1. Purpose

1. PurposeExamine how maternal employment at the child’s age of three affects his/her educational outcome at age of eighteen, using Korean panel data.

2. MotivationThe long-run impact of family environment (maternal employment) on child’s development (educational outcome)?

Two opposite directed effects : maternal employment may increase money input but may decrease time input on child’s education => a total effect of maternal employment on child’s educational outcome is not decisive theoretically

Mother's Labor Force Participation in Early Childhood and the Child's Educational Attainment

Miki Kohara and SunYoun LeeOsaka University

1 Miki Kohara and SunYoun Lee; Osaka University2013/3/3

Maternal employment at age three affects test scores at age eighteen, but the effect is opposite between high (minus effect) and low educational levels (plus effect)

3. Main Result

Introduction

4. Originalities and Contributions- Consider endogeneity of maternal employment and heterogeneity of

its effect- Show a long-term effect of maternal employment on the child’s

development- Examine the Korean case

This result is obtained, after (1) controlling for mother’s educational attainments, father’s occupations, and economic conditions, (2) allowing for the existence of unobserved heterogeneity in a child’s educational outcomes and the mother’s employment, and (3) allowing for non-linearity (heterogeneity) in the effects.


Introduction 2

5. Why Korea? - Important policy issue: there is a social concern about how parent’s

(mother’s) behavior affects educational outcomes. > Education obsession > Extremely low married female labor supply - Good for the analysis: we can use test score data as educational

outcomes “CSAT” College Scholastic Ability Test; once a year at the same time all over the country >Objective measure of educational outcomes >Showing a degree of educational attainments >Measuring outcomes at the end of high-school *Many students take this exam: 82% of the students in the last year of high school (04)


Labor Force Participation of Women (LPR)

2001 1981


LPR of married women

LPR for the 25-29 age group were 7-27% points lower compared to those of other child bearing age groups of 20-24 and the 30-49

LPF for the age group 15-19 appears to have continuously declines since 1970.


Maternal employment deteriorates the child’s educational outcomes?-Ambiguous results. Not always.

The impact of maternal employment on child’s development

Baker, Gruber and Milligan (2008)

Canada ―

Ruhm (2008) USA ― for high economic condition group, butNo effect for lower groups

Bernal (2008) USA ― if a mother started working as a full time worker within a year after giving a birthNo effect of temporary income change

Dustman and Schonberg (2008)

Germany ― Policy change of prolonged maternal leave raises child’s educational outcomes

Tanaka and Yamamoto (2009)

Japan No effect of maternal employment at the child’s age 0-3* But maternal employment after that can lower the probability of going to (probably highly ranked) private or national junior high schools.

6Literature Review 1


Literature on causation behind the effect

(1 )Maternal employment 　⇒　 more income & more investment on education ⇒ 　 child’s educational attainments ↑

… Ambiguous results

(2) Maternal employment 　⇒　 less time with children ⇒　 child’s educational attainments ↓… Ambiguous results

NOTE: Maternal employment － full time worker / high-skilled labor = mother’s higher education level

⇒ 　 child’s educational attainments↑　　　　　　　　　　　　　　－ part-time worker / low-skilled labor = mother’s lower education level ⇒ 　 child’s educational attainments↓☝We need to control for mother’s educational attainment.

Maternal employment － weak preference for child’s care child’s educational attainments↓⇒　　　　　　　　　　　　　　－ strong preference for child’s care child’s educational ⇒attainments ↑☝We need to remove a bias raised by unobserved heterogeneity.

7Literature Review 2


-Estimations with categorical data or quantile regression can be insufficient.

Two difficulties in the estimation

Mother’s employment at age 3

Educational Outcomes at 18 years old

Environmental effect or peer effect of female labor supply at that time, but not to affect child’s educational outcome later at age of 18

Mother’s unobserved ability＋／－　 Over/Under estimateMother’s preference for child’s education－／＋　 Under/Over estimate(1) Problem of Endogeneity

-Linear estimation with endogenous variables can be biased.

