 years) and urban female (70
years) have longer life spans as compared to
Chart 17: Expectation of life at birth, India and bigger States, 2002-06
80
70
60
74
63.5 64.4
58.9
61.6
69.4
67.2
64.1 66.2 65.3
58
59.6
62
66.2
60
64.9
50
40
30
20
10
0
Source: Sample Registration System Statistics, from Databook for DCH, Planning Commission, April 2012
28
In terms of rate of decline in IMR, the states
of Tamil Nadu, Maharashtra and West Bengal
have shown rapid decline since 1991 followed
60
50
58.3
54.5
45
49.6
49.3
41.1
40
32.1
36.2
61.4
54
54.9
43.4
40.6
35.3
41.2
34.2
30
25
20
10
0
Calculated from the Sample Registration System Statistics from
Databook for DCH, Planning Commission, April 2012 & SRS
Bulletin,Volume 47, No. 2, October 2012
Gujarat, which has one of the highest per capita
incomes of all major states (per capita net state
domestic product (NSDP) at constant (2004-05)
prices of Rs 52,708 in 2010-11), has only been
a moderate performer in this regard. Gujarat’s
IMR in 2011 is close to that of much poorer and
less developed Bihar despite the much higher
per capita income in that state (per capita NSDP
of Bihar in 2010-11 is Rs.13,632). The Southern
State of Kerala has shown one of the lowest
infant mortality rates historically. Its IMR has
been many times less than the Indian average.
Kerala’s performance is more creditable than
any other states as it has managed to reduce the
already low IMR even further over the period. High levels of sectoral differences in terms of
rural-urban divide exist in IMR rates in India. The
IMR is very high in rural areas (48 per 1000 live
births) as compared to urban areas (29) in 2011.
Chart 19: Infant Mortality Rate (Rural/Urban/All India),
1992-2011
90
80
70
85
69
79
60 53
50
63
48
40
40
44
38
30
29
20
10
Rural
Urban
2011
2010
2009
2008
2007
2006
2005
2004
2003
2001
2002
2000
1999
1998
1997
1996
1995
1994
0
1993
The North Eastern States, while having low
IMR rates, show some signs of worsening, with
Meghalaya, Mizoram and Nagaland showing signs
of increase. Assam in this region has very high
IMR, and some districts in Assam actually have
the highest IMR rates in the country. [Appendix:
IMR Table]
70
1992
The Central states of Chhattisgarh and Madhya
Pradesh both have very high levels of IMR. It
must be noted that in 1991, Chhattisgarh was
part of Madhya Pradesh itself. Hence the data
for 1991 for Madhya Pradesh incorporates those
for Chhattisgarh as well.
Chart 18: Percent decline in IMR over 1991-2011
Per '000 live births
In the Eastern region, Orissa shows the highest
IMR, despite making some major improvements
since 1991. The relatively better-off state of West
Bengal has had the best record in lowering IMR
in this region.
by Madhya Pradesh and Himachal Pradesh.
The relatively richer states of Gujarat and
Haryana, on the other hand, have shown slower
improvements in lowering IMR.
Evidences on Inequalities in India
One of the most important measures for
children is the basic measure of Infant Mortality
Rate (IMR). IMR denotes the number of infant
deaths (less than one year of age) per 1,000
live births. Infant and child mortality rates
reflect a country’s level of socio-economic
development and quality of life and are used
for monitoring and evaluating population
and health programmes and policies. India
has had historically high IMR. Despite major
improvements a lot remains to be done in
this area. Furthermore, there are significant
differences in IMRs across states, both in
terms of absolute levels and changes over
time. The highest IMR was reported (in 2011)
from Madhya Pradesh (59 per 1000 live births)
followed by Orissa (57), Uttar Pradesh (57) and
Assam (55), while Kerala has the lowest IMR
(12 per 1000 live births). The states that have
performed well over the period 1999-2011 are
Tamil Nadu, Maharashtra, Punjab, Karnataka and
West Bengal, all of which have shown relatively
rapid decline in IMR since 1999.
Total
Source: Sample Registration System Statistics from Databook for
DCH, Planning Commission, April 2012 & SRS Bulletin,Volume
47, No. 2, October 2012
29
REDUCING INEQUALITY
The most recent data indicate that the highest
IMR was reported from rural areas of Madhya
Pradesh (63) followed by Uttar Pradesh (60) and
Orissa (58) while Kerala recorded the lowest
rural IMR (13) in the country. Kerala had the
lowest IMR (11) in urban areas too while Uttar
Pradesh, Orissa and Chhattisgarh recorded
some of the highest IMRs in urban areas
(Source: SRS Bulletin,Volume 47, No. 2, October
2012). Some states show very large rural-urban
gaps like Rajasthan, Madhya Pradesh and Assam
and interestingly, rural IMRs remain high in
some of the relatively richer states like Gujarat,
Haryana and Delhi. It is surprising to note that
even urban IMR is high in the states of Delhi and
State expenditure in social sectors, both as a
percentage of GSDP and as a percentage of total
expenditure, has declined more than the average
decline in other comparable States and stands
below the national average pointing to a clear
shift in the priorities. (Source: Sood, Poverty
amidst Prosperity). The study also observed that
there is a decline in the usage of government
health services in both rural and urban areas of
Gujarat and a very high reliance on the private
sector. In urban areas, the decline has been quite
significant for the lowest income group. (Source:
Development Dynamics in Gujarat)
70
60
50
40
30
63
58
48 47
29 31
45
49
41
34 34
48 48
36
35
43 41
39
20
10
41
33
30
33
32
25
26
24
19
17
13
9
60
57
40
39
28 28 26
26 27
58
Rural
Urban
West Bengal
Uˆar Pradesh
Tamilnadu
Rajasthan
Punjab
Orissa
Maharashtra
Madhya Pradesh
Kerala
Karnataka
Jharkhand
Jammu & Kashmir
Haryana
Gujarat
Delhi
Chhasgarh
Bihar
Assam
Andhra Pradesh
INDIA
0
Source: SRS Statistics from Databook for DCH, Planning Commission, April 2012 & SRS Bulletin,Vol. 47, No. 2, Oct. 2012
Gujarat. In this context it is important to note
that the rapid economic growth that Gujarat
has experienced over the past decade has been
of the nature of exclusionary growth where
goals like social equality, sustainable livelihoods,
access to education and health, justice and peace
have been abandoned in the race for high-speed
growth. A recent study2 has observed that the
2
30
Poverty Amidst Prosperity: Essays on the Trajectory of
Development in Gujarat (Aakar Publication, forthcoming),
Data for some select states of IMR for 2010
(based on availability) reveal that across all states
and across regions, the IMR for females are
relatively higher. This is a clear reflection of the
gender bias that exists in India even today. The
Western states of Gujarat and Rajasthan and
Northern state of Uttar Pradesh show higher
differences than the other states. Incidentally,
states like Orissa or Madhya Pradesh, which has
historically had very high IMR in the country
Table 2: Infant Mortality Rate by Gender, 1997 and 2010
MALE
FEMALE
States
1997
2010
1997
2010
India*
70.3
46
72.2
49
Andhra Pradesh
64.2
44
62.0
47
Assam
74.4
56
77.8
60
Bihar
71.6
46
71.1
50
Delhi
29.0
29
29.2
31
Gujarat
62.2
41
62.5
47
Haryana
68.3
46
68.1
49
Karnataka
50.8
37
54.2
39
Kerala
11.5
13
12.9
14
Madhya Pradesh
Maharashtra
Odisha
98.3
49.7
94.5
62
27
60
90.0
44.7
98.1
63
after Census 2001 revealed skewed sex ratios in
the country.
Among the social groups, infant mortality rates
have substantially declined for the SC category
over the period 1992-93 and 2005-06, although
they are still higher than for other social groups.
The IMR is lower for the STs compared to the
SC category. During this period there was an
increase in the IMR among SC children in Jammu
and Kashmir (from 44.3 in 1998-99 to 62.6 in
2005-06) and Himachal Pradesh (from 43.7 in
1998-99 to 56.4 in 2005-06, and ST children in
Gujarat (from 60.3 in 1998-99 to 86 in 200506)3.
Chart 21: Social Gap in IMR for three periods, 1992-93*,
1998-99 and 2005-06
120
107.3
100
29
61
60
Punjab
48.3
33
54.2
35
Rajasthan
74.7
52
96.2
57
20
Tamil Nadu
48.0
23
57.3
24
0
Uttar Pradesh
81.3
58
90.3
63
West Bengal
59.2
29
51.0
32
A comparison in the change in IMR over the
period 1997-2010 for these select states
reveals that in some of the states (Northern
state of Uttar Pradesh and Punjab, Rajasthan
in the West, southern states of Tamil Nadu
and Karnataka and Orissa in the East) female
IMRs have reduced more than male IMRs (see
table in Appendix). The Northern states have
some of the worse sex ratios and have very
high levels of gender bias that has been sought
to be addressed through various missions and
programmes. Gender specific programmes have
been introduced all across the country especially
83 84.2
76
61.8
40
Source: SRS Bulletin, April 1999 and SRS Statistics from
Databook for DCH, Planning Commission, April 2012
90.5
82.2
80
* 1997 figure excludes data for Jammu & Kashmir due to partreceipt of returns
NOTE: SRS data for IMR by gender is available from 1997, which
is why 1997 is taken as base year for comparison.
Evidences on Inequalities in India
show lower differences, which reveals that the
problem of IMR is more endemic in these states.
However, these differences today are much
lower than in 1990s.
66.4
62.1
SC
56.6
ST
48.6
OBC
Other
1992-93*(NFHSI)
1998-99(NFHS2)
2005-06(NFHS3)
Note: * 1992-93 NFHS round did not collect data separately for
OBCs and those who are not SC, ST and OBCs.
Source: NFHS1, NFHS 2 and NFHS 3
One of the reasons for the fall in IMR may be
the increase in medical attention at the time
of live births over the period. However, data of
the Family Welfare Department (Family Welfare
Statistics in India, 2011) show that more than 31
per cent of rural women are still attended by
untrained functionaries during delivery as against
4.7 per cent of urban females.
The Under-5 mortality rate (U5MR) among the
SCs and STs has been quite high compared to
the OBCs and others. The trends in the under-5
mortality shows that the aver­age annual rate of
reduction in U5MR between 1998-99 and 200506 among SCs (4.2%) and STs (3.9%) was lower
than that among OBCs (4.8%) and the rest of
the popula­tion (4.6%) (Rama Baru et. al.)
3
India Human Development Report, 2011,
31
REDUCING INEQUALITY
Chart 22: Social Gap in Under-5 Mortality for three
periods, 1992-93*, 1998-99 and 2005-06
160
140
149.1
135.2
126.6
119.3
115.5
120
103.1
100
82.6
88.1
95.7
SC
ST
72.8
80
OBC
59.2
60
Other
40
20
0
1992-93*(NFHSI)
1998-99(NFHS2)
2005-06(NFHS3)
* 1992-93 NFHS round did not collect data separately for OBCs
and those who are not SC, ST and OBCs.
Source: NFHS1, NFHS 2 and NFHS 3
Interestingly, SCs in states like Delhi, Tamil Nadu,
Maharashtra, and West Bengal have a lower
U5MR (51.3, 48.3, 50.2 and 46.6 respectively)
as compared to the national average for upper
castes (59.2). This is also true for OBCs in Delhi,
Haryana, Himachal Pradesh, Kerala, Punjab and
Tamil Nadu, where they perform even better
than the national average for upper castes (India
Human Development Report, 2011).
Another important indicator to map health
conditions in general and particularly the
condition of women in the society is the
Maternal Mortality Rate (MMR). The Office of
the Registrar General, India provides data on
maternal mortality in India on a regular basis for
the period of three years averages. However, the
first survey in maternal mortality was conducted
in 1997 and hence the first report released
data from 1997. The performance of West
Bengal has been remarkable in reducing MMR
since 1997. The latest report (2007-09) shows
that Maharashtra again has been an achiever in
reducing the maternal mortality and has joined
Kerala to realize the MDG target of reduction
in maternal mortality in the country (chart 23).
On the other hand, Gujarat again has proved to
be a poor performer as the MMR has actually
gone up in Gujarat over the period 1997-98 to
2007-09 recording a negative rate of decline.
The states of the north western region Uttar
Pradesh, Rajasthan and Bihar still show quite
high rates of maternal mortality (Chart 24).
15.1
9.1
22.5
10.8
9.2
4.1
8.9
5.6
5.2
12.8
16.1
13.5
17.2
6.9
24.4
11.3
25.1
9.2
34.8
16.3
40
64.7
35.9
55.4
27.4
29.7
19.5
65.1
30.1
58.7
27.5
100
90
80
70
60
50
40
30
20
10
0
86.7
Chart 23: Maternal Mortality Rates 1997-98 and 2007-09
Source: Sample Registration System, Office of Registrar General, India
32
1997-98
2007-09
100
53.2
50
53.8
50.5
34.3
44.5
53.9
39.7
59.9
55.4
52
53.7
63.3
53.2
37.1
16.1
0
-50
-100
-150
-146.2
-200
Evidences on Inequalities in India
Chart 24: Per cent Drop in Maternal Mortality Rates over 1997-98 and 2007-09
Source: Sample Registration System, Office of Registrar General, India
Child Labour
One of the big challenges for children over 5
years of age in India is the problem of child
labour. Child labour is a social evil that denies
children their right to survival, development,
education, and adequate standard of living.
Children engaged in work miss out on
opportunities for developing personality, talents,
mental and physical abilities. There is also a high
level of abuse and neglect associated with this
problem. Although there is unanimity about
eradicating child labour, it is a complex and
enormous social problem that has proved to be
difficult to eradicate in India.
A major issue regarding child labour is
estimating its extent. Official statistics are
inadequate in this regard. In India, the decennial
Census and the NSSO Statistics are the only
sources for estimating child labour. The extent of
child labour has to be calculated from age-wise
distribution of workers. The narrow definitions
of the term ‘work’ and consequently ‘worker’
fail to capture the rights-based approach
required to deal with child labour. Moreover,
the differences in data definition and collection
methodology between the Census and NSS
mean that the estimates from these studies
are different. Here, we have tried to collect
evidences from different data sources to capture
the extent and nature of child labour in India.
Census 2001 reported that on one hand, there
is considerable increase in the absolute number
of child labour between 1991 and 2001 in the
states of Uttar Pradesh, Rajasthan, Jharkhand,
Chhattisgarh, Bihar, West Bengal, Haryana,
Uttaranchal, Himachal Pradesh, Punjab, Nagaland,
Assam, Meghalaya, and Delhi. On the other
hand, Maharashtra, Andhra Pradesh, Madhya
Pradesh, Tamil Nadu, Karnataka, Orissa, Gujarat
and Kerala have shown significant decline in the
number of child labor. Sikkim had the highest
Child Work Participation Rate (WPR) in the
country with 12.04 % child labourers among
total children in the age group of 5-14 years,
followed by Rajasthan 8.25 % and Himachal
Pradesh (8.14%) during 2001. The other states
having higher than the national average of 5%
WPR for children are Andhra Pradesh (7.7%),
Chhattisgarh (6.96%), Karnataka (6.91%), Madhya
33
REDUCING INEQUALITY
Pradesh (6.71%), J&K (6.62%), Arunachal Pradesh
(6.06%), Jharkhand and Assam (5.07%). (Children
in India 2012- A statistical appraisal, MOSPI).
The NSSO surveys report Age Specific Worker
Population Ratios (ASWPR) that reports the
number of persons usually employed in a
particular age-group per 1000 persons in that
age-group. The NSSO reports for it for Primary
Status and also All Workers (taking into account
Primary and Subsidiary Status workers).
Chart 25: ASWPR for age group 5-9 Years of Age
12
12
10
10
8
8
6
6
4
4
2
2
0
0
Rural male
1993-94
Rural Female
1999-2000
Urban male
2004-05
Rural male
Urban Female
1993-94
2009-10
Rural Female
Urban male
1999-2000
2004-05
Urban Female
2009-10
The Chart on the left is for Primary Status while the Chart on the right is for All Workers.
Chart 26: ASWPR for age group 10-14 Years of Age
120
100
80
60
40
20
0
Rural male
1993-94
Rural Female
1999-2000
Urban male
2004-05
Urban Female
160
140
120
100
80
60
40
20
0
Rural male
Rural Female
1993-94
1999-2000
2009-10
Urban male
2004-05
Urban Female
2009-10
The Chart on the left is for Primary Status while the Chart on the right is for All Workers.
The NSSO surveys report a steady decline in
ASWPR denoting fall in child labour in India
over time. The age group 10-14, which is the
most vulnerable age group for child labour,
shows considerable fall in both Primary Status
and All Workers Status. Unsurprisingly, child
labour is higher in rural regions than urban
regions across time. Much of rural child labour
is concentrated in the Agriculture and Allied
Activities sector as much of the rural economy
itself is predominantly agriculture based in India.
In the urban areas, All Workers category actually
reports higher figures for Females in the 0-5 age
group, a highly disturbing trend.
34
NSSO data also reveal high caste bias in
incidence of child labour as well. Children
belonging to Scheduled Tribes or Scheduled
Tribes are more likely to engage in to be
engaged in ‘gainful economic activities’ than
children belonging to the Social Category
‘Others’ (NCPCR). This is accordance with
general poverty trends between Social
Categories as discussed before, and also reflects
in terms of school dropout rates and other
educational parameters discussed later in this
report.
There are certain caveats to the NSSO statistics
that have to be kept in mind while judging
The rise in difference between Primary Status
and All Workers that takes into account
Subsidiary Status can perhaps be partially
explained by the rise in informal employment of
children. Given rise in School enrolment figures
post 2004-05, a section of children now report
primary occupation as Students while at the
same time, they are engaging in other various
form of work, that come under the subsidiary
status.
There is a large section of the population
belonging to age group 5-14, who are counted
as Nowhere Children (NWC), thus called as
they are neither counted as Child labourers,
nor are enrolled in any schools. This includes
children who are not attending school for one
reason or the other, maybe generally working
but not counted by enumerators as part of the
labour force because of the sporadic nature of
their work, or because many of the activities
they engage in are not formally counted as work.
For example, girl children who do not attend
schools because they have to look after other
children in the home are counted under this
category. The proportion of Nowhere Children
is quite significant, especially in the rural sectors.
Evidences on Inequalities in India
the trends. Firstly, given the illegality of child
labour in India, there is in any case the problem
of under reporting, as neither parents nor
employers are forthcoming about giving exact
details. Secondly, NSSO 2004-05 had shown
that overall, informal sector employment had
increased substantially in the country over
the period. The extent of self employed rose
across sectors with bare subsistence levels of
remuneration. It has been argued that the rise in
informalisation or marginalised workers in the
country has had worsening impact on children
as well. This is because of the fact that while selfemployed categories often involve the labour
inputs of entire families and children are also
involved in these efforts in varying degrees or
extent, they are often being missed by official
statistics as the latter fails to categorise them
effectively. In such a situation, the NSSO figures
have certain limitations in capturing the extent
of child labour in the country.
Chart 27: Nowhere Children as percentage of Total Child Population
40
37.4
35
32.3
29.4
30
Percentage
25.6
25
22.6
19.8
20
15
1993-4
17.5
16.7
12
11.9
10
15.1
14.5
14.2
7.9
9.7
11.1
2007-8
13
8.8
5
0
Male
Female Persons
Rural
Male
Female Persons
Urban
Male
Female Persons
Total
Source: India Human Development Report 2011, Planning Commission of India
35
REDUCING INEQUALITY
36
A Time Use Based Survey, conducted by the
Department of Statistics in 1998-99 as a pilot
project, helps throw some light in this regard.
