The Privatization of Child Learning in Rural India
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1 The Privatization of Child Learning in Rural India Rohini Somanathan Michael Walton December 12, Introduction Private schooling and learning in India is on the rise. Official statistics report 30 per cent of children between grades 1 and 8 are enrolled in private schools and this share has been increasing at roughly one percentage point per year since Although historically imagined as urban and exclusive, this is no longer the case. A majority of private schools are now rural and their enrollment is 55 per cent of total private enrollment for this age-group. 1 The demand for private options is also reflected in the increase in supplementary tuition rates. For those attending government schools, this fraction went from 12% to 16% between for grade 1 and from 26% to 31% for grade 8. 2 These trends motivate the central questions of this paper. How do poor families combine expenditures on education with public schooling and what do private schools and tutors contribute to learning? Do household choices reflect a preference for some children over others or do financially constrained households appear to treat their children equally and move them strategically Delhi School of Economics (rohini@econdse.org). Kennedy School of Government, Harvard University and Centre for Policy Research, New Delhi (michael walton@harvard.edu) 1 These figures are from the District Information Service on Education (DISE) which reports enrollment in privately managed schools at the primary and upper-primary level for each year between The data almost certainly underestimate the extent of private schooling because they only report schools that are recognized as meeting norms set by state educational authorities. 2 Tuition figures are from the Annual Status of Education Report (ASER). Most of our analysis is based on ASER data and these are described more fully in the following sections. 1
2 across institutions as they progress through school and the returns to these investments vary? We use households, rather than schools as our unit of analysis, and are thereby able to compare school choices and outcomes for siblings in a manner that has been hard to do with data sets widely used in the literature on educational inequality. Our data come from a nationally representative survey of 315,080 rural households conducted by the ASER Institute in For each selected household, school-going decisions were recorded for all children above 3 and those between the ages of 5 and 16 were tested in basic reading, mathematics and comprehension skills. The survey is unusual in that an identical test at the grade 2 level is administered to all children, irrespective of their age and choice of school. This permits a comparison of learning outcomes for children while controlling for the unobservable characteristics of households such as their income, taste for education, parental skills or access to resources and schools, that are potentially available to all siblings. We find that many households appear to make strategic choices in the face of financial constraints. From the set of households that send children to private school, over a third of them send some children but not others. Similarly patterns are seen for supplementary tuition outside school. This mixing increases with the number of school-going children in the household. Private schooling and tuition both increase with the grade level of the child suggesting that children move from one environment to another as the perceived returns from these different options change. Our findings on parental choice of schooling and tuition are much more supportive of the view that parents try to equalize school quality among their children (Becker and Lewis (1973)) rather than focus on favored male offspring. While male children are slightly more likely to be sent to private school and receive supplementary tutoring, these effects seem to be swamped by the grade level of the child and girls in both middle and high school are favored relative to boys in primary school. In all subjects, children attending private school perform better than those attending government school, and those received supplementary tuition in both systems do considerably better than those who do not. It is difficult to correctly estimate the returns to these private options based on performance figures because households clearly do not randomly assign children to these options. While an overall rate of return calculation is complicated by potential sorting of children, we can compare the differences in the performance of children attending private school across different subjects. When we do this, our estimates suggest that private schools 3 The Institute is an offshoot the non-government organization PRATHAM. Details on the organization of the survey and the data are provided in Section 3. ASER surveys have been conducted annually since 2005 but information on supplementary tuition outside school was not recorded before
3 do best in enabling children to read English while effects of supplementary tuition are more uniform across different subjects. The overall effects of these different learning environments seem modest; at best one-fifth of a standard deviation in achievement. In India, as elsewhere, much of the variation in student achievement is yet to be explained. 2 Trends in Privatization The emergence and expansion of low-cost private schooling has been noticed since the early 1990s. The Public Report on Basic Education ound many private schools in in rural North India by the late 1990s and interpreted their presence as a response to the low quality of public schools in villages (Probe Team 1999). Table 1 below shows that between 2006 and 2009, there was an 8 percent rise in the number of schools under government management and a 13 increase in schools under private management. Almost all the increase was in in the category of private unaided schools. Figure 1 shows enrollment in private and public schools by state. Table 1: Private and Government Elementary Schools, Government Private Private- Aided Private- Unaided , , ,002, ,895 70, , ,035, ,920 72, , ,048, ,178 71, ,102 Source: DISE 3