(2) Heterogeneous Effects

Empirical Framework 1

82013/3/3

Female Labor ForceParticipation Rates

Estimation for different thresholds

Ti is a dummy variable indicating 1 if a child’s test score is in a “higher” group Mi is a dummy variable indicating 1 if his or her mother was working

Empirical Framework 2

Data ： Korean Labor & Income Panel Study （ KLIPS)

Method: Probit Model with Endogenous Treatment

Non-linear simultaneous decisions

Note.Heterogeneous effect of maternal employment on child’s test score: the effect could be different among the levels of test-scores. Conduct the estimation, changing the threshold!


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Empirical Framework 3 Non-linear effect of maternal employment on child’s test score

Idea! Rank 12

Rank 1

Rank 9

Rank 7=1 (if test score rank>=7)

=0 (if test score rank<7)=1 (if test score==7) otherwise 0 (if test score≠7)

Rank 10

Rank 8

Rank 11


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Korean Labor and Income Panel Study；KLIPS(1998-2008), conducted by the Korea Labor Institute, a government-sponsored research organization. Household Survey ： Householder or spouse （ nationally representative sample of

5,000 households ） Individual Survey ： Each person in the household aged 15 and over （ approx.12,000

persons) Additional Survey （ 2001 ～ 2008 ）： yearly special modules for restricted sample,

such as the youth, the old or the employed. （ approx.4500 persons ） Survey method ： Household Interview

Data used for this study Additional Survey (2006): contains detailed information on education-related

records of the youth aged 15 to 35 at the time of survey(4,389 persons) Maternal employment

Individual and Household Surveys (1998-2006): individual characteristics Individual (2002): Test score for the College Scholastic Ability Test (CSAT) Individual (1998-2006): Parental and child’s educational attainment, birth year and place to

grow up, socio-economic status at age 14, father’s occupation at age 14 Household (1998-2006): demographic information: family composition, marital status

11

Data 1


Important variables: (1) Educational Outcomes at age 18 Test score for the university entrance

exam (CSAT) Historical changes in university entrance examination test1. 1981-1993: Achievement Test started (Highest = 340) 　2. 1994-1996: College Scholastic Ability Test 1 started (Highest = 200)3. 1997- : CSAT 2 started (Highest = 400) 4. 2002- : Diversification of entrance exam. : University can use other

types of exams. Our sample took either (1), (2) or (3). Test scores are answered as 12 ranks We need to control for the difficulties in each

year.

12

0.1

.2.3

.4D

ensi

ty

1 2 3 4 5 6 7 8 9 10 11 12 13Testscore at age 18

Data 2

Advantages of this indicator1) Achievement test and college scholastic ability test were the most important single

determinant for the university admissions in Korea.2) Most of Korean high school students with the same academic attainment take the same

test on the same day (advancement rate to university: 82%, test takers were 572,218 and third grade of high school students 582,216 in 2004)

3) Because the answers are formatted in score ranges with the interval of 10 to 40 scores, potential measurement errors may be small.


KLIPS answer sheet

13

Data 3


Name of Variable Mean S.D.Educational Outcomes

Test score attained at the university entrance examination 7.856 2.420

Family backgroundMaternal Employment at child's age 3 (=1)

0.390 0.488

Female labor force participation rage at child's age 3 38.062 7.564

Mother's employment rateof the child's birth place

0.378 0.108

Mother's educational attainment 3.028 1.100

Father's educational attainment 3.739 1.330

Living with parents at age 14 (=1) 0.025 0.157

0.049 0.2170.230 0.4210.568 0.4960.154 0.361

Household economic statusat age 14

Name of Variable Mean S.D.Child's characteristicsFirst child (=1) 0.401 0.491Number of siblings 1.885 1.093

Residential area at age 140.211 0.4080.442 0.497

Sex 0.370 0.483

Kinds of university entrance exam 0.252 0.4350.276 0.4470.472 0.500

Degree of interaction with parents at age 14 16.788 5.725

Private education before school entry 0.276 0.447

Data 4

14 Miki Kohara and SunYoun Lee; Osaka University

Father’s occupation= 1 if a father works in agricultural industry

15

Data 5

Notes: Average test scores are controlled for in several ways. - dependent variable: “respondent’s own score － average test score” whether this difference is positive or not / more than 30 or less than 30 / …. - controlling for year dummies and/or average test score

