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How Do Government and Private Schools Differ?

This paper uses primary survey data from government and private schools in the two states of Uttar Pradesh and Madhya Pradesh to explore systematic differences between the two school types. Although private schools have higher raw mean scores than government schools, after controlling for observed student and school characteristics the private school advantage in test scores is not robust. The sources of private school advantage lie in the types of students choosing these schools, lower pupil teacher ratios and much lower teacher salaries. Private schools have seven to eight times lower teacher salaries but do not differ systematically in infrastructure and teacher effort from government schools. Given the large salary differential, private schools are more cost effective although quality of education is low in both school types.

SPECIAL ARTICLE

How Do Government and Private Schools Differ?

Sangeeta Goyal, Priyanka Pandey

This paper uses primary survey data from government and private schools in the two states of Uttar Pradesh and Madhya Pradesh to explore systematic differences between the two school types. Although private schools have higher raw mean scores than government schools, after controlling for observed student and school characteristics the private school advantage in test scores is not robust. The sources of private school advantage lie in the types of students choosing these schools, lower pupil teacher ratios and much lower teacher salaries. Private schools have seven to eight times lower teacher salaries but do not differ systematically in infrastructure and teacher effort from government schools. Given the large salary differential, private schools are more cost effective although quality of education is low in both school types.

This paper is based on a larger report “How Do Government and Private Schools Differ? Findings from Two Large Indian States” (South Asia Human Development Sector, World Bank, 2009). We gratefully acknowledge generous financial support from the Education Program Development Fund trust fund for this work. We thank Samuel Carlson, Amit Dar, Lant Pritchett, Michelle Riboud and James Tooley for very helpful comments. The fi ndings, interpretations and conclusions expressed here do not necessarily represent the views of the World Bank.

Sangeeta Goyal (sgoyal2@worldbank.org) and Priyanka Pandey (ppandey@worldbank.org) are with the South Asia Human Development Unit, World Bank.

Economic & Political Weekly

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June 2, 2012 vol xlviI no 22

1 Introduction

P
rivate schools offering primary education have grown at a rapid rate in India. According to recent estimates, 25% of all enrolment in primary education is in private schools (SRI 2005; Mehta 2006). Attendance in these schools is not limited to the non-poor or children in urban areas; and nearly 30% of villages have access to a private school within the village itself (Kremer and Muralidharan 2006; De et al 2002).

Poor quality of education in government schools is considered to be the key factor for the rapid growth in the number of private schools. Parents perceive private schools as more accountable and offering better quality education. The Probe Report (1999) notes that

In a private school, the teachers are accountable to the manager (who can fire them), and, through him or her, to the parents (who can withdraw their children). In a government school the chain of accountability is much weaker, as teachers have a permanent job with salaries and promotions unrelated to performance. This contrast is perceived with crystal clarity by the vast majority of parents.

Parents value good quality education and are willing to pay for it. Apart from tuition fees, they incur considerable expenditure to send a child to a private school spending money on uniforms and textbooks, which they can otherwise avail for free in a government school.

The evidence from surveys in a number of developing countries including India shows that learning outcomes in private schools, as measured by test scores, are on an average better than that in government schools. In most studies comparing the performance of the two school types, the private school advantage remains even after controlling for a large set of observable student family, school and teacher characteristics (LEAPS 2007; Goyal 2006a and b; Kremer and Muralidharan 2006; Tooley and Dixon 2006; Kingdon 1996a and b). Evidence of the comparative quality of public and private schools has led to a strong policy debate on the conditions of provision of education by the government. It is argued that the government school system is expensive and wasteful and fails in imparting even minimum skills to students. Private schools not only do better but also provide learning at a much lower unit cost (Tooley and Dixon 2006). The set of reforms advocated for government schools range from making teachers and schools accountable for performance (using sticks or carrots or both) to making government schools compete for students with private schools (for example, by giving students vouchers to be used in a school of their choice).

While there is a strong case to be made for reforming the government school system, it is important to note that the evidence on private schools comes mostly from studies (including this one) based on data that show correlation and not causation between school type and outcomes. Any private school effect cannot be attributed to the school if students select into schools. However with lower per student cost private schools would still have a cost advantage.

We use primary data on learning outcomes and correlates collected from government and private schools in the two large states of Uttar Pradesh (UP) and Madhya Pradesh (MP), to explore the differences between the two school types. Both states have historically lagged in educational outcomes compared to the Indian average (literacy rate according to the 2001 Census – 65.4%). MP (literacy rate 2001 – 63.7%) to its credit has taken long strides to improve; whereas UP (literacy rate 2001

  • 56.3%) continues to lag behind. There is considerable presence of private schools in both states, including in rural areas
  • more than a quarter of all enrolment is in the private sector, and more than half of this enrolment is in rural areas (Table 1).
  • Table 1: Private Schools and Enrolment in Madhya Pradesh and Uttar Pradesh (%)

    Private Schools Private School Private School Enrolment Enrolment Rural

    Madhya Pradesh 16 27 15

    Uttar Pradesh 24 28 24

    Source; SRI (2005); Mehta (2006).

    Table 2: Types of Sample Schools by Management

    Government Private Aided Private Aided Private Aided Total Recognised Unrecognised

    Uttar Pradesh 112 4 42 41 199

    Madhya Pradesh 125 1 73 -200

    Comparing raw mean test scores, we find that private school students do better than government school students, a fi nding consistent with other studies. However, mean scores are low in absolute terms in both school types, indicating that the overall school quality is low for both government and private schools. Learning gains from one grade to the next are also small in both school types. Variation in test scores is also large in both private and government schools, implying a variety of school quality in both school sectors. About half the variation in test scores is between schools and the remaining is within schools, similar to what other studies in India find (Pandey et al 2010; Goyal 2006a and b). The observed school and teacher characteristics account for little of the variation in quality between schools.

    Once we control for child and family background and school characteristics, whether there is a significant private school advantage in test scores varies by state, school type, grade and subject. Private unrecognised schools do better than private recognised schools. This is unlike the findings from studies in other states and even other developing countries where a signi fi cant private school advantage remains almost always, after controlling for sample characteristics. As our data is non-experimental, we cannot make any claims about which of the individual characteristics cause the loss of the private school advantage.

    provides an analysis of differences in mean characteristics of government and private schools in terms of student, school and teacher characteristics. Section 6 discusses and concludes.

