Acknowledgements - Documents & Reports - All …documents.worldbank.org/curated/en/616081468042009170/... · Web view59369Report No. 33 South Asia: Human Development Unit Participation

Report No. 33

South Asia: Human Development Unit

Participation in India An Analysis of NSS 64th Round Data

Deepa Sankar

January 2011

Discussion Paper Series

59369

Discussion Papers are published to communicate the results of the World Bank’s work to the development community with the least possible delay. The typescript manuscript of this paper therefore has not been prepared in accordance with the procedures appropriate to the formally edited texts. Some sources cited in the paper may be informal documents that are not readily available.

The findings, interpretations, and conclusions expressed herein do not necessarily reflect the views of the International Bank for Reconstruction and Development/ The World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent.

The World Bank does not guarantee the accuracy of the data included in this work. The boundaries, colors, denominations, and other information shown on any map in this work do not imply any judgment on the part of The World Bank concerning the legal status of any territory or the endorsement or acceptance of such boundaries.

Table of Contents

Acknowledgements........................................................................................................................................1

List of Acronyms...........................................................................................................................................2

Introduction....................................................................................................................................................3

Section 1: Secondary Education Provision Scenario in the Country.............................................................5

Section 2: Secondary Education Participation Trends.................................................................................12

Section 3: Schooling Efficiency at Secondary.............................................................................................15

Section 4: Who Attends Secondary School? A Disaggregated Analysis....................................................19

Section 5: Which School Does the Student Attend?....................................................................................37

List of Tables

Table 1: Number of schools.........................................................................................................................7

Table 2: Availability of primary, middle and secondary schools.................................................................8

Table 3: Secondary schools by type of school management........................................................................9

Table 4: Access to secondary schools: Distance from households.............................................................10

Table 5: Proportion of 14-18 years old with access to a secondary school in desirable distance...............11

Table 6: Age group wise proportion of children / youth in the age group of 5-29 years attending different streams / stages of Education.....................................................................................................................14

Table 7: Proportion of students from various age groups attending different stages of education.............14

Table 8: Details of schooling efficiency as evident from NSS Household survey, 2007-08......................18

Table 9: School participation by location and age group and by stage of education..................................21

Table 10: Description of variables.............................................................................................................32

Table 11: Summary statistics of independent variables.............................................................................33

Table 12: Predicted probabilities of attending and completing secondary education.................................35

Table 13: Multinomial logistic regression predicted probabilities of attending government, aided and private secondary schools..........................................................................................................................40

Acknowledgements

This analysis of National Sample Survey Organization’s 64 th round data on Education was carried out to inform the preparation of the Secondary Education project in India. The findings of this analysis were presented to the officials of Ministry of Human Resource Development (MHRD), Government of India in December 2010. The author would like to acknowledge the support and encouragement provided by Amit Dar and Samuel Carlson. Karthika Radhakrishnan Nair managed the formatting and publishing support.

-1-

List of Acronyms

AIES All India Education Survey ASER Age Specific Enrolment Ratios CSS Centrally Sponsored SchemeGAR Gross Attendance Ratio GER Gross Enrolment Ratio GIA Grants-in-Aid GOI Government of India MHRD Ministry of Human Resource Development MPCE Monthly Per capita Consumption Expenditure NAR Net Attendance Ratio NCERT National Council for Education Research and Training NER Net Enrolment RatioNSS National Sample SurveyNSSO National Sample Survey Organization OBC Other Backward CastesRMSA Rashtriya Madhyamik Shiksha AbhiyanSC Scheduled CasteSEMIS Secondary Education Management Information systemSES Selected Education StatisticsSSA Sarva Shiksha AbhiyanST Scheduled Tribes

-2-

“Secondary education is essential for individual children to achieve their full potential, and for nations to advance social and economic development. Yet, only 60% of children of the appropriate age attend secondary school” (UNICEF, http://www.unicef.org/progressforchildren/2007n6/index_41797.htm.)

Introduction

The significance of secondary education emerges from its critical role in promoting economic growth by determining the quality of those who enter labor market after schooling as well as those who pursue higher education. Secondary education is also important due to the positive externalities on promoting health, social cohesion and sustainable livelihood. Secondary education is undeniably the crucial stage in any education system, as it is in this stage that the elementary school graduates get their basic skills cemented and gain competencies that prepare them to enter either into higher education or into labor market.

While developed economies have been benefiting from developing secondary education early on (countries in North America and Western Europe have secondary gross enrolment ratios (GER) above 100%, while those in East Asia and Pacific are close to 100%), developing countries like India are at a critical juncture where the transformation to such a stage is under way. The Government of India (GOI) has launched a nation-wide program in the mode of a Centrally Sponsored Scheme (CSS) named Rashtriya Madhyamik Shiksha Abhiyan (RMSA, literally translated as National Secondary Education Mission) in March 2009 aimed at improving equitable access to quality secondary education to all. The program is at its infant stage and its implementation needs to be seen in the context of a wide spectrum of issues. One set of issues are related to the opportunities for expansion and improvement of the sector while the other set of issues are mainly due to the size and range of challenges in the process.

The expansion of the secondary education program needs to take into account the impact of similar CSS in elementary education sector in the last decade and a half. The expansion of elementary education in the country (under Sarva Shiksha Abhiyan (SSA), the program for Universalization of Elementary Education) has resulted in an increase in the number of elementary school graduates. This has resulted in an increased demand for secondary education. At the same time, the changing requirements of global labor markets and that of higher education have resulted in focusing on the challenges of quality issues in secondary education sector. Thus the challenges in improving access and quality of secondary education are enormous and diverse – different States are at different levels of secondary education development and have differential capacity to address these issues. There are huge disparities in terms of rural and urban locations, gender, social and economic strata of societies etc.

For targeting the resources under the RMSA, it is important to build an evidence base that could inform the planning and policy decisions. At present, there is very little information available about the status of secondary education participation, except the number of secondary education institutions and students enrolled, as available from Selected Education Statistics (SES, published by the Department of Higher Education, Ministry of Human Resource Development [MHRD]), which is a consolidation of official (administrative) figures reported by States, the latest of which is available for 2007-08. The National University of Education Planning and Administration is the process of developing and consolidating SEMIS – Secondary Education Management Information system – envisaged as an annual Census of schools that impart secondary education and the facilities/ human resources therein. All these data systems, even at its best will only provide the supply side of secondary education provision. In order to

-3-

make any social scheme targeted at needy people, it is important to know the demand side of the program and the reasons for participation or omission, for which information from household surveys are crucial.

So far, studies that look at who are the children attending secondary education in India has been far and few in between. A few studies that provide some information about the secondary education participation at the national level include the reports prepared by National Council for Education Research and Training (NCERT) using the Sixth and Seventh All India Education Surveys (1993-94 and 2002-03) and the reports published by National Sample Survey Organization (NSSO) of India based on the education round surveys (1987-88 and 1995-96), and the World Bank studies (2003 and 2009). To understand the secondary education participation from the household point of view, the data from NSS surveys is perhaps the best source today1.

This analytical report presents the status of secondary education participation2 in India using NSS 64th

round (2007-08). The specific objectives of this policy note are to understand:

the participation rates of adolescents in secondary education, disaggregated by gender, social and religious groups, household economic quintiles and different locations (rural /urban as well as across States)

the transition patterns from elementary to secondary stage and dropouts in between, disaggregated; and the proportion of population who had secondary education; and

Participation in secondary education by type of management of schools.

This policy note is organized in the following way. In the first section, a brief account of the secondary education scenario in the country is provided. In the second section, overall secondary education participation is analyzed. In section three, an analysis of gender and social/ religious gaps in secondary education participation is taken up.

1 While National Family Welfare Survey (NFHS) also collects data from households, the coverage of schooling details is limited. For example, NFHS III (2005-06) covers details of 5-18 years old on whether they attended school during the year and the previous year and the class attended. However, there may be more students attending secondary, many of whom may be above 18 years of age.2 Here, participation is differentiated from enrolments. While officially recorded information reflects enrolments, NSS collects information from household reporting of “attendance” to the course / grade during a particular recall period (two weeks prior to the survey) and hence reflects more on the actual participation.

-4-

Section 1: Secondary Education Provision Scenario in the Country

Secondary education in India is divided into two stages: lower or junior secondary and higher or senior secondary. While the 1964 Kothari Commission recommended a four year secondary education system (which was reiterated by National Policy of Education (1986) and The National Policy on Education and program Action (1992)), the number of years of secondary education varies across States, depending on whether States have adopted an elementary education cycle of eight years3. While education is a subject in the concurrent list of the Indian Constitution, which makes it a responsibility of both Central and State governments, so far the States have been the major player in providing secondary education, with Centre’s role confined to programs such as Kendriya Vidyalayas (since 1965) and Navodaya Vidyalayas (since 1985)4.

In 2002, the Seventh All India Education Survey (AIES) by NCERT reported that there were 90,741 secondary schools and 43,869 senior secondary schools in the country. As per the Selected Education Statistics (2007-08), the number of secondary schools and higher/senior secondary schools had increased to 113824 and 59166 respectively in the country, an indication that many States had made some efforts to improve access to secondary education during the period. The data compiled from Secondary Education Management Information System for the year 2007-08 shows that the number of schools with secondary education sections is around 1.6 lacs (arrived at by including Higher secondary schools that have lower secondary sections / grades attached to it). See table 1 for the number of secondary and senior secondary schools in the country, State wise.

While the overall provision of secondary education seems to have improved, this provision needs to be looked from the point of demand in terms of the adequacy of available schools. In that sense, the adequacy of provision varied across States, and within States, across districts and the nature of provision. Nationally for every 7 primary schools a secondary school was available in 2006-07, this varies across States. For every two primary schools in Kerala, Karnataka, Haryana and Maharashtra, a secondary school was available while in Madhya Pradesh and Uttar Pradesh, on an average, only one secondary school was available for every 21 primary schools. Similarly, the share of States in total schools available also differs from their share in child population. For example, while Bihar accounts for around 10% of child population, it accounts for only around 2.6% of all secondary schools available in the country. On the other hand, Maharashtra, which roughly accounts for 9% of the child population, has around 14% of all secondary schools located in the State. This does not mean that Maharashtra has more schools; it simply indicates that the secondary school facilities available are not enough in the country, and the shortage is even acute in some states. See table 2.

As per the SES 2007-08, 39% of the secondary schools and 34.27% of the senior secondary schools were owned, financed and managed by government / local bodies, around 26% of the secondary schools and 30% of the senior secondary schools were privately managed, but are receiving grants-in-aid from

3 There are 11 States/ UTs in the country which have an elementary cycle of 7 years at present: Assam, Goa, Gujarat, Karnataka, Kerala, Maharashtra, Meghalaya, Mizoram, Dadra Nagar Haveli and Daman and Diu. In these States, the Secondary education stage as of now consists of 5 years (three years of lower secondary and 2 years of higher secondary). The Right to Free and Compulsory Education (RTE) 2009 makes it compulsory for all the States to adopt a national structure of elementary education of 8 years, which will make all States to have a secondary education cycle of 4 years post 8 years of elementary cycle.4 Kendriya Vidyalayas (KV) was established with the aim to establish schools with a common syllabus and medium of education that could be accessed by children of mainly Central government employees on a transferable job. The Navodaya Vidyalayas (NV) was established as residential programs providing quality education to talented rural children. Both these types of schools start with Grade VI.

-5-

government (aided schools). Around 35% of secondary schools and 36% of the senior secondary schools were owned, financed and managed by purely private sector (unaided). In the secondary school provision, government schools accounted for around 96% of all provision in Bihar, while 99% of all secondary schools in West Bengal were grants-in-aid (GIA) schools. In Uttar Pradesh, around 80% of all secondary schools were private unaided schools. Thus overall, there were huge variations across States in terms of who provides and how much. While the SES do not provide information on the geographical distribution of these schools, a broad trend is available from the AISES 2002. Accordingly to AISES 2002 statistics, around 70% of the secondary schools and around 52% of the senior secondary schools are in rural areas. See table 3 for details.

Irrespective of the number of schools, what is important for ensuring participation in secondary education is the “access” part – geographical, social and economic access. While the social and economic access will be taken up for discussion in the broader enrolment and attendance related discussion, it is important to look at the geographical distance to school. Ideally a school mapping exercise would throw best insights into the geographical access to a good quality school, due to lack of information for school mapping, here a simple analysis of finding out how far the secondary schools are from households as the NSS 64th round survey is taken up.

The North Eastern States have high proportion of households who have no access to secondary schools within 5 Km distance. Other hilly States like Uttarakhand and Himachal Pradesh also have more than 10% households who do not have access to secondary schools within 5 km distance. States like Madhya Pradesh, Uttar Pradesh, Bihar, Jharkhand, Chhattisgarh and Rajasthan also have very high proportions of households, especially in rural areas, far removed from the vicinity of a secondary school. See table 4 for details. It is not only that quite a sizeable proportion of households do not have access to secondary schools within 3 Km distance, but also that a large proportion of 14-18 years old children eligible to be attending secondary education also are quite far away from the secondary school locations. Table 5 provides the details.

