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  • Dropping out of school: North South Divide in West Bengal

    Pranab Kumar Das Centre for Studies in Social Sciences, Calcutta

    Bibhas Saha Durham University Business School

  • Motivation Indias achievement in education has been

    mixed

    Adult literacy improvement: about 1% a year (74% in 2011)

    Child literacy: Significant improvement in level (95% in 2007) as well as gender imbalance

    Primary school completion rate is also high (85.7% in 2006)

    (Census, UNICEF from GoI, some education survey data)

  • High school drop-outs Drop out is a persistent problem School attendance rate at the secondary stage:

    2005-06 data Boys -- 58.5% (drop from 85.2% in the primary

    stage) Girls 48% (drop from 84% in the primary stage)

  • West Bengal Overall literacy 75.9% in 2008 Primary school attendance High and

    comparable to national average (drop-out rate below 10%)

    2008 data: only 15.3% of males and 10.1% of females have

    education of 11 or more years. The percentage of males having less than 5

    years of schooling is 42.4% and the same for females is 47.5%

    (UNICEF, Jalan & Pratichi)

  • Economic literature Poor quality of education (poor infrastructure,

    fewer schools, teacher absenteeism): Chaudhury et al (2006) , Pratichi (2009),

    Jalan (2010), Maitra, Pal and Sharma (2013)

    Low returns to secondary education (earnings function study):Saha and Sarkar (1999) Duraisamy (2002)

  • Child labour Child labour: Drop out of school to work for the familyBasu and Van (1998), Gupta (2000), Ranjan (2001),

    Bhalotra and Heady (2003), Basu et al (2009), Jafarey and Lahiri (2002), Pal and Saha (2013)

    Basu and Van (1998): Luxury axiom Child labour or school drop out should decline with familys income/wealth (such as land)

    Bhalotra and Heady (2003): Counter evidence to luxury axiom (Pakistan and Ghana) Land rich families have greater child labour

    Basu et al (2009): Inverted U hypothesis Luxury axiom kicks in at a higher level of landholding

  • Our objective To see

    if the drop-out rate demonstrate inverted U relation with landholding

    if industrially developed districts of the state encourage or discourage greater (secondary or higher secondary level) schooling

    if households adults education level improves childrens school continuation

  • Data Primary household level survey conducted in 2005 by

    Centre for Studies in Social Sciences, Calcutta About 26, 000 households in rural West Bengal (of

    34,000+ surveyed)

    Information on : Household characteristics (land, occupation, caste,

    education etc.) how many children of the age group 5 to 18 have

    stopped going to school Village level information Some school level information

  • Descriptive statisticsMean household size 6.68Mean per capita agricultural land (acres)

    Among all householdsAmong households with dropout

    0.120.08

    Percentage of households with at least 1 dropout 23.80Percentage of households with no agricultural land

    44.32

    Percentage of households which are agricultural labourers

    24.85

    Percentage of household below poverty line (BPL) 24.16Average Adults education in the household (years)

    5.62

    Among landless householdsPercentage of boys dropped out Percentage of girls dropped out

    5645

  • District-wise dropout rate

    District Dropout rate(%)Percentage of boys

    not in schoolPercentage of girls

    not in schoolShare of boys in total

    dropoutsBankura 09 08 09 54Bardhaman 21 21 22 53Birbhum 19 16 20 47Coochbehar 13 13 13 54D Dinajpur 15 15 14 62Darjeeling 09 06 08 54Hooghly 13 14 14 52Howrah 15 18 14 60Jalpaiguri 11 11 11 54Malda 17 18 16 56Murshidabad 14 16 13 59North 24 Pgs 16 18 13 61Nadia 09 10 08 59W Midnapore 15 16 13 61E Midnapore 12 11 13 50Purulia 10 08 12 44South 24 Pgs 17 18 16 57U Dinajpur 23 22 25 50State average 15 16 14 56

  • Summary Statistics at District LevelDistrictCol. 1

    pcland (all) Col. 2

    pcland (with dropout)Col. 3

    Non-agri/ Total empCol. 4

    NVA to Invested KCol. 5

    Invested K to EmpCol. 6

    Pupil-Teacher Sec. & HS SchoolCol. 7

    Bankura 0.199 0.144 0.339 0.217 4.662 48Burdawan 0.199 0.121 0.553 0.242 9.443 49Birbhum 0.192 0.121 0.399 0.362 2.226 53Cooch behar 0.148 0.132 0.330 0.167 1.390 71Darjeeling 0.183 0.100 0.743 0.161 3.011 41Dakshin Dinajpur 0.015 0.012 0.328 0.173 1.226 55Hoogly 0.121 0.133 0.607 0.346 3.157 48Howrah 0.032 0.016 0.846 0.288 3.405 50Jalpaiguri 0.082 0.073 0.616 0.066 2.771 64Maldah 0.109 0.065 0.484 0.366 3.732 55Murshidabad 0.111 0.064 0.533 0.307 2.235 68Nadia 0.102 0.064 0.569 0.190 6.193 65Nort 24 Pgs 0.082 0.064 0.763 0.432 2.544 50W. Medinipur 0.177 0.148 0.349 0.351 6.121 50E. Medinipur 0.223 0.105 0.469 0.112 166.854 57Purulia 0.235 0.150 0.327 0.248 10.140 47South 24 Pgs 0.070 0.053 0.578 0.442 4.298 63U. Dinajpur 0.069 0.066 0.308 0.226 2.266 61