    2 Background

    A number of studies fi nd that even after four and five years of schooling, children in government schools do not acquire the basic skills in literacy and numeracy (Pandey et al 2010; ASER 2007, 2006, 2005; PROBE 1999). Many reasons have been put forward for the poor quality of government schools. Earlier studies considered poor school resources and the poverty and illiteracy of parents as prime reasons. Recent research highlights the pervasiveness of teacher absence and inactivity in government schools.

    Researchers have also looked at the relative learning achievements across government and private schools. On raw scores alone, in most studies, private schools have a distinct advantage over government schools. Based on a survey in urban and semi-urban areas of Hyderabad in south India, Tooley and Dixon (2003,

    Instead we compare across school types mean differences in characteristics that may matter for learning. The socioeconomic characteristics of students, such as caste, gender, parental literacy and household wealth favour private schools implying considerable sorting of students between school types, and this could be one source of the private school advantage. Other sources of private school advantage lie in lower pupil teacher ratios and substantially lower teacher salaries.

    The paper is structured as follows. The second section describes the context and the motivation for the study. Section 3 describes the data. Section 4 presents learning outcomes and an analysis of the variation in learning outcomes. Section 5

    Table 3: Mean Sample Statistics

    Uttar Madhya
    Pradesh Pradesh
    Total 3,435 4,268
    Grade (%)
    4 1,696 2,137
    5 1,739 2,131
    Gender (%)
    Male 54 53
    Female 46 47
    Caste (%)
    General 11 15
    SC 26 22
    ST 0 7
    OBC 62 55
    Other 2 0.5
    Father’s education (%)
    Illiterate 34.26 10.65
    Below primary 3.54 11.35
    Primary 14.16 25.34
    Secondary and below 14.56 24.97

    Higher secondary and below 28.43 21.13

    Below primary 5.22 26.25
    Primary 11.42 24.23
    Secondary and below 5.97 10.02
    Higher secondary and below 4.68 5.65
    Graduate/professional 0.77 0.65
    Father’s occupation (%)
    Government service 1.57 2.03
    Private service 10.13 3.09
    Non-agricultural labourer 42.36 33.21
    Agricultural labourer 27.60 45.29
    Businessman 2.31 3.04
    Professional 0.74 1.25
    Self-employed 15.27 12.11
    Average number of siblings
    Below 18 years 3 2
    Above 18 Years 2 0
    Landownership (%)
    (Above median) 45.49 47.30
    Takes tuition (%) 6 13
    Students by school type (%)
    Government 61 65
    Private aided 2 1
    Private unaided recognised 22 34
    Private unaided unrecognised 15 0

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    2006) find that private school children, including those in unrecognised schools, outperform government school children. The size of the difference falls substantially when background variables are controlled for although the difference continues to be signifi cant. A study of rural primary schools in the Punjab province of Pakistan finds that after adjusting for school and student characteristics, significant differences remain in test scores between government and private schools (LEAPS 2007). Similar results are found for schools in Orissa and Rajasthan (Goyal 2006a, 2006b). Some also report large variation in scores for government and private schools implying there are good and bad schools within each (Goyal 2006a, 2006b).

    Studies indicate that the sources of private school advantage lie in the following factors: (a) private schools have higher

    Table 4: Mean School Physical Facilities by Management

    Uttar Pradesh Madhya Pradesh Government Aided Unaided Unaided Government Aided Unaided Recognised Unrecog-Recognised nised

    Number of usable classrooms 3 2.75 1.75 1.4 2.15 7 3.5

    Whether toilet .37 .5 .51 .27 .40 1 .69

    Whether girls toilet .26 .5 .16 .06 .23 1 .52

    Whether electricity 0 .5 .4 .15 .13 1 .74

    Table 5: Mean School Level Inputs by Management

    Uttar Pradesh Madhya Pradesh Government Aided Unaided Unaided Government Aided Unaided Recognised Unrecog-Recognised nised

    Enrolment 213 203 115 97 122 76 88

    Number of teachers 3.87 6.5 5 5 3 6 6

    Pupil-teacher ratio 57 30 25 21 45 13 16

    Multigrade teaching .76 .75 .69 .51 .83 0 .27

    Teacher attendance .69 .77 .74 .73 .81 .77 .82

    Teacher activity .27 .31 .45 .37 .69 .77 .63

    Table 6: Average Teacher Attendance and Activity

    Uttar Pradesh Madhya Pradesh Attendance Activity Attendance Activity

    Government all .69 .27 .80 .70

    Government regular teachers .69 .26 .84 .72

    Government contract .70 .28 .81 .74

    Former contract – – .73 .62

    Aided .80 .29 .78 .78

    Unaided recognised .77 .45 .82 .63

    Unaided unrecognised .76 .39 – –

    Table 7: Average Teacher Characteristics by Management, Uttar Pradesh

    % Unless Indicated Government Government Government Private Private Private
    Otherwise Regular Contract Aided Unaided Unaided
    Teachers Teachers Recognised Unrecognised

    Male .55 .68 .43 .74 .60 .69

    Age (years) 34 41 27 30 28 32

    SC/ST .12 .12 .12 .17 .19 .09

    OBC .42 .42 .41 .26 .44 .39

    College degree .38 .29 .47 .48 .42 .36

    Graduate degree .28 .34 .21 .30 .24 .22

    Teaching experience (years) 9 14 4 7 5 7

    Pre-service training .5 .93 .07 .09 .12 .09

    Distance to school (km) 7 12 2 11 3 3

    Local (village resident) .49 .10 .69 .43 .36 .47

    Monthly salary (rupees) 6,350 10,461 2,315 546 873 786

    teacher attendance and activity, (b) private schoolteachers get a fraction of the salary of government schoolteachers, and

    (c) private schools have smaller class sizes (LEAPS 2007; Goyal 2006a and 2006b; Kremer and Muralidharan 2006; Tooley and Dixon 2006; Kingdon 1996a and b).