-6-

Table 1: Number of schools2002AIES

2007-08SES

2007-08SEMIS

2007-08SEMIS

2002AIES

2007-08SES

2007-08SEMIS

Secondary Secondary Up to Secondary

Schools with secondary sections

Senior Secondary

Senior Secondary

Senior Secondary

AP 12,343 16937 16,146 16,742 2,730 4032 1896

Arunachal P. 132 163 150 244 72 97 94

Assam 3,714 5072 4,392 5,146 765 748 1064

Bihar 3,057 2951 2,787 2,934 322 795 151

Chhattisgarh 1,213 2042 1,705 3,966 1,560 2184 2379

Goa 344 375 368 376 76 82 83

Gujarat 4,618 5523 5,239 8,152 2,463 2805 3488

Haryana 3,436 3420 2,168 4,069 1,641 2675 1553

HP 1,320 1300 1,294 2,832 807 1664 1901

J& K 1,503 1025 2,094 2,928 386 473 836

Jharkhand 1,165 1429 1,395 1,770 197 225 449

Karnataka 7,721 11835 10,225 11,283 1,789 3426 2936

Kerala 1,414 3145 2,847 3,303 1,600 2380 2091

M P 4,094 4997 4,550 8,986 3,927 4675 4441

Maharashtra 13,162 15762 14,246 18,953 3,488 4575 5316

Manipur 540 701 670 759 112 103 141

Meghalaya 514 676 666 796 83 98 159

Mizoram 340 508 522 524 45 82 98

Nagaland 256 337 365 444 27 69 110

Orissa 6,398 7434 7,057 7,243 416 1088 568

Punjab 2,230 2330 2,642 5,147 1,749 1780 2563

Rajasthan 5,643 8309 8,023 13,787 2,930 5358 5769

Sikkim 88 111 110 170 43 53 60

Tamil Nadu 4,325 2990 4,366 9,341 4,078 4582 4989

Tripura 403 423 428 723 240 290 295

UP 4,480 7518 5,875 16,143 6,992 8000 10296

Uttarakhand 759 1027 920 2,399 1,068 1335 1483

West Bengal 4,790 4686 4,506 8,303 2,895 3954 3805

A&N Islands 45 44 42 94 48 52 52

Chandigarh 70 69 58 120 56 57 62

DN&H 15 34 18 29 9 10 14

D & D 20 19 17 26 6 9 11

Delhi 452 465 1,171 1303

Lakshadweep 7 4 5 9

Pondicherry 130 163 163 258 73 98 99

TOTAL 90,741 113824 106,054 157,990 43,869 59166 59,252Source: Selected Education Statistics 2007-08, MHRD, All India Seventh Education Survey, 2002-03, NCERT; and SEMIS, NUEPA (author estimates) 2007-08

-7-

Table 2: Availability of primary, middle and secondary schools

Number of primary schools per Share of State in total schools available

every middle school

every secondary school

every sr secondary school

Sr Sec Secondary Middle PrimaryShare of state in

total Area

Share of state in total child (6-13) population

Andhra Pradesh 3.49 3.84 15.90 6.81% 14.44% 5.83% 7.92% 8.37% 6.23%Arunachal Pradesh 2.45 9.65 15.80 0.16% 0.13% 0.19% 0.18% 2.55% 0.12%

Assam 2.65 5.96 36.30 1.44% 4.50% 3.71% 3.83% 2.39% 2.68%

Bihar 3.01 13.61 58.31 1.20% 2.64% 4.37% 5.13% 2.86% 9.91%

Chhattisgarh 2.88 16.27 15.24 3.74% 1.79% 3.71% 4.17% 4.11% 2.19%

Goa 17.17 3.22 15.05 0.14% 0.34% 0.02% 0.16% 0.11%

Gujarat 0.73 3.03 6.45 4.44% 4.83% 7.40% 2.10% 5.96% 4.64%Haryana 2.66 2.04 3.00 3.97% 2.99% 0.84% 0.87% 1.34% 2.09%Himachal Pradesh 4.49 10.04 8.77 2.29% 1.02% 0.84% 1.47% 1.69% 0.50%Jammu & Kashmir 2.57 13.04 28.26 0.82% 0.91% 1.70% 1.70% 6.76% 0.93%

Jharkhand 2.40 16.38 152.75 0.22% 1.03% 2.58% 2.41% 2.42% 2.94%

Karnataka 1.02 2.70 10.39 4.78% 9.39% 9.11% 3.63% 5.83% 4.41%

Kerala 2.24 2.18 2.86 4.15% 2.79% 0.99% 0.87% 1.18% 2.28%

Madhya Pradesh 2.65 20.98 22.07 7.76% 4.18% 12.14% 12.53% 9.38% 6.72%

Maharashtra 1.58 2.69 9.28 7.97% 14.05% 8.79% 5.41% 9.36% 8.62%Manipur 3.33 3.66 24.88 0.18% 0.62% 0.25% 0.33% 0.68% 0.17%Meghalaya 2.81 9.39 64.81 0.17% 0.60% 0.74% 0.81% 0.68% 0.27%

Mizoram 1.57 3.39 21.25 0.14% 0.45% 0.35% 0.22% 0.64% 0.08%

Nagaland 3.16 3.82 29.80 0.09% 0.35% 0.16% 0.19% 0.50% 0.16%

Orissa 2.70 6.31 23.36 3.48% 6.60% 5.67% 5.95% 4.74% 3.20%

Punjab 5.36 5.72 7.73 2.99% 2.07% 0.81% 1.69% 1.53% 1.97%

Rajasthan 1.86 6.86 12.45 8.07% 7.50% 10.15% 7.35% 10.41% 6.44%

Sikkim 3.51 6.79 14.92 0.09% 0.10% 0.07% 0.10% 0.22% 0.04%Tamil Nadu 4.33 6.90 7.42 8.25% 4.54% 2.66% 4.48% 3.96% 4.44%Tripura 2.10 5.05 7.41 0.50% 0.38% 0.33% 0.27% 0.32% 0.25%

Uttar Pradesh 3.11 21.38 16.51 14.50% 5.73% 14.44% 17.50% 7.33% 19.32%

Uttarakhand 3.53 14.61 11.57 2.27% 0.92% 1.40% 1.92% 1.63% 0.83%

West Bengal 40.28 10.17 12.73 6.84% 4.38% 0.41% 6.37% 2.70% 6.90%

A&N Islands 3.36 4.78 4.22 0.09% 0.04% 0.02% 0.03% 0.25%

Chandigarh 3.44 0.42 0.65 0.08% 0.07% 0.00% 0.00% 0.00%

D&N Haveli 1.66 7.35 16.90 0.02% 0.02% 0.03% 0.02% 0.01%Daman& Diu 2.21 2.41 8.83 0.01% 0.02% 0.01% 0.01% 0.00%

Delhi 4.07 5.64 2.10 2.15% 0.41% 0.21% 0.33% 0.05%

Lakshadweep 5.25 5.25 2.33 0.02% 0.00% 0.00% 0.00% 0.00%

Pondicherry 2.70 2.06 3.39 0.16% 0.14% 0.04% 0.04% 0.01%

INDIA 2.57 7.00 13.67 100% 100% 100% 100% 100%

Source: Author Estimates using data from Selected Education Statistics 2006-07

-8-

Table 3: Secondary schools by type of school managementGOVT + LB PRIVATE AIDED PRIVATE UNAIDED

Number %age Number %age Number %age TOTAL

AP 10092 59.6 856 5.05 5989 35.36 16937

Arunachal 112 68.7 18 11.04 33 20.25 163

Assam 2539 50.1 1769 34.88 764 15.06 5072

Bihar 2835 96.1 58 1.97 58 1.97 2951

Chhattisgarh 1221 59.8 0 0 821 40.21 2042

Goa 81 21.6 288 76.8 6 1.6 375

Gujarat 433 7.8 3333 60.35 1757 31.81 5523

Haryana 1663 48.6 79 2.31 1678 49.06 3420

HP 825 63.5 25 1.92 450 34.62 1300

J&K 802 78.2 38 3.71 185 18.05 1025

Jharkhand 973 68.1 225 15.75 231 16.17 1429

Karnataka 4372 36.9 2820 23.83 4643 39.23 11835

Kerala 1017 32.3 1422 45.21 706 22.45 3145

MP 2589 51.8 59 1.18 2349 47.01 4997

Maharashtra 1700 10.8 10005 63.48 4057 25.74 15762

Manipur 201 28.7 102 14.55 398 56.78 701

Meghalaya 14 2.1 458 67.75 204 30.18 676

Mizoram 195 38.4 149 29.33 164 32.28 508

Nagaland 119 35.3 0 0 218 64.69 337

Orissa 3704 49.8 1756 23.62 1974 26.55 7434

Punjab 1740 74.7 210 9.01 380 16.31 2330

Rajasthan 3398 40.9 23 0.28 4888 58.83 8309

Sikkim 93 83.8 1 0.9 17 15.32 111

TN 2033 68.0 695 23.24 262 8.76 2990

Tripura 395 93.4 9 2.13 19 4.49 423

UP 343 4.6 529 7.04 6646 88.4 7518

Uttarakhand 798 77.7 51 4.97 178 17.33 1027

West Bengal 2 0.0 4684 99.96 0 0 4686

ANI 43 97.7 0 0 1 2.27 44

Chandigarh 47 68.1 4 5.8 18 26.09 69

DNH 22 64.7 0 0 12 35.29 34

DD 14 73.7 3 15.79 2 10.53 19

Delhi 197 42.4 28 6.02 240 51.61 465

LK 4 100.0 0 0 0 0 4

Pondicherry 71 43.6 20 12.27 72 44.17 163

All India 44687 39.3 29717 26.11 39420 34.63 113824

Source: Selected Education Statistics, 2007-08, MHRD

-9-

Table 4: Access to secondary schools: Distance from householdsOverall RURAL URBAN

Within 2 Km 2-5 Km >5 Km Within 2 Km 2-5 Km >5 Km Within 2

Km 2-5 Km >5 Km

AP 73.23% 18.19% 8.58% 64.95% 23.30% 11.74% 95.71% 4.29% 0.00%

Arunachal 46.09% 19.40% 34.51% 31.98% 22.89% 45.12% 85.02% 9.78% 5.21%

Assam 53.62% 35.40% 10.98% 49.96% 38.09% 11.95% 82.77% 13.94% 3.29%

Bihar 37.29% 45.39% 17.32% 32.20% 48.65% 19.15% 83.38% 15.85% 0.77%

Chhattisgarh 44.22% 38.48% 17.30% 36.13% 43.16% 20.71% 82.80% 16.16% 1.03%

Goa 63.51% 35.31% 1.18% 61.68% 35.62% 2.70% 64.94% 35.06% 0.00%

Gujarat 62.70% 24.99% 12.31% 42.12% 37.99% 19.89% 94.75% 4.73% 0.52%

Haryana 81.58% 13.29% 5.13% 77.30% 15.52% 7.18% 91.60% 8.06% 0.34%

HP 56.16% 32.50% 11.34% 51.49% 35.96% 12.56% 94.88% 3.90% 1.22%

Jharkhand 38.66% 35.70% 25.64% 28.48% 39.95% 31.57% 82.12% 17.54% 0.34%

JK 44.42% 47.88% 7.70% 34.09% 56.48% 9.43% 89.67% 10.22% 0.11%

Karnataka 69.44% 24.56% 5.99% 55.69% 35.17% 9.15% 95.43% 4.53% 0.04%

Kerala 62.21% 32.47% 5.31% 57.29% 36.35% 6.36% 76.85% 20.94% 2.21%

Maharashtra 73.05% 18.30% 8.65% 61.85% 24.62% 13.53% 88.43% 9.63% 1.94%

Manipur 59.70% 25.46% 14.84% 49.41% 30.47% 20.12% 84.90% 13.20% 1.90%

Meghalaya 45.78% 24.20% 30.02% 35.25% 28.25% 36.50% 92.68% 6.14% 1.17%

Mizoram 78.11% 2.13% 19.76% 62.82% 2.01% 35.17% 97.00% 2.27% 0.73%

MP 40.16% 28.99% 30.85% 25.23% 34.67% 40.10% 85.95% 11.58% 2.47%

Nagaland 70.87% 17.22% 11.92% 62.00% 21.89% 16.11% 96.08% 3.92% 0.00%

Orissa 59.13% 30.48% 10.39% 54.54% 33.55% 11.91% 84.75% 13.35% 1.90%

Punjab 76.29% 21.40% 2.31% 65.29% 31.91% 2.80% 95.44% 3.10% 1.46%

Rajasthan 59.46% 23.21% 17.32% 47.71% 29.64% 22.64% 96.62% 2.87% 0.51%

Sikkim 62.67% 25.68% 11.66% 58.87% 28.70% 12.43% 85.43% 7.58% 6.99%

TN 64.04% 24.98% 10.98% 44.34% 36.61% 19.05% 89.55% 9.91% 0.54%

Tripura 73.39% 18.16% 8.46% 67.03% 22.45% 10.52% 99.42% 0.58% 0.00%

UP 47.56% 35.20% 17.24% 35.14% 43.03% 21.83% 91.10% 7.75% 1.15%

Uttarakhand 59.63% 27.41% 12.96% 46.77% 35.66% 17.57% 95.74% 4.26% 0.00%

WB 65.44% 28.25% 6.30% 55.59% 36.53% 7.88% 93.06% 5.06% 1.88%

ANI 58.55% 32.54% 8.91% 39.76% 46.67% 13.56% 91.32% 7.90% 0.78%

Chandigarh 100.00% 0.00% 0.00% 100.00% 0.00% 0.00% 100.00% 0.00% 0.00%

DD 64.41% 30.86% 4.73% 50.66% 42.25% 7.09% 92.03% 7.97% 0.00%

Delhi 93.29% 6.26% 0.45% 97.44% 1.82% 0.74% 93.01% 6.56% 0.43%

DNH 39.20% 38.01% 22.79% 28.31% 44.81% 26.87% 100.00% 0.00% 0.00%

LK 90.55% 9.45% 0.00% 84.30% 15.70% 0.00% 97.09% 2.91% 0.00%

Pondicherry 81.25% 16.59% 2.16% 64.71% 30.06% 5.23% 92.92% 7.08% 0.00%

ALL INDIA 59.75% 27.74% 12.52% 47.40% 35.52% 17.08% 90.80% 8.15% 1.05%

Source: Estimated from NSS 64th round, 2007-08

-10-

Table 5: Proportion of 14-18 years old with access to a secondary school in desirable distanceOverall RURAL URBAN