The Survey covering 18,686 households across
6 states collected data on how people, including
children above 6 years, spend their time in
different activities, based on one day recall
period. The data showed that for children, the
most important economic activity is cattle
grazing (11.47% of boys and 10.69% of girls),
with an average of 2 to 3 hours spend daily.
The second most important activity was
collecting fuel wood, fodder, water, etc., although
a disproportionately higher percentage of girl
children (13.76%, compared to only 4.51% of
boys) were engaged in these activities. The
survey found that while 67.13% of children
engaged in educational activities and 17% in pure
economic activities, the balance 15.87% engaged
in various other activities that would qualify
as work, but is not incorporated in official
statistics which are based on System of National
Accounting (SNA) activities (i.e. activities
that are counted as ‘economic activities’
and incorporated in calculating the National
Accounts). Much of these engagements are in
extended SNA activities (not under SNA but
covered under ‘General Production Boundary,
like household maintenance, caring for siblings
and the elderly, etc) and non SNA activities.
(Indira Hirway (2002) “Understanding Children’s
Work in India: An Analysis Based on Time Use
Data”).
necessary for development is considered to
be a child labour as, more often than not, they
have to engage in activities that even if not
remunerative do qualify as some form of work.
Keeping in view these complications, it has been
argued that a better method to estimate child
labour is to estimate all those children who are
not going to school. In the Indian context, any
child not going to school can be assumed to be
engaged in either domestic work, or helping out
in the family based self employment activity or
involved in some form of remuneration based
employed activity. This is where the a holistic
rights based approach to identifying Child labour
becomes crucial; where any child who is denied
the basic rights to education and all basic means
40
Inequalities in Educational
Outcomes
Education is universally accepted as being among
the most important determinants of economic
well-being of households. Recognising the pivotal
role it plays for development and the existing
inequalities in access to education, achieving
universal primary education is an important
target of the Millennium Development Goals.
Progress in the educational attainment of
girls and women has several positive impacts
on children as well as on economic status of
a family. In India, although universalisation
of education has been quite high on the
development agenda, gender gaps in education
still remain significant. In terms of literacy and
education, India still has the largest number
of illiterate people and illiterate women. The
progress of improvement in literacy has been
very slow, as is evident from the chart below.
Chart 28: Literacy rates and Gender gap in Literacy in
India, 1971-2011
90
30
80
25
70
20
60
50
15
30
10
20
5
10
0
0
1961
1971
Male
1981
Female
1991
2001
2011
Gender Gape
Source: Census 2011
The Gross Enrolment Ratio (GER) is the ratio
between children of a specific age group in
corresponding educational institutions as a ratio
of total child population of that age. It must be
noted that GER can be above 100% because of
for girls. However, many states, especially those
in the North East show very high figures above
100% which probably reflects age related
problems there.
Chart 29a: Gross Enrolment Ratios at Primary School
stages- (I-V), Age 6-10 years
Chart 29b: Gross Enrolment Ratios at Middle School stages- (VI-VIII), Age 11-13 years
140
90
120
115.3
113.9
97.1
100
104.1
100.8
112.6
81.5
115.6
80
115.4
95.7
85.5
80
79.4
76.6
70
67.8
67.2
60
85.2
50
60
40
40
30
66.9
74.4
84.5
78.3
57.7
47
49.8
49.7
20
20
10
0
1990-91
1995-96
1999-2000
2003-04
Boys
Girls
2007-08
0
2009-10
1990-91
1995-96
1999-2000
Boys
2003-04
2007-08
Evidences on Inequalities in India
grade repetition or children of above or under
age categories being admitted in the grades for
which GER is being calculated. School enrolment
ratios show a significant increase across India
over the period 1995-96 to 2009-10, including
2009-10
Girls
Source: Planning Commission Dataset, April 2012
Historically, among the states, the Western and
the Southern parts have the best record of
around 100% GER over the time period, while
the Northern and Eastern States show signs of
improvement from comparatively lower levels
(see table in Appendix).
Chart 30: Gross Enrolment Ratio in some states
160
140
120
100
80
60
2004
40
2009
20
0
Source: Selected Educational Statistics, MHRD, 2004-05 &
2009-10,
NOTE: State-wise data is available only from 2004 given by MHRD
However, even with these data there is need
for caution in interpretation. While the “usual
status” category (which shows the response to
the question “what do you usually do over the
course of a year?”) indicates substantial increase
in education for these age groups, the daily
status and weekly status categories show much
lower participation in education, esp. among
girls. This suggests that even when children,
especially girls, are formally registered in schools
and therefore feel that is their usual activity, they
may not be attending regularly for a variety of
reasons. (Chandrasekhar & Ghosh, Women in
India: A Status Report)
If we look at the Gender Parity Index (GPI)
that measures the progress of gender equity in
terms of education, it is observed that the GPI
for India has increased over time. The figure
increased from 0.82 and 0.80 for primary and
elementary levels respectively in 1995-96 to
0.95 and 0.93 (provisional data) in 2004-05 and
finally to 1.0 and 0.97 in 2009-10. The states like
Assam, Gujarat Haryana, Meghalaya, Tamil Nadu,
Uttar Pradesh, Uttarakhand, West Bengal, Delhi,
Daman and Diu are high on GPI index (usually
more than 1) for primary level of education
which indicates that gender disparities are less
in these states and boys and girls get more or
less equal opportunities for learning.
Incidentally, the GPIs for the SCs and STs
have also increased over time. The GPI for the
SC category stood at 1.01 and 0.99 for the
37
REDUCING INEQUALITY
primary and elementary level respectively and
for ST category the figures are 0.98 and 0.96
respectively in 2009-10. GPI for the SC category
is high in the states like Andhra Pradesh, Goa,
Gujarat, Haryana, Meghalaya, Daman and Diu and
Uttar Pradesh (Statistics of School Education,
2009-2010).
One of the biggest challenges, especially for
India, is the problem of school dropouts.
Although the dropout rate over the period has
come down, the rates are still quite high for the
elementary (class I-VIII) and secondary (class
I-X) levels.
Chart 31: Dropout Rates
80.0
70.0
60.0
50.0
40.0
30.0
20.0
10.0
0.0
1992-93
Class I-V
2004-05*
2009-10
Class I-VIII
Class I-X
Poor educational facilities coupled with
economic distress often force children
to dropout of schools, mostly to look for
employment. The problem is more acute
in the rural regions where large number of
children drop out because of lack of access and
basic infrastructure of schools, for instance,
inadequate number of teachers, school is far
away, unfriendly atmosphere in school, non
availability of lady teachers and non availability
of ladies’ toilets. (Source: Sikdar & Mukherjee).
At the elementary level, the 2009-10 school
education data shows a higher rate of dropout
for girls (65.2 per cent) than that of boys
(58.2 per cent). This indicates that more girls
discontinue their education between standard
I and VIII. Household atmosphere (parents not
interested, education not considered necessary)
and domestic duties (looking after younger
siblings and to attend to other domestic chores)
have been major hindrances towards access
to educational facilities for the girl children
especially in the rural region.
Sources: Selected Educational Statistics, 2004-05, MHRD, GOI
and Statistics of School Education, 2009-2010.
Note: 2004-05 data is Provisional as only provisional data is
available in the Selected Educational Statistics, 2004-05
Chart 32a: Dropout Rates for the primary level (I-V)
50.0
45.0
40.0
35.0
30.0
25.0
20.0
15.0
10.0
5.0
0.0
43.8
46.7 45.0
Chart 32b: Dropout Rates for the elementary level (I-VIII)
70.0
60.0
65.2
58.2
61.1
50.5 51.3 50.8
50.0
31.8
25.4
29.0
30.3
27.3 28.9
40.6
40.0
30.0
20.0
10.0
0.0
1992-93
1992-93
2004-05
Boys
Girls
2004-05
2009-10
2009-10
Boys
Girls
Total
Sources: Selected Educational Statistics, 2004-05, MHRD, GOI and Statistics of School Education, 2009-2010.
Note: 2004-05 data is Provisional as only provisional data is available in the Selected Educational Statistics, 2004-05
38
44.4 42.4
Total
dropout rates for boys as well as girls, the latter
being marginally higher in some states. The
rates vary from 30-65 per cent which is quite
high compared to other parts of the country.
Moreover, the dropout rates are found to be
much higher for the disadvantaged classes (SC
and ST categories) as has been depicted by Table
3.
Table 3: Dropout Rates by social Category between 1990-91 and 2009-10
Class I-V
All
Boys
Girls
Total
Boys
Girls
Total
Boys
Girls
Total
1990-91
40.1
46.0
42.6
46.3
54.0
49.4
60.3
66.1
62.5
2004-05*
31.8
25.4
29.0
32.7
36.1
34.2
42.6
42.0
42.3
2009-10
30.3
27.3
28.9
32.7
25.3
29.3
35.2
33.7
34.5
Class I-VIII
All
Boys
Girls
Total
Boys
Girls
Total
Boys
Girls
Total
1990-91
59.1
65.1
60.9
64.3
73.2
67.8
75.7
82.2
78.6
2004-05*
50.5
51.3
50.8
55.2
60.0
57.3
65.0
67.1
65.9
2009-10
40.6
44.4
42.4
50.6
52.0
51.3
55.2
60.6
57.8
Class I-X
All
Boys
Girls
Total
Boys
Girls
Total
Boys
Girls
Total
1990-91
67.5
76.9
71.3
74.3
83.4
77.7
83.3
87.7
85.0
2004-05*
60.4
63.9
61.9
69.1
74.2
71.3
77.8
80.7
79.0
2009-10
53.4
52.0
52.8
58.5
59.7
59.0
74.71
75.85
75.21
SC
ST
SC
Evidences on Inequalities in India
Among the states of India, the dropout rates for
girls at the primary level are found to be very
high in the states like Bihar (40.9), Rajasthan
(52.1) and Uttar Pradesh (41.7) in 2009-10,
while there are some other that show negative
dropout rates for girls like Punjab (-10.67),
Goa (-4.29), Kerala (-11.02) and Chandigarh
(-18.06). The North Eastern States show higher
ST
SC
ST
Sources: Selected Educational Statistics, 2004-05, MHRD, GOI and Statistics of School Education, 2009-2010.
*Note: 2004-05 data is Provisional as only provisional data is available in the Selected Educational Statistics, 2004-05
Thus despite improvements, the dropout rates
in most states are around 40-60%, which are
very high, as almost half of registered students
do not complete their basic education in this
country. While increasing enrolment figures are
a welcome sign, unless the dropout rates can be
significantly reduced, the benefits of increasing
initial enrolment will be lost. Gender, community
and caste based differentiations put certain
sections of society at greater risk.
ASER 2011 has observed two clear trends
regarding the trends in enrolment and changes
in learning levels in case of India. One is that
private school enrolment in most states is
39
REDUCING INEQUALITY
Annual Status of Education Report 2011 (ASER)
increasing although the Right to Education Act
for free and compulsory education is in place.
Over 25% of rural India’s children go to private
schools and it is expected that the numbers
will increase in coming years as education
and wealth increase. In states of Uttarakhand,
Rajasthan, Uttar Pradesh, Maharashtra, Andhra
Pradesh, Kerala, Manipur and Meghalaya there
has been an increase of over 10 percentage
points in private school enrolment in the last
5 years. In 2011, private school enrolment is
over 35% in rural areas of Jammu &Kashmir,
Punjab, Haryana, Rajasthan, Uttar Pradesh,
Andhra Pradesh, Kerala, Nagaland, Manipur and
Meghalaya.
The second observation made by ASER is that
India’s level of learning has been declining at an
alarming rate. Trends over the last five-six years
indicate that learning levels have been gradually
dropping in most large Northern and Eastern
states while they are steady or improving slowly
in the Southern and Western states. The All
Inequalities in Access to
Some Basic Household
Facilities
Rural-urban inequalities are also observed
within the country with regard to access to safe
drinking water and improved sanitation facilities,
which are considered to be backbone of an
effective public health system.
India figure for the proportion of children in
Standard 5 able to read a Standard 2 level text
has dropped from 53.7% in 2010 to 48.2% in
2011. ASER data shows that since 2010 there
has been a significant drop in estimated reading
levels in the states of Uttarakhand, Rajasthan,
Madhya Pradesh, Chhattisgarh, Bihar, Jharkhand,
Maharashtra, Assam and Meghalaya for children
in Standard 5 who can read Standard 2 level
text. For Gujarat, Punjab and Tamil Nadu,
however, there have been some improvements
since 2010. Several states in the north-eastern
region of India also show positive change; while
for Karnataka and Andhra Pradesh the numbers
remain unchanged from last year. Also basic
arithmetic levels, as observed by the Report,
show a decline which is worrying and needs
immediate attention. (Source: Annual Status of
Education Report (Rural) 2011)
More than half (65 per cent) of urban India gets
water within their homes, while only 35 per
cent of the rural population gets drinking water
in their homes. On the other hand, 21 per cent
of urban population and 43 per cent of rural
population have to collect drinking water from
near the premises.
Chart 33: Availability of Drinking Water by Place of Residence
80
70
60
50
40
30
20
10
0
71.2
65.4
35
28.7
51.8
42.9
22.1
19.5
Within the Near the
premises premises
Rural
40
Away
25.2
2001
20.7
9.4 8.1
Within the Near the
premises premises
Urban
2011
Away
Source: Census of India 2011
are hand pumps (52 per cent), although there
has been an increase in the use of tap water
since 2001.
Chart 34: Source of Drinking Water by Place of Residence
80
68.770.6
70
60
48.9
50
40
30
51.9
30.8
24.3
22.2
20
21.4 20.8
2001
13.3
10
2011
7.7 6.2
4.5 4
2.3 2.5
0
Rural
Evidences on Inequalities in India
Tap water, as a source of drinking water, is
more common in urban areas and high income
households while in villages, the most common
Urban
Source: Census of India 2011, Note: Other sources includes river, canals, springs, tank/pond/lake
It is also observed that states with high
income have piped water as the source for
more households. For instance, 86 per cent
of households in Punjab have water within
their premises as compared with only 16 per
cent in Manipur. Members of the households
without piped water need to fetch water from
sources that are often away from their premises
or involve waiting in long queues. Most of
this burden of fetching drinking water for the
households falls on women members. In most of
the houses it is the responsibility of women to
collect water, and they may have to travel several
miles for the task. Almost 83 per cent of rural
women are engaged in this job as against 11 per
cent of males. Often the female members are
helped by children of the household and girls
under age 15 are four times as likely as male
children of the same age to fetch drinking water.
Chart 35: Persons collecting drinking water by gender/age, 2005-06
120
100
1.2
80
0.6
3.3
20.3
1.1
0.4
4.7
10.7
1.1
0.4
4.4
12.6
60
40
74.2
82.7
81
20
0
Urban
Adult Female 15+
Adult Male 15+
Rural
Female child under age 15
Total
Male child under age 15
Other
Source: NFHS- 3. Note: 0.4 per cent of households do not know the answer or data missing across all categories
41
REDUCING INEQUALITY
Sometimes multiple trips have to be made to
collect water in order to meet a household’s
minimum daily drinking water needs. The
process involves quite a lot of time. Twelve per
cent of Indian households spend an average
time of 30 minutes or longer fetching water,
which is a substantial loss of time from the
household’s quality of life and productivity. Most
urban households have drinking water on their
premises while in the rural areas, for one in
seven households, each round trip to collect
water takes at least half an hour (NFHS-3).
Chart 36: Average Time Spent in Collecting Water, 2005-06
100%
80%
6.9
11.9
14.4
22.4
36.5
43.3
60%
40%
70.2
20%
42.1
51.3
Rural
Total
0%
Urban
Water on premises
Less than 30 minutes
30 minutes or longer
Note: 0.2 per cent of households do not know the answer or data missing across all categories, Source: NFHS- 3
The proportion of the world’s population using
improved sanitation facilities has increased from
54 per cent in 1990 to 61 per cent in 2008, but
there is a vast disparity in the use of improved
sanitation between urban areas (68 per cent)
and rural areas (40 per cent) in the developing
countries. The incidence of open defecation,
the riskiest sanitation practice, declined from
25 per cent in 1990 to 17 per cent in 2008
but that still leaves 1.1 billion people practising
open defecation. (Source: Progress for Children,
UNICEF 2010). In India, only 166 million people
have gained access to improved sanitation since
1995 and very little progress has been made in
the poorest households. Equity remains elusive
in this sector and progress for the poorest
remains lagging. (Source: Progress for Children,
UNICEF 2010)
42
Chart 37: Trends in the use of sanitation facilities in India,
by household wealth quintile
100%
20
80%
64
83
95
60%
56
6
0
2
4
94
94
5
83
94
99
0
75
40%
4
20%
2
0
3
1
0%
1995 2008
Poorest 20%
4
0
0
13
6
1995 2008
Second 20%
32
17
1995 2008
Middle 20%
44
1995 2008
Fourth 20%
Source: UNICEF Progress for Children 2010, Achieving The
MDGs with Equity (Number 9, September 2010) http://www.
unicef.org/publications/files/Progress_for_Children-No.9_
EN_081710.pdf
1995 2008
Richest 20%
and 2011 show that 69 per cent of households
in rural areas are without any sanitation facilities
compared to the 19 per cent in urban areas.
Chart 38: Percentage of Households in India without any Sanitation
90
80
78.1
69.3
70
6
63.6
60
53.1
50
40
30
26.3
18.6
20
Evidences on Inequalities in India
Stark inequalities are observed between rural
and urban areas regarding use of different kinds
of toilets as well. The Census figures for 2001
10
0
2001
2011
Rural
Urban
n
Total
Source: Census 2011
In a number of Indian states, a large percentage
of the population still practise open defecation.
More than 70 per cent of population is without
any sanitation in the states of Orissa (78 per
cent), Jharkhand (78 per cent), Bihar (77 per
cent), Chhattisgarh (75 per cent) and Madhya
Pradesh (71 per cent). All three are among
India’s poorest states with sizeable population.
On the other hand, in states like Kerala and
Mizoram the figures stand at 5 per cent and
8 per cent respectively in 2011 that have
come down from 16 per cent and 11 per cent
respectively in 2001. In many states households
still have human excreta removed by manual
scavengers.
The more developed states in terms of
improved sanitation facilities are the states of
Sikkim where 75 per cent of households are
using Water Closet (flush/pour flush latrine
connected to piped sewer system or septic
tank) followed by Goa (74 per cent), Gujarat (53
per cent), the North-eastern states of Mizoram
(61 per cent), Nagaland (48 per cent) and
Manipur (47 per cent) (See table in appendix).
The inequalities in access to basic facilities like
drinking water or sanitation play a big role
in the standards of health and hygiene of the
children and can create other burdens on them.
For example, access to drinking water has a
direct connection with the extent of household
chores and unpaid work that children often
have to engage in. The issue of sanitation is
directly linked to numerous epidemics and other
forms of illnesses to which children are more
vulnerable than others. These measures also
reflect deprivation in basic standards of living
and the basic rights of children in India.
43
REDUCING INEQUALITY
44
III Understanding the
Determinants of
Inequalities
The inequalities evidenced in India are
direct results of long-term features of socioeconomic development as well as some more
recent processes. While there were many
deep-rooted forms of economic and social
inequalities in India well before the process of
economic liberalisation, the latter has certainly
exacerbated the problem.
social policies affect livelihoods as well as the
social and political situations of individuals
and households. They thus directly affect the
horizontal and vertical inequalities facing
children, who initially depend on their parents
and other adults in the household, economically,
socially, and in terms of their dignity and status
in the community.
