Draft for discussion
Statistics on Education:
Advantages and Limitations for Studies on Social Groups*
P. Duraisamy
University of Madras
I. Introduction
Social statistics are crucial for making informed decision on policy
issues, to formulate appropriate social policy and also to assess the impact
of social and economic policy. There is still a lack of sufficient awareness
on the linkages between data and policy development and as such the
social statistics is still weak and inadequate in India, Education plays an
important role in the process of human development and hence
educational statistics particularly relating to social groups assume
relevance in policy making. .
An important form of inequality among social groups is
educational access, particularly in access to higher education. Unequal
access to education across social groups leads to inequality in skills these
groups bring to labour markets. The educationally backward groups tend
to be pushed to low skill, and hence low paying jobs. This would further
widen the gap in productivity, incomes, consumption, savings etc.,
Studies reveal that inequality in access to and quality of education among
social groups leads to inequality in wages and employment (Heckman et
al. 200?). Besides labour market outcomes, education also has nonmarket benefits and the lower status groups stand to lose these benefits.
Overall, the differences in educational access across social groups would
hinder full and effective utilization of resources and eventually lead to
slower economic growth
The problem of inequality among social groups especially based on
gender, caste, religion and income is not a recent phenomenon in India.
What is appalling is that despite affirmative action (reservation policies of
governments) such disparities remain substantial and their magnitude,
form and causes are still less understood. In this paper I consider the
database on education in India focusing on the availability and limitations
This is a preliminary draft for discussion at the National Seminar on “Social Group
Statistics and Present Statistical System: Emerging Policy Issues, Data Needs
and Reforms” jointly organised by Indian Institute of Dalit Studies & Ministry of
Statistics and Programme Implementation held at New Delhi during February 23-24,
2012.
*
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o f the data to understand the disparities among social groups. The social
groups considered are gender (male, female), caste (SC/ST, OBC and
Others), religion (Hindu, Muslim, Christian etc.) economic class (poor,
rich).
II.
Sources of Educational Statistics
There are several agencies that collect data pertaining to educational
indicators. The following agencies collect and disseminate data on
regular basis:
(i) Selected Educational Statistics (SES), published annually by the
Ministry of Human Resource Development (MHRD), Government
of India (GOI).
(ii) Employment and Unemployment Surveys (various rounds) of the
National Sample Survey Organisation (NSSO), GOI.
(iii) Population Census of India, published by the Registrar General,
Census of India, GOI.
School education data at National, State and District level are
provided by the DISE. The UGC collects data on higher education from
Universities and Colleges and these are published in its annual report.
There are other agencies such as MCI, AICTE, ICAR, ICSSR, ICHR and
ICPR which also provide statistics relating to institutions and research
output. National level surveys of the CERT, socio-economic surveys of
the NCAER and the NFHS conducted by the IIPS also provide data on
education. There is very limited information on social groups in these
surveys. The focus of this paper is on the three sources of data mentioned
above with specific attention to higher education on which reliable
information on institutions and student enrolment are still hard to come
by.
III. Selected Educational Statistics (SES)
The SES data are compiled by the MHRD based on information
provided by the state governments (as reported by the educational
institutions) and also information provided by the UGC and the Councils
such as MCI, AICTE etc., The data are available on annual basis over a
long period of time and contains information on the number of
educational institutions as well as enrolment in them. The enrolment data
are provided by gender (male, female), level (primary, secondary, and
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higher education), caste (SC, ST and others) and by region (by state and
Union Territories). The SES data are widely used by government and
international agencies. The major advantages of this data base are that it
provides data on a regular basis over a long period time, covers all of
India and data are tabulated based on comparable classification.
However there are several limitations and drawbacks:
(i)
(ii)
(iii)
(iv)
The MHRD does not receive the enrolment data on a timely and
regular basis from some states and hence extrapolations are
used to fill the gaps arising from such delayed/non-reporting by
some of the states.
It is well known that the education institutions over-report
enrolments at school level if grants or benefits are based on
enrolment and underreport higher education enrolment if they
are constrained by sanctioned strength.
The student enrolment in unrecognized institutions is not
collected.
The time lag in collection and dissemination is still more than 3
years.
A. Limitations of Data on Social Groups
The SES data collects information only on enrolment by gender and caste
(SC, ST). However, even the more recent publications do not provide
information on enrolment in OBC category. Further no information is
available on the other social characteristics of the students such as
religion, economic particulars of the family (parental income, education,
occupation etc.,). Hence this data is of limited usefulness to estimate or
study social group inequality.
B. Data Needs and Suggestions for Improvement
From the beginning of the 11th Five Year Plan period (2006-07), the data
pertaining to higher education are being published separately as
“Statistics of Higher and Technical Education “by the Department of
Higher and Technical Education. It is interesting to note that the coverage
has improved. The following additional information on student enrolment
may be collected and disseminated:
1. Students enrolment by SC/ST to include OBC
2. Boys /Girls enrolment by caste groups to reflect multiple
disadvantages
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3. Enrolment by student Religion
4. Enrolment of students from other States
IV. National Sample Surveys (NSS)
The NSS surveys on social consumption and employment and
unemployment gather a lot of information pertaining to education. I
discuss the advantages and limitations of these survey data for analysing
the inequality among social groups.
A. Participation and Expenditure in Education (Schedule 25.2)
The survey on participation in education and expenditure was
conducted as part of social consumption in the NSS 35th (1980-81), 42nd
(1986-87), 52nd (1994-95) and 64th (2007-08) rounds using schedule 25.2.