4 Thousands 35,000 30,000 25,000 20,000 15,000 10,000 5,000 - Govt Private Aided Private Unaided Ker TN Mah AP Raj Del Kar UP MP Har Pun HP Guj Asm Chh Jha WB Ori Bih Figure 1: State-wise Enrollment in Private and Government Schools, Data 4 Empirical Strategy and Results 5 Discussion 5.1 Learning Outcomes 6 Policy Implications References Becker, Gary, and H. Gregg Lewis (1973) On the interaction between the quantity and quality of children. Journal of Political Economy 81(2), S279 S288 Probe Team (1999) Public report on basic education in India (Oxford University, New Delhi, IN) 4
5 Table 2: Child Characteristics Variable Mean Std. Dev. Obs. Age Male Standard or class of children Mother schooled Mother s grade completed Below age Government school Private school Dropped out of school Never schooled Supplementary tuition Primary school Middle school High school Class not identified Source: ASER 2007, Child Level Data 5
6 Table 3: Child Achievement in Reading and Mathematics Variable Mean Std. Dev. Obs. Local language Reads nothing Reads alphabets Reads words Reads paragraphs Reads stories Mathematics No number recognition Recognizes one-digit numbers Recognizes two-digit numbers Two-digit subtraction Division (3 digit by 1 digit) English Reads no english Reads english alphabets-small Reads english alphabets-capitals Reads english words Reads english sentences Notes: Source: ASER 2007, Child Level Data Each child is listed only at the highest level of performance. 6
7 Table 4: Reading and Mathematics Achievement by School Level. Primary Middle High Total Local language No alphabets Alphabets Words Paragraphs Simple stories Total Mathematics Cannot recognize numerals Recognizes one-digit numbers Recognizes two-digit numbers Two-digit subtraction Division (3 digit by 1 digit) Total English No english alphabets English alphabets-small English alphabets-capitals English words English sentences Total N 306, ,931 52, ,441 Source: ASER 2007, Child-level Data 7
8 Table 5: Reading and Mathematics Achievement by Learning Environment. Private & Tuition Private Govt. & Tuition Govt Not in School Total Local language No alphabets Alphabets Words Paragraphs Simple stories Total Mathematics Cannot recognize numerals Recognizes one-digit numbers Recognizes two-digit numbers Two-digit subtraction Division (3 digit by 1 digit) Total English No english alphabets English alphabets-small English alphabets-capitals English words English sentences Total N 25,756 80,939 68, ,147 31, ,385 Source: ASER 2007, Child-level Data 8
9 Table 6: Household Schooling Choices Govt. Private Govt. & Private Total Grades Attended Primary Middle High Multiple Levels Total School-Going Children 1 child children children children or more children Total Mother s Schooling No School Primary Middle High Total N 189,754 46,815 26, ,620 Source: ASER
10 Table 7: Household Tuition Choices No Tuition All Tuition Some Tuition Total Grades Attended Primary Middle High Multiple Levels Total School-Going Children 1 child children children children or more children Total Mother s Schooling No School Primary Middle High Total N 200,156 43,072 19, ,620 Source: ASER
11 Table 8: School and Tuition Choices, OLS with Fixed Effects (1) (2) (3) (4) Private Private Tuition Tuition Male (31.34) (33.07) (20.18) (20.26) Age *** 0.004*** 0.009*** 0.010*** (-4.54) (13.46) (34.14) (42.11) Middle school (24.23) (18.26) (11.25) (4.58) High school (41.75) (26.01) (38.19) (29.06) Mother Schooled (72.76) (63.83) Children in HH (-23.56) (-20.52) Constant (63.35) (56.48) (27.99) (32.30) Fixed Effects Village Household Village Household Clusters Adj R-squared Obs p < 0.05, p < 0.01, p < Source: ASER 2007, Child Level Data 11
12 Table 9: School and Tuition Choices, Gender Interactions (1) (2) Private Tuition Male 0.03*** 0.01*** (25.58) (10.78) Age 0.004*** 0.010*** (13.49) (42.04) Middle school 0.03*** 0.00 (12.96) (0.93) High school 0.07*** 0.05*** (22.66) (17.33) Male * Middle 0.01** 0.01*** (2.26) (4.39) Male * High -0.01*** 0.03*** (-2.68) (10.65) Constant 0.14*** 0.07*** (55.78) (33.27) Fixed Effects Household Household Clusters Adj R-squared Obs p < 0.05, p < 0.01, p < Source: ASER 2007, Child Level Data 12
13 Table 10: Determinants of Achievement, Fixed Effects Estimates. (1) (2) (3) (4) (5) (6) Reading Reading Mathematics Mathematics English English Private (42.92) (15.70) (43.22) (15.60) (64.60) (20.94) Tuition (48.65) (22.78) (58.10) (26.91) (55.64) (27.24) Male (1.96) (3.86) (11.84) (10.58) (9.43) (8.56) Age (242.41) (99.69) (196.86) (76.30) (141.16) (54.27) Birth Order (-13.39) (-32.96) (-10.94) (-29.37) (-0.09) (-18.51) Middle school (126.87) (78.35) (135.04) (92.90) (147.14) (108.40) High school (58.47) (19.38) (99.74) (57.50) (154.12) (105.09) Mother Schooled (32.65) (30.10) (33.56) Children in HH (4.89) (11.13) (3.13) Constant ( ) (-20.38) ( ) (-18.34) (-87.12) (-14.48) Fixed Effects Village Household Village Household Village Household Clusters Adj R-squared Obs p < 0.05, p < 0.01, p < Source: ASER 2007, Child Level Data 13
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