-11-

Within 2 Km 2-5 Km >5 Km Within 2

Km 2-5 Km >5 Km Within 2 Km 2-5 Km >5 Km

AP 72.7% 18.6% 8.7% 64.1% 23.9% 12.0% 95.5% 4.5% 0.0%

Arunachal 42.2% 18.1% 39.7% 27.9% 19.7% 52.4% 81.5% 13.8% 4.7%

Assam 47.4% 43.5% 9.1% 43.5% 46.7% 9.8% 87.8% 10.1% 2.0%

Bihar 40.8% 42.5% 16.8% 34.3% 46.5% 19.1% 83.4% 15.6% 1.0%

Chhattisgarh 46.5% 38.6% 14.9% 39.7% 43.0% 17.3% 85.2% 13.3% 1.4%

Goa 51.8% 47.7% 0.5% 49.9% 48.7% 1.3% 53.0% 47.0% 0.0%

Gujarat 60.3% 27.5% 12.2% 39.9% 40.7% 19.4% 93.6% 6.0% 0.4%

HP 53.8% 34.6% 11.6% 49.8% 37.6% 12.6% 95.4% 3.0% 1.6%

Haryana 79.5% 15.3% 5.2% 75.9% 17.2% 6.8% 91.3% 8.7% 0.0%

J&K 46.2% 47.6% 6.3% 38.5% 54.1% 7.4% 87.2% 12.7% 0.1%

Jharkhand 39.6% 41.9% 18.5% 29.6% 47.4% 22.9% 79.8% 19.6% 0.6%

Karnataka 69.9% 23.7% 6.4% 58.5% 32.4% 9.1% 95.3% 4.4% 0.3%

Kerala 60.1% 33.1% 6.7% 55.3% 36.6% 8.0% 75.6% 21.8% 2.5%

MP 39.9% 31.5% 28.7% 23.5% 37.4% 39.1% 84.0% 15.3% 0.7%

Maharashtra 72.3% 18.5% 9.2% 62.2% 23.9% 13.8% 88.6% 9.7% 1.7%

Manipur 55.9% 26.8% 17.3% 44.9% 32.3% 22.7% 89.2% 10.0% 0.8%

Meghalaya 48.7% 23.9% 27.4% 40.2% 27.5% 32.3% 92.9% 5.2% 1.9%

Mizoram 78.6% 2.9% 18.5% 61.9% 3.7% 34.4% 97.9% 2.0% 0.2%

Nagaland 74.8% 13.6% 11.6% 66.1% 17.4% 16.5% 95.3% 4.7% 0.0%

Orissa 62.8% 27.7% 9.4% 59.2% 30.5% 10.2% 87.0% 8.9% 4.1%

Punjab 72.8% 24.8% 2.4% 62.8% 34.7% 2.5% 93.1% 4.8% 2.1%

Rajasthan 60.0% 23.1% 17.0% 48.9% 29.1% 22.0% 95.4% 3.7% 0.9%

Sikkim 58.3% 28.2% 13.4% 55.8% 30.3% 13.9% 86.5% 4.9% 8.7%

TN 65.7% 24.4% 9.9% 47.9% 35.5% 16.6% 90.2% 9.2% 0.6%

Tripura 70.9% 19.7% 9.3% 65.6% 23.3% 11.2% 98.3% 1.7% 0.0%

UP 47.8% 36.7% 15.5% 36.6% 44.0% 19.3% 90.1% 9.2% 0.7%

Uttarakhand 60.6% 27.1% 12.4% 48.9% 34.6% 16.6% 95.2% 4.8% 0.0%

WB 62.5% 30.3% 7.3% 55.6% 36.0% 8.4% 90.3% 7.0% 2.7%

ANI 60.9% 27.0% 12.0% 48.0% 35.0% 17.0% 86.9% 11.0% 2.1%

Chandigarh 100.0% 0.0% 0.0% 100.0% 0.0% 0.0% 100.0% 0.0% 0.0%

DD 82.1% 17.9% 0.0% 66.9% 33.1% 0.0% 100.0% 0.0% 0.0%

DNH 27.4% 51.5% 21.1% 20.5% 56.4% 23.1% 100.0% 0.0% 0.0%

Delhi 93.1% 6.3% 0.6% 96.2% 2.4% 1.5% 92.8% 6.7% 0.6%

LK 89.0% 11.0% 0.0% 80.1% 19.9% 0.0% 97.2% 2.8% 0.0%

Pondicherry 79.5% 18.5% 2.0% 66.7% 29.3% 4.0% 91.9% 8.1% 0.0%

Total 58.0% 29.4% 12.6% 46.9% 36.6% 16.6% 90.1% 8.9% 1.0%

Source: Estimated from NSS 64th round, 2007-08

Section 2: Secondary Education Participation Trends

-12-

In this section, an analysis of secondary education participation in India is carried out using the following indicators estimated from the household survey: (a) the number of students attending; and (b) gross and net attendance rates (GAR and NAR).

Number of students attending secondary education in India

The MHRD statistics (Selected Education Statistics, 2007-08) shows that in 2007-08, more than 28.2 million students were enrolled at secondary level (grades IX and X) and 16.26 million in senior (or higher) secondary level (grades XI and XII), thus a total of 44.46 million attending grades IX-XII. However, if we take the number of students enrolled in all grades in the existing patterns of secondary education in many states in India, where grade VIII was actually part of secondary education system, the number of students enrolled in “lower secondary” turns out to be around 34 million. In addition, another 180176 adolescents were enrolled for secondary courses and 163245 for higher secondary courses in open schools (Source: National Institute of Open School).

While SES provides information from official sources, using NSS data, it is possible to estimate the number of children actually attending secondary education in the country. NSS 52nd round (1995-96) provided an estimated number of students attending lower secondary (grades IX and X) at around 17.7 million and higher secondary at 8.5 million, and thus lower and higher secondary together, around 26.2 million. An analysis of NSS 61st round data5 (2004-05) estimates shows that the overall enrolments at secondary level (lower and higher secondary levels together) were 45.7 million. Estimates using the latest round of National Sample Survey on education (NSS 64 th round, 2007-08), shows that around 50.6 million children were attending secondary grades (lower and higher secondary taken together) in 2007-08. This is an increase in participation by around 5 million more children in a matter of three years, as evident from a comparison with the secondary enrolments estimated using NSS 61st round. Further disaggregation shows that around 30 million students were attending grades IX and X, but taking together grade VIII enrolments in those states where grade VIII was part of secondary, the overall lower secondary enrolments increase to 33.6 million. Around 17 million children were attending grades XI and XII.

Different measures of Participation

While actual number of adolescents attending secondary grades is one measure of secondary / higher secondary school participation, the participation ratios reveal more in terms of what proportion of the expected age group is attending secondary schools. Using official statistics, one derives gross enrolment ratios (GER), net enrolment ratios (NER) and age specific enrolment ratios (ASER), depending on the nominator and denominator concerned, for various purposes. As per Selected Education Statistics, the Gross Enrolment Ratios (GER) at lower secondary level (enrolments in grades IX-X as a percentage of 14-16 years adolescents) was 58% (SES, MHRD, 2007-08), and for higher secondary level (grades XI-XII enrolments as a percentage of 16-18 years adolescents) was 33.5%. However, the GER/NER estimations from official sources may get predisposed due to problems in age-group population projections using decadal population Census data.

The estimations using household survey data like NSS have its own advantages. First, the focus is not on enrolments, but on actual participation in terms of attending secondary schools. Secondly, the denominators to estimate the rates are from the same survey data and not Census projections. However, the disadvantage is that such survey data is not available on a yearly basis, hence possible to estimate the enrolment / participation rates at certain points in time.

5 National Sample Survey covers different issues in different rounds. So far, there have been three rounds that specifically covered education issues – 42nd round (1986-87), 52nd round (1995-96) and 64th round (2007-08). Other rounds also provide rich information about the household members’ participation in education. The 61 st round (2004-05) was basically an employment / unemployment survey round, but covered education participation. However, the 61st round schedule did not differentiate the participation in lower and higher secondary, and hence we do not have the estimates for participation in lower and higher secondary separately for comparative purpose.

-13-

Corresponding to official GER, NER and ASER, using NSS data one could estimate the gross attendance ratio (GAR), net attendance ratio (NAR) and age specific attendance ratios (ASAR). Graph 1 below shows the discrepancies in GER and GAR estimated using official data and NSS data for different stages of education. Graphs 2-4 shows the ASAR, GAR and NAR compared across different age groups and stages of education, and the improvements between NSS 52nd round (1995-96) and 64th round (2007-08). The graphs clearly indicate (a) an improvement in participation at all levels /stages of education from 1995-96 to 2007-08; and (b) lesser participation in secondary education compared to primary / upper primary education.

Graph 1 Graph 2

Primary Upper primary Secondary Sr. Secondary0%

20%

40%

60%

80%

100%

120%

114%

79%

58%

34%

104%

84%

70%

48%

Comparison of GER (Dept of Edu data) and GAR (Household survey :NSS)

Gross Enrolment Ratio (GER): Dept of Education; 2006-07

Gross Attendance Rate (GAR):NSS; 2007-08

6-10 yrs 11-13 yrs 14-17 yrs 18-24 yrs

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

69% 72

%

50%

14%

88%

86%

64%

18%

Age Specific Attendance Rate (ASAR): All India; (Source: NSS 52nd (1995-96) and 64th (2007-08))

1995-96 2007-08

Graph 3 Graph 4


20%

40%

60%

80%

100%

120%

85%

65%

51%

32%

104%

84%

70%

48%

Gross Attendance Rate (GAR): All India; (Source: NSS 52nd (1995-96) and 64th (2007-08))

1995-96 2007-08


10%

20%

30%

40%

50%

60%

70%

80%

90%

66%

43%

26%

15%

84%

59%

41%

27%

Net Attendance Rate (NAR): All India; (Source: NSS 52nd (1995-96) and 64th (2007-08))

1995-96 2007-08

Estimating country wide GAR in a country as diverse as India is often misleading, especially since different States so far had different policies for “age at entry” to school, and hence having a uniform age group as denominator is often not provide appropriate estimates. The same issue applies to the estimations of Net Attendance Ratio (NAR) also. Hence, it is important to look at all these indicators in a much more integrated manner. This is done by analyzing various factors.

Here we take up two issues- age at entry and the attendance status of 5 year olds. The analysis of data reveals that around 46% of all 5 year olds were already attending schools. Further, a whopping 58% of all 6-29 years old reported that they entered school when they were only 5 years of age. These indicators points to the fact that many children might have reached grade IX by the time they reached 13 years of age or before attaining 14 years of age. Hence, the idea of taking the 14-15 years as the age group for

-14-

participating in secondary education may not provide an accurate picture of gross or net participation rates. In addition, an analysis of the age profile of children who were attending secondary education shows that around 10% students were less than 14 years of age. Further disaggregation shows that in grade IX, 27.6% of children were less than 14 years of age.

Similarly, not all children enter school by the time they were 6 years of age, as many enter school late, and many repeat some of the grades before reaching secondary education. Hence not all 14-15 year olds were in the secondary grades where they fit in when the age appropriate grades are considered. Around 27% of 14-15 years old were still attending primary / upper primary grades. Around 32% of the students attending secondary grades (grade IX and X) were above 16 years of age or more.

Among the 14-15 years old, ASAR was around 71.4% while among 16-17 years old, it was around 55%. However, among the 14-15 years old, 27% (or 37% of those who were currently attending school) were attending grades below secondary (elementary grades), thus virtually only 44% of the total population in the age group were currently attending secondary education. On the other hand, only 58% of those attending secondary education was from the 14-15 years old group, with rest, mostly from an age group above 15 years. Similarly, only around 28% of all 16-17 years old were attending senior / higher secondary education, with around 25% still attending below higher secondary, and within higher secondary, only around 58% belonged to 16-17 years of age. See tables 6 and 7. The analysis virtually shows that it is not enough to merely look at GAR or NAR.