Apart from shifting to a paradigm of private
sector-led economic growth strategy through
domestic deregulation, the launch of the
economic liberalisation policies in 1991 also
altered the terms of India’s integration with
the world economy significantly through trade
and financial liberalisation policies. Since then,
the government’s economic policymaking has
been preoccupied with raising the growth
rate of the economy, with an underlying
assumption that higher growth will translate
into higher incomes for the population. But the
distributional outcomes associated with any
economic growth trajectory (and the associated
inequalities) are determined by the volume of
employment generated, as well as by the pattern
and nature of employment. These, in turn, are
determined by the nature of the growth process
and the underlying development strategy and
associated policies. Only appropriate sets of
macroeconomic policies can promote equitable
growth that includes the creation of productive,
remunerative and satisfying employment for
individuals, which affect children’s development
prospects. Further, government services have
to help make up for the inadequacy of citizens’
primary incomes. By affecting employment,
incomes, prices and the provision of services
and essential goods like food, economic and
Therefore, apart from the growth rate of
the economy, the pattern and composition
of economic growth are key determinants of
child survival and development and so it is
crucial to look at policies designed to shape
that growth. Fiscal policies have a direct impact
on jobs because of the impact of government
expenditure as well as the indirect effects
of public investment. The state’s ability to
tax to finance its development expenditures,
constraints on government borrowing and its
impact on public expenditures, links between
government’s fiscal stance and the possibilities
for counter-cyclical macroeconomic policies and
measures1, all of these affect the developmental
activities of the government with implications
for employment generation and inequalities. The
level and structure of allocation of government’s
social expenditures and the design of the general
as well as women- and child-specific policy
measures are also linked to the development
framework and macroeconomic stance. Similarly,
1
During a recession, an expansionary macroeconomic
policy tries to increase output by relying on either an
expansionary fiscal stance (through a bigger government
deficit) or looser monetary policy (by lowering the
interest rate and easing bank credit). By contrast, during
an economic boom, a contractionary or deflationary
macro-economic policy relies on a tighter fiscal stance (by
reducing government deficits through increased taxation
and reduced expenditures) or tighter monetary policy (by
increasing interest rate and tightening bank credit).
The following sections try to explain the
inequalities described in the previous sections by
analysing the various policy level determinants.
The study covers both general macroeconomic
developments in post-liberalisation India, and
also tracks the changes brought about in social
policies during the same period. While at a level
both these factors are entwined, a separation in
analysis is necessary to understand causalities
between the various factors and how they end
up affecting inequalities.
We will first examine the nature of employment
response to economic growth and the trends in
national income shares of employees in relation
to the structural changes in the economy, as
well as the various macro policies that have
had implications for the observed inequality
outcomes.
Trends in Employment
and Wage Shares of
Income
India’s post-liberalisation economic performance
has not been one of steady or continuous
growth. Although post-liberalisation there was
an initial increase in aggregate GDP growth from
the levels attained in the 1980s,2 there was a
2
It is now widely acknowledged that the Indian economy
breached the post-independence trend growth rate of
about 3 per cent per year in the sixties and seventies to
annual rates of 5.4 per cent in the 1980s, well before the
1991 economic reforms were implemented.
six-year period of slightly subdued growth in
the second half of the 1990s. It was only from
2003-04 onwards that the economy shifted to
an 8-9 per cent growth trajectory. Meanwhile,
the evidence presented in this section suggests
that whatever moderate increase in employment
was generated during the years of high growth,
it was not manifested either in the productive
sectors or in forms that have been termed by
the ILO as ‘decent work’ of one kind or another.
As Table 4 below on the distribution of all
workers by status of employment shows,
although there was a declining trend in selfemployment in the rural sector from 1993
onwards (except for the period 1999-2000 to
2004-05), the decrease during 2004-2010 was
sharper. Further, it is very important to note that
more than half of the rural population (54%) is
still dependent on self-employment. Evidently,
this is linked to the fact that even though its
proportionate contribution to the nation’s GDP
has been reducing over time3, agriculture is the
mainstay of the rural economy. This is in addition
to the well known fact that this sector is also
characterised by underemployment, especially
disguised unemployment. But given that the
performance of the sector continues to be
rainfall-dependent, employment opportunities
in this sector are erratic. This is also reflected
in the trends in the share of casual employment
among rural workers, which has shown a steady
rise (except for the period between 1999 and
2005) and increased sharply during 2004-10.
Casual workers accounted for as much as 39
per cent of total rural employment in 2009-10.
Regular employment in the rural sector has
hovered around an abysmal 7 per cent of total
rural workers.
3
Understanding the Determinants of Inequalities
monetary policies focussed on inflation targeting
also leads to a deflationary fiscal stance and
thus impacts upon government’s productive
investments and social sector spending in a
number of ways. Trade liberalisation and financial
liberalisation also impact upon government’s
fiscal and monetary policy choices and
therefore children’s survival and development
opportunities in important ways. Thus, examining
the growth and employment implications of
macro policies that accompany economic
liberalisation becomes imperative.
In 2010-11, its contribution to GDP stood at 14.5 per cent.
45
REDUCING INEQUALITY
Table 4: Percentage Distribution of All Workers by Status
of Employment, 1993-2010
199394
19992000
200405
200910
Self-Employed
58.0
55.8
60.2
54.2
Regular
6.5
6.8
7.1
7.3
Casual
35.6
37.4
32.8
38.6
Self-Employed
42.3
42.2
45.4
41.1
Regular
39.4
40.0
39.5
41.4
Casual
18.3
17.7
15.0
17.5
Years
Rural
Urban
Source: DGET (2011), Based on various NSSO Rounds
When it comes to the urban sector too, the
share of the self-employed category shows a
slight declining trend (except during 1999-2005),
which became sharper between 2004 and 2010.
On the other hand, the share of regular workers,
after stagnating at around 40 per cent of total
urban employment since 1993, showed a two
percentage increase during the period 2004-05
and 2009-10. In 2009-10, the self-employed and
regular employed workers accounted for equal
(41 per cent) shares in total urban employment.
However, the share of casualisation, which was
showing a declining trend between 1993 and
2005, increased by nearly 3 percentage points to
18 per cent of urban employment in 2009-10.
While there was a significant pick-up in the
rates of growth of employment between the
55th and 61st NSSO Rounds relating to 19992000 and 2004-05 (NSSO, 2001 and 2006),4 the
subsequent years of high growth witnessed a
dramatic deceleration in the rate of employment
generation. As seen in Chart below, total
employment growth (on the basis of usual
principal status activity) decelerated from an
annual rate of around 2.7 per cent in the fiveyear period between 1999-2000 and 2004-05 to
4
46
Ironically, this period includes the phase of moderate
growth rates mentioned earlier.
only 0.8 per cent in the period between 200405 and 2009-10 (Chandrasekhar and Ghosh,
2011a). Net employment growth during the
period 2004-05 to 2009-10 on usual principal
and subsidiary status (UPSS) taken together
was even lower at just 0.28 per cent per annum
(DGET, 2011).
This slowdown in employment generation
during the rapid growth period is evident across
both rural and urban areas. This decline in the
generation of employment opportunities at least
partly explains the rising inequalities evidenced
in India despite high economic growth. Further,
given that the rate of employment growth
was already lower in rural India, the nearly
stagnant rural sector employment generation
(0.42 per cent) would have contributed to
severe economic and social stress in the rural
households and explains the growing rural-urban
(income and consumption) inequalities.
Chart 39: Rates of Growth of Employment (Usual
Principal Status Activity, 15+ group, annual compound
rates %)
5.00
4.00
4.00
3.00
3.14
2.66
2.49
2.00
1.00
2.21
1.92
1.70
0.83
1999-2000 to 2004-05
2004-05 to 2009-10
0.42
0.00
-1.00
-2.00
Total
Male
Rural
Female
Urban
-1.72
-3.00
Source: Chandrasekhar and Ghosh (2011a)
The abysmal growth in employment during
the period 2004-05 to 2009-10 was mainly
on account of the fall in female employment.
Growth rate in female employment, which
was 3.14% between 1999-2000 and 2004-05
actually turned negative (-1.72%) for the latter
period. The biggest element of the decline in
female employment related to women’s selfemployment5 (Chandrasekhar and Ghosh,
2011a). However, self-employment has also fallen
for rural male workers. Further, self-employment
5
Self-employment among rural females showed a decline of
more than 20 per cent compared to 2004-05.
It is important to note that even as regular
employment in rural India has been largely
stagnant during the period between 2004-05
and 2009-10, the increase in employment has
been in casual work for both rural male and
female workers, though it was especially marked
for men. As of 2009-10, 40% of rural women
workers were employed as casual workers
(compared to 39.6% in 2004-05), while the same
share for urban female workers was around 20%
(compared to 16.7% in 2004-05).
On the other hand, the increase in regular
employment has been marginal for both
categories. But notably, in 2004-05, when the
urban female regular employment figures were
higher at 35.6%, the largest increase had come in
the form of domestic help, which is not the most
desirable form of employment (Chandrasekhar
and Ghosh, 2011a). Again, for both males and
females, casual employment has increased to a
greater extent.
Thus while there is a decline in self employment
in the period between 2004 and 2010, even
when seen against the back drop of longer
term trends, more than half of all India’s
workers continue to remain self-employed.
Simultaneously, there has been a significant rise
in casualisation of the workforce (in both rural
and urban sectors) and only some improvement
in regular employment. Both casual and selfemployed are unsupported by any form of
social security. Evidently, the rapid economic
growth trajectory followed by India has not
generated a commensurate rise in decent work
opportunities for the population. While females
have had to face the worst brunt, even male
employment shows quite a sharp deceleration
during the high growth period between 2004-05
and 2009-10.
In general, income generating opportunities have
been getting severely limited for both rural and
urban households, whether headed by males
or females. This would have extremely adverse
distributional and social welfare implications
with attendant negative impacts on children’s
survival and development.
On the other hand, while open unemployment
is not very significant, the fact of having
employed parents does not seem to have been
guarantee against inequalising economic and
social development outcomes for children even
in households with any kind of employment,
because of the inequities in the labour market.
Trends in Wage Shares
of Income
The apparent disconnect between output
growth and employment generation can be
related to the changes in production structure
across sectors and within sectors in the
economy (Ghosh, 2011). These structural
changes get reflected in the changes in factor
shares (or incomes accruing to different factors
of production). Factor shares are arrived at by
looking at the share of national income received
by employers, workers, those receiving “mixed
incomes” (usually because of self-employment),
and those receiving incomes from financial
investments (including interest, rent, etc).6
Understanding the Determinants of Inequalities
has decreased for both men and women in
urban India too.
The implications of aggregate income growth
for the conditions of workers, self-employed
and casual persons can be estimated at one level
from the break-up of national income between
the organised and the unorganised (or informal)
sectors. Even as unorganised sector employment
accounts for the overwhelmingly dominant
share (> 94 per cent) of all workers, its share
of national income (or NDP) has been falling
sharply even through the recent period of rapid
economic growth (see Chart 40).
6
Thus factor shares give us another way of looking at
income distribution in an economy. See Ghosh and
Chandrasekhar (2012).
47
REDUCING INEQUALITY
Chart 40: Share of Unorganised sector in National Income, 1980-2010
70.0
650.0
68.0
550.0
66.0
450.0
64.0
62.0
350.0
60.0
250.0
58.0
150.0
56.0
50.0
Index of real NNP (left axis)
2009-10
2008-09
2007-08
2005-06
2006-07
2003-04
2004-05
2002-03
2001-02
2000-01
1999-00
1998-99
1997-98
1996-97
1995-96
1994-95
1993-94
1992-93
1991-92
1990-91
1989-90
1988-89
1987-88
1986-87
1985-86
1984-85
1983-84
1982-83
1981-82
1980-81
54.0
Share of unorganised to total NDP (%)
Source: Chandrasekhar and Ghosh (2012).
The organised sector consists of the public
sector as well as the registered private sector
with more than 10 employees. It is important
to note that subsequent to the adoption of
liberalisation and privatisation policies (and
the divestment of shares in public sector
undertakings), public sector’s share in aggregate
output (NDP) and in total organised sector
output declined between 1990-91 and 2007-08
– from a fourth to a fifth, and from 64 per cent
to 45 per cent, respectively (Majumdar 2012b).
On the other hand, the private corporate
sector’s share in aggregate output, which had
steadily stayed below 15 per cent till 1991,
increased to nearly a quarter by 2007-08.
Data from the Directorate General of
Employment and Training (DGET) shows that
there has been a persistent decline in public
organised manufacturing sector employment
too.7 As a result, the overall increase in total
organised manufacturing employment has been
marginal, even though there has been some
recovery in employment in the private organised
manufacturing sector between 2004 and 2007
(Chandrasekhar, 2011c).
7
48
The figures available from the Annual Survey of Industries
(ASI) suggest that there has been no absolute decline in
employment between the mid-1990s and the mid-2000s.
See Chandrasekhar, 2011c for a detailed discussion.
But while the private corporate sector has
grown faster than the rest of the economy
and played the leading role in driving Indian
growth, there have been significant inter-sectoral
changes (which also have impacted the nature
of India’s employment growth). Since the mid1990s, services and construction have shown a
marked tendency to leave behind the agriculture
and industrial sectors (Majumdar, 2012b). As the
Table shows, nearly the entire increase in the
private corporate sector’s share in aggregate
output has been on account of the expansion in
services and construction.
Table 5: Role of Industry and Services in the Growth of
GDP, at 2004-05 prices
Growth Rate (per cent per
annum)
Contribution
to Increase in
GDP, 1990-91
to 2010-11
(percentage
shares)
199091 to
199697
199798 to
200203
200304 to
200708
200809 to
201011
Industry
excluding
Construction
7.38
4.37
8.96
6.83
19.71
Services and
Construction
6.47
7.82
9.95
9.58
71.61
Sector
Source: Majumdar (2012a)
These structural changes are also reflected in sectoral
distribution of workers since 1993.
Primary
Secondary
Construction
Chart 42: Trends in Organised and Unorganised Sector
NDP per Employee, 1983-2010
(At constant 2004-05 prices)
Tertiary
70
60
7,00,000
% of workers
50
Unorganised sector NDP per Employee (Rs)
40
5,90,766
6,00,000
Organised sector NDP per Employee (Rs)
30
5,00,000
20
4,20,505
10
4,00,000
0
1993-94
1999-2000
2004-05
2009-10
Note: Share of employment is estimated based on UPSS workers
from various NSSO Rounds.
Source: DGET, 2011.
2,83,851
3,00,000
1,81,488
2,00,000
1,11,826
1,00,000
20,617
At the same time, the chart below shows that
in the post-liberalisation period, the trends
in per-employee NDP of the organised and
unorganised sectors have diverged dramatically,
which accelerates sharply from 1999-2000
onwards. Organised sector NDP per employee,
which was already 6 times the unorganised
sector NDP per employee in 1988, increased
to nearly 11 times by 2004-05. Despite a rise
in unorganised sector NDP per employee
subsequently, it was still lower than the
organised sector NDP per employee by about
11 times in 2009-10.
23,649
27,718
36,507
39,202
56,042
0
1983
In 2009-10, the contribution of agriculture to
total employment declined by about 5 per cent
as compared to that in 2004-05 and the share
of the manufacturing sector also registered
a slight decline; it was tertiary sector and
construction that showed an increase. The major
increase in the sectoral share of employment
in 2009-10 was registered in construction,
followed by financing and real estate. The
categories of hotels, restaurants and trade, as
well as public administration and community
services registered a marginal increase in their
share in 2009-10, as did transport, storage and
communication.
1,38,812
1988
1994
1999 - 2000
2004 -05
2009-10
Note: Per-employee organised and unorganised sector NDP
values have been obtained by dividing the respective sectoral
NDP at factor costs (at constant 2004-05 prices) by the number
of workers in that sector. (Source: RBI Handbook, CSO and
DGET).
While the per-employee NDP values have
increased for both the organised and
unorganised sectors, the performance of
the share of NDP components captures the
distributional inequalities within the organised
sector itself. Data calculated from the CSO’s
statistics on factor incomes (current price
variables) shows that in terms of overall NDP,
there has been a slight and slightly uneven
decline in the share of compensation of
employees.
Understanding the Determinants of Inequalities
Chart 41: Percentage Share of Employment in Different
Sectors across Different Years*
Even as the organised sector’s share in total
NDP steadily went up from about 35 per cent
in the 1980s to 42 per cent during the period
between 2002-03 and 2009-10 (see chart
below), the share of compensation of employees
in total NDP declined from an average of 39 per
cent in the period 1991-92 to 2001-02 to about
34 per cent during the period between 200203 and 2009-10 (Chandrasekhar and Ghosh,
2012). As the chart below shows, the decline of
compensation of employees within organised
sector NDP was much sharper, with the share
falling from 71 per cent in 1990-91 to about
51 per cent in 2009-10. On the other hand, the
share of surplus/profits increased from 29 per
cent in the 1980s to nearly 49 per cent by 200910.
49
REDUCING INEQUALITY
Chart 43: Factor Shares in Net Domestic Product (NDP), 1980-2010
1991--92 to 2001-02
1980-81 to 1990-91
20 02-03 to 2009-10
48.8
50.0
42. 1
45.0
34.6
40.0
39..4
38.0
39.4
37.9
34.3
29.0
35.0
30.0
25.0
20.0
15.0
10.0
5.0
0.0
Organised sector to total ND
DP
Compensati on
o of employees to
o
to
otal NDP
Share of surpl us to organised
NDP
Source: Based on Chandrasekhar and Ghosh (2012)
shows a marginal rising trend from around 2001
onwards, in 2007-08, this share was still lower
than that in 1990-91 (Majumdar, 2012).
There is also evidence that even though the
share of compensation of employees in the
private organised sector in aggregate NDP
Chart 44: Share of Private Organised NDP and its Components in Aggregate NDP (1999-00 base year series)
25.00
23.44
20.00
18.56
16.62
16.22
15.00
14.07
11.96
10.40
10.00
7.72
5.82
6.82
6.61
5.00
0.00
Pvt Org Compensation of Employees
Pvt Org Operating Surplus
Pvt Org NDP
Source: Majumdar (2012a)
Given that compensation of employees includes
wages as well as salaries, its share depends
on both the levels of these two as well as
labour productivity. It would be true that some
50
categories of private corporate sector white
collar employees in both manufacturing and
services sectors have certainly experienced
exceptional gains in salaries during the period
interest and wages rose only marginally over a
long period, the increase in emoluments, which
include managerial salaries, was substantial
(Chandrasekhar and Ghosh, 2012).
Chart 45: Components of Net Value Added, 1981-2010
35000000
30000000
25000000
Emoluments
Rent
Interest
Profits
Wages
to workers
20000000
15000000
10000000
0
1980-81
1981-82
1982-83
1983-84
1984-85
1985-86
1986-87
1987-88
1988-89
1989-90
1990-91
1991-92
1992-93
1993-94
1994-95
1995-96
1996-97
1997-98
1998-99
1999-00
2000-01
2001-02
2002-03
2003-04
2004-05
2005-06
2006-07
2007-08
2008-09
2009-10
Rs. Lakh
5000000
Understanding the Determinants of Inequalities
of liberalisation (Chandrasekhar 2011; and
Majumdar 2012a and 2012b). This is reflected in
the trends in Chart below, which depicts trends
in the different components of net value added.