LPR of women when our sample was 2 to 5 years old （ % ） Source: National Statistical Office, Annual Report on the Economically Active Population Survey Economically Active Population: The employed and those are who are currently looking for a job LPR: (Economically Active Population/labor force aged 15 and over)＊100

1 ） By age range Imputed from i) mother’s age when the child was 3 years old and ii) LPR of women in Korea at the time at

the child’s age 3 => LPR by age range of mothers at child’s age 3 2) By educational level

Imputed from i) mother’s educational attainment ii) LPR of women in Korea at the time at the child’s age 3 3 => LPR by educational attainment of mothers at child’s age 3

Test score ranks, 7 and 10 are focused.


Estimation Results 1 Dependent variable:12 test score ranks

Considering endogeneity but not heterogeneity in the effect

(linear IV)

Eq(1)(2)：２SLS 2SLS EstimationEndogenous variableMaternal employment at child's age 3 -0.3438

(2.666)Instrumental variableFemale Labor Force Participation Rate (By age) 0.005 *

(0.003)Father's educational attainment 0.3233* -0.053 **

(0.186) (0.024)Mother's educational attainment 0.2160 0.027

(0.167) (0.033)Household economic status at age 14 (2) 1.2143** 0.058

(0.573) (0.093)Household economic status at age 14 (3) 0.6414 0.095

(0.591) (0.091)Household economic status at age 14 (4) 0.9177 0.097

(0.656) (0.106)Father's occupation at age 14 0.3422 0.392 ***

(1.101) (0.073)Testscore_mean 15.7105*** -0.122

(4.224) (0.860)Observations 483F Test of all explanatory variables 5.14*** 4.39 ***F Test of excluded instruments 2.94 *

First-stage regression

Estimation Results 2 Dependent variable:Probability of being classified to each test score rank (12 ranks)

Considering heterogeneity in the effect but not endogeneity

(ordered probit)

Variable

Maternal employment at child's age 3 -0.0494 Test Score Ranks(0.086)

Father's educational attainment 0.1104** Rank 1 0.0001(0.047) (0.000)

Mother's educational attainment 0.1425** Rank 2 0.001(0.058) (0.001)

Household economic status at age 14 (2) 0.5252*** Rank 3 0.002(0.198) (0.004)

Household economic status at age 14 (3) 0.3052 Rank 4 0.003(0.189) (0.006)

Household economic status at age 14 (4) 0.3343 Rank 5 0.005(0.211) (0.009)

Father's occupation at age 14 0.1011 Rank 6 0.005(0.140) (0.009)

Testscore_mean 6.8340*** Rank 7 0.003(1.672) (0.005)

Observations 636 Rank 8 -0.001LR chi2(14) 98.20*** (0.001)

Rank 9 -0.003(0.005)

Rank 10 -0.005(0.008)

Rank 11 -0.005(0.008)

Rank 12 -0.007(0.011)

Maternal employmentMarginal Effect

Estimation Results 3 Dependent variable:Probability of being classified to each test score rank (3 ranks)

Considering heterogeneity in the effect but not endogeneity (ordered probit)

Variable

Maternal employment at child's age 3 -0.0205 Test Score Ranks(0.096)

Father's educational attainment 0.1269** Rank 1 0.0068(0.052) (0.032)

Mother's educational attainment 0.1141* Rank 2 -0.00013(0.065) (0.001)

Household economic status at age 14 (2) 0.3883* Rank 3 -0.0067(0.221) (0.031)

Household economic status at age 14 (3) 0.2442(0.210)


Father's occupation at age 14 0.0781(0.156)

Testscore_mean 6.6600***(1.866)

Observations 636LR chi2(14) 87.79***

Maternal employmentMarginal Effect

18

Rank 1= test ranks 1-4 2= 7-9 3= 10-12

Estimation Results 4 Dependent variable:12 test score ranks

Considering heterogeneous effects but not endogeneity

(quantile regression)

Variable

Maternal employment at child's age 3 -0.1565(0.293)

Father's educational attainment 0.4139***(0.160)

Mother's educational attainment 0.0065(0.196)




Father's occupation at age 14 0.0263(0.470)-5.6133(4.006)