    3 Data and Methods

    Data for this study come from school surveys conducted in MP and UP between November 2006 and February 2007. Six districts were selected in each state, covering every geographical region of the state as defi ned by the National Sample Survey Offi ce (NSSO). Madhya Pradesh is divided into six geographical regions, south, south western, northern, vindhya, central and Malwa. These six regions are roughly even in the number of districts, each with six to 10 districts. One district was randomly selected from each of these regions. Uttar Pradesh is divided into four geographical regions, eastern, western, central and southern. The eastern and western regions have more than twice as many districts (26-28 districts in each) as in the other two regions (8-10 in each). Given the unequal sizes of regions, two districts from each of the two larger regions and one from each of the two smaller regions were randomly selected.

    In each district, two blocks and in each block six gram panchayats and urban wards were randomly selected.1 The ratio of urban wards and gram panchayats was kept the same as the ratio of urban and rural population in the state. All primary schools, government or private, were surveyed in each gram panchayat and urban ward in the sample. Fifteen students randomly selected from each of the grades 4 and 5 in the sample schools were tested in language and mathematics. Data on teacher attendance and activity were collected by making three unannounced visits to a school. In each visit field investigators recorded whether the teacher was present in school and what they were doing at the time of the visit. Teacher activity is constructed as 1 if teacher is teaching, writing on the board, supervising written work, teaching by rote, 0 if teacher is absent, chatting, sitting idle/ standing outside the classroom, keeping order in classroom but not teaching, doing other non-teaching work. Although we have data on all teachers teaching grades one to fi ve, as multigrade teaching is widespread in the sample, we use

    Table 8: Average Teacher Characteristics by Management, Madhya Pradesh

    % Unless Indicated Government Government Government Govern- Private Private
    Otherwise Regular Contract ment Aided Unaided
    Teachers Teachers Former Recognised Recognised
    Contract
    Male .65 .74 .58 .53 .67 .46
    Age (years) 38 44 32 33 22 27
    SC/ST .33 .28 .41 .35 0 .09
    OBC .28 .27 .32 .27 0 .47
    College degree .29 .30 .27 .29 .33 .40
    Graduate degree .26 .25 .26 .29 .17 .19
    Teaching experience 14 20 6 9 3 6
    Pre service training .35 .39 .36 .26 0 .05
    Distance to school 5 5 6 5 1 2
    Local .35 .42 .27 .28 .83 .67
    Monthly salary 6,681 10,326 2,696 3,054 933 1,006

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    school level averages of teacher attendance and activity in the analysis.

    Data on school and teacher characteristics were also collected. Data on sample student characteristics were collected from parent interviews conducted in their homes in the presence of the student.

    Types of Schools: There are two types of private schools in India: private aided and private unaided schools. Private aided schools are privately managed, but the teacher salaries and other expenses are funded by the government. Their teachers are paid at government-teacher salary rates directly from the state government treasury and are recruited by a governmentappointed Education Service Commission rather than by the school. Private unaided schools are entirely privately managed and privately funded, and are of two types, recognised and unrecognised. These schools run entirely on revenue from fees.

    To understand the real dimension of the private education sector the distinction between recognised and unrecognised schools is important. While government educational data collection exercises are intended to be a census of all schools in the country, they cover the recognised schools and do not cover the unrecognised private schools. The recognised schools have met the regulatory requirements of the State, while the unrecognised ones have either not applied for, or have not succeeded in gaining, recognition.2 Students from private unrecognised schools cannot appear for any state or central examinations. In reality, many recognised private schools may not fulfil all the conditions of recognition (Kingdon 1994). Because we sampled all schools in the selected gram panchayats and urban wards, our sample has four types of schools: government schools, private aided schools, private unaided recognised schools and private unaided unrecognised schools. In MP, there were no private unaided unrecognised schools in the sampled gram panchayats or urban wards.

    To fi nd all the schools in any location, the field teams were briefed on how to identify and classify different school types. In every village or urban ward, the team sat down with the village head (gram pradhan) and few other persons who knew the village well to make a list of schools in each neighbourhood. They then visited each neighbourhood to check the list of schools. The field teams in MP did not find any private unrecognised schools in any of the locations they visited. All the six teams in the state, which visited a separate district each found “zero” unrecognised schools.3

    Descriptive statistics of the sample are in Tables 2-8 (pp 68, 69). Private aided schools are a very small fraction of schools in the sample. For this reason, averages presented by school type do not report on private aided schools. Student and teacher level regression anal yses include private aided schools but results of these school types are not reported since the number of observations is small.4

    The statistical strategy employed is the ordinary least squares (OLS) regression. Standard errors are clustered at the school or block level as appropriate, unless stated otherwise.

    3.1 The Tests

    The tests were based on the National Council of Educational Research and Training (NCERT) tests for grade four in language and mathematics. The language tested is Hindi, the language in use in both states. All the tests were in the multiple choice format. Both grade 4 and 5 students took the same test.

    Reading Comprehension Test: This consisted of 34 items aimed at assessing the student’s ability to comprehend paragraphs.

    Word Meaning Test: The test consisted of 35 items aimed at assessing the student’s ability to identify synonyms and antonyms.

    Mathematics Test: The test consisted of 33 items aimed at assessing the students’ ability to do simple additions, subtractions, multiplications, fractions, and area and weight analysis.

    The test items correspond to competencies that children are expected to have mastered by end of grade 4. Each child’s score on a test is the number of questions he or she answered correctly converted into a percentage.

    4 Learning Decomposition
    4.1 Unadjusted Test Scores

    Mean test scores, overall and by type of school management are presented in Tables 9 and 10. Scores are low in absolute terms and certainly much lower than 60% which is the government’s own indicator for a child’s acceptable level of competency on a test.

    Table 9: Mean Scores, Uttar Pradesh

    Read Word Math

    Private aided 37 (24) 50 (20) 33 (22)

    Private unaided recognised 37 (18) 50 (18) 26 (13)

    Private unaided unrecognised 40 (21) 52 (18) 31 (16)

    Grade 5 Overall 34 (19) 48 (19) 26 (14)

    Government 30 (14) 43 (18) 22 (12)

    Private aided 44 (25) 59 (22) 42 (29)

    Private unaided recognised 43 (20) 56 (18) 31 (13)

    Private unaided unrecognised 44 (24) 57 (21) 32 (17)

    Standard deviation in parentheses.