As observed, even as the nominal value of rent,
Source: Chandrasekhar and Ghosh (2012), ‘Of Profits and Growth’
But this is not true of wages. The average
real wage paid per worker employed in the
organized sector, calculated by adjusting
for inflation as measured by the Consumer
Price Index for Industrial Workers [CPI(IW)
with 1982 as base], rose from Rs. 8467 a
year in 1981-82 to Rs. 10777 in 1989-90 and
then fluctuated around that level till 200910 (Chandrasekhar and Ghosh, 2012). The
stagnation in real wages after liberalisation
meant that the share of the wage bill in net value
added, which stood at more than 30 per cent
through the 1980s, declined drastically to 11.6
per cent by 2009-10. This is despite the fact that
labour productivity, as measured by net output
per worker adjusted for inflation, registered
a close to five-fold increase over the 30-year
period beginning 1981-82.8
This is related to the fact that since the early
1990s, when liberalisation permitted much
freer import of technology and equipment
from abroad and opened the doors to
broader range of foreign investment flows
than earlier, organised manufacturing has been
able to expand and modernise using imported
technologies. This has been abetted by a
continuous liberalisation of the regulations
relating to foreign direct investment (FDI)
inflows and terms of operation of foreign direct
investment companies since the 1991 Industrial
Policy Act, which accelerated from around the
mid-2000s (Francis, 2011). At the same time,
there has also been a reduction or dismantling
8
Net value added (or the excess of output values over input
costs and depreciation) per employed worker measured in
constant 2004-05 prices, rose from a little over Rs. 1 lakh
to more than Rs. 5 lakh (Chandrasekhar, 2011). Meanwhile,
the organised manufacturing sector has witnessed a sharp
rise in the capital-output ratio, reversing the trend observed
in the 1980s (Majumdar, 2012b).
51
REDUCING INEQUALITY
deficit vis-a-vis all its major regional partners
shows a drastic deterioration in the period of
high growth. This reflects the growing import
dependence of manufacturing sector growth
and clearly points to the interplay between
continuing market failures and the trade and
investment liberalisation that has been carried
out in the last two decades in the absence of
coordinated industrial and trade policy support
(Francis and Kallummal, 2011).
Chart 46: Region-wise Trends in India’s Trade Balance,
2001-2012 (US$ Millions)
4000
2000
0
-2000
Mar-Apr 2011
Mar-Apr 2010
Mar-Apr 2009
Mar-Apr 2008
Mar-Apr 2007
52
Indigenisation or ‘local content’ policies are used to
mandate the local sourcing of a specific proportion of
inputs used in manufacturing, in order to help establish
effective forward and backward linkages in the economy.
In coordination with import controls, the former allow
domestically grounded industrial development which is
more employment generating and sustainable from both
supply and demand sides.
Mar-Apr 2006
9
Mar-Apr 2005
Thus the post-liberalisation period has
been marked by a clear and decisive trend
of worsening of India’s trade deficit, where
as an adverse movement in the current
account situation was kept in check by the
large invisibles surplus on account of services
exports and remittances. Indeed, India’s trade
Mar-Apr 2004
-8000
But even as liberalisation of imports and other
restrictions has led to greater productivity
growth and while India’s export to GDP
ratio has increased significantly, as argued by
Chaudhuri (2010), the sharp increase in Indian
imports and the slowdown in the export growth
of advanced technology products since 2001
would point to a lack of dynamic industrial
competitiveness and a failure to develop new
industries. This is supported by the available
evidence on India’s technological lag and absence
of broad-based industrial growth (Alessandrini
et al, 2009; Chandrasekhar and Ghosh, 2008
and 2011; Joseph and Reddy (2010); etc. among
others).
Mar-Apr 2003
-6000
Mar-Apr 2002
-4000
Mar-Apr 2001
of a plethora of industrial policy instruments
in India, which had been used to help improve
domestic manufacturing capabilities and
create the conditions for the development of
technologies in the post-independence decades.
Apart from import protection and a regulated
FDI policy, coordination of plans/strategies,
public sector manufacturing, directed credit,
etc., these included small-scale industrial policy,
patent protection, strong indigenisation policies,9
controls on imports of final products as well
as intermediates and components, etc. These
were successful in a broad range of industries,
and particularly in textiles and garments,
pharmaceuticals, automobiles, iron and steel and
other metal-based industries, light and heavy
electrical machineries, etc.
-10000
-12000
-14000
-16000
Europe
Africa
America
CIS & Baltics
Unspecified Region
Total Trade balance
Source: Department of Commerce
This import-dependent and capital-intensive
nature of industrial growth explains why the
private organised sector’s rapid growth has
not been accompanied by sufficient additional
employment to compensate for the decline in
public sector employment, as mentioned earlier.
At the same time, there is a clear rise in the
share of profits. The ratio of profits to net value
added, which has been on a rising trend, soared
after 2002-03, and reached a peak of 61.8 per
cent in 2007-08 (Chandrasekhar and Ghosh,
2012).
That is, in the period of rapid growth, while that
growth has been focussed on the organised
sector in aggregate income (NDP) terms (while
not in employment), there has been stagnation
in organised sector real wages per worker on
the one hand and a dramatic increase in nonwage salaries and incomes (accruing to persons
earning profits, rents and financial incomes) on
the other.
Asia & ASEAN
It is known that the registered manufacturing
sector is an important provider of decent
employment. Thus the trend in real wage
stagnation in organised manufacturing – even as
organised sector NDP per employee (see Chart
42) was growing rapidly under liberalisation
– can be considered indicative of what has
happened to the incomes of a large category of
households dependent on casual, irregular and
informal work in agriculture and non-agriculture.
According to the NSSO (2011), during 200910, members of about 47 per cent of rural
households and nearly 35 per cent of the
urban households had income from selfemployment. Another 40 per cent of all rural
households were rural labour households.
Among urban households, regular wage/salaried
employment was the mainstay of only 40 per
cent of households. Meanwhile, during the
period 2004-05 and 2009-10, the proportion
of households depending mainly on regular
wage/salaried employment had decreased by
1 percentage point, while those depending
mainly on casual employment had increased by
1 percentage point (NSSO, 2011; See also Table
4 on ‘Percentage Distribution of All Workers by
Status of Employment, 1993-2010’).
It is important to note that while the proportion
of regular wage/salaried employees is lesser
in informal sector than that in ‘all’ enterprises,
the proportion of self-employed persons is
more in the informal sector than that in ‘all’
enterprises.10 Indeed, in 2009-10, among selfemployed non-agricultural workers, about 92
per cent in the rural areas and 95 per cent in
the urban areas worked in the informal sector.
10 The proportion of casual labour is almost the same in these
two sectors.
Among the non-agricultural workers who were
casual labourers (engaged in works other than
public works), again a substantial chunk was
employed in the informal sector – 73 per cent in
both rural and urban areas.11
It is evident that the exclusion of such a large
majority of households depending on irregular
and informal work (with significantly lower
earnings and irregular source of incomes and
insecure working conditions) from the growth
process explains the observed disparities in
income and consumption levels among different
sections of the population. Such inequalities
in labour market outcomes have had severe
adverse effects on the survival and development
prospects of children in such households.
In the case of agriculture, which is related to the
wellbeing of at least half of the population, there
was a decade-long period of output slowdown
beginning in the mid-1990s (Chand, Raju and
Pandey, 2007). The combination of the agrarian
crisis and greater use of mechanised techniques
of cultivation has reduced the demand for
labour per unit of output in this sector (Ghosh
2011). Employment growth has also been
affected by the slowdown or reduction in
government expenditure, which has strong
direct and indirect employment generating
effects. In particular, growth in the stock of
public sector capital formation in agriculture
declined from 3.94 per cent between 1980-81
and 1990-91 to 1.87 per cent between 199091 and 1996-97, and increased very marginally
to 1.97 per cent during 1996-97 to 2004-05
(Chand, Raju and Pandey, 2007). Such a decline in
capital expenditure has led to undercapitalisation
of the rural sector at both the social and
infrastructure level, implying a degradation
of the rural conditions of life. Meanwhile, the
liberalisation of trade meant that a downward
trend in international prices of agricultural
11
Understanding the Determinants of Inequalities
N
This nature of organised manufacturing
employment with declining share of wages
in national income and increasing import
dependence during the period of high GDP
growth and high manufacturing sector growth
has been a major factor behind the observed
increase in vertical inequalities.
However, among the regular wage/salaried non-agricultural
workers, a much lower proportion was employed in the
informal sector: 39 per cent in the rural areas and 40 per
cent in the urban areas. Source: NSSO, 2012, Informal
Sector and Conditions of Employment in India: NSS 66th
Round Report no. 539.
53
REDUCING INEQUALITY
commodities after 1997-98 was transmitted to
domestic prices, thus contributing to the severe
pressure on farm incomes.
On the other hand, despite optimism regarding
growth in service sector employment, the
employment generation in this sector is also low
and has not been commensurate with the high
rates of income growth and also show inequities
in earnings and job security (see earlier chart on
sectoral shares of employment and the table on
service sector’s contribution to GDP growth).
Ramaswamy and Agrawal (2012) found that
during the period of dynamic service sector
growth in India (1999-2000 to 2009-10), there
has been no evidence of any acceleration in the
service-sector employment growth relative to
manufacturing even in the urban areas of India.
Further, sub-sectoral analyses of service sector
employment have established the dualistic
nature of service sector employment, with high
income and better quality jobs limited to a small
section of the workforce, while the vast majority
remains trapped in low wage income and
relatively insecure occupations (DGET, 2011; and
Ramaswamy and Agrawal, 2012). In the servicesector, those with more skills have received
higher increases in real wage. Thus, whatever
increase in employment has occurred in the
service sector has come with greater duality
in services sector in terms of the incidence of
informality and wage inequalities.
All these various inequalities in employment
and labour market outcomes have led to the
observed inequalities in consumption levels
between rural and urban areas, as well as across
states.
While the structural changes induced by
liberalisation policies in combination with trade
and financial liberalisation have set in motion a
self-reinforcing dynamics of imbalanced and less
employment-generating growth with significant
54
labour market inequalities, these have got
worsened under deflationary macroeconomic
policies that have been pursued by the
government.
Impact of Macroeconomic
Policy Choices and their
Interactions
While fiscal policies – in terms of the pattern
of mobilisation of public resources and the
pattern of government expenditure – affect the
economic and social conditions of all persons in
a household, they have disproportionate impact
on children because of latter’s dependence
on their parents for fulfilling their socioeconomic needs. During a period of overall less
employment generation and income squeeze,
lower government spending leads households to
cut back on their spending and prioritise among
competing household needs, and weaken the
capabilities of households to invest in children.
Similarly monetary policy measures for inflation
control like higher interest rates can lead to
higher unemployment and thereby worsen
poverty and inequalities.
In post-liberalisation India, central government
expenditure as a proportion of GDP has shown
a clear declining trend as seen in the chart
below. From 18 per cent of GDP in 199091, central government expenditure declined
sharply to 14 per cent in 1996-97. Although
there was a slight recovery during 2000-03,
expenditure/GDP ratio registered a significant
decline during the high growth period and
touched a low of 13.6 per cent in 2006-07. The
expenditure ratio shows a slight increase only
following the fiscal stimulus implemented by the
government in the aftermath of the 2008 global
financial crisis, and it fell again to below 15 per
cent of GDP in 2011-12.
20.0
18.0
Expenditure/GDP
18.0
Tax Revenue/GDP (Net)
16.5
16.6
16.0
15.7 15.9 15.6
15.0
14.2
13.6
14.0
14.3
14. 9
12.0
10.0
8.0
8.8
7.3
6.7
6.0
7.3
5.8
6.0
7.9
7.3
8.2
7.5
7.1
5.7
4.0
2.0
0.0
91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12
0 - 91 - 92 - 93 - 94 - 9 5 - 9 6 - 9 7 - 9 8 - 9 9 - 0 0 - 01 - 02 - 03 - 04 - 05 - 0 6 - 0 7 - 0 8 - 0 9 - 1 0 - 1 1 9
19 19 19 19 19 19 19 19 19 19 20 20 20 20 20 20 20 20 20 20 20 20
Source: Compiled from the Indian Public Finance Statistics, Ministry of Finance.
On the other hand, the central government’s
tax revenue mobilisation was suffering and net
tax-GDP ratio declined through the nineties’
decade of liberalisation (from about 7.3 per
cent in 1990-91 to about 6 per cent in 2001-02).
Subsequently, it registered an increase during the
period of rapid growth, reaching a peak of about
9 per cent in 2007-08. With the slowdown in
domestic economic growth following the Global
Recession starting in 2008, tax-GDP ratio has
declined again and stood at an estimated 7.5 per
cent in 2011-12.
At the same time, the chart below reveals that
states’ expenditure to GDP ratio has also shown
a declining trend in the 1990s. After a touching a
low in 1996-97, it recovered and reached a preliberalisation peak in 2004-05. However, it has
also declined subsequently and stood at nearly
the same level as during 1990-91. Meanwhile,
the states’ tax-to-GDP ratio (wherein states’ tax
revenue constitutes both their share in central
taxes as well as states’ own taxes) has registered
an increase since 2003-04 and has hovered
around 9 per cent since 2006.
Understanding the Determinants of Inequalities
Chart 47: Central Government’s Tax and Expenditure Ratios, 1990-2012 (As percentage of GDP)
Chart 48: State Governments’ Tax and Expenditure Ratios, 1990-2012 (As percentage of GDP)
20.0
18.0
16.0
14.0
12.0
10.0
8.0
18.1
15.5 16.0
16.2
15.2
15.1 15.7
16.1 15.7
8.3
9.0
8.4
14.0
7.6
7.9
7.8
6.0
4.0
2.0
7.8
9.4
53
0.0
States' Exp./GDP
States' Tax Revenues/GDP
Note: State governments’ tax revenue = State’s own taxes + States’ prescribed share in central taxes12.Source: Source: Compiled from
the Indian Public Finance Statistics, Ministry of Finance.
12
States’ share in respect of various Central taxes was 29.5 percent for the period 2000-01 to 2004-05, while it was 30.5 per cent
during 2005-06 to 2009-10. For the five years commencing from 2010-11 onwards, it is 32 per cent.
55
REDUCING INEQUALITY
Thus since the initiation of liberalisation and
economic reforms, while central government
expenditure has fallen from 18 per cent of
GDP in 1990-91 to about 15 per cent of GDP
in 2011-12, state governments’ expenditure
to GDP ratio appears to have stagnated in the
range of 15-16 per cent of GDP, except for a
brief duration in the early 2000s. In order to
examine the extent to which these expenditure
trends were related to any decline or change
in the pattern of tax revenue mobilisation, we
examine these below.
The chart below on the composition of central
government tax revenues reveals that the share
of indirect tax revenue in GDP declined during
the nineties. However, it increased significantly
from around 2001, and by 2006-07 had reached
nearly the same level as in 1990-91 (about 6
per cent), before registering a decline with the
onset of the recession. On the other hand, the
share of direct tax in GDP began increasing
significantly from around 2001 onwards and
reached just above 6 per cent of GDP in 200708, before declining slightly with the slowdown
in GDP growth.
Chart 49: Direct and Indirect Tax Components of Central Government’s Tax Revenue (Percentage of GDP)
7.0
6.0
6.2
5.8
4.9
5.0
4.8
4.0
3.0
1.8
2.0
5.3
4.3
4.4
4.0
1.0
5.3
1.8
4.0
2.1
3.7
4.1
4.4
6.3
5.7 5.7
5.7
5.2
5.6
4.6
5.1
4.0
5.9
4.5
2.3
1.2
0.0
DirectTaxes
Indirect Taxes
Note: These tax figures of the central government are net of states’ share in central taxes till 2001-02. So they do not add up to the
total tax/GDP ratios given in the earlier chart for that period.
Source: Compiled from Indian Public Finance Statistics, Ministry of Finance.
The chart below shows the trends in the
contribution of various components of central
government’s total tax revenue as a percentage
of GDP. When it comes to indirect taxes, it
is clearly seen that trade liberalisation led to
a sharp fall in the share of customs revenue,
especially after 2000. On the other hand, the
share of excise duties, which declined during the
1990s, increased from 2000 onwards and, on
average, remained higher than the 1990-91 level
56
during the entire high growth period 2000-08.
While the share of service tax in GDP also
registered an increase from around 2004 and
has hovered around one per cent of GDP, it can
be seen that the increase in the share of indirect
tax revenue in GDP is primarily attributable to
the increase in excise duties in this period. The
post-2008 decline in the share of excise duties
was related to the fiscal stimulus measures
undertaken to counter the economic slowdown.
Chart 50: Contribution of various Direct and Indirect Taxes to Central Government’s Tax Revenue (Percentage of GDP)
Excise duties
Corporation tax
Income tax
Customs duties
Service tax
4.1
3.8
3.5
3.1
2.9
2.8
2.8
2.4
2.4
1.8
1.7
0.9
0.0
1990-91
0.4
0.1
1995-96
1.8
1.8
1.9
1.4
1.6
1.5
1.3
0.2
1.9
1.8
1.6
1.5
0.5
0.7
0.1
1999-2000
1.0
1.9
1.7
0.9
0.2
2001-04
2004-2008
2008-2011
2011-12 (BE)
Note: These tax figures of the central government are net of states’ share in central taxes till 2001-02. Source: Compiled from Indian
Public Finance Statistics, Ministry of Finance.
We saw in the earlier section that the period
of rapid GDP growth was a period of significant
increase in inequalities in job opportunities as
well as wage incomes not just between the
formal and informal sectors but also within the
formal sector. The period after 2002-03 has
seen a sharp rise in profits in India’s organised
sector. However, the government has reduced
tax rates and offered substantial tax concessions
to the private sector in the process of creating
an investor-friendly environment. As a result,
marginal tax rates have come down sharply
during the liberalisation years. Even though
marginal rate of taxes on personal income was
already brought down from 62 to 50 per cent
and the corporate tax rate from around 60
to 50 per cent in 1985-86, they were further
reduced in 1992-93 and 1994-95. Currently, they
stand at around 33 per cent.
Thus, while the improvement in the tax-to-GDP
ratio was on account of increased corporate
tax collections and the service tax mobilisation,
Understanding the Determinants of Inequalities
corporation tax has registered a significant rise
from an average 1.7 per cent during 2001-04
to an average 3.1 per cent during 2004-08 and
further to 3.8 per cent during 2008-11.
As for direct taxes, both personal income tax
and corporation tax show a rise. However, while
personal income tax share began rising from
around 2000, its share in GDP has stagnated
since 2006-07. At the same time, the share of
this was due to the fact that the corporate
sector has been increasing its share of national
income (as seen earlier) and not because of
increase in tax rates. Moreover, the fact that
the central government’s total tax-GDP ratio
in 2011-12 was only marginally higher than the
level in 1990-91 (prior to the liberalisation-led
high growth in the economy), these trends mean
that the growth in direct taxes has still not been
commensurate with the growth in profit shares
and growing inequalities in the economy. On the
other hand, the increase in excise tax share in
GDP reveals the increasing burden of regressive
sales taxes on an already highly unequal society
with the large majority having insecure and lowpaying jobs.
Meanwhile, considering them as essential for
economic growth (despite no such proven
direction of causality), liberalised financial
markets and open capital markets have been an
integral part of India’s economic liberalisation
policies, just like in other developing countries.
57
REDUCING INEQUALITY
real estate sub-sectors within the service sector.
The government catalysed that growth with
multiple concessions at central and state levels
for private investors, important among which
were easy access to and low taxes on imports of
technology, capital equipment and intermediates
as well as low cost access to land and mineral
and other scarce resources (Chandrasekhar and
Ghosh, 2012).
The result has been that huge amount of
speculative foreign capital flows in, especially
due to the low interest rates that have been
prevailing in the developed country markets.
Successive liberalisation of global capital flows to
India since 1992-93 led to a rise in the inflows
of foreign direct investment (FDI) and especially
of portfolio capital to the country, with capital
account surpluses much in excess of that
needed to finance the current account deficit
the country was experiencing.
