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Licensed Unlicensed Requires Authentication Published by De Gruyter April 2, 2014

The Effect of Parental Migration on the Educational Attainment of Their Left-Behind Children in Rural China

Sophie Xuefei Wang

Abstract

About 60 million children under the age of 18 are left behind by their parents in rural China. This paper studies the effect of migrant parents on the educational attainment of their left-behind children in rural China. A theoretical model of optimal schooling in the context of parental migration is proposed. Then, reduced-form equations are estimated using probit model, instrumental variables probit model, and linear instrumental variables model. Results show that parental migration has a negative effect on children’s school enrollment. This negative effect is significant and sizable on the school enrollment of boys, but insignificant on the school enrollment of girls. The most important source of this robust negative effect on boys is the absence of fathers. Results suggest that left-behind mothers or relatives cannot fulfill fathers’ role successfully in disciplining boys and help with their educational needs.

Appendix

Table 7

Effect of being in a migrant household on children’s enrollment (result from OLS and linear instrumental variables regression)

BoysGirls
LPMIV LPMIV LPMLPMIV LPMIV LPM
Migrant household–0.132***–0.231*–0.256**–0.019–0.266–0.270
(0.038)(0.132)(0.129)(0.04)(0.219)(0.225)
Child characteristics
Age0.260***0.248***0.247***0.288***0.266***0.273***
(0.035)(0.038)(0.038)(0.04)(0.045)(0.043)
Age squared–0.013***–0.012***–0.012***–0.014***–0.013***–0.014***
(0.002)(0.002)(0.002)(0.002)(0.002)(0.002)
Ethnic minority–0.150**–0.148**–0.149**–0.137***–0.161***–0.162***
(0.065)(0.061)(0.061)(0.05)(0.055)(0.056)
First born child0.0140.020.0230.040.0310.035
(0.03)(0.031)(0.031)(0.031)(0.031)(0.031)
Household characteristics
Father’s education–0.0010.0010.0010.016**0.022**0.021**
(0.006)(0.006)(0.006)(0.006)(0.008)(0.008)
Mother’s education0.012**0.012**0.012**0.010*0.0070.006
(0.006)(0.005)(0.005)(0.005)(0.007)(0.007)
Father in occupation 20.097***0.119***0.122***0.067*0.101**0.099**
(0.037)(0.046)(0.045)(0.037)(0.049)(0.048)
Father in occupation 30.097*0.101**0.099**0.093**0.092*0.090*
(0.051)(0.05)(0.050)(0.047)(0.049)(0.049)
Mother in occupation 20.074**0.085**0.086**0.0070.010.014
(0.037)(0.04)(0.040)(0.047)(0.049)(0.049)
Mother in occupation 30.0640.073*0.074*0.0590.060.059
(0.044)(0.044)(0.044)(0.042)(0.047)(0.047)
Log of wealth–0.006–0.008–0.0080.0120.0170.017
(0.012)(0.012)(0.012)(0.013)(0.014)(0.014)
Log of land–0.02–0.015–0.0140.029*0.036**0.039**
(0.018)(0.018)(0.019)(0.016)(0.018)(0.019)
# siblings–0.025–0.022–0.022–0.037*–0.036–0.042*
(0.024)(0.024)(0.024)(0.022)(0.024)(0.024)
# adults at home–0.034**–0.056*–0.061**0.029–0.032–0.034
(0.016)(0.031)(0.031)(0.02)(0.056)(0.058)
Village characteristics
Log of income/person0.041*0.039*0.039*0.0240.0320.029
(0.021)(0.021)(0.021)(0.024)(0.025)(0.025)
Distance to primary school–0.032*–0.031*–0.032*–0.064***–0.062***–0.063***
(0.017)(0.016)(0.016)(0.015)(0.016)(0.016)
Instrumental variables in first stage
Historical village migrant/labor ratio0.143***0.142***0.125***0.125***
(0.027)(0.027)(0.027)(0.027)
Father’s age–0.006–0.004
(0.005)(0.005)
Hansen J statistic0.3840.005
(p-value)(0.536)(0.945)
Kleibergen–Paap rk LM statistic13.009***11.972***10.280***9.468***
Kleibergen–Paap rk Wald F statistic16.34832.37413.04825.289
Endogeneity test statistic0.4630.7051.2811.295
(p-value)(0.496)(0.401)(0.258)(0.255)
R20.3770.3670.3600.4130.3660.360
Observations440439440429426429