Table 6: Age group wise proportion of children / youth in the age group of 5-29 years attending different streams / stages of education

Attending primary (gr I -V)

Attending middle (gr VI-VIII)

Attending secondary (gr IX-X)

Attending Sr secry (gr

XI-XII)

Attending above Sr Secondar

y

Out of school Total

5 years 46.1% 53.9% 16,785,6786-10 years 84.5% 3.6% 12.0% 118,777,18011-13 years 22.7% 58.7% 4.7% 13.8% 63,715,87614-15 years 2.6% 24.4% 41.0% 3.4% 28.6% 42,753,35716-17 years 0.5% 3.8% 20.1% 27.5% 2.8% 45.3% 37,415,23218-29 years 0.0% 0.1% 1.0% 3.1% 7.8% 87.9% 195,499,850

Table 7: Proportion of students from various age groups attending different stages of educationAttending primary

(grade I-V)

Attending middle (gr. VI-VIII)

Attending secondary (gr IX-X)

Attending Sr secondary

(grade XI-XII)Attending 12+ Out of school

5 years 6.2% 3.9%6-10 years 81.0% 7.9% 6.1%11-13 years 11.7% 69.7% 10.1% 3.8%14-15 years 0.9% 19.4% 58.3% 8.1% 5.3%16-17 years 0.1% 2.7% 25.1% 57.6% 6.5% 7.3%18-29 years 0.0% 0.3% 6.5% 34.2% 93.5% 73.7%Total 123,861,525 53,653,097 30,013,426 17,840,173 16,392,980 233,185,972

Section 3: Schooling Efficiency at Secondary

-15-

Of the several measures of schooling efficiency, the significant ones are retention rates (within secondary and senior secondary), transition rates (from the exit grade of upper primary to entry grade of secondary stage) and completion rates (grade 10 and 12). In this section an attempt to look at these indicators using NSS data is made.

There are different ways in which completion rates of a particular stage could be looked at. One simple method is of estimating “gross completion rates”. In simple words, gross completion rate is a measure in which the total number of grade / stage completers (irrespective of whether the proportion /number of students in the cohort achieving the expected competencies) in a particular academic year is taken as a proportion of total number of children in the expected age group. The secondary education completion rate, using this crude method, will be calculated as the number of students who completed grade X in a particular year, (irrespective of the proportion /number of students in the cohort who passes the Secondary school completion board exams), as a proportion 16 year olds. Using NSS 2007-08 data, while the total number of children who completed grade X in 2006-07 was estimated to be 12.46 million, and the gross completion rate for 2006-07 was estimated to be 59.4%.

Another measure of gauging completion rates is to look at the age specific completion rates. This is a measure in which the proportion in a particular population who has completed a particular stage of education is assessed, irrespective of the year in which the students completed or the cohort in which the students were part of. See graphs 5 and 6 below which compares the distribution of grade X enrollees and the proportion of secondary education completers in each age group.

Graph 5 Graph 6

14 yrs; 14%

15 yrs; 35%16 yrs; 30%

17 yrs; 10%>17 yrs; 11%

Age wise distribution of students attending grade X : 2007-08

15 16 1718-19

20-2425-29

30-4546-60

60-75

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

7.6%

28.7%

45.6%

42.8%

38.8%

31.9%

23.6%

16.9%

11.0%

Proportion of the age /age group population who have completed secondary (or above) education: 2007-08

age / age group

Applying this method to different age groups in the population, it is possible to look at the progress in secondary school completion over the years (by looking at the proportion that had completed secondary education from oldest to the youngest population groups). Graph 7 shows that while only 10% of the population in the 65+ years’ age group had secondary education, it had increased to 38% of the population in the 18-25 years age group. However it also shows the slow progress made in four decades.

One of the measures of estimating completion rates is the cohort completion rates, wherein the number of students entered into the school system in a particular year is tracked for completion of secondary school education without repetition or dropping out in between. To estimate this, data is needed for 10 years, which is not possible using a one-time household survey. However, this is possible using school surveys, if data is available for ten years. See graph 8.

Graph 7 Graph 8

-16-

65+ years 56-65 years 46-55 years 36-45 years 26-35 years 18-25 years0%

5%

10%

15%

20%

25%

30%

35%

40%

10.41%13.42%

18.21%21.66%

27.82%

38.01%

Percent of population with secondary or above education:

Age group

primary elementary Secondary0%

10%

20%

30%

40%

50%

60%

70%

58.60

%

43.90

%

32.98

%

58.50

%

50.77

%

40.11

%

Cohort retention / completion rates using Selected Education Statistics (MHRD) data

1990-91 cohort 1997-98 cohort

While secondary education participation and completion rates are important indicators, it is equally important to look at transition rates – both transition from elementary to secondary as well as from secondary to senior secondary and higher education. Participation in secondary education of a student depends on his/ her completing elementary. Hence it is important to look at elementary completers.

As per the District Information System for Education (DISE)6 data of 2005-06, 11.3 million children were attending grade VIII. The enrolment in Grade IX in the next year (2006-07) was, according to Selected Education Statistics (SES, MHRD) 13.4 million. However, it is not clear whether such disparities in enrolment figures (increase in grade IX compared to the enrolments in grade VIII in the previous year) is due to under – enumeration of grade VIII enrolments by DISE or an over-reporting of the number of enrolments in grade IX in SES.

Tracking transition from elementary to secondary, from secondary to higher secondary and higher secondary to higher or technical education is possible using the NSS data since NSS collects information about the status of attendance in two years (current and previous years)7.

As per the 2007-08 NSS data, there were 17,962,764 students who were in grade 8 in the previous year (2006-07), of which 561,262 went on to repeat grade 8 in the current year (or year of the survey, which roughly translates into a repetition rate of 3.1%), and 1,596,869 reportedly dropped out after completing grade 8 last year (a crude dropout rate of around 9% after grade 8). Similarly in grade 9, in the year of survey, 16,445,056 students were attending, of which 621,901 were repeaters (3.8% of those currently attending were repeaters). Adjusting for these figures, it turns out that the transition rates from grade 8 to grade 9 was 88%. This is slightly less than the transition rates from primary to upper primary, which was around 92%, but better than the transition rates from secondary to senior secondary, which was only 75%. However, if the state specific grades for different stages of education is considered, the transition rates differs, as shown in graph 10, transition rates B.

Graph 9 Graph 10

6 DISE is virtually a school census – of all recognized elementary schools in the country, done every year7 NSS provides information on (a) for those students currently attending, current grade of attendance, and (b) grade they attended in the previous year, using both of which it is possible to know who transited from grade 8 last year to grade 9 this year; NSS also provides information about children who dropped out by age and grade, using which it is possible to estimate the number of children who dropped out last year after completing grade 8. Putting this information together, it is possible to estimate a crude transition rate from upper primary to secondary and completion rates.

-17-

grade 5 grade 8 grade 100

5,000,000

10,000,000

15,000,000

20,000,000

25,000,000

20,826,383

17,962,287

12,461,808

19,103,826

15,823,155

9,350,899

Transition from the last grade of a stage to the first grade of the next stage: NSS 64th round 2007-08

Total attended the last grade of the stage in prev year

transited to next grade this year

Primary to Upper Primary Upper Primary to Secondary Secondary to Sr Secondary0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

91.7%

88.1%

75.0%

92.0%

87.0%

71.1%

Transition rates estimated using NSS 64th round : 2007-08

transition rates A transition Rates B

Transition Rate A refers to transition rate from grade 5 to grade 6 (primary to upper primary)/ grade 8 to grade 9 (upper primary to secondary) and grade 10 to 11 (secondary to senior secondary) while transition rate B refers to transition from last grade of primary (grade IV in the case of some states and grade V otherwise) to first grade of upper primary (grade V in the case of some and grade VI otherwise); from last grade of upper primary (grade VII/VIII) to first grade of secondary (grade VIII/IX) and grade X to XI for secondary to senior secondary.

An overall analysis shows that in the 14-15 years age group, 29% were not attending any school while 71% were attending some school. Of those who were attending, around 38% (or 27% of overall 14-15 years child population) were still attending elementary grades (grade 8 or below) while the rest were attending secondary grades or beyond. Of those who were not attending schools in the age group, 29% (or around 8% of total children in the age group) were children who had never been to school while the rest were dropouts. Around 77% of all dropouts had not completed grade 8 while the rest dropped out after completing grade 8. Similar trends are observable in older age groups too.

-18-

Table 8: Details of schooling efficiency as evident from NSS Household survey, 2007-08

% attending

% attending

<8

attending 8

attending beyond grade 8

% not attendin

g

never enrolled

ever enrolled

& dropped

out

dropped out before completing

grade 8

dropped out after

completing gr 8

dropped out after

completing beyond

gr 8age14-15

years A B C D E F G H I J

Total 71.36% 11.85% 15.15% 44.36% 28.64% 8.49% 20.04% 15.63% 2.70% 1.71%

Boys 74.61% 12.18% 16.53% 45.89% 25.39% 6.54% 18.75% 14.79% 2.31% 1.64%

Girls 67.62% 11.46% 13.55% 42.60% 32.38% 10.75% 21.52% 16.59% 3.14% 1.79%

SC 65.62% 13.90% 15.37% 36.35% 34.38% 10.54% 23.77% 18.56% 3.60% 1.61%

ST 59.15% 16.24% 15.07% 27.85% 40.85% 12.26% 28.58% 23.98% 3.20% 1.40%

OBC 72.04% 11.50% 14.48% 46.06% 27.96% 9.21% 18.63% 14.14% 2.65% 1.85%

Muslim 54.85% 13.46% 11.86% 29.53% 45.15% 15.59% 29.06% 24.26% 2.94% 1.86%Gen cat Hindu 86.27% 8.39% 17.23% 60.65% 13.73% 2.53% 11.14% 7.87% 1.68% 1.58%

Non-Muslim rel minorities

80.59% 6.54% 15.65% 51.94% 19.41% 4.46% 14.92% 11.74% 1.97% 1.21%

MPCE Q1 61.12% 14.23% 14.14% 32.75% 38.88% 11.39% 27.34% 22.74% 2.74% 1.86%

MPCE Q2 67.74% 13.30% 16.12% 38.31% 32.26% 10.27% 21.95% 17.45% 2.93% 1.56%

MPCE Q3 69.19% 11.98% 15.53% 41.69% 30.81% 9.59% 21.20% 16.56% 2.95% 1.69%

MPCE Q4 77.10% 10.69% 14.93% 51.47% 22.90% 6.15% 16.54% 12.16% 2.55% 1.83%

MPCE Q5 86.99% 7.46% 14.65% 64.88% 13.01% 3.13% 9.77% 6.17% 2.02% 1.58%

age16_17

Total 54.71% 1.92% 2.37% 50.42% 45.29% 8.68% 36.44% 19.59% 6.31% 10.55%

Boys 59.14% 2.06% 2.49% 54.59% 40.86% 6.35% 34.35% 19.14% 5.60% 9.61%

Girls 49.50% 1.75% 2.24% 45.51% 50.50% 11.43% 38.89% 20.10% 7.14% 11.65%

SC 47.76% 2.30% 2.77% 42.69% 52.24% 10.44% 41.72% 25.07% 7.08% 9.57%

ST 42.59% 2.51% 3.58% 36.50% 57.41% 14.30% 43.09% 28.03% 5.25% 9.82%

OBC 53.75% 1.96% 2.41% 49.39% 46.25% 9.35% 36.68% 18.10% 7.03% 11.55%

Muslim 40.50% 2.57% 2.37% 35.57% 59.50% 16.14% 42.56% 26.70% 7.23% 8.64%Gen cat Hindu 71.17% 1.27% 1.77% 68.14% 28.83% 2.71% 26.08% 10.91% 4.54% 10.63%

Non-Muslim rel minorities

64.98% 2.78% 3.44% 58.75% 35.02% 5.59% 29.23% 16.26% 3.93% 9.04%

MPCE Q1 40.78% 2.44% 2.92% 35.42% 59.22% 11.58% 47.40% 28.63% 6.72% 12.05%

MPCE Q2 46.63% 2.00% 2.57% 42.06% 53.37% 11.10% 42.19% 23.66% 7.41% 11.12%

MPCE Q3 51.27% 1.88% 2.16% 47.23% 48.73% 9.98% 38.67% 21.23% 5.74% 11.70%

MPCE Q4 61.10% 2.10% 2.57% 56.44% 38.90% 6.50% 32.19% 15.25% 6.72% 10.21%

MPCE Q5 76.06% 1.09% 1.57% 73.40% 23.94% 3.60% 20.05% 8.09% 4.72% 7.24%

-19-

Section 4: Who Attends Secondary School? A Disaggregated Analysis

The analysis so far has found that around 30 million adolescents were participating in secondary education and another 17.8 million were in higher secondary education. This aggregate picture does not capture the diverse backgrounds from which these students come from. It is equally important to look at who these students are – a disaggregated profiling in terms of gender, social / religious groups, economic class, location etc, with further disaggregation within some of these groups.

The disaggregated analysis here takes into account different types of indicators – the numbers, shares and ratios.

How do Indian States perform on account of secondary education participation?