Another consequence of external financial
liberalisation has been that monetary policy in
India has been subject to the constraints arising
out of the liberalised capital account, which
makes the central bank’s tasks of managing the
real exchange rate of the rupee at a competitive
level, while controlling inflation simultaneously
extremely difficult. Given that excessive foreign
capital inflows lead to appreciation of the rupee,
avoiding appreciations of the exchange rate
meant that the central bank has to neutralise
the influx of foreign exchange by purchasing
the latter in the foreign exchange market. This
contributes to expansions in the level of official
reserves (Chandrasekhar; Ghosh; Majumdar,
2012a, Sen, 2012, etc.).
One consequence of financial liberalisation and
the excess liquidity in the system created by
the inflow of foreign financial capital has been
the growing importance of credit provided
to individuals for purchases of property,
automobiles and consumer durables of various
kinds. The liquidity thus infused into the system
led to a boom in debt-financed investments
in housing (and real estate) and debt-financed
purchases of automobiles and durables. This
indeed explains the faster growth experienced
from around 2004 onwards by specific segments
of the manufacturing sector, the construction
industry as well as the telecom, financial and
Chart 51: India’s Balance of Payments, 2000-2011
150000
100000
50000
10
-1
1
0
20
-1
09
20
08
-0
9
8
20
-0
07
20
06
-0
7
6
20
-0
05
20
04
-0
5
4
20
-0
03
20
02
-0
3
2
20
-0
01
20
20
-5000
00
-0
1
0
-100000
-150000
Source: Chandrasekhar and Ghosh (2012), “India’s External Sector”, The Business Line, January 9.
58
Trade balance
Current account
Capital account
Change in reserves
Apart from the fact that India’s external reserves
were growing largely because of non-reliable
types of capital inflows dominated by portfolio
inflows and external commercial borrowing
(ECBs), it is also true that no amount of foreign
exchange reserves may prove sufficient to
support a concerted speculative attack on an
emerging market currency as the East Asian
crises of the late 1990s showed. But at the same
time, the thrusts towards accumulating both
primary surpluses and foreign exchange reserves
have been severely problematic on several
accounts.
First of all, the RBI’s attempt to reduce money
supply associated with foreign capital inflows
and accumulation of foreign exchange reserves –
by means of bond sales to the public – leads to
an increase in interest payments in the budget.
This adds to expenditure in the fiscal budget
(Sen, 2012). As a consequence of the rising
expenditure on account of interest payments,
the government has been under continuous
pressure to reduce the primary deficit (which
is overall/gross fiscal deficit minus interest
payments), measured as a proportion of GDP.
The primary deficit is an indicator to assess
whether government expenditure is constrained
by interest payments. If interest payments absorb
a large part of current revenues, expenditures
other than on interest payments would be
limited if there are constraints on mobilising
additional revenues or on raising government
borrowing. The latter was the case with the
FBRM Act requiring the Central Government
to reduce the fiscal deficit by 0.3 per cent of
GDP each year starting from 2004.13 Further,
the Act prohibits the Central Government
from borrowing from the RBI (that is deficit
financing, involving the printing of money) to
meet its deficit, and thus unnecessarily forces
the government to pay much higher interest
on all its debt, instead of allowing for some
low interest debt to the RBI. This raises the
interest cost of the government and thereby the
total revenue expenditure, perversely making
it harder to achieve the revenue deficit targets
(Chandrasekhar and Ghosh, 2004).
The chart below reveals this situation starkly.
There is a consistent decline in central
government’s gross primary deficit/GDP ratio
from the early 1990s. But in particular, during
the fast growth period of 2004-08, when the
most rapid accumulation of foreign exchange
reserves occurred, government expenditures
other than on interest payments was squeezed
to the extent that gross primary balance was in
surplus (0.2 per cent of GDP). During the entire
post-liberalisation period, it is only because of
the fiscal stimulus package introduced in the
aftermath of the 2008 global financial crisis that
the central government’s gross primary deficit
shows an increase.
Understanding the Determinants of Inequalities
But the accumulation of official reserves far in
excess of the current account deficit leads to
an increase in money supply, which has been
contributing to pressures on the Reserve Bank
of India (RBI) to adopt policies towards inflationtargeting. Faced with expansions in money
supply, the RBI has been selling government
bonds (to absorb some of the excess liquidity),
among other kinds of contractionary monetary
policy measures to deal with inflation.
13 The Act requires the Central Government to reduce
the fiscal deficit by 0.3 per cent of GDP each year, and
the revenue deficit by 0.5 per cent each year, beginning
with 2004, regardless of the prevailing macroeconomic
circumstances. If this is not achieved through higher tax
revenues, the necessary adjustment has to be made by
cutting expenditures. See Chandrasekhar and Ghosh (2004)
59
REDUCING INEQUALITY
Chart 52: Fiscal Indicators of the Central Government,
1990-2012 (Per cent)
7.0
GrossFiscal Deficit/GDP
5.7
5.7
6.0
5.8
GrossPrimary Deficit/GDP
5.0
4.0
3.4
3.0
2.6
1.7
2.0
1.3
1.0
-0.2
0.0
1990-1997
1998-2003
2004-2008
2009-2012
-1.0
Source: RBI Handbook of Statistics, 2011-12
Meanwhile, the chart below reveals the break-up
of central government expenditure and captures
the clearly secular decline in capital expenditure
as a percentage of GDP. The share of capital
expenditure to GDP, which was just below 5 per
cent in 1990-91, declined sharply to less than 3
per cent of GDP by the mid-1990s, continued
to plummet well into the mid-2000s. In 200304, central government’s capital expenditure
declined in absolute terms (recording negative
0.1 per cent of GDP). Although the ratio has
recovered slightly since 2005, it hovers around
an average 1.7 per cent of GDP since 2008 less than half the level in 1990-91. On the other
hand, the ratio of revenue expenditure to GDP,
which stood at 12.5 per cent in 1990-91 and
increased slightly during 1998-2003 and 2008-10,
was again at 12.3 per cent in 2011-12.
Chart 53: Major Heads of Central Government Expenditure (Percentage of GDP)
20.0
Total Expenditure
12.8
10.0 12.5
12.4 12.9
11.4
11.4
4.7
2.8 2.4 1.8 1.9 2.0
5.0
1.6 1.9
13.4
11.9
11.9
14.0
12.0
12.811.8
1.1
-0.1 0.6
2003-04
11.2
12.0
2002-03
15.0
Revenue exp./GDP
14.0
13.7
12.3
1.5 1.2 2.2 1.5 1.7 2.0 1.7
2011-12 (BE)
2010-11 (RE)
2009-10
2008-09
2007-08
2006-07
2005-06
2004-05
2001-02
2000-01
1999-2000
1998-99
1997-98
1996-97
1995-96
-5.0
1990-91
0.0
Source: Compiled from the Indian Public Finance Statistics, Ministry of Finance.
Thus the major brunt of the pressure to
accumulate primary surplus has been on public
expenditures for capital formation, which has
significant implications in creating in supply
bottlenecks as well as in the provision of basic
amenities to the population. Together with
the reduction in publicly provided goods and
services, which thereby force the poor to pay
more on essential services like power and
water, health, sanitation and education, this fiscal
stance has been exacerbating the inequalities
60
already facing the large majority of households
particularly belonging to the informal sector with
irregular jobs and insecure working conditions.
Secondly, to make its efforts to absorb the excess
money supply by means of sales of government
securities in the domestic market attractive, the
RBI has had to offer higher interest rates (than
would be warranted by real economy needs).
Thus there was an upward push in interest rate
from the mid-1990s especially, which continued
pocket expenditure, particularly for the poor,
and increased inequality and exclusion.
But high interest rate and tight monetary
policies work against children by bringing about
a decline in access to credit particularly among
farmers and other small producers. High interest
rates are particularly bad for informal sector
enterprises and others who already have less
access to finance. It can thus lead to broader
adverse impact by reducing overall employment.
All these lead to reduction in household
incomes, which affects children the worst.
As the chart below shows, Government
expenditures for both Centre and States in
developmental activities as percentage of total
expenditures have gone down substantially
since the early 1990s. While there has been
some recovery in this trend in the very
recent past, in the case of state governments
it still remains significantly below the levels
prevailing in the early 1990s. And this has been
happening precisely at the time when the
growth process has failed to generate adequate,
decent employment and has instead given rise
to an increasing percentage of the population
being pushed into low paying, insecure and
low productivity informal jobs with no social
security whatsoever for this vast mass of the
population engaged in informal work. Some
positive moves by the central government after
2004, such as the Mahatma Gandhi National
Rural Employment Guarantee Act (MGNREGA)
and associated programme, and enhanced
spending on rural areas and on education
operated slightly to reverse this process, but
could not effectively counter the continuing
low levels of public spending on essentials that
have exacerbated the inequalities generated by
market processes.
Thus the surge in foreign capital inflows under
external financial liberalisation has thus not only
constrained India’s monetary policies and made
it more contractionary, but has also changed
the composition of public expenditure away
from the developmental goals of the country.
Apart from reducing subsidies to the people
and privatising public sector assets, the typical
measures that have been undertaken by the
government to keep fiscal deficit targets under
the FBRM Act involved: cutting down welfare
expenditure, raising administered prices, making
the State retreat from the responsibility of
providing the essential services needed by the
people, increasing the burden of indirect taxes
to close the fiscal deficit, etc.
Impact of Social
Policies on inequality
The impact of such neoliberal polices has been
the delinking of economic policies and social
policy. A systematic withdrawal of the State
from
75.00 social welfare manifested in terms of
reduction
of budgetary allocation, increasing
70.00
commercialisation of services and/or handing
65.00
over
of service provision and its financing
to
private parties and introduction of cost60.00
recovery measures such as user fees for public
55.00
services. In the process, the previous progress
50.00
towards
universal access has been thoroughly
undermined
and has resulted in rise in out-of
45.00
40.00
35.00
30.00
Understanding the Determinants of Inequalities
until the onset of the global financial crisis during
the third quarter of 2008 (Sen, 2012)
Chart 54: Government Developmental Expenditures as %
of Total Expenditures
75.00
70.00
Developmental
Expenditure of C
Government (%
65.00
60.00
Developmental
Expenditure of
Government (%
55.00
50.00
45.00
40.00
35.00
Developmental
Expenditure of Central
Government (%)
30.00
Developmental
Expenditure of Central
Government (%)
Developmental
Expenditure of State
Government (%)
Source: Compiled from RBI Handbook of Statistics on Indian
Developmental
Economy
Expenditure of State
Government (%)
61
REDUCING INEQUALITY
There are several ways that reduced
government expenditure on social sector has
affected public provisioning of and people’s
access to important goods and services. So
important areas of public spending such as the
Public Distribution System (PDS), or education,
health, ICDS, etc., did not receive the impetus
required to provide for good quality universal
provision. Despite some recent increases in
education and ICDS spending, the amounts
are still far below even the most minimal
requirements and have not grown sufficiently
despite that fact that high aggregate income
growth rates would have generated greater fiscal
and policy space for the central government
to enable more such spending. Each of these
services has strong implications for reducing
inequalities and generating more equitable
outcomes for poor children and their families.
We look at some of the specific social welfare
instruments meant to ensure food security
and access to cheap food by the poor such as
the PDS; programmes meant to ensure public
provisioning of health and education. We also
analyze one of the programmes that aim to
address the problems of high unemployment
and social security for those engaged in
informal employment and finally examine the
programmes meant for ensuring protection for
children.
Liberalisation, Public
Distribution System and
Exclusion of the Poor
One of the biggest food-based interventions in
India is the system of public distribution of food.
The PDS was established in the British period as
a rationing system during the World War II and
after independence was made universal in 1965.
As noted by Swaminathan, 2009, from being
a rationing scheme in the pre-independence
period, the PDS was converted into a universal
programme with the aim of providing cheap
food and subsequently it also became an
62
important component of poverty alleviation
strategy.
The basic aim of the PDS was to (i) ensure
stability in the prices of essential commodities;
(ii) provide food entitlements to the population
at affordable prices; and (iii) keep “a check on
private trade, hoarding and black-marketing”
(Ramakumar, R. 2010). While the outcomes of
the PDS in the pre-liberalisation period in terms
of reaching India’s population and reducing
regional disparities in food grain consumption
was mixed, the National Sample Survey
Organisation (NSSO) 42nd round sample survey
on the utilisation of the PDS showed that for
India’s population “subsidised purchases from
the PDS acted as an important supplement to
other sources of purchase of food” (Ramakumar,
R. 2010).
Since 1997 however, in line with the neoliberal
agenda of reducing fiscal subsidies, the earlier
universal PDS was converted into a targeted
scheme with different price rates operating
for different groups. Under the new targeted
PDS (TPDS) only Below Poverty Line (BPL)
households are eligible for subsidised purchases
of commodities from ration shops (later on,
under the Antyodaya programme another new
category, denoting the “poorest of the poor”,
have been introduced for whom rice and wheat
are made available at prices that are lower than
that for BPL households). Other households are
supposed to access food grain at the “economic
cost” to the government, which is lower than
the market prices but not subject to subsidy.
Since the state governments also have the
power to provide their own subsidies in addition
to this, there is significant variation between
states in terms of actual provision. Some states,
such as Tamil Nadu, Kerala, Andhra Pradesh
and most recently Chhattisgarh, have tried to
provide extremely subsidised grain (at Rs. 1 or
2 per kilogramme) to a very large proportion of
the population or close to universal provision
– and interestingly, these are also the states
where the lowest levels of leakage from the
The report of the “High Level Committee on
Long Term Grain Policy” (2002), noted that “the
narrow targeting of the PDS based on absolute
income-poverty is likely to have excluded
a large part of the nutritionally vulnerable
population from the PDS”. Indeed other studies
based on empirical data corroborate the above
observation and establishes that the Targeted
PDS has failed to benefit the poor and has led
to large scale exclusion of the needy. Other
than not benefiting the poor, as the Performance
Evaluation by the Planning commission (PEO
2005), notes, “the transition from universal
PDS to TPDS” has not even “helped reduce
budgetary food subsidies”. What is more,
the introduction of targeting has adversely
affected the very core of the PDS, impairing
its functioning as well as endangering the
economic viability of the PDS network, leading
to a situation where the delivery system itself
has collapsed in several states (Swaminathan, M.
2010). As noted earlier, the closer the system is
to universal in certain state, the better and more
accountable the delivery system.
Indeed, the argument that targeting benefits the
poor and is more cost effective fly in the face of
evidence from many poor developing countries
where the practice of targeting benefits to
only those considered as poor and “needy” has
been increasingly used in recent years. These
problems substantially reduce the scope of such
policies as instruments of reducing inequality
and poverty. This is because targeting always
involves direct and indirect costs, some of which
are:
• Exclusion and inclusion errors: Targeting
often leads to the actual poor not getting
the benefits (Type I error, also known as
exclusion error), and leakage to better-off or
to those who do not ‘need’ the benefit (Type
II error or inclusion error)14.
• Regressive: Because of problems such
as wrong identification of the poor, class
interests that influence the distribution
of resources, leakages and so on, targeted
programmes could also turn out to be
regressive, i.e. transfer less resources to
the poor than a universal scheme would
have done. A World Bank study, evaluating
122 antipoverty targeting interventions
in 48 countries in various parts of the
world, shows that one out of four targeted
programmes turn out to be regressive.15
Understanding the Determinants of Inequalities
PDS have been reported (Dreze and Khera
2011). However, given the uncertain financial
position of many states, it is obviously necessary
to have a national policy of universal provision,
which has so far not been forthcoming. In
such a context, the TPDS has operated to limit
the amount of grain that state governments
can access at subsidised rates. This affects the
poorest states the most, and since most of the
children suffering from under-nutrition live in
these states, this has a direct effect on their
nutritional and health indicators. The lack of the
universal policy has therefore had unfortunate
effects for inequalities in access to basic food for
children as well.
• Differentiation of service: Targeting often
creates two-tiers of service provision, one
for the better-off and other for the poor,
with poor quality services provided to the
latter (T. Mkandawire, 2005, UNRISD).
• Stigmatisation: Most targeting methods
often require the intended beneficiaries to
openly declare their vulnerable status, which
sometimes can be stigmatising. In India, for
example, benefits like subsidised food items
are provided to ‘deserted women’. This often
forces ‘deserted women’ to face the ‘stigma’
of being deserted simply to be able to get
the benefits (Jhabvala, R. and G. Standing,
2010).
• High administrative costs: For the
identification of beneficiaries and reaching
benefits to them, targeting often requires
14
For details see Cornia, Giovanni Andrea and Frances
Stewart, 1993.
15 Coady et al, 2004.
63
REDUCING INEQUALITY
complex methods and advanced institutional
capacity. These, in turn, translate into
high administrative costs, which often
consume a large chunk of allocated funds.
Studies based on simulations of transfer
programmes in low-income countries show
that total administrative costs for targeted
programmes can be as high as 30 per cent,
compared to 15 per cent for universal
programmes.16
Some of the general problems associated with
targeted schemes, especially with regards to
exclusion of large number of the poor, are
evident in the case of targeted PDS in India
as well. Evidence from a Government of India
report “Public Distribution System and Other
Sources of Household Consumption 20042005” (GOI, 2007), corroborates the fact of high
rates of exclusion of needy households from the
Public Distribution System.17 The report, further
establishes that even in States like Kerala where
the universal PDS was most effective, there has
been a significant deterioration of coverage
after the introduction of the targeted PDS
(Swaminathan, M., 2008).
The extent of exclusion of the poor from the
PDS is evident from the fact that in 200405 at the all-India level, more than seventy
per cent of rural households either did not
possess any card or held an APL card (in several
States there is negligible difference between
APL prices and market prices, which amounts
to effectively excluding households with APL
cards from the PDS). State-wise data show
that in 2004-5 an extremely large proportion
of the rural households had no access to the
PDS(Table 6), with only three States, namely
Andhra Pradesh, Karnataka and Tamil Nadu,
being exceptions to this trend. Even in Andhra
Pradesh and Karnataka, where a simple majority
of households possess a BPL or Antyodaya card,
the proportion amounted to a mere 56.5 per
cent and 51.7 per cent respectively.
16
17
64
Cited in Dutrey, Alexander Peyre, 2007.
Originally cited in Swaminathan, M., 2008.
Table 6: Percentage of Rural Households having No Card
or Holding an APL card, 2004-05
State
Percentage of Rural
households Having No Card
or Holding an APL card
Assam
87.7
Uttar Pradesh
83.5
Himachal Pradesh
83.2
Bihar
82
Rajasthan
81.5
Uttaranchal
73.4
Source: Swaminathan, M., 2010, based on the report titled
Public Distribution System and Other Sources of Household
Consumption 2004-2005 (GOI, 2007)
In addition, there are significant inequalities of
access to PDS that are determined by caste,
occupation, land ownership and consumer
expenditure category. “The data from the 61st
round of the NSS make it quite clear that a high
proportion of agricultural labour and other
labour households, of households belonging
to the Scheduled Castes and the Scheduled
Tribes, of households with little or no land
and households in the lowest expenditure
classes, are effectively excluded from the PDS”
(Swaminathan, M., 2008).18
More recent evidence suggests that revival of
the PDS in some states in the last couple of
years (e.g. in Chhattisgarh, Orissa, and Uttar
Pradesh), which can be traced, in large part,
to a renewed political interest, has positively
impacted access to the PDS and food security
situation in these states. Studies show that the
States which have well functioning PDS have
brought in policy reforms in terms of raising
the number of BPL households entitled to PDS
commodities, beyond the caps imposed by the
central government. In addition, in some states,
APL households have been included in the
PDS. In Kerala, for instance, from 2009-10, in
order to reduce exclusion of needy households
classified previously as APL households, all Dalit
households, adivasi households, fisherperson
18
For details see, Swaminathan, M., 2008.