    Table 10: Mean Scores, Madhya Pradesh

    Read Word Math

    Grade 4 Overall 30 (21) 42 (22) 25 (17)

    Government 24 (18) 38 (22) 21 (15)

    Private aided 25 (8) 49 (12) 18 (6)

    Private unaided 40 (21) 49 (22) 32 (17)

    Grade 5 Overall 36 (22) 47 (23) 29 (17)

    Government 30 (18) 45 (22) 25 (15)

    Private aided 40 (14) 56 (17) 27 (15)

    Private unaided 48 (24) 54 (23) 37 (18)

    Standard deviation in parentheses.

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    Figure 1: Within and Between School Variations in Test Scores, Uttar Pradesh Figure 2: Within and Between School Variations in Test Scores, Madhya Pradesh

    Within Within

    Between

    100 80

    100 80 60 40 20 0 Between Grade 4 Grade 5 Read Word Math Read Word Math Percentage (%) 58 70 58 54 70 57 42 30 42 46 30 43
    Grade 5 Word 47 6553 35 55 53 34 56
    45
    47
    66
    44

    Percentage (%)

    60 40 20 0

    Read

    Word

    Math

    Read

    Math

    Grade 4

    Each question had four or five options to choose the answer from. Therefore, even if a child was randomly guessing the answer, he or she could score an average of 20-25%. Accounting for guessing would imply an even smaller level of learning.

    The standard deviations of the test scores are high. High variation implies that there are few students who do exceedingly well but the majority performs poorly. If we were to take the difference in the mean scores between grades 5 and 4 as an indicator of average gain in learning between the two grades, the mean gain is only about 3-4 percentage points in each area. The variation in scores also increases which implies a further pulling away of the top scorers with little improvement in the test scores of the majority.

    Tables 11 and 12 (p 72) give the distribution of scores by percentile. The distribution of scores of government schools is to the left of private schools. But learning is poor in all school types. If we take scoring 50-60% on a test as a benchmark of acceptable levels of learning (NCERT uses 60%), government schools in both states achieve this standard somewhere between the 90th and 95th percentile, whereas private schools do so between the 75th and 90th percentile.

    4.2 Varied Test Scores Within and Across Schools

    The total variation in test scores is the sum of variation arising due to differences between schools and within schools. What share each source of variation contributes can be computed using OLS regression analysis with test scores as the dependent variable and the school attended as the only independent variable. The amount of variation “explained” in this case is the share of the variation coming from differences between schools. The remaining is that due to sources of differences within schools (i e, what happens if all the schools were identical).

    Variation between schools accounts for 30-56% of the total variation in scores (Figures 1-2). The remaining variation in scores is within schools. We repeated the above analysis separately by school type. The results (available with the authors) are not very different from those of the overall sample. This implies there are good and bad schools within all school types. School quality differences matter; however differences across students within a school also matter considerably for test scores. From the point of view of policy, there is opportunity for improving education outcomes both by pursuing polices that improve school quality and also policies directed towards students.

    4.3 Is There a Private School Effect?

    We analyse the private school effect before and after controlling for differences in observed student and school characteristics. Tables 13 (Uttar Pradesh) and 14 (p 73) (Madhya Pradesh) show the unadjusted and adjusted difference in mean scores between private and government schools. The adjusted differences in mean test scores are the remainder differences after

    Table 11: Percentile Distribution of Scores, Uttar Pradesh

    5th 10th 25th 50th 75th 90th 95th 99th
    Read
    Grade 4 All schools 6 12 21 26 35 53 65 82
    Government 6 9 18 24 29 38 44 59
    Private aided 12 15 21 28 44 78 82 82
    Private unaided recognised 12 18 24 35 50 65 74 82
    Private unaided unrecognised 10 15 26 35 53 72 79 88
    Grade 5 All schools 9 15 21 29 41 62 76 91
    Government 6 12 21 26 35 44 50 74
    Private aided 15 18 24 35 68 88 88 88
    Private unaided recognised 18 21 26 38 56 71 79 94
    Private unaided unrecognised 12 18 26 38 59 82 91 97
    Word
    Grade 4 All schools 11 20 31 46 57 66 74 89
    Government 9 14 29 40 51 60 63 80
    Private aided 11 17 40 49 66 77 83 89
    Private unaided recognised 20 26 40 51 60 74 80 94
    Private unaided unrecognised 20 29 40 53 63 74 83 94
    Grade 5 All schools 14 23 37 49 60 71 83 94
    Government 11 20 34 43 54 66 71 86
    Private aided 26 34 43 54 69 97 97 97
    Private unaided recognised 26 34 46 57 66 80 86 94
    Private unaided unrecognised 20 29 43 57 71 86 91 97
    Math
    Grade 4 All schools 6 9 15 21 27 39 45 70
    Government 3 6 12 18 24 30 36 48
    Private aided 9 10 18 27 58 67 70 75
    Private unaided recognised 9 12 18 24 33 39 45 73
    Private unaided unrecognised 9 12 21 27 39 54 63 81
    Grade 5 All schools 6 9 15 24 33 45 55 76
    Government 6 9 15 21 27 36 45 64
    Private aided 0 3 15 45 67 79 82 82
    Private unaided recognised 12 18 21 27 36 48 58 73
    Private unaided unrecognised 9 15 21 30 42 61 64 79

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    controlling for a set of characteristics. Scores have been adjusted using two models: (a) the model uses as controls child and family background characteristics, school characteristics, district of location dummies and rural location dummy;5 and (b) same as (a) except the district and rural location dummies are replaced with village dummies.