Table 8

Exclusion restriction test for the instrumental variables (reduced-form results for sample of children of non-migrant parents)

BoysGirls
ProbitLPMProbitLPM
Historical village migrant/labor ratio–0.001–0.002–0.008–0.055
(0.043)(0.045)(0.024)(0.032)
Father’s age–0.005–0.0070.0030.004
(0.003)(0.006)(0.003)(0.005)
F statistic for jointly significance0.811.93
Chi statistic for jointly significance2.391.18
p-Value of F-test0.3030.4440.5540.1478
Pseudo R20.5320.4160.4900.443
Observations284284306306

Table 9

Average marginal effect of being in a migrant household on enrollment of children aged 13–17 (result from probit regression)

12345
Panel A: Boys
Migrant household–0.083–0.168***–0.167***–0.219***–0.099
(0.057)(0.055)(0.055)(0.067)(0.079)
Child characteristics
Ethnic minority–0.212**–0.205**–0.200**–0.198**–0.205**
(0.091)(0.094)(0.095)(0.094)(0.093)
First born child0.0570.0400.0420.0300.043
(0.051)(0.050)(0.050)(0.052)(0.050)
Household characteristics
Father’s education–0.006–0.009–0.010–0.008–0.008
(0.009)(0.009)(0.009)(0.009)(0.008)
Mother’s education0.016**0.017**0.018**0.019**0.020***
(0.008)(0.007)(0.008)(0.007)(0.006)
Father in occupation 20.230***0.220***0.223***0.216***
(0.051)(0.051)(0.050)(0.048)
Father in occupation 30.233***0.223***0.234***0.228***
(0.077)(0.081)(0.078)(0.078)
Mother in occupation 20.117**0.117**0.127**0.099*
(0.059)(0.059)(0.056)(0.057)
Mother in occupation 30.0100.0140.0070.007
(0.118)(0.119)(0.116)(0.113)
Log of wealth–0.016–0.013–0.011–0.026
(0.021)(0.021)(0.022)(0.020)
Log of land–0.060**–0.060**–0.055**–0.056**
(0.028)(0.027)(0.028)(0.026)
# siblings–0.068–0.103**–0.107**–0.101**
(0.046)(0.044)(0.044)(0.045)
# siblings aged 6–17–0.125***
(0.040)
# siblings aged < 6–0.000
(0.108)
# adults at home–0.048
(0.030)
# young male adults at home0.080
(0.059)
# young female adults at home–0.023
(0.048)
# old male adults at home–0.165**
(0.067)
# old female adults at home–0.005
(0.060)
Parent remitted0.044
(0.082)
Village characteristics
Log of income/person0.064**0.0220.0200.0100.002
(0.032)(0.036)(0.036)(0.037)(0.034)
Distance to primary school–0.006–0.015–0.014–0.015–0.007
(0.026)(0.022)(0.022)(0.022)(0.020)
Pseudo R20.3150.4190.4200.4260.457
Observations207203203203203
Panel B: Girls
Migrant household–0.111*–0.092–0.092–0.029–0.011
(0.067)(0.064)(0.064)(0.067)(0.066)
Child characteristics
Ethnic minority–0.168**–0.132*–0.129–0.122–0.145*
(0.084)(0.079)(0.080)(0.079)(0.080)
First born child0.114**0.094**0.093**0.107**0.110***
(0.048)(0.045)(0.044)(0.042)(0.041)
Household characteristics
Father’s education0.032***0.020**0.020**0.018**0.017*
(0.009)(0.009)(0.009)(0.009)(0.009)
Mother’s education0.0090.011*0.011*0.012**0.014**
(0.007)(0.006)(0.006)(0.006)(0.006)
Father in occupation 20.128**0.120**0.128**0.131**
(0.055)(0.057)(0.056)(0.057)
Father in occupation 30.215***0.210***0.232***0.252***
(0.067)(0.066)(0.063)(0.061)
Mother in occupation 20.0770.0800.0750.088
(0.063)(0.062)(0.063)(0.060)
Mother in occupation 30.0730.0620.0710.051
(0.095)(0.097)(0.096)(0.094)
Log of wealth0.049**0.050***0.047**0.047**
(0.019)(0.019)(0.019)(0.019)
Log of land0.082***0.080***0.078***0.076***
(0.024)(0.024)(0.024)(0.024)
# siblings–0.086***–0.071***–0.069***–0.053**
(0.028)(0.025)(0.025)(0.025)
# siblings aged 6–17–0.060**
(0.024)
# siblings aged < 6–0.030
(0.103)
# adults at home0.050
(0.038)
# young male adults at home0.046
(0.061)
# young female adults at home0.124*
(0.068)
# old male adults at home–0.044
(0.121)
# old female adults at home0.040
(0.060)
Parent remitted0.080
(0.067)
Village characteristics
Log of income/person0.0430.0090.0080.0170.008
(0.036)(0.037)(0.036)(0.036)(0.037)
Distance to primary school–0.063***–0.047**–0.047**–0.045**–0.043**
(0.022)(0.020)(0.019)(0.020)(0.019)
Pseudo R20.2890.3670.3690.3750.384
Observations205201201201201