Observations 636Pseudo R2 0.0702

Quantile Regression (Dependent Variable: Test score ofuniversity entrance exam)

19

These results suggest: We cannot find a robust unambiguous effect of maternal employment: either

positive, negative, insignificant??? The effect of maternal employment may be heterogeneous: positive in lower

groups, and negative in higher groups

Estimation Results 5 Testscore_mean, included

Maternal employment at child's age 3 -1.5935*** 1.5216***(0.091) (0.088)

Female Labor Force Participation Rate (By age) 0.0151*** 0.0172***

(0.005) (0.005)Father's educational attainment 0.0070 -0.1813** 0.2048*** -0.1701**

(0.066) (0.072) (0.065) (0.069)Mother's educational attainment 0.1021 0.0991 -0.0089 0.0994

(0.080) (0.087) (0.083) (0.089)Household economic status at age 14 (2) 0.4126 0.2350 0.0844 0.1212

(0.257) (0.272) (0.240) (0.269)Household economic status at age 14 (3) 0.3485 0.3635 -0.0480 0.2586

(0.245) (0.260) (0.233) (0.262)Household economic status at age 14 (4) 0.3825 0.3171 0.0350 0.1713

(0.274) (0.285) (0.275) (0.303)Living with parents at age 14 (=1) -0.3341 -0.3107 0.2274 -0.1904

(0.298) (0.345) (0.306) (0.403)First child (=1) 0.1986* 0.0910 0.1275 0.0788

(0.116) (0.126) (0.119) (0.131)Number of siblings 0.0047 0.0381 -0.0397 -0.0173

(0.069) (0.078) (0.065) (0.074)Male (=1) 0.0695 0.1447 -0.2727** 0.1976

(0.121) (0.133) (0.121) (0.133)Residential Area at age 14 (6 metropolital cities) -0.2395* -0.1885 0.0352 -0.2911*

(0.145) (0.155) (0.152) (0.171)Residential Area at age 14 (9 provinces and Jeju) -0.1008 -0.0023 -0.0572 -0.0548

(0.151) (0.163) (0.155) (0.175)CSAT_1 -0.0122 -0.0205 -0.0050 0.0140

(0.165) (0.180) (0.168) (0.182)CSAT_2 -0.0140 -0.0011 -0.3358** -0.0121

(0.161) (0.178) (0.165) (0.171)Father's occupation at age 14 0.8035*** 0.8262*** -0.5900***1.2082***

(0.166) (0.185) (0.213) (0.239)Testscore (mean value by year) 5.6941*** -0.2346 2.3708 -1.1752

(2.143) (2.392) (2.024) (2.304)Constants -4.3390***-0.8206 -2.0998 -0.1002

(1.504) (1.677) (1.438) (1.655)Observations 483 483 483 483rho:correlation between errors 13.7974 -11.6281

(9.489) (19.522)

Higher than 10 Higher than 7

Controlling for ave test scores

Probit with endogenous decisions Considering

endogeneity and heterogeneous effects

Dependent variable:

Pr(T* 10)≧Higher threshold

Dependent variable:

Pr(T* 7)≧Lower threshold

Pr(M=1) Pr(M=1)


Female Labor Force Participation Rate (By age) 0.0151*** 0.0172***(0.005) (0.005)

Father's educational attainment 0.0070 -0.1813** 0.2048*** -0.1701**(0.066) (0.072) (0.065) (0.069)

Mother's educational attainment 0.1021 0.0991 -0.0089 0.0994(0.080) (0.087) (0.083) (0.089)

Household economic status at age 14 (2) 0.4126 0.2350 0.0844 0.1212(0.257) (0.272) (0.240) (0.269)

Household economic status at age 14 (3) 0.3485 0.3635 -0.0480 0.2586(0.245) (0.260) (0.233) (0.262)


Father's occupation at age 14 0.8035*** 0.8262*** -0.5900***1.2082***(0.166) (0.185) (0.213) (0.239)

Testscore (mean value by year) 5.6941*** -0.2346 2.3708 -1.1752(2.143) (2.392) (2.024) (2.304)

Observations 483 483 483 483rho:correlation between errors 13.7974 -11.6281

(9.489) (19.522)