    The remaining effect of school type is not totally unbiased because there is a likelihood of systematic selection into various types of schools correlated with unobserved children and family characteristics. If more able or motivated students select into private schools then any private school advantage over government schools in the test score, after controlling for observed student and school characteristics, cannot be attributed to school-type. In fact, as we see later, there are reasons to believe that “better” students attend private schools and this may be partly responsible for the higher average private school test scores. To obtain an unbiased private school

    Table 12: Percentile Distribution of Scores, Madhya Pradesh

    5th 10th 25th 50th 75th 90th 95th 99th
    Read
    Grade 4 All schools 0 0 15 26 41 59 71 85
    Government 0 0 12 24 32 47 59 62
    Private aided 9 13 24 26 32 34 35 35
    Private unaided recognised 0 15 26 38 59 71 76 88
    Grade 5 All schools 0 9 21 32 50 68 76 88
    Government 0 6 18 26 38 53 65 85
    Private aided 24 26 32 35 44 62 71 71
    Private unaided recognised 0 18 29 47 65 79 85 91
    Word
    Grade 4 All schools 0 0 29 46 57 69 74 91
    Government 0 0 26 41 54 63 71 89
    Private aided 31 33 37 50 57 63 66 66
    Private unaided recognised 0 17 40 51 63 74 80 94
    Grade 5 All schools 0 14 37 49 63 77 86 94
    Government 0 11 34 46 57 71 80 94
    Private aided 37 37 43 51 69 77 91 91
    Private unaided recognised 0 29 43 54 69 86 91 97
    Math
    Grade 4 All schools 0 0 12 24 33 48 55 73
    Government 0 0 9 21 30 39 48 70
    Private aided 3 9 15 18 21 24 27 27
    Private unaided Recognised 0 9 21 33 45 55 61 76
    Grade 5 All schools 0 6 18 27 39 52 58 75
    Government 0 6 15 24 33 45 52 69
    Private aided 12 12 12 24 36 48 58 58
    Private unaided recognised 0 15 27 39 48 58 67 79

    estimate when selection is going on, one needs a way to correct for selection bias. In the commonly used approaches to correct for selection bias, one needs a valid instrument which belongs in the school choice equation but not in the test score equation. Since we do not have a convincing instrument, we do not correct for selection bias.

    Without adjusting there is a significant private school effect in every test and grade. Results change once controls are included. The advantage varies by state, type of private school and grade. In UP, the private schools have an advantage in grade five. Private unrecognised schools outperform private recognised schools in having a greater number of signifi cant differences from government schools. In MP, there is no robust private school advantage in either grade.

    5 Where Do Government and Private Schools Differ?

    We present unadjusted and adjusted mean differences in the socio-economic characteristics of students, school and teacher characteristics between government and private schools using two different model specifications. In the first model we control for the district and rural dummies. In the second model we adjust for the village where the school is located.

    5.1 Socio-economic Characteristics of Students in Government and Private Schools

    For both states, most factors of disadvantage are less represented in the private school, and all the differences across government and private schools are significant at the 1% level (Tables 15-16, p 74). Private school students are less likely to be from the scheduled castes (SCs) and scheduled tribes (STs) households, are more likely to be male and have parents educated above primary school. They also are more likely to have fathers who are in occupations other than agricultural labour, and come from households that own more than the median landholding in the sample.

    The adjusted mean differences in these characteristics between school types become larger in magnitude, and are larger for private unaided unrecognised schools. These results suggest considerable sorting of students across school types. It is likely that sorting also goes on along unobserved family and student characteristics such as attitude and motivation.

    5.2 School Inputs

    There are few consistent differences in infrastructure between private and government schools except private schools have significantly lower pupil-teacher ratios (Tables 17-20, p 74). Mean teacher attendance and activity at the school level do not differ between private and government schools, except for private unrecognised schools in UP that have higher activity.

    5.3 Do Teachers Differ across School Types?

    Demographics: Teachers in private schools are likely to be younger than teachers in government schools (Table 21, p 74). In MP, teachers are also more likely to be from the local area than teachers in government schools (Table 22, p 74).

    Professional Credentials and Salary: Overall, teachers in government schools are more likely to be trained, have greater experience and a higher salary than teachers in private schools. Teacher salary in government schools is eight times that in private schools. The differences in these characteristics are bigger between regular teachers in government schools and teachers in private schools.

    5.3.1 Mean Teacher Effort

    Government and private schools are similar in rates of teacher attendance, while differences in rates of teacher activity vary by state and by the type of school.

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    Figure 3: Within and between School Variations in Teacher Effort, Uttar Pradesh and Madhya Pradesh

    Between

    Percentage (%)

    100 80 60 40 20 0

    Attendance Activity Attendance Activity Uttar Pradesh Madhya Pradesh Within 84 16 20 80 85 15 40 60

    Private recognised and unrecognised schools have similar rates of attendance and higher rates of teacher activity compared to government schools in UP. Activity rates are 11-18% points higher in private schools (Table 23, p 75). However after controlling for teacher characteristics and district or village fixed effects, teachers in private and government schools are similar in mean attendance and activity rates, except for private unrecognised schools that have higher teaching activity. In MP, private schools are similar to government schools in rates of teacher attendance and activity, before as well as after controlling for teacher characteristics and district or village fixed effects (Table 24, p 75).

    5.3.2 Variation in Teacher Effort between and within Schools

    Differences between schools explain 40% or less of the variation in teacher effort. This implies more than 60% of the variation in rates of teacher attendance and engagement in teaching is within schools. Only a small fraction of the variation in effort within schools is explained by observed teacher characteristics.

    The r-square from a regression of teacher attendance (and activity) on school fixed effects gives the percentage of

    Table 13: Difference between Private and Government Schools (Private-Government), Uttar Pradesh

    Private Unaided Recognised Private Unaided Unrecognised
    Grade 4
    Read Unadjusted 13** 16**
    Adjusteda 3.38 9.47
    Adjustedb 9.68 16.17*
    Word Unadjusted 11** 12**
    Adjusteda 0.95 2.90
    Adjustedb 22.06** 27.04**
    Math Unadjusted 7** 11**
    Adjusteda 1.36 7.24
    Adjustedb 3.64 6.67
    Grade 5
    Read Unadjusted 15** 16**
    Adjusteda 13.16* 17.49*
    Adjustedb 26.64** 33.40**
    Word Unadjusted 13** 13**
    Adjusteda 14.07** 16*
    Adjustedb 31.64** 36.57**
    Math Unadjusted 9** 11**
    Adjusteda 7.20 11.1*
    Adjustedb 24.34** 28.69**

    *Significant at 5% level; **significant at 1% level. a Controls + District FE + rural dummy, b Controls + Village FE.