Secondary education participation differs across States. While the GAR at secondary level was above 100% in States like Kerala and HP, it was below 70% (all India average) in bigger States like Bihar, Jharkhand, UP, MP, Chhattisgarh, Orissa and West Bengal, and even in an economically developed Gujarat. Similarly, NAR at secondary level was around 78% in Kerala while it was only around 26% in Bihar. See graphs 11 and 12 for state wise overall GAR and NAR estimated from NSS 64th round data.

Graph 11 Graph 12

KeralaManipur

HPNagaland

TNMizoram

UttarakhandJK

ArunachalGoa

MaharashtraPondicherry

APTripura

ChandigarhHaryana

KarnatakaDelhi

PunjabMeghalayaRajasthanALL INDIA

GujaratSikkimOrissaAssam

ChhattisgarhWBMPUP

JharkhandBihar

0% 20% 40% 60% 80% 100% 120%

116.4%107.7%

104.0%101.0%

98.9%98.8%

96.7%92.8%

91.5%88.2%

86.3%84.7%

83.6%81.7%81.6%81.3%

80.3%78.7%

74.9%72.8%

71.4%70.2%

66.3%64.2%64.0%63.5%63.1%

60.6%60.0%

58.2%55.0%

49.4%Gross Attendance / Participation Rate at Secondary (Gr IX-X) level

SikkimMeghalaya

BiharMP

ChhattisgarhJharkhand

WBUP

TripuraJK

AssamManipur

RajasthanNagaland

PunjabALL INDIA

GujaratUttarakhand

DelhiArunachal

ChandigarhOrissa

HaryanaGoa

MaharashtraAP

KarnatakaMizoram

PondicherryHPTN

Kerala

0% 10% 20% 30% 40% 50% 60% 70% 80% 90%

11.8%14.7%

25.6%28.5%

30.0%30.5%31.0%31.4%31.6%31.7%

36.1%37.1%37.8%38.4%

40.8%41.0%

42.5%45.6%46.3%46.8%46.8%

48.0%50.6%

55.4%55.7%56.2%

57.3%57.3%

59.0%60.8%

64.5%77.8%

Net Attendance / Participation Rate at Secondary (Gr IX-X) level

-20-

Rural-urban variations in secondary school participation

Another dimension of spatial variations in secondary education participation is evident by the variations across rural and urban areas. As per NSS 64th round, 72% of the households belonged to rural areas while 28% of the households belonged to urban. However, 74% of the population was rural while only 24% urban. However, due to demographic trends in population growth, the proportion further changes when it comes to children or adolescents. Among the 6-10 year olds, 79% of the children belong to rural areas while in the 11-15 age group, around 77% belong to rural areas. However, among the total adolescents attending secondary grades (grades 9 and 10), only 71.6% belong to rural areas. This share further deteriorates when it comes to higher secondary grades (grades 13 and 14) enrolments – only 62% of those enrolled in higher secondary grades were from rural areas.

Graph 13 Graph 14

Pop_age6-10

Grade 1-V

Pop_age11-13

Grade VI-VIII

Pop_age14-15

Grade IX-X

Pop_age16-17

Grade XI-XII

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

79%

79%

77%

75% 77%

72%

72%

62%

21%

21%

23%

25% 23%

28%

28%

38%

Shares of rural and urban in child population and school attendance: NSS 64th round 2007-08

URBAN RURAL

GAR: Rural GAR: Urban NAR: Rural NAR: Urban0%

20%

40%

60%

80%

100%

120%

104.7

%

102.9

%

84.3% 85.0%

82.5%

89.9%

56.7%

65.2%65.6%

85.2%

37.8%

51.3%

41.1%

64.8%

22.7%

39.7%

GAR and NAR by rural and Urban: NSS 64th round, 2007-08

Primary U primary

Secondary Sr Secondary

The rural –urban divide varied across States, and the differences between the two were most prominent in States where the overall participations in general were low (like Bihar, Jharkhand, and West Bengal etc). The ruralurban variations were least pronounced in States with high participation (Kerala and HP) or with more urbanized areas. See graphs 15 and 16.

Graph 15

Ker

ala

Utt

arak

han

d

HP

Man

ipu

r

Ch

and

igar

h

Nag

alan

d

TN

Miz

ora

m JK

Del

hi

Po

nd

ich

erry

Aru

nac

hal

Mah

aras

htr

a

Go

a

Har

yan

a

AP

Trip

ura

Kar

nat

aka

Pu

nja

b

Meg

hal

aya

Raj

asth

an

All

Ind

ia

Sikk

im

Ass

am

Ori

ssa

Ch

hatti

sgar

h

Gu

jara

t

UP

WB

MP

Jhar

khan

d

Bih

ar

0%

20%

40%

60%

80%

100%

120%

Gross Attendance / participation Rate at Secondary (Gr. IX-X) by Location

RURALURBAN

-21-

Graph 16Si

kkim

Meg

hal

aya

MP

Bih

ar JK WB

Jhar

khan

d

Ch

hatti

sgar

h

Trip

ura

UP

Man

ipu

r

Nag

alan

d

Pu

njab

Ass

am

Raja

sth

an

All

Indi

a

Gu

jara

t

Del

hi

Aru

nac

hal

Miz

ora

m

Ori

ssa

Go

a

Har

yan

a

Cha

ndi

garh

Utt

arak

han

d

AP

Mah

aras

htra

Kar

nat

aka

TN HP

Po

ndic

her

ry

Ker

ala

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%Net Attendance / Participation Rate at Secondary (Gr IX-X) by location

RuralUrban

The age appropriate grade / education sub-stage enrolment was also better in urban areas. See table below where the shaded areas indicate the age appropriate stage enrolments. While at primary level the disparities are almost nil, by the time of upper primary enrolments, the differences started showing up and at secondary and higher secondary level, the differences are huge. This is also because the proportion of 14-17 years old attending upper primary stage have been more in rural areas than in urban areas.

Table 9: School participation by location and age group and by stage of educationOut of school Attending Gr 1-5 Attending Gr 6-8 Attending Gr 9-10 Attending Gr 11-12

RURAL URBAN RURAL URBAN RURAL URBAN RURAL URBAN RURAL URBAN

Age 5 55.15% 49.59% 44.85% 50.41%

Age 6_10 12.67% 9.45% 84.32% 84.99% 3.01% 5.55%

Age 11_13 14.75% 10.82% 24.57% 16.55% 56.74% 65.22% 3.94% 7.41%

Age 14_15 30.92% 21.20% 2.85% 1.81% 25.92% 19.38% 37.79% 51.34% 2.52% 6.26%

Age 16_17 51.55% 39.29% 0.52% 0.38% 4.27% 2.63% 20.94% 17.96% 22.72% 39.73%Age 18_plus 95.75% 95.82% 0.02% 0.01% 0.10% 0.04% 1.12% 0.71% 3.00% 3.42%

-22-

Are girls and boys participating in secondary education in an equal manner?

The starting point of a gender- disaggregated analysis is the sex ratio in the population. Among 5-18 years old population, sex ratio has been abysmally low – below 900. The analysis of sex ratio among different age groups show that in the 6-10 years of age group, sex ratio was 857 (only 46% of the age group population was girls), among 11-13 years age group it was 870 (46.5% of the total population being girls), among 14-15 age group it was 866 (or girls account for 46.4% of total population in the age group), and among 16-17 years age group, it was as low as 850 (girls account for just 46% of total population in the age group). This means that among the younger population, the difference between the shares of boys and girls were already around 7-8 percentage points.

While girls accounted for a little more than 46% of the population, they accounted for more than half of the total population currently not attending schools. The gap in the proportion of girls and boys attending schooling were more or less the same till they were around age 11, after which, the proportion of girls attending schools always fell below that of the boys. See graphs 17 and 18. Correspondingly, the share of girls in total students attending was less than their share in total population. While the sex ratio among population remained somewhere more than 850 girls for every 1000 boys, in education participation, the sex ratios were below that. At primary level, the sex ratio was 833, at upper primary level, 804 (both at primary and upper primary level, boys accounted for 55% of participating students while girls account for 45%), at secondary level, sex ratio was 739 (boys’ share in education participation increase to almost 57.5% and the rest, girls), and at senior secondary level, sex ratio of only 676 (boys constitute 58% of all participants with only 42% girls). As per the estimates from NSS 64 th round, in 2007-08, around 17.3 million boys attend secondary education while only around 12.8 million girls attend the same. Similarly at higher secondary level, 10.6 million boys and 7.2 million girls attended.

Graph 17 Graph 18

5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Education participation rates among 5-29 year olds by gender: NSS 64th round (2007-08)

MALEFEMALE

Age

Primary (gr I-V) Middle (gr VI-VIII) Secondary (gr IX-X) Sr Secondary (gr XI-XII) Above Sr Secondary0%

10%

20%

30%

40%

50%

60%

70%

54.55

%

55.43

%

57.49

%

59.67

%

58.40

%

45.45

%

44.57

%

42.51

%

40.33

%

41.60

%

Shares of boys and girls in total students attending: NSS 64th round (2007-08)

Boys Girls

The ASAR, GAR and NAR also shows that girls lag behind boys in participation, and the gender gaps becomes more intensive with each successive stage of education, thus while primary level may have the least disparities, at the secondary and higher secondary level, the disparities increase. For example, the gap between boys and girls in GAR at primary level was only 3 percentage points, by the time of upper primary it increases to almost 6 percentage points, but at secondary / senior levels, the differences is around 11 percentage points. See graphs 19 and 22.

-23-

Graphs 19 Graph 20

age5 age6_10 age11_13 age14_15 age16_17 age18_290%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%46

.4%

89.0%

88.6%

74.6%

59.1%

14.6%

45.8%

86.9%

83.4%

67.6%

49.5%

9.5%

ASAR among boys and girls: NSS 64th Round 2007-08: All India estimates

Boys Girls

Primary Upper primary Secondary Sr Secondary Higher

0%

20%

40%

60%

80%

100%

120%

105.6

%

87.3%

75.3%

52.6%

14.9%

102.7

%

80.7%

64.3%

41.9%

11.4%

GAR among boys and girls estimated using NSS 64th round 2007-08: All India

Boys Girls

Graphs 21 Graph 22

Primary Upper primary Secondary Sr Secondary Higher0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

85.6%

60.7%

42.7%

29.5%

13.3%

83.1%

56.4%

39.0%

25.1%

10.1%

NAR among boys and girls estimated using NSS 64th round 2007-08: All India estimates

Boys Girls


5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

10%13%

18%22%

28%

38%

17%

21%

26%29%

35%

43%

4%6%

10%

14%

21%

33%

Percent of population with secondary or above education: By gender

TotalMaleFemale

Age group

Gender disparity issues in the participation in secondary education need to be understood in the context of historical trends in education participation among boys and girls. One way of doing this is by looking at the proportion of secondary school completers in adult population by gender. Among the adult population (18 years and above), around a fourth (25.4%) had attained secondary education completion or studied further, but among adult men, 32% had secondary education or above while only 19% of females had the same. Similarly, 18% of adult men and 10.6% of females had higher secondary education and/or above. So historically, fewer females had the opportunity to complete secondary education.

The gender disparities in secondary education participation are not uniform across States. In States that are lagging behind in overall secondary education participation rates, girls’ participation rates also lag behind that of boys (for example, Bihar, UP, MP, Rajasthan etc) while in some States where the secondary education participations are high, girls’ participation was found to be more than that of boys’ (for example, Kerala, Mizoram, etc). See graphs 23 and 24 below.

-24-

Graph 23

Kerala

Mizo

ram

Man

ipurTN HP

Uttarakh

and

Goa

Pondicherr

y

Karnat

aka

Arunac

hal

Nagala

nd

Chandiga

rh

Delhi

JK AP

Harya

na

Mah

arash

tra

Tripura

Punjab

All India

Meg

halaya

WB

Chhattisg

arh

Rajasth

an

Orissa

Sikkim

Assam

Gujarat UP

MP

Jhar

khan

dBih

ar0%

20%

40%

60%

80%

100%

120%Gross Attendance / Participation Rates at Secondary (Gr IX-X) by gender and State

BoysGirls

Graph 24

Sikkim

Meg

halaya

Bihar JK

Jhar

khan

d

Chhattisg

arh

MPAss

am UP

Trip

ura

Rajast

han

Man

ipur

WB

Nagala

nd

Gujarat

Punjab

All India

Arunac

hal

Delhi

Chandiga

rh

Orissa

Harya

na

Uttarak

hand

Mah

aras

htra

GoaAP HP

Mizo

ram

Karnat

aka

TN

Pondicher

ry

Kerala

0%

10%

20%

30%

40%

50%

60%

70%

80%

90% Net Attendance / Participation Rate at secondary (Gr. IX-X) by gender and States

BoysGirls

-25-

Variations in Secondary education participation across Social and religious groups

Taking into consideration the heterogeneity of Indian society, especially given its socio-religious, caste fabric, it is important to see whether children from marginalized groups are getting a chance to pursue their secondary education dreams. Using NSS data on caste groups and religion, this analysis basically looks at social dimensions of secondary education participation in the following lines: (a) social groups by Scheduled Tribes (ST), Scheduled Caste (SC), Other Backward Castes (OBC), and general category Hindus. These groups are compared with muslim minorities and other religions like Christians, Buddhists, Jains etc taken together.