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  1. 1

    There is also a steam of research studying the impact of internal migration on migrant children in China (Feng and Chen 2012; Liang and Chen 2007; Liang, Guo, and Duan 2008).

  2. 2

    A survey based on 2000 census by the All-China Women’s Federation research team shows that 88.2% of all left-behind children report that they can only communicate with their migrant parents by phone; among them 53.5% cannot talk longer than 3 minutes (People’s Daily Online 2007). Furthermore, 8.7% of left-behind children never have contact with their migrant parents. About 24.2% of children with both migrant parents never or seldom talk with their adult guardians.

  3. 3

    E is the earnings net out of migration cost in the case of migration.

  4. 4

    A large literature in sociology and educational psychology suggests that parental involvement has sizable positive effect on children’s educational achievement, and recent economic studies confirm this (Fan 2001; Fehrmann, Keith, and Reimers 1987; Feinstein and Symons 1999; Garg et al. 2002; George and Kaplan 1998; Gonzalez-Pienda et al. 2002; Haveman and Wolfe 1995; Izzo et al. 1999; Ma 2001; Marchant, Paulson, and Rothlisberg 2001; Mau 1997; McNeal 2001; Paxson and Schady 2007; Sacker, Schoon, and Bartley 2002; Sui-Chu and Willms 1996).

  5. 5
  6. 6

    Significant is significant at 5% level unless otherwise stated.

  7. 7

    Table 2 shows the statistics conditional on being in a migrant household not conditional on being a migrant.

  8. 8

    For example, some might concern that father’s age may directly related to father’s age at birth of the child which might be related to health and ability of the child, and therefore affects schooling.

  9. 9

    Though the theoretical model suggests that local wage should have a negative effect on school enrollment, wage only has an insignificant trivial effect in the regression. One hundred yuan increase in wage may decrease enrollment by less than 1%. Also, including wage shrinks the sample size by about 40%, and thus, regressions with local wage are not reported.

  10. 10

    There are two cases of zero farmland size; I substitute them with 0.01 when taking log. I tried substituting them with other small positive numbers, and it does not affect the regression results.

  11. 11

    These results are available upon request.

Published Online: 2014-4-2
Published in Print: 2014-7-1

©2014 by Walter de Gruyter Berlin / Boston

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