These surveys collect information on persons in the age group of 5-24
except the recent one which covers the age group of 5-29. Household and
individual level data are available to researchers for the latest two rounds
only. These surveys provide valuable information for computing net
enrolment/attendance rates by education levels (or age groups) and social
groups. It is also possible to examine enrolment by type of management
(government, private aided and private unaided) and unit private cost of
education among others. With increasing educational aspirations and
availability of education through distance mode, people enrol in higher
education even at later ages. To capture this, the 64th round survey
extended its coverage to include persons aged 25-29 years. Further,
information was also collected from persons enrolled in vocational
stream; expenditure incurred on second course and particulars of course
repetition etc.
A. Limitation of the Data for Analysis by Social Groups
Despite the large volume of information collected by these surveys,
the sample design and sample size impose constraints for brining out
reliable estimates of net attendance rates and unit costs for different
educational levels among social groups. For instance, the overall sample
size of the 64th round data is very large (1, 00,681 households and 4, 46
960 persons). But the number of sample persons who are currently
attending schools and colleges is only 73,597 in the age group of 5-29.
The sample size becomes even smaller when we classify by age groups
corresponding to various educational levels (see Table 1). The sample
size corresponding to the social groups is quite small making it difficult
to derive reliable estimates even at the national level.
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Table 1: Sample size of persons currently attending schools/colleges
by age group
Category
All
SC
ST
Muslim
5
6-10
11-13
3,028 31,157 16,192
14-15
9,267
16-17
6,396
18-24 25-29
7,262 295
All
73,597
B. Data Needs and Suggestions for Improvement
(i)
Considering the rapid changes taking place in education and this
being the only survey that provides information to compute net
enrolment rates and private cost of education, it is desirable to
improve the periodicity of the survey. It can be conducted on an
annual or quinquennial basis like the employmentunemployment surveys.
(ii)
The survey design and sampling procedure need to be changed.
The household stratification must give due weight by age-group
of the persons in the household and persons enrolled in
educational institutions. The list of households in a sample
village or urban block was stratified into two (SSA): (i)
households having any member of age 5–29 years enrolled at
primary and above levels and (ii) other households, and 4
households were selected in each stratum. To increase the
sample size of persons enrolled, the NSSO must consider the
stratification of households based on age-group of persons
enrolled such as 5-9, 10-14, 15-17, 18-24, 25 and above
corresponding to primary, secondary, higher secondary and
higher education and select appropriate number of households in
each stratum. In order to ensure sufficient sample size at higher
education level, at least two households must be selected in each
sub stratum age group 18 and above who are enrolled.
(iii)
The available data for school level education is quite good.
However, the data for higher education is inadequate. The NSSO
may consider the possibility of collecting information on
persons who are enrolled in post higher secondary education or
the age group of 18-29. Information on enrolment in selffinancing institutions/courses, quality of the institutions,
performance in terms of grades/class or marks obtained in the
examinations need to be gathered.
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V. Employment and Unemployment Surveys (Schedule 10.0)
The NSS quinquennial surveys on employment and unemployment
(1983, 1987-88, 1993-4, 1999-2000, 2004-5 and 2009-10) provide data
on educational attainment and educational attendance of the population.
These surveys collect information for more than 100 thousand households
and about 500 thousand persons. Thus the coverage is excellent. State and
National level estimates of educational indicators such as NER and EER
can be computed from these surveys.
A. Limitations of the Data for Analysis by Social Groups
(i)
(ii)
The focus of the survey is on employment and unemployment
particulars and not on compiling data on educational enrolment
and attendance. Enrolment by type of institution, cost of
education and at higher educational level the courses in which
enrolled is not available.
Sample size is a constraint if we want to make estimates at the
state level by social groups.
B. Data Needs and Suggestions for Improvement
(i)
(ii)
The scope of the survey may be enlarged to include additional
questions for persons who report their activity particular as
“studying”. The details about the course (general, technical),
level (UG, PG), year of study, type of institution (Govt, private,
self financing), mode of education (regular, distance) etc., may
be collected incorporating a separate section for these persons
The sample size for certain social groups is not sufficient to
make estimates at the State level. The NSSO may consider the
possibility of increasing the sample size or stratification based
on social groups.
VI. Population Census
The decennial population census is yet another source of data that
provides enrolment and educational attainment of the population. It is
wider in coverage and is collected from households. One has to however
depend on published tables and information at individual level are not
available for generating tables by various sub-groups. Whereas for urban
areas it provides detailed classification of education, for the rural areas
the classification is too broad namely graduates and above. Further, the
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population census data does not distinguish between enrolment in
professional degree and in diploma programmes. It is collected once
every ten years and hence it is not possible to construct long time series
data.
At the higher education level, there is a need for finer classification
based on levels of education (UG, PG, MPhil/PhD, Diploma, Certificate)
in both general and technical education and disciplines (Humanities,
Social Sciences, Languages, Science, and technical degrees such as
agriculture, veterinary science, engineering, medicine, law, education
etc.,
VII. Concluding Remarks
There are two main sources of data on education: (i) collected from
educational institutions (SES, DISE, NCERT survey etc.,) and (ii)
household surveys (NSS, Population Census and occupational surveys by
other agencies such as NCAER etc.). Both the sources are important as
they serve different purposes. The data from institutional sources do not
shed light on student and household socio-economic characteristics such
as caste, religion, occupation, income etc., while the household surveys
do not contain information pertaining to educational institutions.
To improve the data needs for social group level studies, the data
collected from the institutions can be enlarged by collecting additional
information on students’ socio-economic characteristics. Efforts may be
made to ensure timely, regular and accurate reporting of information.
The sampling design and sample size of the NSS household
surveys relating to education and employment and unemployment also
need to be improved. Household stratification based on social groups and
age groups will further enrich the usefulness of these surveys. The NSSO
may consider pooling of central and state samples with a single sampling
framework so that the sample size can be increased to arrive at reliable
estimates by social groups at State level.