Advantages and Limitations for Studies on Social Groups icon

Advantages and Limitations for Studies on Social Groups


Draft for discussion

Statistics on Education:

Advantages and Limitations for Studies on Social Groups1

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 non-market 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 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 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:

  1. 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.

  2. 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.

  3. The student enrolment in unrecognized institutions is not collected.

  4. 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

  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.

  1. 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.

^ Table 1: Sample size of persons currently attending schools/colleges by age group






















^ B. Data Needs and Suggestions for Improvement

  1. 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 employment-unemployment surveys.

  1. 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.

  1. 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 self-financing institutions/courses, quality of the institutions, performance in terms of grades/class or marks obtained in the examinations need to be gathered.

^ 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

  1. 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.

  2. 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

  1. 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

  2. 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 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.

1 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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