Several States have also reduced the PDS prices
at which grains are made available, with Tamil
Nadu providing free grain since June 2011. In
short, some States have instituted quasi-universal
PDS and thereby helped raise access to the PDS
by the poor (Khera, 2011 and Puri, 2012).
The experience of these States provides
additional lessons as to why universalising the
PDS, along with taking steps to plug leakages,
makes Fair Prices Shops (FPS) viable, etc. are
necessary to reach the poor. It is well known
that not only are universal schemes easier and
less costly to administer, they are definitely
more appropriate in countries where poverty
rates are high and the poor face different kinds
of social and economic discrimination. Further,
as Mkandawire (2005) notes, universal access
is most effective in ensuring “political support
by the middle class of taxes to finance welfare
programmes”.
In this context, the proposed National Food
Security Bill (NFSB) has raised some important
concerns about the future of the PDS in India.
Ironically, instead of taking lessons from the
States that have been reviving PDS or have
well-functioning PDS, the Central Government’s
idea of ensuring access to food by the poor at
affordable prices has been to exclude 25 per
cent of rural India and 50 per cent of urban India
from the PDS.
Further, the purported Bill is said to even
allow State governments to replace physical
provision with a system of cash transfers to
those identified as poor (Ghosh, 2010). In fact, in
the official circles the view that the PDS should
be replaced with a system of coupons or cash
transfers has been gaining ground in the recent
period (Basu, 2010). To this end, the Government
of Delhi has already embarked on a pilot project
to replace food grain distribution under the PDS
with cash transfers (Ghosh, 2011).
While, in the past decade, cash transfers have been
gaining in popularity as a preferred strategy for
pov­erty reduction in different parts of the world,
it is critical to understand the specific context
of and reasons that can make cash transfers
a success. Most of all, they should be seen as
additions to, rather than substitutes for, public
provision of goods and services.Two significant
aspects of the well-known success stories of cash
transfers, for example in Latin America, are:
These have typically complemented public
provision of essential social services. In most
programmes of conditional cash transfers
in Latin America, the conditionalities often
manda­ted the use of government-managed
facilities such as schools and clinics. Understanding the Determinants of Inequalities
households and destitute persons have been
brought under the purview of the system of
subsidized food provisioning (Isaac, T.M. Thomas
and R. Ramakumar, 2010). Further, in 2010-11,
the scope of PDS was further expanded to
“include all agricultural labourer households
and all traditional industrial worker households
to be eligible for subsidized rice, irrespective
of their BPL/APL status”, thereby including all
workers and producers in the unorganized
sector in the BPL list (Isaac, T.M. Thomas and R.
Ramakumar, 2010).
Typically, extensive efforts were
simultaneously made to expand and improve
the public delivery of such services and
facilities. So the success of cash transfer
schemes has been associated with continued
and enlarged investment in public services.
Clearly, it is important to combine different
strategies to ensure social protection, and
emphasis on any one instrument (such as cash
transfers) should not lead to the exclusion
or even diminution of other redistributive
measures and social policies.
Despite this, in India, there is a growing
tendency is to see cash transfers as a substitute
for publicly provided goods and services. There
are several reasons why such a move may not
be desirable and may fail to deliver on its stated
objective.
65
REDUCING INEQUALITY
• Rising prices in deregulated markets:
The most immediate threat of direct public
provision of some essential goods (like food
and fuel) being substituted by cash transfers
to consumers, is that of rising prices in
these deregulated markets. Rise in prices
would render such goods unaffordable for
the lower-income segments, i.e. those who
need them most. Typically, in situations of
volatile and rising prices, the real value of
cash transfers can get quickly eroded. While
it can be argued that cash transfer systems
can be indexed to inflation (for example in
the case of food items, to the price index
for the foods in question) to get around
this problem, it is well known that in most
developing countries the systems of price
indexation of such transfers are typically
slow and inadequate to cover the price
increases. Given the lags in public response
to price changes, depending on price
indexation to take care of the problem of
rising prices is unlikely to prevent erosion of
the entitlements of the poor.
• Ensuring that the cash transfer actually
goes to the intended beneficiaries: The
possibility of cash transfers being diverted
for expenditure that do not meet the
intended purpose is another issue that can
pose serious problems. Even when the poor
household is correctly identified, structures
of power within households as well as social
constructions of gender behaviour can affect
decisions about how the money is spent, in
ways that are not always expected or desired.
The argument that handing over the cash
payments directly to women will solve this
problem is not necessarily correct. Especially
with respect to food, it has been found
(particularly in south Asia) that women and
girls are guilty of voluntary self-denial rather
than being forced into choices that reduce
their own consumption (Ghosh, 2011).
These problems perhaps explain why poor
people in general prefer public provision of the
66
good or service in question at a defined price,
when it is of reasonable quality. In fact, several
studies show it is the relatively better off who
prefer cash, while the poor are more likely to
prefer provision in kind.19
In short, it is better to view cash transfers as
complements that will enhance the effectiveness
of public provision, rather than as alternatives.
Poor families are better able to get the benefits
of cash transfers when there are public services
and provision of goods that they can access with
those payments.
What this means is that for reducing inequalities
in access to affordable food and essential
commodities it is essential to increase public
funding for not just revamping the PDS but
also for building stronger backward linkages for
strengthening supply of food by way of providing
remunerative prices for farm products for making
cultivation viable, providing inputs at affordable
prices, more public investment in agricultural
research and extension services and so on.
Health and Education
The need for increased public funding is
equally urgent in other areas of the social
sector, in particular in health and education.
This is especially so as there are large positive
externalities associated with health and education
spending, which makes such spending clear merit
goods. This also means that with greater reliance
on private delivery of health and educational
infrastructure and services, these are likely to be
socially underprovided by private agents, and also
deny adequate access to the poor.
In the case of India, it is widely recognised that
health expenditure is dominated by private
spending as government expenditure remains
abysmally low (Chart below) — WHO estimates
that as much as 70 per cent of total expenditure
on health is accounted for by private expenditure.
19
Parsai, Gargi (2011. Also see, Puri, Raghav (2012).
1.68
26.70
Public Expenditure
Private Expenditure
External Flow
71.62
Source: National Health Profile, 2011
In the period since the 1990s, barring the last
couple of years, central government expenditure
has remained below 1% of GDP. Although
there has been some increase in the share of
government expenditure in the last couple
of years, it still remains among the lowest in
the world and ahead of only four countries—
Burundi, Myanmar, Pakistan, Guinea and Laos.
The situation is even worse when per capita
health expenditures are assessed. At purchasing
power parity $ per person, India’s health
expenditure is only about half that of Sri Lanka’s
and a third of China’s and Thailand’s (Kumar et
al, 2011). What is of particular significance is
that India, which is currently seen internationally
as an economic powerhouse and one of the
success stories of global economic growth in
the past decade, has one of the lowest ratios
of public to private health expenditure in the
world, including the poorest countries. Further, a
large proportion of private expenditure (Chart
56) in India is constituted by out-of-pocket
expenses. This is inherently regressive and puts a
disproportionate burden of health care on poor
households.
Chart 56: Private Expenditure on Health as share of Total Health Expenditure
78
76
74
74
72
74.3
74.9
76.1
74.4
74
76.8
77.2
77.3
76.1
75.2
Understanding the Determinants of Inequalities
Chart 55: Sources of health spending in India, 2008-09
74.2
72.4
72
70
69.7
70.8
68
66
64
1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
Private expenditure on health as a percentage of total expenditure on health
Source: WHO
Such a pattern of health financing has
implications for household expenditure on
health care. As the chart below shows, spending
on health as a proportion of total household
consumption has been on the rise, until 2004-05.
This is especially notable in rural areas, where
household expenditure on health accounted
for nearly 7 per cent of total household
consumption expenditure in 2004-05, up from
5.4% in 1993-94. While in 2009-10 there has
been some decline in household expenditure on
health as share of total household consumption,
it still remains higher than the 1993-94 levels
(Chart 57). On the whole, the more or less
consistent increase in health spending of
household total expenditure till 2004-05
probably reflects three separate trends:
• the greater valuation placed on health such
that even poor households are willing to
spend and incur debt to ensure minimal
health care;
• the worsening quality and spread of, and
67
REDUCING INEQUALITY
the public health system, as governmentrun hospitals and clinics that are starved of
public funds resort to making citizens pay
more for medicines, diagnostic procedures
and surgical aids (ERF, 2006).
therefore the reduced access to, reliable
public health services; and
• the increase in user charges and other
effective charges upon consumers even in
Chart 57: Health spending as per cent of household consumption expenditure, 1993-94 to 2009-10
7
6
6.01
6.61
5.3
5.74
4.6
5
5.06 5.19 5.03
4
3
2
1
0
Rural
1993-94 1999-00
Urban
2004-05
2009-10
Source: ERF, 2006 and NSSO (2011), Key Indicators of Household Consumer Expenditure in India, 2009-10.
There has, in fact, been a sharp rise in the
costs of medical care in the last two decades.
As Kumar, et al, 2011 note, “between 1986 and
2004, for instance, the average real expenditure
per hospital admission has increased three times
in government and private hospitals in rural and
urban areas. The sharp increase in the prices
of drugs has been one the main reason for the
rising costs of medical care, which more than
tripled between 1993–94 and 2006–07”. Further,
expenditures on inpatient and outpatient health
care are consistently higher in private facilities
than in public facilities (ERF, 2006 and Kumar, et
al, 2011).
As mentioned earlier, low public financing and
the resultant high out-of-pocket expenditures
are the two major factors that affect equity in
health financing and financial risk protection.
Evidence from national sample surveys of
expenditures shows that during the past two
68
decades the proportion of money spent on
health has increased most for the poorest
households (Chart 58) (Balarajan, et al, 2011).
Clearly then, inequalities in health financing have
worsened over this period.
Inadequate protection against financial shocks
arising from high costs of medical treatment
has worsened poverty in many households.
It has been estimated that high private health
spending adds to the proportion of households
under the poverty line by 3.6% for the rural and
2.9% for the urban sector. “The effect of health
expenditures are greater in rural areas and in
poorer states, where a greater proportion of
the population live near the poverty line, with
the burden falling heavily on scheduled tribes
and scheduled castes” (Balarajan, et al, 2011).
160
140
Out-of-pocket expenditure*(%)
120
Episodes
100
Outpatient 1995 -96
80
Outpatient 2004
Inpatient 1995 -96
60
Inpatient 2004
40
20
0
Low
High
Rural areas
Low
High
Urban areas
Note:1. *As a share of income. 2. †Lowest quintile income group. 3. ‡Highest quintile income group.
Source: cited in Balarajan, et al, 2011
Health Expenditure by the
Centre and States
Given that health is mostly seen as a state subject,
it is the state governments which are primarily
responsible for the funding as well as delivery of
health services. However, in addition to direct
central government spending on specific budget
items, there is a range of centrally mandated
expenditures which are also effectively spent
by state governments, as well as some joint
spending. While there are some specific central
interventions, the bulk of the health provision is
the result of spending by state governments.
What is of significance is that per capita
expenditure for health by the Central
government is more or less similar across states,
irrespective of the different capabilities and health
needs of the states. This in turn impacts the statelevel financing of health expenditure and health
outcomes. Apart from the problem of the lack
of political will to accord priority to health and
the limitations of public administration, states
with low public health expenditure are fiscally
constrained by two factors. “First, the centre’s
distribution of revenues across the states does
not offset the fiscal deficits of the states that are
poor. Second, the fiscal space for development
spending in the poor states is small, and these
incur a large share of the obligatory expenditures
(including salaries, wages, pensions, and interest
payments)” (Kumar et al, 2011).
Understanding the Determinants of Inequalities
Chart 58: Trends in out-of-pocket health expenditures in households per episode, as a share of income by income group
and residence
The effects of such Centre-State Fiscal
relationship in health financing are reflected in
the sharp inter-state differences that exist in
health financing, outputs and outcomes (Table
7). In general, the southern states fare better
than the northern states in terms of these
three indicators (Kumar, et al, 2011). In 2004-05,
average per capita public expenditure on health
in the 14 most populous states of India differed
by huge margins, ranging from Rs. 287 in Kerala
to as low as Rs. 93 in Bihar. These variations
in turn are reflected in health indicators of
the states with a group of states (Kerala,
Maharashtra and Tamil Nadu) having health
indicators similar to those in more developed
middle-income countries and the other group of
states (Uttar Pradesh, Orissa, Madhya Pradesh
and Bihar) showing health indicators similar to
sub-Saharan and other low-income countries
like Sudan, Nigeria and Myanmar.
69
REDUCING INEQUALITY
Table 7: Per capita public health spending and some indicators of health outputs and outcomes in 14 most populous states, 2004–05
State
Per person public health
expenditure (in Rs.)
Proportion of children
(age 12–23 months) fully
immunised in 2005–06
(%)
Proportion of primary
healthcare centres with
at least 60% staff in 2003
(%)
Kerala
Punjab
Karnataka
Tamil Nadu
Maharashtra
Haryana
Gujarat
Andhra Pradesh
Rajasthan
Orissa
West Bengal
Madhya Pradesh
Uttar Pradesh
Bihar
287
247
233
223
204
203
198
191
186
183
173
145
128
93
75.3
60.1
55.0
80.8
58.8
64.3
45.2
46.0
26.5
51.8
64.3
40.3
22.9
32.8
91.4
38.0
58.0
96.8
95.6
51.1
85.7
88.4
25.6
0.2
5.7
35.4
52.8
19.6
Source: Kumar, et al, 2011
These regional disparities also extend to
the availability of medical personnel which
is not only shockingly low, but also much
more concentrated in the South and in more
developed states (so that in the late-2000s
Punjab had more than five times the availability
of Uttar Pradesh). Even medical colleges are
unevenly spread: the four southern states
have the major share of the colleges and the
seats. On the other side, the states with the
biggest shortfalls in medical personnel are
predictably the states which have low public
funding for health (in this case Bihar, Madhya
Pradesh, Rajasthan, Uttar Pradesh, Jharkhand
and Chhattisgarh) along with the North-eastern
states, Orissa and Haryana (Ghosh, 2009).
The Integrated Child
Development Services (ICDS)
The paucity of adequate public funding is also
reflected in some of the ‘flagship’ programmes
of the government that had been initiated and
designed to ensure holistic development of
children. The Integrated Child Development
Services (ICDS) is one such programme in
70
operation since 1975. The scheme integrates
several aspects of early childhood development,
such that in addition to supplementary nutrition,
immunisation, health check-ups, etc., the
programme also provides non-formal pre-school
education to children in the 3-6 age group, as
well as health and nutrition education to women
in the 15-45 age group.
“ICDS services are delivered through a network
of over one million anganwadi centres (AWCs),
each of which is staffed by anganwadi workers
(AWWs) and helpers and reaches more than
70 million children and 15 million pregnant and
lactating mothers”(Centre for Policy Research,
2011). The existing public health infrastructure,
consisting of health sub-centres, and primary
and community health centres deliver three
(immunisation, health check-up and referral
services) of the eight services under the ICDS
scheme.
ICDS used Below Poverty Line (BPL) as a
criteria for delivery of services prior to 2005,
after which, following a 2004 Supreme Court
order, ICDS was expanded in 2005 to cover the
entire country.
At the same, it is also clear that for a scheme
that has been in operation for three decades,
the benefits are still far too limited, and maternal
and child health and nutrition are still areas
of major concern for policy. Even today, a high
proportion of children are born with low birth
weight. The chart below indicates the extent
of severe stunting and severe under-nutrition
among young children in rural and urban India,
both of which are still unacceptably high.
Chart 59: Nutritional Status of Children in India, 2011 (in %)
Wasting
Underweight
Stunting
70
60
50
40
30
20
10
Understanding the Determinants of Inequalities
By many accounts, thus far the scheme has been
a success and most of the studies conducted
on the functioning of the ICDS Scheme have
recognised its positive role in the reduction of
infant mortality rate, in improving immunisation
rates, in increasing the school enrolment and
reducing the school drop-out rates.
0
100 Focus Districts
Districts From Best States Best Districts From Focus States
Note: 100 Focus Districts refer to districts that were selected from the bottom of a child development district index developed
for UNICEF India in 2009. These 100 districts are located in 6 states (Bihar, Jharkhand, Madhya Pradesh, Orissa, Rajasthan and Uttar
Pradesh). Districts from Best states refer to another set of 6 districts, 2 each from the best-performing states - Himachal Pradesh,
Kerala and Tamil Nadu. Source: The HUNGaMA (Hunger and Malnutrition) Survey, 2011
The continuing dismal picture of the health
status of children can be largely attributed to
lack of enough resources devoted to the scheme
in relation to the huge requirement it needs to
meet in a country like India. For most part of
the 1990s until the mid 2000s, spending on ICDS
was very inadequate and hardly showed any
increase (ERF, 2006). In the 2000s, following the
Supreme Court’s judgement about universalising
ICDS and the Court’s strictures on the central
government for its tardy response have forced
some increase in spending in the very recent
past. However, even during the period between
2005-06 and 2011-12, when allocations for ICDS
in absolute terms have increased significantly
from Rs. 3,326 crores in FY 2005-06 to Rs.
9,294 crores in FY 2011-12, there has not been
any significant increase in it as a share of GDP
(Chart 60).
Chart 60: ICDS Allocation as %age of GDP
0.14
0.12
0.10
0.10
0.10
0.11
0.11
2007-08
2008-09
0.12
0.12
2009-10
2010-11
0.11
0.08
0.06
0.04
0.02
2005-06
2006-07
2011-12
ICDS Allocation as %age of GDP
Source: Calculated using data cited in Budget Briefs-Integrated
Child Development Services,Vol. 3 Issue 3, Accountability
Initiative, Centre for Policy Research, February 2011 and
Economic Survey, GOI, 2011-12.
71
REDUCING INEQUALITY
Thus, despite recent increases in funds allocated
for the ICDS (in absolute terms), the fact that it
remains inadequate in terms of the requirements
is reflected in the different indicators of the
programme. While at the all-India level, 84%
of the required Anganwadi centres (AWCs)
and mini AWCs were operational by March
2010, there are huge inter-state variations in
“the number of operational AWCs/mini AWCs
vis-à-vis project targets or sanctioned AWCs,
suggesting delays in construction of centres
in some states”. Thus, while Tamil Nadu and
Jharkhand are reported to have completed their
AWC/mini AWC requirement as of March 2010,
the progress of Chhattisgarh and Haryana has
been sluggish with only about 56 and 68 percent
respectively of AWCs being operational by the
end of March 2010 (Centre for Policy Research,
2011).
In terms of fulfilling the requirements of
Anganwadi Workers (AWWs), as of March
2010, 78 percent of AWWs were in position.
Here too, the all-India figures mask the large
inter-state differences. Jharkhand is reported
to have not only nearly reached its target in
operationalising the required AWCs, it also has
93 percent AWWs in-position. Uttarakhand and
Chhattisgarh on the other hand, lagged behind
with only 45 percent and 53 percent AWWs
respectively (Centre for Policy Research, 2011).
The continuing paucity of AWWs for a number
of states can be gauged from the inter-state
variations in the number of children per
AWW. While the all-India average stands at 33
children per AWW, as the chart below shows,
some states such as Himachal Pradesh, Kerala
and Punjab which had low ratios of children
per AWW in 2006, have registered further
improvement (or have maintained the low
ratio) in this indicator in 2010. These are also
the states that have more than 95 per cent
of the required AWCs/mini AWCs in place.