    Economic & Political Weekly

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    June 2, 2012 vol xlviI no 22

    variation in teacher effort that is due to differences across schools and villages. The remaining variation would be attributable to variation in within school variables such as observed and unobserved teacher characteristics, classroom characteristics etc.

    We then add observed teacher characteristics to the school fixed effect regression to see how much of the within school variation can be explained by these. The vector of teacher characteristics includes age, gender, caste, education, whether teacher has pre-service training, number of years of service, number of days of in service training in last school year, whether teacher’s appointment is on a contract basis and whether teacher is a resident of the village.

    There are two main points here. First, most of the variation in teacher effort is within schools. Variation in teacher attendance that is explained by differences between schools and villages is 15% in MP and 16% in UP (Figure 3). Variation in teacher activity that is explained by differences between schools and villages is 40% in MP and 20% in UP. In particular, whether the school is government or private recognised or private unrecognised contributes less than 2% of the variation in teacher effort. Second, observed teacher characteristics explain very little of the variation in teacher effort within schools. These observations are consistent with the fi ndings of other studies, although mainly from developed countries, that find: (a) substantial variation in teacher quality within schools, and (b) observed teacher characteristics explain very little of the variation in teacher quality within schools (Rockoff 2004; Rivkin, Hanushek and Kain 2005).

    5.3.3 Teachers’ Reward

    The unadjusted salary difference for pre sence compared to absence seems highest for regular teachers in gover nment schools.

    We then compute the adjusted salary difference due to attendance by regressing salary on attendance and other teacher characteristics such as education, experience, residence, gender and age (Table 25, p 75). Salaries of teachers in private schools and of regular teachers in government schools are not correlated positively with attendance. But salaries of contract teachers in government schools are positively correlated with attendance. The salary difference is 13% between an always present contract teacher and a never present contract teacher with all other factors being similar.

    Table 14: Difference between Private and Government Schools (Private-Government), Madhya Pradesh

    Private Unaided Recognised

    Grade 4 Read Unadjusted 17**

    Adjusteda 8.33

    Adjustedb 0.95

    Word Unadjusted 11**

    Adjusteda 7.45

    Adjustedb 3.32

    Math Unadjusted 11**

    Adjusteda 8.20*

    Adjustedb -0.83

    Grade 5 Read Unadjusted 18**

    Adjusteda 14.2**

    Adjustedb 9.52

    Word Unadjusted 9**

    Adjusteda 9.83*

    Adjustedb 17.44

    Math Unadjusted 12**

    Adjusteda 11.35**

    Adjustedb 4.47

    *Significant at 5% level; **Significant at 1% level. a Controls + District FE + rural dummy, b Controls + Village FE.

    Table 15: Difference in Student Characteristics between Private and Government Schools (Private-Government), Uttar Pradesh

    Table 19: Difference in School Characteristics between Private and Government Schools (Private-Government), Madhya Pradesh

    Mean Share Unadjusted Difference District FE + Rural Dummy Village FE Unaided Dis trict FE + Rural Dummy Village FE
    Unaided Unaided Reco-Unreco gnised gnised Unaided Unaided Unaided UnaidedRecog-UnrecogRecog-Unrecognised nised nised nised Enrolment Number of teachers Recognised -34 2.59** Unaided Recognised -55* 2.01** -58 1.68

    SC -0.073** -0.11** -0.13** -0.14** -0.2** -0.21**

    OBC 0.03** 0.033** 0.09** 0.05** 0.15** 0.11**

    General 0.04** 0.08** 0.04** 0.09** 0.05** 0.10**

    Female -0.10** -0.15** -0.11** -0.18** -0.15** -0.23**

    Tuition 0.04** 0.055** 0.04** 0.06** 0.07** 0.09**

    Father's education primary school and below -0.09** -0.16** -0.12** -0.13** -0.17** -0.26**

    Mother's education primary school and below -0.11** -0.12** -0.10** -0.10** -0.15** -0.13**

    Father agricultural labourer -0.06** -0.031** -0.04** 0.04** 0.07** -0.01**

    Land-owned more than median -0.007 0.075** 0.024* 0.11** 0.15** 0.11**

    *Significant at 5% level; **Significant at 1% level.

    Table 16: Difference in Student Characteristics between Private and Government Schools (Private-Government), Madhya Pradesh

    Mean District FE +
    Rural Dummy Village FE Teacher attendance .05 .04 -.01 .04 -.01 .05
    SC Unaided Recognised -0.15** Unaided UnaidedRecognised Recognised -0.15** -0.23** Teacher activity .18** .11** .10 .09* .09 .11* *Significant at 5% level; **Significant at 1% level.
    STOBC -0.065** 0.058** -0.083** -0.078** 0.087** 0.18** Table 21: Difference in Teachers between Private and Government Schools (Private-Government), Uttar Pradesh

    General 0.15** 0.15** 0.13**

    Female -0.093** -0.12** -0.18**

    Tuition 0.08** 0.06** 0.05**

    Father's education primary school and below -0.28** -0.28** -0.3**

    Mother's education primary school and below -0.23** -0.19** -0.19**

    Father agricultural labourer -0.05** 0.08** 0.15**

    Land-owned more than median 0.05** 0.16** 0.23**

    *Significant at 5% level; **Significant at 1% level.

    Unaided District FE +Rural Dummy Village FE Recognised Unaided Recognised Unaided Recognised

    Number of usable classrooms 1.35* .65 .78

    toilet .28** .09 .00

    girls toilet .29** .09 -.04

    Functional electricity .61** .44* .30

    water .16 .05 -.06

    playground -.10 -.29** -.29*

    *Significant at 5% level; **Significant at 1% level.

    District FE +Rural Dummy Village FE Unaided Unaided Unaided Unaided Unaided Unaided Recognised Unrecognised Recognised Unrecognised Recognised Unrecognised

    Number of usable classrooms -.86 -1.21* -1.07* -1.38** -.85 -1.25

    toilet .15 -.09 .01 -.19 -.01 -.15

    girls toilet -.10 -.19* -.16 -.23* -.10 -.20

    Functional electricity .4** .15 .31** .11 .25* .10

    water -.03 -.19 -.04 -.25* -.11 -.28

    playground -.20 -.07 -.06 -.08 -.06 -.14

    *Significant at 5% level; **Significant at 1% level.