Estimation Results 6

21

Probit with endogenous decisions Dependent variable: Pr(T*>=μ) Higher threshold Lower threshold

Controlling for ave test scores


Female Labor Force Participation Rate (By age) 0.0192*** 0.0172**(0.007) (0.007)

Father's educational attainment 0.0323 -0.1905*** 0.2189*** -0.1618**(0.066) (0.072) (0.067) (0.073)





Father's occupation at age 14 0.7786*** 0.8733*** -0.5786***1.2090***(0.173) (0.201) (0.214) (0.227)

Testscore (year dummies) Controlled Controlled



22

Probit with endogenous decisions Dependent variable: Pr(T*>=μ)

Higher threshold Lower threshold

Controlling for test years


23

Probit with endogenous decisions Dependent variable: Pr(T* －AveT*>=μ)

Higher threshold Lower threshold

Maternal employment at child's age 3 -1.0580** 1.3462***(0.523) (0.077)

Female Labor Force Participation Rate (By age) 0.0173** 0.0101*(0.007) (0.006)

Father's educational attainment 0.0361 -0.1663** 0.1615*** -0.1612**(0.085) (0.073) (0.061) (0.067)




Household economic status at age 14 (4) 0.6204** 0.2863 -0.0697 0.3034(0.315) (0.319) (0.277) (0.317)

Father's occupation at age 14 0.3116 1.0131*** -0.7989*** 1.1700***(0.328) (0.243) (0.209) (0.250)

Observations 483 533 483rho:correlation between errors 0.7469 -4.5578

(0.566) (5.395)Marginal EffectMaternal employment at child's age 3 -.4657106 .5297742

Testscore Difference >=30 Testscore Difference >=0

= 1 if a father works in agricultural industry

Summary of the results

Maternal employment at age 3 lowers the probability that a child is ranked in higher than or equal to 10 (whether or not a child can go to so-called good universities)

Maternal employment at age 3 raises the probability that a child is ranked in higher than or equal to 7 (whether or not a child can go to universities or colleges)

• Unobservables are controlled for by a simultaneous estimation mechanism.

• Parent’s education, occupation, and economic conditions are also controlled for.

• We attempted the other splits based on parent’s educational levels, occupation, and economic conditions, but we could not find any difference between the groups.


Maternal employment deteriorates the child’s educational outcomes for students in high ranks. But maternal employment raises the child’s educational outcomes for students in low ranks.


25

Why opposite effects?

Maternal employment may decrease an interaction time with children, which discourages test score for children in high test-score groups. This deteriorating effect may be offset by the positive effect of money inputs increased by maternal employment in low test-score groups.


Maternal employment Child’s education

High-ranked groups: time (-) >>> money (+)Low-ranked groups: time (-) <<< money (+)


Maternal employment at age three affects test scores at age eighteen, but the effect is opposite between high (minus effect) and low educational levels (plus effect)

Results and Implications

Conclusion

Explanation other than parent’s education, occupation and economic conditions should be given.One possibility is that maternal employment may decrease an interaction time with children, which discourages test score for children in high test-score groups. This deteriorating effect may be offset by the positive effect of money inputs increased by maternal employment in low test-score groups.

1. Not only discouraging effect but also encouraging effect of maternal employment on child’s educational attainments is found at least for those who were born between 80s & 90s in Korea.2. We need to consider both endogeneity of maternal employment and heterogeneity in its effect when discussing maternal effect on the child’s educational outcomes.

c.f.


Female Labor Force Participation Rate (By age) 0.0158*** 0.0092(0.005) (0.006)

Father's educational attainment -0.0453 -0.1514** 0.1372** -0.1521**(0.062) (0.073) (0.062) (0.069)




Household economic status at age 14 (4) 0.5356* 0.3135 -0.1695 0.3466(0.278) (0.333) (0.285) (0.324)

Degree of interaction with parents at age 14 0.1891 -0.2777** 0.3876*** -0.1956(0.122) (0.135) (0.115) (0.129)

Observations 482 533 482rho:correlation between errors 12.1083 -11.0742

(12.100) (7.871)Marginal EffectMaternal employment at child's age 3 -.7800035 .5375795

Testscore Difference >=30 Testscore Difference >=0

Documents

1. Purpose