Uttar Pradesh, on the other hand, not only has
a very high density of 65 children per AWW,
it has actually gone up from 41 children per
72
AWW at the end of FY 2005-06. Similarly, the
performance of the state Madhya Pradesh too
has worsened with 43 children per AWW in
2010-11, up from 31 in March 2006 (Chart 61).
Chart 61: Number of Children per Anganwadi Worker
(AWW) in Various States
41
Uttar Pradesh
65
31
Madhya Pradesh
43
37
38
Jharkhand
Maharashtra
44
37
35
Assam
28
Bihar
24
Rajasthan
24
37
36
30
Punjab
21
21
Kerala
India: 33
(March 2010)
16
17
9
Himachal Pradesh
0
10
20
30
40
Children/AWW as on March 2006
50
60
70
Children/AWW as on March 2010
Source: Centre for Policy Research, 2011
Lack of resources are also reflected in the fact
that AWWs and helpers are still not seen as
proper workers and still do not even receive
the legal minimum wage. The undervaluation of
their services, owing largely to miserliness in
government spending on education contributes
not only to the low status of women workers
but also to the inadequate level of services that
ICDS can provide. Lack of resources also means
that many anganwadis do not have proper
buildings or amenities and related facilities.
Clearly then despite 35 years of ICDS and
a couple of years of universal ICDS, the
programme is yet to fulfil its basic objectives
as public funding has continued to lag behind
in terms of the sheer scale of the needs ICDS
is required to meet. Quite clearly, the required
expansion, in terms of allocation of resources for
the scheme, including hiring of more workers,
paying the workers adequate remuneration, etc.
EDUCATION
Education services is another area in which
public spending is critical as relying on private
provision is likely to lead to very substantial
under-provision and socially suboptimal
outcomes, because the social returns to
education far outweigh the private returns.
Besides, provision of education based on profit
invariably has the effect of excluding a major part
of the population and does not ensure adequate
representation by gender, class or social group.
While in general public spending on education
tends to increase with per capita GDP, this is
not the inevitable pattern as it can be influenced
by public policy attitudes. In the case of India,
there has been some increase in public spending
as percentage of GDP in the last two decades.
However, even at present it continues to remain
much below the target set by the Report of the
Education Commission (1964-66) –also known
as the Kothari Commission Report - way back
in the mid-1960s or even that set by the UPA-I
government in the mid-2000s, even as the public
spending on education has purportedly got a
renewed thrust with the National Common
Minimum Programme of UPA-1 pledging to raise
public spending in education to least 6 per cent
of GDP with a significant proportion of it being
spent of primary and secondary sectors. In fact, in
the decade of 2000s, a number programmes with
respect to education have been initiated with the
aim of universalising education at the elementary
level, increasing literacy, reducing drop-out rates,
universalising mid-day meal scheme at elementary
level, etc. The major developments in this regard
include: “(1) estab­lishment of the Sarva Shiksha
Abhiyan (SSA) as the vehicle for universal
elemen­tary education; (2) extension of the
Mid-day Meal scheme (MDM) in all elementary
schools; (3) enactment of the Right to Ed­ucation
Act 2009” (Sikdar and Mukherjee, 2011).
Indeed, when seen in absolute terms, there
has been a significant increase in budgetary
allocation and expenditure by the central
government between 2005-06 and 2011-12.
Budgetary allocation for education has increased
manifold in the period between 2005-06 and
2011-12, with that for secondary education and
higher education registering significant jump in
allocation (Chart 62).
Understanding the Determinants of Inequalities
is much greater than is being envisaged by the
Government even now. In short, the continuing
paucity of public funds and lack of political will to
spend even on programmes that are universally
acknowledged to be critical for welfare of the
country’s children continue to be a major area of
policy concern.
Chart 62: Central Government Expenditure on Education, 2005-06 to 2011-12 (in Rs. Crores)
35,000
30,000
25,000
20,000
15,000
10,000
5,000
0
32,150
12,244
1,723
Elementary
Education
12,435
8,692
8,352
2,363
1,478
Secondary Education University and Higher Technical Education
Education and
Distance Learning
2005-06 (RE)
2011-12 (BE)
Note: 1. BE denotes Budget Estimates. RE = Revised Estimates.
2. Components such as Adult Education, Development of Languages and Development of ICT are not shown in this figure.
Source: Calculated using Union Expenditure Budget,Vol.2, 2005-06 till 2011-12, the Ministry of Human Resource Development.
73
REDUCING INEQUALITY
Government Expenditure as
share of GDP
However, a rather different picture emerges
when total expenditure (by both Centre and
States) on education as percentage of GDP is
seen. Barring three years in the decade of 2000s,
government expenditure on education in the
period of liberalization has remained below
the peak (of 3.93 per cent) reached in 198990. Although the share of public spending on
education as percentage of GDP was highest
ever in 2000-01(4.28%), this level could not
be sustained in the following years as it has
consistently declined until 2004-05. Since 200506 the share has started increasing but at a very
slow rate (Chart 63).
3.26
3.34
3.4
2004 -05
2005 -06
2007 -08
3.98
3.8
2010 -11 (BE)
Government Expenditure (Centre and States)
on Education by Education & OtherDeptts. as % age of GDP
3.51
2003 -04
1997 -98
3.81
2001 -02
3.49
4.28
2000 -01
3.56
1999 -00
3.62
1995 -96
4.19
1993 -94
3.8
1991 -92
3.93
1989 -90
3.73
1987 -88
3.49
1985 -86
4.5
4
3.5
3
2.5
2
1.5
1
0.5
0
2009 -10 (RE)
Chart 63: Government Expenditure (Centre and States) on Education as % age of GDP
Source: Statement Indicating the Public Expenditure on Education and Analysis of Budgeted Expenditure on Education, 2008-09 to
2010-11, Ministry of Human Resource Development, 2012, http://mhrd.gov.in/statistics_data?tid_2=238 accessed on 31 October 2012
Further, in the total public expenditure on
education, the bulk of spending is undertaken
by the State Governments. But there are
substantial inter-state variations in state
spending on education. While states such as
Tamil Nadu, Sikkim, Mizoram, Arunachal Pradesh,
and Manipur spent 10.2 per cent, 9.8 per cent,
9.1 per cent, 7.1 per cent, and 6.4 per cent,
respectively, of their total state Domestic
Product (SDP) on education in 2007-08, there
were several states (e.g. Maharashtra, Delhi,
Gujarat, Haryana, Punjab, Andhra Pradesh, Goa)
which spent less than 2 per cent of their SDP on
education (India Human Development Report,
2011).
At the same, there have been certain positive
developments with regard to Centre-State
Fiscal relationship in financing education, with
the share of the central government in total
74
government expenditure on education having
risen from 0.61% in 1999-2000 to 0.93% in
2010-11 (Analysis of Budgeted Expenditure
on Education, 2008-09 to 2010-11, MHRD,
2012). The greater involvement of the Centre
in providing financing for expansion of school
education in the 2000s20 is largely driven by
SSA, under which the Centre provided 75 per
cent of the funds (at least until 2007)21 with the
goal of universalising primary education. This
has led to a greater expansion of the school
system, especially in States that previously could
20
During the 1990s, the greater involvement of the Centre in
providing financing for expansion of school education was
on account of the District Primary Education Programme
(DPEP) initiated in some districts.
21 However, it also needs to be noted that not only has
there been an absolute fall in expenditure after 2007 in the
Sarva Shiksha Abhiyan (SSA), the flagship scheme of the
Central government, even the share of States’ contribution
to the SSA has been raised, and that too without any
corresponding increases in total transfers to States
(Ramakumar, R., 2009).
the poorer states (such as Rajasthan, Jharkhand,
and Assam) which have a relatively higher
proportion of schools dependent on parateachers. In Jharkhand, for instance, nearly 40
per cent of schools are entirely dependent
on para-teachers (India Human Development
Report, 2011). As is well known, lack of
adequate funds is one of the prime reasons for
the prevalence of the phenomenon of parateachers.
The increase in Central government funding
notwithstanding, the continued paucity of
adequate resources spent on education has
given rise to processes that have the potential
to exacerbate inequality. Among various such
processes two most significant ones relate to
dilution of quality norms in education imparted
in India and increasing reliance on private
education even for schooling.
Inadequate funding has also meant that pupilteacher ratio (PTR) in India is extremely high as
compared to other poor countries. In addition,
it continues to be above the 30:1 pupil teacher
ratio norm at the primary level set by the RTE
Act, 2009. There were also wide inter-state
disparities in pupil-teacher ratio in 2007-08.
States which are either known to have a good
government schooling system (Kerala) or have
been seen as recent successes in achieving
universal and good quality school education
(Himachal Pradesh) have relatively low pupilteacher ratio. At the other end, states (both
relatively wealthy as well as less-wealthy) such
as Uttar Pradesh, Jharkhand, Bihar, Punjab,
Haryana, had extremely high pupil-teacher ratio,
especially at the primary level, in 2007-08 (Table
8). Significantly, in 2009-10, number of districts
where PTR was above 30 has increased to 304
during 2009-10 compared to 284 in 2008-09.
These districts are mainly concentrated in Bihar,
Gujarat, Jharkhand, Madhya Pradesh, Orissa,
Uttar Pradesh and West Bengal.
The combination of the pressure to increase
enrolment on one hand and the inadequate rise
in public funding on the other, has inevitably
resulted in the dilution of quality norms, such
that “schools” or rather “educational centres”
have been permitted to come up, based on
single (often untrained or minimally trained)
and underpaid local teachers handling multigrade classes (Ghosh, J., 2010). Data shows
that the number of single-teacher schools has
risen by nearly 10 percentage points from 2
per cent in 2002-03 to 10 per cent in 200708. Even with regard to the new appointments
in primary schools, majority are of a shortterm contract nature, with grossly low salaries
paid to these teachers (Ramakumar, R. 2009).
In 2007-08, for instance, such teachers (also
known as para-teachers, shiksha-mitras, contract
teachers) constituted more than 10 per cent of
total school teachers. Reports point out that
“para-teachers were much more predominant
in the rural areas as compared to the urban
areas and the proportion of para-teachers
was much higher at the primary level than at
other levels of school education” (India Human
Development Report, 2011). In addition, it is
Understanding the Determinants of Inequalities
not or would not provide more resources for
such growth. The impact of such expansion has
been positive in several ways. The findings of
The Annual Survey of Education Report (ASER)
2011, for instance, show that the proportion
of children out of school in the 6-14 age group
has nearly halved, declining from 6.6% 2006 to
3.4% in 2011. There has also been a major drop
in percentage of out of school girls in the 11-14
age group (ASER, 2011).
75
REDUCING INEQUALITY
Table 8: Pupil–Teacher Ratio at Primary and Upper
Primary Levels, 2007–08
State
Primary
Level
Upper Primary
Level
Kerala
Punjab
Tamil Nadu
Maharashtra
Haryana
Gujarat
Andhra Pradesh
Rajasthan
Orissa
West Bengal
Madhya Pradesh
Uttar Pradesh
Bihar
Jharkhand
28
53
44
34
53
30
32.0
43
42
51
41
76
68
73
25
21
54
32
37
37
32.0
32
35
70
33
79
54
55
Source: Statistics of School Education, Ministry of Human
Resource Development, 2007–08.
The state of educational infrastructure too
continues to be poorly developed. As pointed
out by Ramakumar, 2009, in 2007-08, 50 per
cent did not have a separate girls’ toilet, 27 per
cent of schools did not have pucca buildings
and 13 per cent did not have drinking water
facility. While there has been some improvement
in these indicators in 2009-10, educational
infrastructure continues to suffer from
inadequacies in terms of schools not having
pucca buildings (24.4 per cent), lack of separate
toilet for girls (41 per cent) and unavailability
of drinking water facilities in school (8 per
cent). Besides, there are significant inter-state
as well as rural-urban divide in educational
infrastructure with facilities, in general,
being much lower in poor states (e.g. Bihar,
Chhattisgarh, and Jharkhand) and in rural areas.
absenteeism, there has been a growing reliance
on private education even for schooling. ASER
2011 survey shows that overall, private school
enrollment has increased from 18.7% in 2006
to 25.6% in 2011. “Increases are visible over
time in all states except Bihar. Further, in several
states like Uttarakhand, Rajasthan, Uttar Pradesh,
Maharashtra, Andhra Pradesh, Kerala, Manipur
and Meghalaya, there has been an increase of
over 10 percentage points in private school
enrollment in the last 5 years. In several states,
in recent years private school enrolment has
been going up across all grades. In Uttar Pradesh,
previously, “private school enrollment was high
in middle school years. But recently, private
school enrollment has been high across all grade
levels. A similar trend is noticed in the case of
Tamil Nadu, where enrolment in Private school
which is relatively higher in early grades in
primary school, has got further strengthened in
recent years” (ASER, 2011) (Charts 64 and 65).
Chart
64: Private school enrollment 2007-2011: Uttar Pradesh
80
70
60
50
40
30
20
10
0
Std 1
Std 2
Std 3
Std 4
2007
Std 5
2009
Std 6
Std 7
Std 8
2011
Chart 65: Private school enrollment 2007-2011: Tamil Nadu
80
70
60
50
40
30
20
As is known, quality not only is influenced by
spending but certainly does play an essential
role, and, therefore, it is crucial for that public
spending on education to be raised. However, in
India, partly because of inadequate public funding
of education, and also other problems with
the government school system such as teacher
76
10
0
Std 1
Std 2
Std 3
Source: ASER, 2011
Std 4
2007
Std 5
2009
Std 6
Std 7
Std 8
2011
As is generally known, out of pocket
expenditure is much higher in private unaided
institutions. Thus increasing role of private
Equity and inclusion through public expenditure:
The potential of Mahatma Gandhi National
Rural Employment Guarantee Act (MGNREGA)
As mentioned above the nature of growth
process of the Indian economy since the
initiation of economic reforms has been
associated with increasing unemployment and
worsening conditions of employment, that has
forced workers to find any other economic
activity, in the form of ‘self-employment’, largely
as a survival strategy rather than as a positive
choice (Ghosh, 2011). Evidence shows that
economic growth in the 1990s and 2000s in
particular, instead of generating opportunities
for decent employment, has mainly translated
increasingly into casual employment and selfemployment, which are unsupported by any
form of social security. In such a scenario,
“inclusive” public expenditure such as on
employment programmes assumes great
significance in mitigating inequalities generated
by market-led development model followed
since the period of liberalisation.
In this regard, the MGNREGA, at least in the
way it had been conceived, has significant
potential in generating more equity. The
programme, which is generally accepted to be
a novel initiative, is very different in conception
from earlier government employment schemes
since it treats employment as a right and the
programme is intended to be demand-driven.
Launched in February 2006, the programme has
been substantially expanded since. Under the
scheme, every rural household is guaranteed
up to 100 days of unskilled manual wage
employment per year, at the statutory minimum
wage for agricultural workers in the state. If
employment is not provided within 15 days,
the applicant is entitled to unemployment
allowance. The scheme aims to provide work
on labour-intensive projects focusing on rural
infrastructure.
Several features of the programme make it
necessarily “inclusive” at the most basic level
in economic terms. One, it self-targets those
who are willing to engage in arduous physical
work for a daily wage, i.e. the poorest sections
of society. Two, it is designed to offer gainful
employment at a wage at which employment is
not generally available in the labour market. It
also acts as an instrument of social protection
for those who need it the most since the
government declares that whenever it is unable
to ensure the availability of employment on
demand to the eligible it would provide a dole
which is some proportion of the wage to be
paid under the programme. Three, employment
programmes of this kind are also an obvious
form of social insurance, since they guarantee
even those with alternative and better
employment a minimum amount of employment
in case they are displaced from the labour force.
This too has long term implications in reducing
inequity as instead of being merely reactive in
a situation of need or in the context of a crisis,
the programme is designed to provide more
pro-active social protection.
Understanding the Determinants of Inequalities
institutions in education that charge relatively
higher fees are likely to constrain access,
especially among the less well-off sections of
the population, and perpetuate economic and
social distinctions. Evidence shows that high
out-of-pocket expenditure was a deterrent to
educational attainment for the economically
disadvantaged who were mostly SCs, STs, and
Muslims (India Human Development Report,
2011).
Indeed, evidence shows that MGNREGA has
been successful in reducing both economic
and social inequalities. Field reports suggest
that there has been some improvement in
consumption of the poor and reduction of
distress migration in the areas where the
programme has functioned successfully. Further,
the programme has also been successful in
reducing labour market inequities, especially for
women workers in rural areas. As the analysis
by Chandrasekhar and Ghosh (2011), based on
comparison between 64th Round (2007-08)
77
REDUCING INEQUALITY
and 61st Round (2004-05) of the NSS shows,
MGNREGA had made a difference in terms
of increasing real wages for both the male and
female workers in rural areas. This is especially
true in the case of rural women workers as
there has been significant reduction in the
gender gaps in wages since the initiation of the
programme. That this is mainly an impact of the
MGNREGA can be gauged from the fact that
in urban India the gender gap in terms of this
indicator worsened in the first half of the past
decade and remained at around the same level
thereafter. In addition, owing to the exceptionally
high participation of rural women in the
programme there has been significant increase
in rural women’s involvement in paid work with
the introduction of the programme. As the chart
below indicates, the days of employment of rural
women increased from 0.29 in 2004-05 (i.e.
prior to the launching of MGNREGA) to 1.44 in
2007-08, i.e. by 4.4 times.
Chart 66: Public Works as % of Total Rural Economic
Activity
1.6
1.44
1.4
1.2
1.01
1
0.85
0.8
0.6
0.4
0.2
0.21
0.29
0.24
0
rural male
rural female
2004-05
rural persons
2007-08
Source: Chandrasekhar and Ghosh (2011)
Significantly, the employment guarantee
programme has also been successful in being
“inclusive” in terms of providing employment
to social groups such as Scheduled Castes
(SCs) and Scheduled Tribes (STs) that tend to
be economically marginalised in India. Evidence
shows that in 2008-09, these categories too
had disproportionate participation in the
programme, relative to their share of population.
While this may reflect the fact that they are
78
also more likely to be represented among rural
workers, even so it is a sign that the MGNREGA
has succeeded in reaching the more socially
disadvantaged sections (Chandrasekhar and
Ghosh, 2008).
However, certain “inclusive” aspects of the
scheme seem to have waned somewhat over the
years. As the table below shows the share of STs
in total workdays generate by the scheme has
declined consistently, while that of women has
stagnated (Table 9).
Table 9: Share of STs, SCs and Women in MGNREGA work
Scheduled
Castes
Scheduled
Tribes
Women
2007-08
27.44
29.27
42.52
2008-09
29.29
25.43
47.88
2009-10
30.48
20.71
48.10
2010-11
30.6
20.9
47.7
2011-12
22.04
18.16
48.18
Source: Calculated using MGNREGA work from www.nrega.nic.
in, accessed on 31 October 2012.
At the same time, the number of rural
households receiving some work in the scheme
has been on the rise in the period between
2007-08 and 2009-10. Given that MGNREGA
was initially implemented in 200 districts and
was extended to cover all districts within
India in FY 2008-09, there has been significant
expansion of the official coverage of the scheme
in several states. However, while during the
period between 2007-08 and 2008-09, most
states, barring the northern states of Punjab,
Haryana and to a lesser extent Uttar Pradesh,
had improved on the provision of job cards
between 2007-08 and 2008-09, the percentage
of households that had received some work
under the scheme had been significantly
lower. Only in Chhattisgarh in 2007-08 and
in Rajasthan in the 2008-09, more than 50
per cent of estimated rural households had
got some work under the scheme. In most
states the gap between job card distribution
and actual provision of employment remained
huge even in 2008-09. Even in Madhya Pradesh,
variations in the percentage of rural households
that received some work under the scheme
persisted even in 2009-10, what is significant is
that barring Bihar and Jharkhand, a number of
previously low performing states (such as Orissa,
Punjab and West Bengal) have registered sizeable
increase in the percentage of rural households
getting work under MGNREGA (Table 10).