    6 Conclusions

    This study looks at the performance of government and private schools in UP and MP. We find that mean test scores are low in both states. Although students in private schools perform better than students in government schools, the average

    Unaided Recognised

    Pupil-teacher ratio -29** -30** -24**

    Multigrade teaching -.55* -.44** -.35

    Teacher attendance .01 .00 .03

    Teacher activity -.06 -.06 -.04

    *Significant at 5% level; **Significant at 1% level.

    Table 20: Difference in School Characteristics between Private and Government Schools (Private-Government), Uttar Pradesh

    District FE +Rural Dummy Village FE Unaided Unaided Unaided Unaided Unaided Unaided Recognised Unrecognised Recognised Unrecognised Recognised Unrecognised

    Enrolment -96** -114** -97* -121** -93* -134*

    Number of teachers 1.28** 1.40* 1.21* 1.14 .67 1.04

    Pupil-teacher ratio -33** -37** -32** -35** -30** -39*

    Multigrade teaching -.07 -.25* -.15 -.25 -.12 -.19

    Table 17: Difference in School Characteristics between Private and Government Schools (Private-Government), Madhya Pradesh

    % Unless Stated Otherwise District Fixed Effect + Rural Dummy
    Unaided Unaided Unaided Unaided
    Recognised Unrecognised Recognised Unrecognised
    Age (years) -6.28** -2.62** -5.74** -2.93**
    Male .04 .12** .11* .19**
    Local -.04 .07 -.06 .11*
    Pre-service training -.38** -.41** -.33** -.43**
    Graduate degree -.04 -.06 -.03 -.08
    Experience (years) -3.38** -1.78** -3.33** -1.73*
    Salary (rupees) -5,477** -5,564** -5,435** -5,700**

    *Significant at 5% level; **Significant at 1% level.

    score as well as the gain Table 22: Difference in Teachers between Private and Government Schools,

    in learning from one

    Madhya Pradesh

    grade to the next are low

    % Unless Stated Otherwise DistrictFE+ Unaided Rural Dummy

    for both school types.

    Recognised Unaided Recognised

    Table 18: Difference in School Characteristics between Private and Government Schools (Private-Government), Uttar Pradesh

    The test is in multiple choice format, subject to Age (years) Male -11.53** -.19** -12.10** -.04
    random guessing. If a Local .32** .21**
    child was randomly Pre-service training -.30** -.30**

    guessing every answer, Graduate degree -.08** -.09**

    he or she could have Experience (years) -7.72** -8.34**

    scored an average of Salary (rupees) -5,675** -5,732** **Significant at 1% level

    20-25%. Accounting for guessing will imply even lower actual learning.

    There is a great degree of variability in test scores within and between schools in government as well as private schools. Observable school and teacher characteristics are weakly correlated with test scores. Most of the variation in teacher effort is within schools and has weak links with observed teacher characteristics that are commonly used by school administrators as indicators of teacher quality such as training, experience and education. This suggests rewarding teachers on the basis of their credentials may not be effective in raising effort. The existing salary structure is related to effort neither

    June 2, 2012 vol xlviI no 22

    Table 23: Difference in Teacher Effort between Private and Government Schools, Uttar Pradesh

    Unadjusted Adjusted Adjusteda Adjusteda District FE District FE+ Village + Rural Rural FE + Dummy Dummy Controls

    + Controls

    (1) (2) (3) (4)

    Attendance Private unaided recognised .06 .01 .00 -.03
    Private unaided unrecognised .06 .06 .05 .05
    Activity Private unaided recognised .18** .08 .06 .04
    Private unaided unrecognised .11** .10* .08* .11*

    *Significant at 5% level; **Significant at 1% level. a Controls are a full set of teacher characteristics.

    Table 24: Difference in Teacher Effort between Private and Government Schools, Madhya Pradesh

    Unadjusted Adjusted Adjusteda Adjusteda District FE + District FE + Village Rural Rural FE + Dummy Dummy Controls

    + Controls

    (1) (2) (3) (4)

    Attendance Private unaided recognised .02 -.01 .06 .09

    Activity Private unaided recognised -.06 -.08 -.08 -.02

    *Significant at 5% level; **Significant at 1% level. a Controls are a full set of teacher characteristics.

    Table 25: Difference in Salary between Teachers with 100% and 0% Attendance

    Uttar Pradesh Madhya Pradesh
    Salary Difference in Rupees→ Unadjusted Adjusteda Unadjusted Adjusteda
    District FE + District FE +
    Rural Dummy Rural Dummy
    + Controls + Controls
    (1) (2) (3) (4)
    Private aided 250 -38 - -
    Private unaided recognised 112 228 -756** -458*
    Private unaided unrecognised -184 -286 - -
    Contract teacher-government 391** 308** 307 346*
    Former contract-government - - 277** 182*
    Regular teacher-government 1,270* 101 -478 -789

    *Significant at 5% level; **Significant at 1% level. aControls are a full set of teacher characteristics.

    in government nor in private schools, except for contract teachers in government schools. It fails to reward those more present and active in the classroom.

    After controlling for student and school characteristics, the private school advantage in scores varies by state, type of private school, grade and subject. In UP, private unrecognised schools outperform private recognised schools in having a greater number of significant differences from government schools. In MP, there is no robust private school advantage. This is unlike the findings from other studies in India where after adjusting for student and school characteristics the private school advantage usually remains significant. One reason for the difference in results can be that our sample is largely rural. The urban areas in the sample are small towns located within the same block as the villages and are more likely to resemble the villages than the larger cities where private schools are found to perform better after controlling for sample characteristics as in studies such as Tooley and Dixon (2006) and Kingdon (1996a). Another reason could be that our data are from two states lagging in most development outcomes, where just as the public sector has low accountability, the private sector may be functioning in a largely unregulated

    Economic & Political Weekly

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    June 2, 2012 vol xlviI no 22

    environment and parents who largely have little education in the sample may be making school choices based on perceived school quality.