The first level of analysis looks at the share of each of these caste /religious groups in population and this is compared to their shares in participation in different levels of education - primary, upper primary, secondary and senior secondary separately. It is interesting to note that a certain degree of parity in population shares and education participation shares is achieved in all groups at primary level, but the shares of ST and Muslims in upper primary participation / attendance was less than their shares in the relevant age population. At secondary education levels, the ST, SC and Muslim minority students were found to be under-represented as a share (participation shares less than population shares) while the general category Hindus and other religious minorities were found to be over-represented. See graphs 25-28.

Graphs 25 Graph 26

ST SC OBC Other Hindus Muslims Other Religions0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

9.6%

21.1%

44.3%

16.0%

14.9%

4.1%

9.4%

20.5%

44.0%

16.7%

14.5%

4.1%

Population and participation shares of Social / religious groups at Primary level: NSS 64th round 2007-08

% in 6-10 pop % in primary Attendance


5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

9.2%

20.5%

43.4%

17.9%

14.2%

4.8%8.5

%

20.1%

43.0%

20.4%

10.8%

5.3%

Population and participation shres of social / religious groups at upper primary level: NSS 64th round 2007-08

% in 11-13 pop

% in Upper primary Attendance

Graph 27 Graph 28


5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

8.5%

20.6%

43.4%

18.5%

14.1%

4.7%6.4

%

17.9%

43.6%

24.1%

10.3%

5.4%

Population and participation shares of social / religious groups at secondary level: NSS 64th round 2007-08

% in 14-15 pop

% in Secondary Attendance


5%

10%

15%

20%

25%

30%

35%

40%

45%

8.1%

19.5%

42.8%

20.0%

14.5%

5.1%

5.2%

15.5%

42.3%

28.2%

10.1%

6.3%

Population and participation shares of social / religious groups at higher secondary : NSS 64th round 2007-08

% in 16-17 pop

% in Higher secondary attendance

-26-

The under-representation of SC/ ST/ Muslim minority children and adolescents in post- primary education participation compared to their shares in population and the over-representation of general category Hindus and non-Muslim religious minority groups are explained by the GAR and NAR at secondary education level among these groups. At secondary level (grades IX and X) GAR for ST and Muslims were 52.5% and 51% respectively, while that of general category Hindus was 92%. Similarly, the NAR at secondary level was only 27% among Muslims while it was 56% - more than double of that of Muslims -among general category Hindus. See graphs 29 and 30.

Graph 29 Graph 30

ST SC OBC Gen cat Hindus Muslims Other rel minrty0%

20%

40%

60%

80%

100%

120%

102.0

%

101.7

%

103.8

% 109.1

%

101.5

% 105.6

%

78.0% 82

.9% 83.5%

96.4%

64.0%

93.1%

52.5%

61.0%

70.5%

91.7%

51.0%

81.9%

30.5%

37.9%

47.2%

67.2%

33.4%

58.8%

GAR by caste / religious groups: NSS 64th round, 2007-08

Primary U primary Secondary Sr Secondary

ST SC OBC Gen cat Hindus Muslims Other rel minrty0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

83.0%

82.0% 83

.9%

90.2%

79.0%

85.0%

54.0% 55

.6% 58.2%

70.1%

42.6%

64.4%

27.2%

34.1%

41.8%

56.4%

27.2%

46.4%

14.0%

20.6%

28.1%

40.2%

17.2%

33.2%

NAR by caste / religious groups: NSS 64th round, 2007-08

Primary U primary Secondary Sr Secondary

As in the case of other categories, the participation rates not only differ across social and religious groups, but the differences between the groups also vary across different States. The example of a few States is shown for ST, SC and Muslim participants in secondary education in the graphs below.

Graph 31

Arunac

hal

Chhattisg

arh

Jhar

khan

dM

P

Man

ipur

Meg

halaya

Mizo

ram

Nagala

nd

Orissa

Sikkim

Trip

ura

72%

34%

29%

22%

34%

91%

100%

96%

23%

40%

31%

76%

27%

22%

13%

37%

86%

100%

96%

14%

44%

30%

97%

50%41%

35%

119%

68%

99% 101%

39%

70%79%

Secondary education participation of ST across States with >20% ST population

Share in population Share in enrolment GAR

-27-

Graph 32

APBih

ar

Chhattisg

arh

Delhi

Gujara

tHP

Haryan

a

Jhar

khan

d

Karnat

aka

MP

Mah

arash

tra

Orissa

Punjab

Rajast

hanTN

Trip

uraUP

Uttarakh

andW

B

All In

dia0%

5%

10%

15%

20%

25%

30%

35%

40%

0%

20%

40%

60%

80%

100%

120%Secondary Education Participation of SC across States

Share in population Share in participants GAR

Shar

e in

po

pu

lati

on

an

d a

mo

ng

par

tici

pan

ts: S

C

Gro

ss A

tten

dan

ce R

ate:

SC

Graph 33

APAss

amBih

ar

Delhi

Gujara

tJK

Jhark

hand

Karnata

ka

Keral

a

Mahar

ashtr

a

Pondicherr

yUP

Uttarak

hand

WB

Tota

l0%

10%

20%

30%

40%

50%

60%

70%

80%

0%

20%

40%

60%

80%

100%

120%

8%

31

%

14

%

14

%

11

%

67

%

10

%

14

%

32

%

12

%

10

%

20

%

20

%

27

%

14

%

8%

27

%

10

%

9%

6%

60

%

11

%

12

%

31

%

8%

8%

11

%

7%

24

%

10

%

78%

54%

34%

53%

40%

83%

56%

69%

110%

57%

71%

32% 33%

53% 51%

Secondary Education participation of Muslims across States>=10% Muslim population

Share in pop Share in participants GAR

Graph 34

MP Maharashtra Rajasthan WB0%

20%

40%

60%

80%

100%

120%

35

.1%

61

.2%

56

.0%

31

.9%4

3.9

%

39

.6%

27

.9%

60

.5%

59

.4%

81

.6%

50

.3%

52

.8%

68

.7%

89

.4%

77

.2%

60

.3%

78

.3%

10

4.7

%

92

.5%

83

.0%

Secondary education GAR of social groups: Comparison within and across se-lected states

STMuslimSCOBCGen Hindu

-28-

Variations in Secondary education participation by MPCE Quintiles / Deciles

Monthly Per capita Consumption Expenditure (MPCE) of the households is used as a proxy for grouping households into economic status quintiles for the analysis here. While households may be classified into the “richest 20%” or “poorest 20%” households, the proportion of child population in each of the quintiles differs due to the demographic features in these categories of households. Given low fertility / population growth rate, the richest 20% households usually accounts for less than 20% children while the poorest quintiles account for more children than the household proportions. School participation is also looked at in this context. As could be seen from the graph below, given the near universalization of primary education, the variations in participation shares of each of the quintiles is more or less closer to their population shares. However, by secondary education stage, the differences become apparent.

Graph 35

Pry: Pop

Pry: Attend

U Pry: pop

U Pry: Attend

Sec: Pop

Sec: Attend

High Sec: Pop

High Sec:

Attend

Higher edu: pop

Higher edu:

Attend

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

21.2

%

20.8

%

19.7

%

18.2

%

19.6

%

14.8

%

17.1

%

10.9

% 21.6

%

7.2%

26.3

%

25.7

%

25.0

%

24.2

%

23.8

%

21.0

%

22.1

%

16.8

%

21.4

%

13.0

%

22.3

%

22.3

%

22.3

%

22.0

%

21.9

%

21.2

%

22.1

%

19.8

%

19.3

%

16.7

%

18.4

%

18.9

%

20.0

%

21.1

%

20.9

%

24.1

%

22.3

%

26.9

%

20.8

%

25.8

%

11.8

%

12.2

%

12.9

%

14.5

%

13.8

%

18.9

%

16.4

%

25.6

%

16.9

%

37.2

%

Shares in population and participation in education by stage of education and MPCE Quintiles: NSS 64th round 2007-08

MPCE Q5MPCE Q4MPCE Q3MPCE Q2MPCE Q1

The GAR and NAR graphs also show similar divergence. See graphs 36 and 37 below. The variations across States are also apparent. On an average, at all India level, the differences are around 30 percentage points. It is interesting that while Bihar and Jharkhand share a common past, the variations in secondary education participation among the rich and poor are very stark in Bihar while much less in Jharkhand. Interestingly, the poor in Jharkhand is less disadvantaged than compared to Bihar while the richest in Bihar is better off than the richest in Jharkhand.

-29-

Graph 36 Graph 37

MPCE Q1 MPCE Q2 MPCE Q3 MPCE Q4 MPCE Q50%

20%

40%

60%

80%

100%

120%

102% 102% 105% 107% 107%

78%81% 83%

89%94%

53%

62%68%

81%

96%

30%36%

43%

58%

74%

GAR by MPCE Quintiles: NSS 64th round; 2007-08

Primary U Primary



10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

82.8% 82.6% 84.6% 86.4% 88.5%

53.2%55.9% 57.5%

62.1%

69.3%

31.0%35.8%

38.9%

46.4%

59.2%

17.6% 19.9%25.1%

30.8%

46.5%

NAR by MPCE Quintiles: NSS 64th round; 2007-08

Primary U Primary


Graph 38

Punjab

Rajast

han JK WB

MP

Chhattisg

arh

Bihar

Assam UP

Uttarak

hand

All In

dia

Jhar

khand

Harya

na

Gujara

t

Delhi

Orissa

Mah

aras

htra

Karnat

aka

AP TNKer

ala

HP0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

8.0% 10

.9%

13.2

%

17.4

%

18.0

%

18.4

%

18.7

%

19.5

%

22.4

%

27.8

%

31.0

%

31.2

%

33.3

%

34.0

%

39.6

%

39.6

% 48.8

%

49.9

%

51.6

%

53.2

%

56.5

%

80.2

%

58.6

%

56.9

%

37.6

%

61.4

%

63.0

%

42.6

%

59.3

%

54.6

%

45.4

%

65.7

%

59.2

%

42.0

%

65.2

%

62.2

%

58.3

%

52.6

%

66.7

%

66.8

% 75.2

%

75.4

%

87.3

%

69.1

%

Secondary Education NAR among the richest and poorest 20% households across States

MPCE Q1: poorest 20% HH MPCE Q5: Richest 20% HH

-30-

Secondary education: Trends over the years: An analysis using secondary educated among different age groups

Using NSS data, it is possible to estimate what proportion of the adult population had the opportunity to complete secondary education. Overall, among the 18+ years age group, while 53% had primary or more education and 39% had upper primary or more education, only 25% had secondary or above education and around 14.6%, higher secondary or more education. Around 31.2% of men had secondary plus education while only 18% of the females have the same. Around 19% of men and 10% of females in the 18+ age group have higher secondary education or more.

In terms of location, around 17% of rural adults (18+ years age group) had secondary or above qualification, while around 45% of urban adults had secondary or more education. In the same pattern, only 8.5% of rural adults had completed higher secondary or more education compared to around 30% of urban adults.

Less than 14.5% of SC adults and 10.5% of ST adults had gone up to completing secondary education and gone beyond. Among OBC adults, around 21% were fortunate to complete secondary and go beyond. Among Muslims, 16.6% had secondary education or more. In comparison, around 45% of the general Hindu population had secondary education and beyond. Among SC adults, around 8% had higher secondary education (or more) while among ST, 5.5% had the same, and among OBCs, 11%. Among Muslims, 8% had higher secondary education and beyond while among general Hindu community, 30% had the same.

An analysis of what proportion of population in different age groups had secondary education shows interesting results. If the oldest age group is taken as a proxy for secondary education completion almost 50 years ago and the youngest adults as the proxy for last decade, then by tracking the proportion of secondary education graduates in these groups provide a trend in secondary education completion over 50 years. It shows how over a period of time proportionately more population got secondary education in all disaggregated categories, but how certain categories had better progress. For example, while proportionately more male completed secondary education, the gaps between male and females have been declining. It also shows how OBCs with each generation had moved ahead in getting secondary education while Muslims in general improved in a slow manner. See graphs 39-42. Overall, the graphs show progress in the proportion of population completing secondary education over time. Similar patterns are observed in the case of people with higher secondary education or more.

Graph 39 Graph 40


5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

10.41%13.42%

18.21%

21.66%

27.82%

38.01%

16.75%

20.69%

25.70%28.65%

34.75%

42.98%

3.59%6.20%

10.43%

14.25%

21.22%

32.89%

Percent of population with secondary or above education: By gender

TotalMaleFemale

Age group


10%

20%

30%

40%

50%

60%

10.41%13.42%

18.21%21.66%

27.82%

38.01%

4.24%6.35%

10.04%13.65%

19.28%

30.75%27.31%

33.48%

39.38%41.76%

49.50%

54.85%

Percent of population with secondary or above education: By location

TotalRuralUrban

Age group

-31-

Graph 41 Graph 42


10%

20%

30%

40%

50%

60%

70%

1.55% 2.76%5.59%

8.19%11.68%

20.62%

22.82%

28.97%

38.31%

42.81%

51.57%

60.76%

Percent of population with secondary or above education: By social/ religious groups

ST

SC

OBC

Other Hindu

Muslims

Age group65+ years 56-65 years 46-55 years 36-45 years 26-35 years 18-25 years

0%

10%

20%

30%

40%

50%

60%

70%

2.47% 2.65% 4.37%6.40%

10.79%

17.91%

26.69%

38.69%

48.85%

56.74%

62.96%65.20%

Percent of population with secondary or above education: By MPCE Quintiles

MPCE Q1 MPCE Q2

MPCE Q3 MPCE Q4

MPCE Q5

Age group

Who participate in secondary education in India? A Multi-variate Analysis

So far, the analysis has looked at participation in secondary education disaggregated by gender, social groups and economic quintiles, separately. However, often, many of these factors compounded. In order to decompose the effect of these factors, a multi-variate analysis is useful.