Table 10: Progress in MGNREGA Implementation in 2007-08, 2008-09 and 2009-10
Per cent of households
with job cards
Per cent of households that received some work
2007-08
2008-09
(till August)
2007-08
2008-09 (till
August)
2009-10
Andhra Pradesh
58.32
70.70
31.65
32.87
35
Bihar
52.91
57.52
25.56
12.01
10
Chhattisgarh
83.12
92.98
66.04
34.58
48
Gujarat
13.63
32.51
4.58
5.50
18
Haryana
5.35
8.46
2.35
1.51
5
Jharkhand
69.13
73.94
39.25
19.90
16
Karnataka
19.50
28.55
7.04
3.62
8
Kerala
8.45
16.34
3.27
3.23
11
Madhya Pradesh
78.17
119.67
46.94
35.92
36
Maharashtra
25.01
31.90
3.79
2.66
4
Orissa
55.78
65.91
14.95
7.42
22
Punjab
3.11
8.19
1.58
0.72
5
Rajasthan
32.53
87.01
24.61
52.70
59
Tamil Nadu
24.98
55.84
14.02
27.48
34
Uttar Pradesh
29.50
39.21
16.52
8.21
16
West Bengal
65.13
65.51
29.18
15.15
43
Understanding the Determinants of Inequalities
where more job cards had been distributed
than number of households, only 35 per cent
of rural households had actually received
some employment under the scheme. In
2009-10, on the other hand, only in one state,
namely Rajasthan, that more than 50 per cent
of estimated rural households had got some
work under the programme. While inter-state
Note: (1) The All India Total includes all states and UTs.
(2) Rural Households have been projected using 2001 and 2011 census.
(3) Corresponding MGNREGA figures for June 2009 to July 2010 have been calculated.
Source: Chandrasekhar and Ghosh, 2008 and MGNREGA Sameeksha, MORD, GOI, 2012.
In short, even though there have been several
challenges and issues with regard to the
implementation of MGNREGA, such as delays
in wage payments to workers, non-payment of
full wages, misappropriation of funds, inadequacy
in the number of days of work of provided in
relation to demand, it has had some measure
of progress in enhancing equity, whether seen
in terms of increased involvement of rural
women in paid work, reduction in gender gap
in rural wages, more than proportionate (to
share in population) engagement of socially
79
REDUCING INEQUALITY
disadvantaged groups such as SCs and STs in the
programme, increased consumption among the
low income sections of the population, etc.
At the same time there is no doubt that the
enormous potential of MGNREGA, among other
things, in reducing inequality is still incipient
and requires to be substantially supported in
many different ways. In this context, other than
addressing issues such as utilization of funds, the
capacity (including technical and administrative
capacity) and willingness of local government
and panchayats to plan works and run the
programme effectively, increasing awareness
about the programme and its guidelines to local
people, etc. what is crucial for realizing the
potential of MGNREGA is to increase Central
government funding. However, what is extremely
disconcerting is that Central government
funding, after growing significantly in the initial
few years since the launch of the programme,
has tapered off since 2009-10 and even fallen in
absolute terms in 2011-12 (Table 11). In 201213, allocation for MGNREGA is budgeted to
increase to only Rs. 33,000 crore. However,
since this was in general a period of high
inflation, the amount allocated, in all likelihood,
has actually declined substantially.
reducing inequality and generating “inclusive”
growth.
Child Protection
As is known, India has the highest number of
working children in the world and as HAQ:
Centre for Child Rights (2010) notes, India
also has the highest number of sexually abused
children.Yet, government spending on protection
for children continues to fare poorly compared
to other countries in the world (Budget Analysis
for Child Protection, Ministry of Women and
Child Development). In fact, among all the childfocused schemes in education, development
(relating mainly to interventions for early
childhood care and nutrition), health and
protection, government spending on protection
for children has been the lowest. In 2010-11, for
instance, the Central government spending on
child protection accounted for a mere 0.04 per
cent of the Union Budget (Chart 67).
Chart 67: Share of Child Protection in Union Budget
2010-11
.9
Table 11: Allocation for MGNREGA, 2006-07 to 2011-12
Growth
2006-07
In Rs. Crores
8694.25
2007-08
12661.2
45.6
2008-09
30000.2
136.9
2009-10
33539.4
11.8
2010-11
35841.5
6.9
2011-12
29215.1
-18.5
Source: Ministry of Rural Development, various issues of the
Budget
Such a trend of public expenditure on
MGNREGA seems to clearly indicate that for
the government, the agenda of containing fiscal
expenditure far outweighs its lofty goals of
80
.5
3.2
Education
0.4
Development
Health
Protection
Source: HAQ, 2010
The low priority accorded to child protection is reflected in
the fact that over the years, barring the very recent period,
even when the proportion of central government spending for
child-specific schemes has gone up somewhat, that for child
protection has not kept pace (Chart 68).
6
4.91
5
4.87
4.53
4.22
3.86
4.63
4
2.44
3
2
1
0.033
0.034
0.038
0.034
0.031
0.02
0.04
0
2004-05
2005-06
2006-07
2007-08
Share of Total Child Budget in Union Budget %
2008-09
2009-10
2010-11
Share of Child protection in Union Budget %
Note: The figure for the year 2010-11 is Budget Estimate, rest all are Revised Estimates.
Source: HAQ, 2010 and Budget Analysis for Child Protection, Ministry of Women and Child Development1
Further, there are large gaps between the
budgeted estimates and the revised estimates
of the budget with the latter being consistently
lower than the former in various child-focused
schemes in education, health, protection and
development (HAQ: Centre for Child Rights,
2010).
While the above relates to Union Budget, even
spending by States do not fare very well when
it comes to child protection. As the Ministry
of Women and Child Development website
documents point out there are significant
inter-state variations in allocations for childfocused expenditures. “States with larger child
populations are spending disproportionately
less on child-related sectors, with some
exceptions and variations” (Budget Analysis for
Child Protection, Ministry of Women and Child
Development).
Understanding the Determinants of Inequalities
Chart 68: Outlays for Child Specific Schemes and Child Protection as a Proportion of Union Budget
In this scenario the initiation of the Integrated
Child Protection Scheme (ICPS) in 2007 under
the Ministry of Women and Child Development
has been a welcome move. However, even in this
case, not only has the revised estimates been
consistently lower than the budget allocated for
the centrally sponsored programme (Chart 69),
even the recent increase in the budget allocated
to ICPS has been inadequate.
Chart 69: Gap in Budget Estimates and Revised Estimates in Allocation for Integrated Child Protection Scheme (ICPS) in
Union Budget (in Rs. Crores)
200
180
160
140
120
100
80
60
40
20
0
180
85.5
54
38.5
2007-08
Budget Estimate (BE)
2008-09
54
44
2009-10
Revised Estimate (RE)
Source: HAQ, 2010
1 Union Budget proportion devoted for child-specific schemes provided by CBGA (2012) differ somewhat from those provided by
HAQ (2010).
81
REDUCING INEQUALITY
Thus while there has been significant increase
in allocation for Integrated Child Protection
Scheme (ICPS) since 2010-11, as HAQ (2010)
notes, this falls far short of the resources
needed to implement even the 2001 Juvenile
Justice law and the 2006 amendments all over
the country.22 Even the increased budget
allocation of Rs.400 crore in for 2012-13 is
grossly inadequate compared to the target
average annual amount of Rs.1,060 crore
recommended by the Planning Commission’s
working group for ICDS (CBGA, 2012).
In short, it is obvious that despite the
government’s rhetoric of paying more attention
to protection for children, commitments
in terms of resources allocated and spent
remain measly and fall far short of even
recommendations made by various expert
groups.
22
82
HAQ, 2010 notes that “the old programmes, such as the
Prevention and Control of Juvenile Social Maladjustment,
are no longer running”.
The inequalities evidenced in India are
direct results of long-term features of socioeconomic development as well as some more
recent processes. While there were many
deep-rooted forms of economic and social
inequalities in India well before the process of
economic liberalisation, the latter has certainly
exacerbated the problem.
The analysis of the nature of employment
response to economic growth in the post
liberalisation suggests that whatever moderate
increase in employment was generated during
the years of high growth, it was not manifested
either in the productive sectors or in forms
that have been termed by the ILO as ‘decent
work’ of one kind or another. In particular, while
India witnessed rapid output growth especially
from 2003-04 onwards, it was not manifested
in rapidly growing employment in productive
sectors or in the expansion of decent work. In
general, income generating opportunities have
been getting severely limited for both rural and
urban households, whether headed by males
or females. More than half of all India’s workers
remain self-employed and there has been
significant rise in casualisation of the workforce
in both rural and urban sectors. It is well known
that all casual and self-employed, and a significant
proportion of regular workers, are unsupported
by any form of social security.
At the same time, the fact of having employed
parents does not seem to have been guarantee
against iniquitous economic and social
development outcomes for children even in
households with any kind of employment,
because of the inequities in the labour market.
Unorganised sector employment accounts for
the overwhelmingly dominant share (more than
94 per cent) of all workers. Meanwhile, its share
of national income has been falling sharply even
through the recent period of rapid economic
growth. As a result, the per-employee NDP of
the organized and unorganized sectors have
diverged dramatically, which accelerates sharply
from 1999-2000 onwards. Organised sector
NDP per employee, stood at nearly 11 times
the unorganised sector NDP per employee in
2009-10. At the same time, while rapid growth
has been focussed on the organised sector
in aggregate income terms, there has been
stagnation in organised sector real wages per
worker on the one hand and a dramatic increase
in non-wage salaries and incomes accruing
to persons earning profits, rents and financial
incomes on the other. The trend in real wage
stagnation in organised manufacturing can be
considered indicative of what has happened to
the incomes of a large category of households
dependent on casual, irregular and informal
work in agriculture and non-agriculture. Such
inequalities in labour market outcomes have
had severe adverse effects on the survival and
development prospects of children.
Conclusion and Recommendations
IV Conclusion and Recommendations
These labour market inequalities have
worsened under deflationary macroeconomic
policies pursued by the government. In postliberalisation India, while central government
expenditure as a proportion of GDP has shown
a clear declining trend, state governments’
expenditure to GDP ratio has stagnated, except
for a brief duration in the early 2000s. Share of
developmental expenditures as proportion of
total expenditure showed a decline for both
Central and State Governments until 2004-05
83
REDUCING INEQUALITY
after which there was a slight rise. However,
they are still lower than the level of the early
1990s.
This expenditure squeeze was partly because
the period of high growth was not sufficiently
exploited to generate fiscal resources for the
necessary expansion in public spending. While
there was improvement in the tax-to-GDP
ratio on account of increased corporate tax
collections and the service tax mobilisation, it
was not because of increase in tax rates, but due
to the fact that the corporate sector has been
increasing its share of national income.
Further, the huge amount of speculative
foreign capital inflow owing to liberalised
financial markets and open capital markets
have meant that the central bank’s tasks of
managing the real exchange rate of the rupee
at a competitive level, while controlling inflation
simultaneously, have been made extremely
difficult. The accumulation of official reserves
far in excess of the current account deficit
has been contributing to pressures on the
Reserve Bank of India (RBI) to adopt inflationtargeting policies. The resultant high interest
rates together with the pressure to lower fiscal
and revenue deficits under the FBRM Act have
had significant deflationary impacts on the
economy. The major brunt has been on public
expenditures for capital formation.
Apart from privatising public sector assets,
the systematic withdrawal of the State
from social welfare activities have resulted
in reduced budgetary allocation, increased
commercialisation of services and/or handing
over of service provision and its financing
to private parties and introduction of costrecovery measures such as user fees for public
services. In the process, the previous progress
towards universal access has been thoroughly
undermined and has resulted in increased
inequality and exclusion.
Thus, in the realm of food-based interventions
in India, for instance, the neoliberal stance of
84
reducing fiscal subsidies and the attendant move
from a universal Public Distribution System
(PDS) to a Targeted Public Distribution System
(TPDS) in the 1990s, has resulted in widespread
exclusion of poor and needy households from
the PDS. Moreover, the introduction of targeting
has adversely affected the very core of the PDS,
impairing its functioning as well as endangering
the economic viability of the PDS network,
leading to a situation where the delivery system
itself has collapsed in several states.
The revival of the PDS in some states in the
last couple of years (e.g. in Chhattisgarh, Orissa,
and Uttar Pradesh), owing, in large part, to
a renewed political interest, has positively
impacted access to the PDS and food security
situation in these states. However, in the official
circles, the view that the public distribution
scheme should be replaced with a system of
coupons or cash transfers has been gaining
ground. This can have severe implications in
terms of increasing inequality in access to food,
both across different segments of the population
as well as across States.
In both health and education, government
expenditure continues to be woefully
inadequate. With respect to health expenditure,
such a pattern of financing has resulted in
a general rise in household expenditure on
health care as a proportion of total household
consumption, at least until 2004-05. This is
especially notable in rural areas. Low public
financing and the resultant high out-of-pocket
expenditures are the two major factors that
affect equity in health financing and financial
risk protection. Evidence from national sample
surveys of expenditures shows that during the
past two decades the proportion of money
spent on health has increased most for the
poorest households, thereby worsening poverty.
Even in the case of ICDS, while there has been
some increase in public funding, it remains
inadequate. In short, the continuing paucity of
public funds and lack of political will to spend
In the area of education, even though there
has been some increase in public spending as
percentage of GDP in the last two decades, it
continues to remain much below the target set
by the Report of the Education Commission
(1964-66) or even that set by the UPA-I
government in the mid-2000s.
At the same, there have been certain positive
developments with regard to Centre-State
Fiscal relationship in financing education, with
the share of the central government in total
government expenditure on education having
risen from 0.61% in 1999-2000 to 0.93% in
2010-11. The increase in Central government
funding notwithstanding, the continued paucity
of adequate resources spent on education has
given rise to processes that have the potential
to exacerbate inequality. Among various
such processes, the significant ones relate to
dilution of quality norms in education and
increasing reliance on private education even
for schooling. The increasing role of private
institutions in education has constrained access,
especially among the less well-off sections of the
population.
Child Protection, which has traditionally been
a neglected area, has witnessed some increase
in Central government expenditure with the
initiation of the Integrated Child Protection
Scheme (ICPS). However, even at present the
budget allocated remains much below that
required for fulfilling the objectives of the
scheme.
One of the positive moves in the period of
liberalisation has been the initiation of the
employment guarantee programme, MGNREGA.
Such “inclusive” public expenditure assumes
great significance in mitigating inequalities
generated by market-led development model
followed under liberalization. Studies show that
MGNREGA, where successful, has helped to
reduce both economic and social inequalities.
Increased spending in the initial period resulted
in a sizeable rise in the number of rural
households getting work under MGNREGA.
However, with the economic crisis hitting India,
Central government funding for the programme
has reduced drastically. In effect then, the
enormous potential that MGNERGA has in
lowering inequalities is still to be realized.
Policy
Recommendations
While mapping of inequalities are necessary,
understanding inequality outcomes necessitate
an immediate focus on process indicators.
There is a need to consider the processes that
generate the observed inequality outcomes, and
here policy interventions are most important.
Conclusion and Recommendations
even on programmes that are universally
acknowledged to be critical for welfare of
the country’s children continue to be a major
concern.
Macroeconomic policies have a direct link to
development and reduction of inequalities and
must be designed to encourage employment
creation directly and indirectly. Below are
some of the fiscal policy choices that improve
distributional outcomes and reduce inequalities.
• The low level of capital expenditure has to
be increased significantly to create domestic
productive and infrastructural capacities.
• In particular, public investments in
agriculture, agricultural research and
rural infrastructure have to be increased
significantly.
• Tax exemptions for capital gains should
be removed, both from the point of view
of reducing income and asset inequalities
and for increasing revenue mobilisation
domestically. This would also make the tax
structure significantly more progressive.
In a situation when even the organised sector
household incomes have not been rising, even
85
REDUCING INEQUALITY
relatively low rates of inflation can immediately
and directly affect the conditions of children.
But an excessive focus on inflation control
through consistently higher interest rates can
create higher unemployment and thereby
worsen inequalities. Removing the deflationary
bias of monetary policies require moving away
from a single-minded focus on interest rate
management and including financial policies that
reduce vulnerability to crisis. This would involve:
• directed credit and other ways such as
guarantees for encouraging banks to lend to
more employment generating sectors;
• a focus on financial inclusion of small
producers in informal activities.
• creation of specific packages for sectors
such as agriculture and small-scale
enterprises;
• creation of specific packages for regions
identified as priority areas for addressing
regional disparities; etc.
• Dynamic management of capital flows to
reduce the possibility of financial booms and
busts and to ensure that current account
deficits are financed with stable and nondebt creating kind of foreign capital inflows.
Public expenditure in the social sectors has to
increase substantially to increase both availability
and access to basic public goods and services.
Education
• Public funding needs to increase to at least
6 per cent of GDP as set by the Kothari
Commission report in the mid-1960s.
• Recommendations by a sub-group
formed by the Ministry of Human
Resource Development to review the
operationalisation of RTE Act, that the Union
government should shoulder the major
part of the responsibility (75 percent) of
garnering funds to implement RTE Act, needs
to be adopted.
86
The recommendations of the Tapas
Majumdar Committee Projections for
outlays to universalise elementary education
need to be followed to reduce inequities in
access to education.
• Learning outcomes should be emphasised
rather than school attendance to improve
the quality of elementary education. Teachers
as well as the parents should be engaged in
the process for an effective assessment.
• As per the recommendations of the Right to
Education Act, child’s mother tongue should
be used as medium of instruction at the
primary level.
Health
• In addition to increasing public funding to
at least 3 per cent of GDP, measures to
universalise basic health services need to be
initiated urgently.
• Per capita public spending on health across
different states needs to be equalised so as
to ensure greater equity in entitlements to
essential healthcare for all citizens.
• Spending on ICDS needs to be increased in
line with the objectives it aims to fulfill. In
this context, the AWWs and AWHs need
to be paid adequate remuneration and their
employment regularised.
• Bringing in measures to regulate the private
medical sector is also extremely necessary.
The Public Distribution System
• Given the large exclusion of poor
households from the PDS since it was
converted into a targeted scheme in the
1990s, strategies for food security must
begin with increasing public funding for:
• Expanding and revamping a universal PDS;
• Improving domestic food supply through
measures like remunerative crop prices, credit
to small farmers, providing inputs at affordable
• Cash transfers must be additions to public
provision, not substitutes.
Water and Sanitation
The overall budget allocation for rural water
supply and sanitation has recently increased, but
the urban sanitation has not received the due
attention. While increased investment is a part
of the challenge, there are several other issues
that need to be addressed:
• Investment should be prioritised in a sense
that the regions that are lagging behind the
most should be targeted first.
Conclusion and Recommendations
prices, more public investment in agricultural
research and extension services, etc.
• While advocating for sanitation programmes
especially in rural regions, it is important
to consider the cultural factors and levels
of literacy and try to create awareness
among the community and generate effective
demand from them.
• For household sanitation and effective
drainage system, affordable and sustainable
options need to be explored.
• Although government has been emphasising
on Public Private Partnership (PPP) projects,
there are limitations for the state and local
bodies to implement such projects. Hence
effective implementation of PPP is needed to
overcome the limitations of the local bodies.
87
REDUCING INEQUALITY
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