  • Econometric Model: GLM with logit (probit) link logit & probit model

    Regressorspcland pcland_sqr district FE

    pcland interaction with district FE

    average highest family edn

    BPL Caste(Gen) Religion(Hindu) ext_money vec mdm

  • Logit model (Dependent variable Drop out rate)

    Variables Coefficient Standard Error

    District dummy (Bankura base)

    Bardhaman 0.93*** 0.11

    Birbhum 0.73*** 0.11

    Coochbihar 0.24* 0.13

    Darjeeling -1.16*** 0.43

    D Dinajpur 0.34** 0.14

    Hooghly 0.52*** 0.11

    Howrah 0.50*** 0.11

    Jalpaiguri -0.05 0.12

    Malda 0.32*** 0.12

    Murshidabad 0.26*** 0.11

    Nadia -0.02 0.12

  • Logit model (Contd.)Variables Coefficient Standard Error

    North 24 Pargana 0.48*** 0.10

    W Midnapore 0.55*** 0.11

    E Midnapore 0.50*** 0.11

    Pururlia 0.18 0.15

    South 24 Pargana 0.57*** 0.10

    U Dinajpur 0.44*** 0.12

    Per capita land -0.49*** 0.10

    Per capita land squared 0.02*** 0.004

    Adult members education -0.11*** 0.005

    Hindu -0.35*** 0.04

    Village education council -0.06*** 0.03

    Mid-day meal at school -0.31*** 0.03

  • Differential effects of land We run the same model with interaction of per

    capita land and district dummy variables

    Only 9 districts exhibit sensitivity of landholding on dropout

    Strongest effects are observed in D Dinajpur, Howrah, Murshidabad, Nadia

  • Logit model (Dependent variable Drop out rate):

    Variables Coefficient Standard Error

    Interaction of District dummy and per capita land

    Bakunra -0.88 0.61

    Bardhaman -0.93** 0.41

    Birbhum -0.58 0.38

    Coochbihar 0.24 0.41

    Darjeeling -0.97 0.71

    D Danijpur -7.59* 4.59

    Hooghly 0.17 0.25

    Howrah -2.35* 1.25

    Jalpaiguri 0.46** 0.20

    Malda -0.68** 0.28

    Murshidabad -1.91*** 0.43

  • Logit model (Contd.)Variables Coefficient Standard Error

    Nadia -1.62*** 0.53

    North 24 Pargana -0.49* 0.29

    W Medinipore -0.049 0.28

    E Medinipore -0.705*** 0.28

    Pururlia -1.21 0.84

    South 24 Pargana -0.41 0.41

    U Dinajpur -0.06 0.48

  • Marginal effect of land interaction with districtDistrict dy/dx SE Z P(z>|1|)

    Bankura -0.0761 0.055 1.4 0.16Burdwan -0.1526 0.068 -2.24 0.025Birbhum -0.0878 0.058 -1.51 0.13Cooch behar 0.0243 0.042 0.58 0.56Darjeeling -0.0294 0.025 -1.2 0.23D. Dinajpur -0.4533 0.089 -5.9 0Hoogly 0.0214 0.032 0.66 0.51Howrah -0.2567 0.112 -2.28 0.02Jalpaiguri -0.0374 0.017 -2.19 0.03Maldah -0.0744 0.031 -2.41 0.02Murshidabad -0.1887 0.041 -4.6 0Nadia -0.1285 0.040 -3.19 0.001North 24 Pgs -0.0606 0.035 -1.72 0.09W Medinipur -0.0063 0.034 -0.17 0.86E. Medinipur -0.0877 0.036 -2.45 0.01Purulia -0.1239 0.090 -1.38 0.17South 24 Pgs -0.0545 0.054 -1.00 0.32U. Dinajpur -0.0083 0.059 -0.14 0.89

  • Note: 1=Bank, 2=Burdwan, 3=Birbhum, 4=C_Bihar, 5=Darj, 6=D. Dinaj, 7=Hooghly, 8=HWH, 9=Jalp, 10=MLD, 11=Murshi, 12=Nadia, 13=N 24 Pgs, 14=W. Med, 15=E. Med, 16=Puru, 17=S. 24 Pgs, 18=U. Dnj

    -.6-.4

    -.20

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    1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18District

    Conditional Marginal Effects of pcland_new with 95% CIs

  • Summary of results Support for the luxury axiom (with respect to land). Though the relationship is of a U-curve, the turning

    point is 12 acres per capita, which is too high, and therefore, the relationship between land and dropout is primarily a negative one.

    Wide variation of the effects of land across districts.

    50% of the districts do not show any effect of landholding on dropout.

    The evidence of luxury axiom is not robust across the districts

  • Summary of results North-South divide: Southern districts generally

    have stronger (positive) effects on dropout, Bankura and Purulia being exceptions

    Some of the industrially advanced districts show higher dropout

    Burdwan, Hooghly, Howrah & N. 24 Pgs. Adult members education discourages dropout Midday meal and village education committee

    have positive effects on school continuation Gen Caste, Religion(Hindu), Pol Part, External

    Money positive effect

  • Thank You!