The probability of an adolescent in the age group of 14-15 years attending any education and adolescent in the age group of 14-16 years old attending secondary education is analyzed using logit models. Binary /logit models are used in the analysis of binomial response models. The description of the model is as follows:

Let, y be a binary dependent variable, wherey = 1, if attending school

= 0, otherwise

It is assumed that the probability of attending education is dependent on sex, household head’s education (proxy for parental education) and gender, social group to which the household belongs to, economic quintile of household (defined on the basis of household monthly per capita expenditure) and location / region.

Prob (y=1) = f (x),

where x is the vector of the explanatory variables. In this analysis, using binary logistic regression model the coefficients of the independent variables is estimated. Since parameters to be estimated in the logit model are non-linear in nature, the estimated co-efficient cannot be used to infer about the extent of influence of each variable on the probability of participating in education. Hence the predicted probability of each of the dependent variables is taken up for inferences. An alternative method of binary regression, dprobit is also used to estimate the marginal effect, that is, the change in the probability for an infinitesimal change in each independent, continuous variable and, by default, reports the discrete change in the probability for dummy variables.

Given the nature of the NSS household surveys, the independent variables used in the regression analysis for understanding education participation of adolescents in the age group of 14-16 years, especially their participation in secondary education and the probability of 17-18 years completing secondary education are: (a) gender of the adolescent; (b) location where the adolescent is staying; (c) household size, as a proxy to understand the burden on the households; (d) type of households – whether the family depends on self-employment of its members (like in agriculture) or wage / salary earnings of its member /members or casual labor; (e) monthly per capita consumption expenditure quintile (MPCE Quintiles) to which the household belongs to, as a proxy for the economic status of the household; (f) gender of the head of the

-32-

household head; (g) education levels of household head; (h) distance to the nearest secondary school, to see the role of geographical access in participation; and (i) the State in which the child resides, as a proxy to see the impact of historical policies and practices of socio-economic and educational policies of the states after controlling for other factors. Ideally, demand side indicators such as the quality of the schools available, its costs etc would have helped to explain the reasons for participation or non-participation of adolescents. Thus, this analysis is limited to household factors in explaining secondary education participation and completion.

A description of predictors used in the regressions here is described below:

Table 10: Description of variablesCategory Variable descriptionGender Boy 1 if the adolescent is a boy, 0 otherwise (if girl)

Location / area Urban 1 if urban area, 0 otherwise (rural)

Social groupSC Dummy variables describing the social groups SC, ST and OBC.

The reference category is “others” describing the non-SC, non-ST and non-OBC categories

STOBC

Religion Muslim Dummy variable describing muslim minority. Reference category here is all non-muslim adolescents

Household size hhsize Number of persons in the household, a proxy to measure household burden

Household typeLabor Dummy variables “labor” and “wage_salary” describes

households whose main occupation is casual labor or wage/ salaries class respectively. Reference category is self-employed households in agriculture or non-agriculture activities

wage_salary

Monthly Per Capita Consumption Expenditure Quintiles

mpce_q2Reference category here is MPCE Q1, or the poorest 20% of the households. MPCE Q5 refers to the richest 20% households and other categories refer to categories in between. MPCE Quintiles are proxy to gauge household wealth.

mpce_q3 mpce_q4 mpce_q5

Gender of HH head hh_hd_fem 1 if the household is headed by a female and zero otherwise (if the head is a male)

Education of HH head

ed_hd_pryDummy variables describe the education of hh head, primary, middle, secondary, senior secondary and above senior secondary. Reference category is education being illiterate.

ed_hd_middleed_hd_sec ed_hd_hseced_hd_ahsec

Distance to nearest school dist_s>3m Dummy variable to describe the geographical access to secondary

school being more than 3 Km, and zero other wise

States

AP, Assam,Bihar, Chhattisgarh,Delhi, Goa, Gujarat, HP, Haryana, J&K,Jharkhand, Karnataka, Kerala, MP, Maharashtra,Orissa, Punjab, Rajasthan, TN, UP, Uttarakhand,Union Territories, North- East (except Assam)

Dummies for States; reference category is West Bengal

A summary description of the indicators used is given below:

-33-

Table 11: Summary statistics of independent variablesAttend schools Secondary grade

participantsSecondary completers

No of estimated observations 63740752 30013426 41943458

MEAN STD DEV MEAN STD DEV MEAN STD DEVboy 0.535 0.499 0.575 0.494 0.548 0.498urban 0.244 0.430 0.284 0.451 0.278 0.448SC 0.203 0.402 0.179 0.383 0.202 0.402ST 0.085 0.279 0.064 0.245 0.082 0.274OBC 0.433 0.495 0.436 0.496 0.422 0.494Muslim 0.144 0.351 0.103 0.303 0.146 0.353hh-size 5.882 2.426 5.611 2.422 5.746 2.411labor 0.306 0.461 0.229 0.420 0.297 0.457wage_salary 0.087 0.282 0.114 0.318 0.103 0.304self_empl 0.519 0.500 0.539 0.498 0.510 0.500mpce_q1 0.189 0.391 0.148 0.355 0.179 0.383mpce_q2 0.236 0.424 0.210 0.407 0.219 0.413mpce_q3 0.220 0.414 0.212 0.409 0.217 0.412mpce_q4 0.212 0.409 0.241 0.428 0.223 0.416mpce_q5 0.143 0.350 0.189 0.391 0.162 0.369hh_hd_fem 0.096 0.294 0.099 0.299 0.097 0.295ed_hh_illit 0.396 0.489 0.262 0.440 0.385 0.487ed_hh_pry 0.146 0.353 0.151 0.358 0.155 0.362ed_hh_midle 0.150 0.357 0.199 0.399 0.142 0.349ed_hh_sec 0.093 0.290 0.128 0.334 0.096 0.295ed_hh_hsec 0.045 0.208 0.068 0.252 0.048 0.213ed_hh_ahsec 0.059 0.236 0.086 0.280 0.062 0.241dist_sec_m3km 0.256 0.437 0.211 0.408 0.244 0.429AP 0.068 0.251 0.079 0.269 0.071 0.257Assam 0.023 0.149 0.022 0.145 0.022 0.146Bihar 0.071 0.257 0.052 0.223 0.057 0.231Chhattisgarh 0.026 0.159 0.023 0.151 0.024 0.152Delhi 0.009 0.097 0.011 0.104 0.012 0.110Goa 0.001 0.033 0.001 0.037 0.002 0.041Gujarat 0.048 0.213 0.044 0.206 0.053 0.224HP 0.006 0.078 0.009 0.096 0.006 0.077Haryana 0.024 0.153 0.027 0.163 0.026 0.159JK 0.010 0.097 0.012 0.107 0.011 0.105Jharkhand 0.023 0.150 0.019 0.135 0.023 0.150Karnataka 0.042 0.201 0.047 0.212 0.049 0.217Kerala 0.022 0.147 0.036 0.185 0.024 0.152MP 0.060 0.238 0.052 0.223 0.064 0.244

-34-

Maharashtra 0.090 0.287 0.110 0.313 0.097 0.296Orissa 0.034 0.182 0.032 0.175 0.033 0.180Punjab 0.025 0.157 0.026 0.158 0.026 0.158Rajasthan 0.065 0.247 0.067 0.250 0.060 0.238TN 0.048 0.214 0.065 0.246 0.051 0.219UP 0.209 0.407 0.175 0.380 0.195 0.396Uttarakhand 0.010 0.100 0.013 0.115 0.010 0.101WB 0.072 0.258 0.062 0.242 0.072 0.259UTs 0.002 0.045 0.003 0.053 0.002 0.046north_east 0.034 0.181 0.035 0.184 0.032 0.177

The analysis shows that the probability of a 14-16 year old adolescent boy attending any education is 69% while the same for an adolescent girl is only 60%, after controlling for other household factors. However, the probability of the 14-16 year old boy attending secondary education (grade IX-X) is only 0.33 while for a girl of the same age group, it is further lower 0.28. So, while the 14-16 year old may be participating in education, the probability of them attending age-appropriate grade is less than half. Interestingly, after controlling for other household factors, the probability of an adolescent attending education is better for rural adolescents. Among the social groups, the probability of muslim adolescents attending is less than that of SC, ST or OBC adolescents. Household size has an adverse impact on the participation of adolescents – that is, the more the burden on the households in terms of catering to the needs of family members, more adolescents drop out to take this burden on. Children belonging to casual labor type of families have lesser probabilities of participating in secondary education.

As expected, adolescents from richer MPCE quintiles have higher chances of participating in secondary education and completing the same as compared to adolescents from poorer households. The adolescents from richest 20% of the households have 0.18 times better chance of attending schools compared to their counterparts from the poorest 20% of the households. The education levels of household members too matter, even after controlling for other factors. If the household head is a graduate or more, the chances of the adolescent belonging to the house participating in secondary education are 34 percentage points more compared to a household headed by an illiterate person. Interestingly, children belonging to a household headed by females have better chances of attending and completing secondary education.

Distance to secondary school impacts the secondary school participation of adolescents – more the distance, lesser probability of participation. Among States, adolescents from Kerala, HP, Uttarakhand and Tamil Nadu have higher probabilities of attending secondary education and completing it. See the dprobit results as well as the estimated probability of y=1.

Table 12: Predicted probabilities of attending and completing secondary education

ATTEND (14-16 years old) 14-16 years old Attend Secondary school

17-18 years old completed secondary education

1 2 3 4 5 6

-35-

Independent variables dF/dx Prob (y=1) dF/dx Prob (y=1) dF/dx Prob (y=1)GenderBoys 0.0801 0.6932 0.0584 0.3307 0.0051 0.205

Girls 0.604 0.2786 0.1559

Location

Rural 0.6932 0.3307 0.205

Urban -0.0516 0.6393 -0.0280 0.3045 0.0145 0.2187

Social Group

SC -0.0603 0.628 -0.0704 0.2688 -0.0175 0.1389

ST -0.1189 0.5642 -0.1270 0.2223 -0.0302 0.1413

OBC -0.0227 0.6664 -0.0233 0.3099 -0.0029 0.1621

Muslim Minority -0.1991 0.4773 -0.1748 0.1878 -0.0374 0.0985Other (general category Hindus and non-Muslim minority groups)

0.6932 0.3307 0.205

Hhsize -0.0189 -0.0210 -0.0036

Household type

Wage_Salaried -0.0020 0.6888 -0.0049 0.3266 0.0028 0.2073

Casual labor -0.1192 0.565 -0.1066 0.2394 -0.0206 0.1338

Self employed 0.6932 0.3307 0.205Household level MPCE QuintileMPCE Q1 0.6932 0.3307 0.205

MPCE Q2 0.0527 0.7463 0.0818 0.4112 0.0249 0.2355

MPCE Q3 0.0599 0.753 0.1045 0.4339 0.0341 0.2759

MPCE Q4 0.1094 0.8011 0.1693 0.5029 0.0562 0.3104

MPCE Q5 0.1807 0.8683 0.2667 0.6126 0.0848 0.397

Sex of Household head

Male 0.6932 0.3307 0.205

Female 0.0280 0.7205 0.0630 0.391 0.0198 0.285Education of the head of the householdIlliterate 0.6932 0.3307 0.205

Primary 0.1044 0.7945 0.1144 0.4413 0.0286 0.2817

Middle 0.1686 0.8533 0.2147 0.5484 0.0452 0.3744

Secondary 0.2274 0.9084 0.2997 0.6453 0.0874 0.5406

Higher secondary 0.2411 0.9314 0.3255 0.6827 0.0974 0.6295

Graduate and above 0.2622 0.949 0.3433 0.7038 0.1168 0.6977

Distance to sec school

<3 km 0.6932 0.3307 0.1526

>3 Km -0.0554 0.6344 -0.0693 0.269 -0.0243 0.205

States

AP -0.0050 0.6889 0.2228 0.5599 0.2055 0.3299

Assam -0.1786 0.5036 0.0196 0.3503 0.0365 0.2878

Bihar -0.0731 0.6176 -0.0942 0.2482 0.0088 0.1468

-36-

Chhattisgarh 0.0782 0.7755 0.0737 0.3995 0.0289 0.2422

Delhi -0.0403 0.6502 -0.0896 0.2502 0.0198 0.1048

Goa 0.0994 0.8184 0.1081 0.4398 0.0597 0.2382

Gujarat -0.1698 0.5115 0.0149 0.3427 0.0698 0.1695

HP 0.1762 0.8797 0.2123 0.551 0.1310 0.3796

Haryana 0.0070 0.7025 0.0959 0.4231 0.1185 0.1928

J&K 0.1580 0.855 0.0841 0.4119 0.0052 0.3376

Jharkhand 0.0006 0.6963 -0.0520 0.2796 0.0104 0.218

Karnataka 0.0311 0.7264 0.2016 0.538 0.1134 0.3178

Kerala 0.2503 0.9492 0.4446 0.8448 0.2904 0.6241

MP -0.0013 0.6942 -0.0229 0.3092 0.0198 0.1767

Maharashtra 0.0415 0.7379 0.1607 0.4935 0.0692 0.2795

Orissa -0.0887 0.6028 0.1275 0.4586 0.0816 0.1447

Punjab -0.0951 0.5932 -0.0528 0.2823 0.0501 0.1837

Rajasthan -0.0320 0.659 -0.0019 0.3282 0.0261 0.1563

TN 0.1010 0.7991 0.3477 0.7106 0.3186 0.3334

UP -0.0334 0.6586 -0.0188 0.3128 0.0727 0.2115

Uttarakhand 0.0254 0.7193 0.0480 0.3736 0.0740 0.2371

West Bengal 0.6932 0.3307 0.205North East (except Assam) 0.1167 0.8165 -0.0327 0.2993 -0.0193 0.1466

UT's (except Delhi) 0.0459 0.7647 0.1825 0.5133 0.1680 0.3036

obs. P 0.669203 0.4679 0.1042

pred. P 0.710077 0.4684 0.0751dF/dx is for discrete change of dummy variable from 0 to 1

-37-

Section 5: Which School does the Student Attend?