    The sources of private school advantage lie in the types of students choosing these schools, lower pupil-teacher ratios and much lower teacher salaries. Private schools differ considerably in the types of students who attend even within the same district or village. Students in these schools are less likely to belong to low caste groups. They are likely to have more educated and wealthier parents. It is likely that sorting is also going on along unobserved family characteristics such as attitude and motivation. Private and government schools do not differ in physical facilities but private schools have a lower pupil-teacher ratio which implies greater teacher-time per student. Teacher salary in private schools is between one-seventh and one-eighth of the government schools, although teacher effort is largely similar except for private unrecognised schools in UP.

    Since data indicate considerable sorting among students into school types, it is not surprising that the private school effect is less systematic after controlling for observed student and school characteristics. In the cases where the private school effect remains, we cannot be sure this effect is attributable to school type as there may be sorting in unobserved characteristics. Nevertheless, as teacher salaries in private schools are one-seventh or one-eighth of government schools and assuming salaries form a large fraction of the operating cost as is the case for government schools, private schools would unambiguously be more cost effective even in the case of no absolute advantage in test scores.

    Our results may suggest at first that government regulations are redundant, and it is the market in schooling that is more effective in determining quality: private unrecognised schools, which account for half of all private schools in the sample in UP, do better than private recognised schools. But this is not so clear. In both states, learning standards are strictly enforced in neither government nor private recognised schools. The government schools have a minimum level of learning framework, but no functioning mechanism that ensures this standard. The private recognised schools can pay bribes to get recognition without meeting the required criterion for obtaining formal registration. The market does not ensure good quality education either since the unregulated schools are also way off the mark in basic competencies; moreover, we cannot disentangle the sorting effect from the school quality effect with respect to learning outcomes. Private schools may be choosing to locate above but close to government schools along the quality spectrum because it is rational for them to do so given supply-side (incomplete government regulations, poor enforcement) and demand-side (poverty and illiteracy of parents) characteristics. It is costly for schools to adhere to enforced standards of quality. We speculate that if the government were to enforce learning standards on all schools, there would be a change in the composition of supply of private education with low cost (and low quality) private schools likely leaving the market.

    Notes

    1 A gram panchayat is the lowest administrative unit in rural areas consisting of two to three revenue villages on average. The lowest administrative unit in urban areas is an urban ward. A block is an administrative unit between a district and a gram panchayat/urban ward.

    2 In UP, a recognised school must be a registered society, have an owned rather than a rented building, employ only trained teachers, pay salaries to staff according to government prescribed norms, have classrooms of a specifi ed minimum size and charge only government-set fee rates (Kingdon 1994).

    3 On further probing it came out that in MP, all schools which have up to grade 5 have to have a registration number at least. This registration number is not unique to schools but unique to an umbrella organisation like an NGO/trust/ society. Because of this, schools up to grade 5 are perceived as recognised by the villagers but may not necessarily be so. The distinction between recognised and unrecognised schools in MP is therefore blurred or ambiguous and this should be kept in mind when interpreting the results.

    4 We did a check by doing the analyses both with and without private aided schools. The results stay similar in both cases.

    5 Child and family background characteristics included as controls are the child’s age, gender and caste, sibling size, whether the child takes private tuition or not, mother’s and father’s education levels, father’s occupation, and landownership. School characteristics included as controls are infrastructure, mid-day meal provision, free textbook provision, and average teacher characteristics at the school level – female, education level, training and experience.

    References

    Annual Status of Education Report (ASER) (2005, 2006, 2007): Pratham Foundation, http:// www.pratham.org/aser-report/

    De, A, M Majumdar, M Samson and C Noronha (2002): “Private Schools and Universal Elementary Education” in R Govinda (ed.), India Education Report: A Profile of Basic Education (Oxford: Oxford University Press), 131-50.

    Goyal, S (2006a): “Learning Achievements in India: A Case-Study of Primary Education in Orissa”, World Bank, Manuscript.

    – (2006b): “Learning Achievements in India: A Case-Study of Primary Education in Rajasthan”, World Bank, Manuscript.

    Kingdon, Geeta G (1994): An Economic Evaluation of School Management-Types in India: A Case Study of Uttar Pradesh, Unpublished D Phil thesis, Economics Department, Oxford University.

  • (1996a): “The Quality and Efficiency of Private and Government Education: A Case Study of Urban India”, Oxford Bulletin of Economics and Statistics, 58.1, 57-81.
  • (1996b): “Private Schooling in India: Size, Nature and Equity Effects”, Economic & Political Weekly, 31, No 51, December.
  • Kremer, Michael and Karthik Muralidharan (2006): “Government and Private Schools in Rural India” in School Choice International edited by Paul Peterson and Rajashri Chakrabarti, Manuscript, forthcoming.

    Learning and Educational Achievements in Punjab Schools (LEAPS) (2007): Insights to Inform the Education Policy Debate, World Bank, Washington DC. http://siteresources.worldbank.org/ PAKISTAN EX TN/Resources/Publications-and-Reports/367132-1208398596098/2008LEAPS.pdf

    Pandey, Priyanka, Sangeeta Goyal and Venkatesh Sundararaman (2010): “Public Participation, Teacher Accountability, and School Outcomes in Three States”, Economic & Political Weekly, 12 June.

    Mehta, Arun (2006): “Elementary Education in India, Annual Report 2004-05”, National Institute of Educational Planning and Administration and Department of Elementary Education and Literacy, Ministry of Human Resources Development, Government of India.

    PROBE Team (1999): Government Report on Basic Education in India (New Delhi: Oxford University Press).

    Rockoff, Jonah (2004): “The Impact of Individual Teachers on Student Achievement: Evidence from Panel Data”, American Economic Review, May, Vol 94(2).

    Rivkin, Steven, Hanushek, Eric and John Kain (2005): “Teachers, Schools and Academic Achievement”, Econometrica, Vol 73 (2).

    Social and Rural Research Institute (SRI) (2005): “Survey on Assessing the Number of Out-of-School Children in the 6-13 Years Age Group”, New Delhi.

    Tooley, James and Paula Dixon (2003): Private Schools for the Poor: A Case Study from India, CfBT Research and Development.

    – (2006): De facto’ Privatisation of Education and the Poor: Implications of a Study from Sub-Saharan Africa and India, Compare, Vol 36, No 4, December, pp 443-62.

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