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

• India’s 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 family’s 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 household’s adults’ education level improves children’s 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 statistics

Mean household size 6.68

Mean per capita agricultural land (acres)Among all households

Among households with dropout0.120.08

Percentage of households with at least 1 dropout 23.80

Percentage of households with no agricultural land

44.32

Percentage of households which are agricultural labourers

24.85

Percentage of household below poverty line (BPL) 24.16

Average 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

dropouts

Bankura 09 08 09 54

Bardhaman 21 21 22 53

Birbhum 19 16 20 47

Coochbehar 13 13 13 54

D Dinajpur 15 15 14 62

Darjeeling 09 06 08 54

Hooghly 13 14 14 52

Howrah 15 18 14 60

Jalpaiguri 11 11 11 54

Malda 17 18 16 56

Murshidabad 14 16 13 59

North 24 Pgs 16 18 13 61

Nadia 09 10 08 59

W Midnapore 15 16 13 61

E Midnapore 12 11 13 50

Purulia 10 08 12 44

South 24 Pgs 17 18 16 57

U Dinajpur 23 22 25 50

State average 15 16 14 56

Summary Statistics at District LevelDistrict Col. 1

pcland (all) Col. 2

pcland (with dropout) Col. 3

Non-agri/ Total emp Col. 4

NVA to Invested K Col. 5

Invested K to Emp Col. 6

Pupil-Teacher Sec. & HS SchoolCol. 7

Bankura 0.199 0.144 0.339 0.217 4.662 48

Burdawan 0.199 0.121 0.553 0.242 9.443 49

Birbhum 0.192 0.121 0.399 0.362 2.226 53

Cooch behar 0.148 0.132 0.330 0.167 1.390 71

Darjeeling 0.183 0.100 0.743 0.161 3.011 41

Dakshin Dinajpur 0.015 0.012 0.328 0.173 1.226 55

Hoogly 0.121 0.133 0.607 0.346 3.157 48

Howrah 0.032 0.016 0.846 0.288 3.405 50

Jalpaiguri 0.082 0.073 0.616 0.066 2.771 64

Maldah 0.109 0.065 0.484 0.366 3.732 55

Murshidabad 0.111 0.064 0.533 0.307 2.235 68

Nadia 0.102 0.064 0.569 0.190 6.193 65

Nort 24 Pgs 0.082 0.064 0.763 0.432 2.544 50

W. Medinipur 0.177 0.148 0.349 0.351 6.121 50

E. Medinipur 0.223 0.105 0.469 0.112 166.854 57

Purulia 0.235 0.150 0.327 0.248 10.140 47

South 24 Pgs 0.070 0.053 0.578 0.442 4.298 63

U. 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 0.16

Burdwan -0.1526 0.068 -2.24 0.025

Birbhum -0.0878 0.058 -1.51 0.13

Cooch behar 0.0243 0.042 0.58 0.56

Darjeeling -0.0294 0.025 -1.2 0.23

D. Dinajpur -0.4533 0.089 -5.9 0

Hoogly 0.0214 0.032 0.66 0.51

Howrah -0.2567 0.112 -2.28 0.02

Jalpaiguri -0.0374 0.017 -2.19 0.03

Maldah -0.0744 0.031 -2.41 0.02

Murshidabad -0.1887 0.041 -4.6 0

Nadia -0.1285 0.040 -3.19 0.001

North 24 Pgs -0.0606 0.035 -1.72 0.09

W Medinipur -0.0063 0.034 -0.17 0.86

E. Medinipur -0.0877 0.036 -2.45 0.01

Purulia -0.1239 0.090 -1.38 0.17

South 24 Pgs -0.0545 0.054 -1.00 0.32

U. 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

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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!