According to the Selected Education Statistics (2007-08) data (which is provided in table 3 earlier), 39% of all secondary schools are provided and managed by government and local body institutions while another 26% are either partially (more than 50%) or fully funded by government, though managed by private sector (known as the grants-in-aid or government aided private schools). Around 35% of all secondary schools are in the purely private sector segment. These are managed and funded by private trusts/ religious bodies/ corporate etc.

Juxtapose the statistics on the share of government and private management data on the supply side of secondary education with that of participation rates by the management type as emerging from NSS data as well as SEMIS data, and it brings out an interesting picture. While government provision accounts for less than 40% of supply, SEMIS data (except for Delhi and Lakshadweep data) shows that around 46% of enrolments were in government schools and NSS data shows that 62% of all participants of secondary education attend a government school. Similarly, grants-in-aid school (GIA) which accounts for 26% of all provision accounted for 29% of enrolments according to SEMIS data while NSS data shows that only 19% of all participants in GIA schools. The different shares of government and GIA schools in total secondary school participants, as emerging from SEMIS and NSS could be due the parental perception about a school’s management status. However, while purely private schools (private unaided schools) accounted for around 35% of all provision, the enrolment / participant shares as estimated from NSS data as well as reported from SEMIS data shows that enrolment / participation shares (18% according to NSS data and 26% as per SEMIS data) were less than the provision shares. Putting all these information together, one can infer that: (a) government schools may be accounting for more students than their capacity due to demand for secondary education; (b) due to household perception / cost factors, households in certain areas/ circumstances may not differentiate between government and GIA schools while reporting secondary school participation; and (c) private schools may be fixing their admissions as per their capacity or below that even if there is more demand. This could also be due to the fact that private provisions are mostly concentrated in urban areas whereas more number of students is found in rural areas. See graph 43 for details.

Graph 43

-38-

Share

in se

condary

s...

Share in

seco

ndary...

Share in

seco

ndary...0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

39.

3% 62

.4%

45.

6%

26.

1%

19.0

%

28.

6%

34.

6% 17

.9%

25.

8%

Provision and participation shares by management type of secondary schools: 2007-08

Private unaided

Private aided

Govt + LB

The shares of government, GIA and private unaided schools in secondary school participation differed across states, as evident from NSS data. While private unaided schools accounted for almost 35-40% of the secondary stage (gr IX-X) participants in States like Haryana, Rajasthan and Punjab, while GIA accounted for major participation shares in States like Kerala, Maharashtra, Nagaland and Gujarat. In West Bengal, more than 90% of the provision is in the GIA sector (but in all practical purpose, these are government schools only and for technical purpose, called as GIA schools), households reported the participation as in government schools. See graph 44 for state wise variations in private unaided schools versus government and GIA together.

Graph 44

Haryana

Rajasth

an

Punjab

Manip

urUP

Uttarakh

andDelh

iAP

Nagala

ndM

P

Chandiga

rhTo

tal

Karnata

ka HPKera

la

Jhark

hand JK

Pondicherry

Mahara

shtra

Mizo

ram

Chhattisg

arh

TNSik

kim

GujaratBih

ar

Orissa

Goa

Assam

Meg

halaya

WB

Trip

ura

Arunac

hal0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Shares of government, GIA and private unaided schools in secondary education (gr IX-X) partic-ipation: NSS 64th round, 2007-08

GOVT GIA PVT UNAIDED

Share of girls in secondary education participation by type of school attending: As evident from graph 18, only 42% of all students attending secondary education were girls (as against the population shares of 46% among all 14-15 year olds). However, girls accounted for 44% of those who reported attending

-39-

government schools while only 42% and 39% of those attended GIA schools and private unaided schools were girls. Looking at the data differently, among the boys who were attending secondary (grades IX and X), 61% were attending a government school and 19% each in grants-in-aid (GIA) and private unaided schools, while among girls, 64% were attending government schools, 19% in GIA and 17% in private unaided schools.

Share of government and private schools in rural and urban areas in secondary education participation : As discussed earlier, while only 23% of all households belonged to urban areas, 28% of all secondary school participants belonged to urban areas. However, only 21% of students in government schools were from urban areas. In contrast, 46% of all private unaided schools belonged to urban areas, almost 18 percentage points more than the shares of urban students in total. 69% of all rural students attended a secondary school in government sector while in urban areas, only 45% attended a government school.

Proportion of social and religious groups by schools attended: Around 77% of ST, 71% of SC and 66% of Muslim students in secondary education attended government schools. Participation in private unaided schools was maximum among general category Hindus and religious minority students other than Muslims. In all types of schools, the proportion of students from general category Hindus and non-Muslim minority communities were better than their share in population, while among SC, ST, and Muslim minorities, it was less than their share in population. See graphs 45 and 46.

Graph 45 Graph 46

ST

SC

OBC

Gen Cat Hindu

Muslim

Oth. rel minorities

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

76.8%

70.5%

63.0%

51.6%

66.0%

48.2%

12.9%

16.9%

18.8%

22.5%

18.0%

26.6%

9.9%

11.9%

17.3%

25.4%

15.5%

24.3%

Type of school attended by secondary (gr IX & X) students by social / religious groups

Govt GIA Pvt UAST SC OBC Gen Cat Hindu Muslim Oth. rel minorities

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

8.5%

20.6%

43.4%

18.5%

7.5%

1.6%

7.9%

20.2%

44.1%

20.0%

6.6%

1.4%4.3

%

15.9%

43.2%

28.6%

4.9%

3.1%3.5%

11.8%

42.1%

34.2%

4.3%

4.0%

Proportion of social / religious groups in total secondary school students by type of school attended

14-15 years Pop shares Govt

GIA Pvt UA

Proportion of adolescents in secondary education among richest and poorest expenditure quintiles: While the students from poorest 20% households accounts for the least in all categories of schools, the richest 20% accounted for 37% of all attendees in private unaided schools. Among the poorest, 76% attended a government school while among the richest quintile, only 40% did so. See graphs 47 and 48.

Graph 47 Graph 48

-40-

Govt GIA Pvt UA0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

18.0%11.9% 6.6%

24.5%

17.8%

11.9%

22.9%

20.5%

16.4%

22.3%

26.7%

28.0%

12.2%23.2%

37.1%

Distribution of secondary students by MPCE Quintiles in schools by Management types

MPCE Q1 MPCE Q2 MPCE Q3 MPCE Q4 MPCE Q5


10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

76.1% 73.0% 67.3%57.5%

40.4%

15.3%16.1%

18.3%

21.0%

23.4%

8.0% 10.2% 13.8%20.8%

35.2%

Type of school attended by secondary stage students by MPCE quintiles

Govt GIA Pvt UA

Who attends which school? A multi-variate analysis

Similar to the analysis of who attends secondary education and complete it, a multi-variate analysis of who attends which type of school uses multinomial logistic regression, a regression model which generalizes logistic regression by allowing more than two discrete outcomes. Multinomial logistic regression model predicts probabilities of different possible outcomes of a categorically distributed dependent variable, after controlling for a set of independent variables. Here again, the estimated predicted probabilities of a secondary school student attending education in a government, aided and private unaided schools are provided instead of the regression co-efficients.

Table 13: Multinomial logistic regression predicted probabilities of attending government, aided and private secondary schools

Predicted probability

for attending government

school (GOVT)

dy/dx


for attending Aided school

(GIA)dy/dx


for attending Private unaided school (PUA)dy/dx

Mean X

Gender (ref: Girl)Boy -0.039 0.012 0.026 0.575Location / area (ref: Rural)urban -0.118 0.032 0.086 0.284Social Group (ref: others)SC 0.093 -0.041 -0.052 0.179ST 0.081 -0.046 -0.036 0.064OBC 0.061 -0.040 -0.021 0.436Religion (ref: non-Muslim)Muslim 0.063 -0.031 -0.032 0.103Household size/ burdenhhsize 0.017 -0.007 -0.010 5.611

-41-

Household type (ref: self employed)Labor 0.041 0.007 -0.049 0.229wage_salary 0.015 0.005 -0.020 0.114Household MPCE Quintiles (ref: MPCE Q1 or poorest 20% Households)mpce_q2 -0.040 0.009 0.031 0.210mpce_q3 -0.083 0.018 0.065 0.212mpce_q4 -0.157 0.033 0.125 0.241mpce_q5 -0.299 0.054 0.245 0.189Gender: Household head (ref: male)hh_hd_fem 0.002 -0.005 0.004 0.099Education of HH head (ref: Illiterate)ed_hd_pry 0.009 0.005 -0.015 0.151ed_hd_middle -0.048 0.019 0.029 0.199ed_hd_sec -0.002 -0.005 0.007 0.128ed_hd_hsec -0.040 0.018 0.022 0.068ed_hd_ahsec -0.189 0.047 0.142 0.086Distance to nearest facilities (ref: <3 Km)dist_s>3m 0.032 -0.018 -0.013 0.211States (ref: West Bengal)AP -0.458 -0.104 0.562 0.079Assam 0.149 -0.102 -0.047 0.022Bihar -0.073 -0.150 0.223 0.052Chhattisgarh -0.294 -0.009 0.304 0.023Delhi -0.196 -0.056 0.252 0.011Goa -0.153 0.135 0.018 0.001Gujarat -0.424 0.296 0.128 0.044HP -0.334 -0.125 0.459 0.009Haryana -0.561 -0.081 0.643 0.027JK -0.300 -0.049 0.348 0.012Jharkhand -0.355 -0.031 0.386 0.019Karnataka -0.500 0.080 0.420 0.047Kerala -0.586 0.306 0.280 0.036MP -0.466 -0.057 0.523 0.052Maharashtra -0.558 0.380 0.178 0.110Orissa -0.336 0.059 0.277 0.032Punjab -0.523 -0.021 0.544 0.026Rajasthan -0.549 -0.102 0.652 0.067TN -0.364 0.161 0.203 0.065UP -0.642 0.134 0.508 0.175Uttarakhand -0.418 -0.075 0.492 0.013UTs -0.251 0.090 0.161 0.003north_east -0.306 0.079 0.227 0.035

-42-

The analysis shows that the probability of an adolescent boy attending government school is less than that of girls while attending aided and private unaided schools are higher than that of girls. Similarly, in urban areas, the probability of a student attending government school is less than that in a rural area whereas the probability of urban student attending aided or private unaided schools is higher than that in a rural area. SC, ST and OBC students have higher probabilities of attending a government secondary school and lesser probabilities to attend private aided and unaided schools compared to students from general category. Similarly, muslim students also have higher probabilities of attending government schools compared to other religious groups and less so with respect to aided and unaided schools. The larger the household size, the higher the probability that an adolescent attend government instead of private schools. The richer the households as evident from MPCE quintiles, higher the probabilities of attending private unaided schools- the fact that students from richest 20% households have 0.30 times less chances of attending a government schools while 0.25 times more probability of attending a private unaided school.

Overall, the analysis shows that the probabilities of attending a government, aided and private school varies with the socio-economic characteristics of households.

Summary

The above analysis was an attempt to compile the evidences emerging from National Sample Survey 2007-08 regarding the secondary education participation among adolescents in India and the patterns in their participation. The analysis shows that more than a third of adolescents in the age group of 14-17 years remains out of education, and among those who are participating, a large proportion were still attending lower grades than age appropriate grades. The gender and social differences in secondary education participation points to the existing disparities /inequities in secondary education. The inequities in terms of household economic status are also evident. The variations across States / UTs also reflect the variations in socio-economic inequities.

As evident in the case of participation, the differences in terms of socio-economic, gender and location are also evident in the case of the type of school the adolescent was attending. The richer, socially upward mobile households prefer to send their wards to private unaided schools more compared to a government school. However, government schools still cater to the majority of secondary school students, especially those from socially and economically marginalized groups.

Any program that aims to improve secondary education in the country needs to be tuned to reduce the socio-economic differences not only in participation, but also the type of education they receive.

-43-