Parental education and child health evidence from a natural experiment in taiwan
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Parental Education and Child Health: Evidence from a Natural Experiment in Taiwan. Shin-Yi Chou Lehigh University & NBER Jin-Tan Liu ( 劉錦添) National Taiwan University & NBER Michael Grossman City University of New York Graduate Center & NBER Theodore Joyce Baruch College & NBER.

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Parental Education and Child Health: Evidence from a Natural Experiment in Taiwan

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Parental Education and Child Health: Evidence from a Natural Experiment in Taiwan

Shin-Yi Chou

Lehigh University & NBER

Jin-Tan Liu (劉錦添)

National Taiwan University & NBER

Michael Grossman

City University of New York Graduate Center & NBER

Theodore Joyce

Baruch College & NBER


臺灣過去50年,兩大公共政策

  • 1968年 九年國教

  • 1995年 全民健保

    Duflo (2001), “Schooling and Labor Market Consequences of School Construction in Indonesia:Evidence from an Unusual Policy Experiment,” American Economic Review, 91, 795-813.

    Currie and Moretti (2002),”Mother’s Education and the Intergenerational Transmission of Human Capital: Evidence from College Openings,” Quarterly Journal of Economics, 118, 1495-1532.

    Clark and Hsieh (2000), “Schooling and Labor Market Impact of the 1968 Nine-Year Education Program in Taiwan,” Working Paper, Department of Economics, Princeton University


Education and Health:

  • Michael Grossman (1972), “On the Concept of Health Capital and The Demand for Health,” Journal of Political Economy, 80, 223-255.

  • Michael Grossman (2000), “The Human Capital Model,” in Culyer and Newhouse eds. Handbook of Health Economics, Vol. 1. Elesevier Science B.V.

  • Michael Grossman and Robert Kaestner (1997), “Effects of Education on Health,” in Behrman and Stacery eds. The Social Benefits of Education, University of Michigan Press.


Education and Health

  • Michael Grossman, “Education and Nonmarket Outcomes,” in Hanushek and Welch eds. Handbook of the Economics of Education, Elsevier Science.

  • (NBER working papers No. 11582).

  • Conceptual Foundations:

  • 1. Productive efficiency

  • 2. Allocative efficiency

  • Causality?

  • Y = X B + U

  • “The third variable” may cause schooling and health to vary in the same direction.

  • “The time preference hypothesis”


Empirical Methods:

  • 1. Include past health measures in regressions

  • 2. Siblings or twins samples:

  • control for unmeasured third variables

  • differences in outcomes due to differences in

  • schooling between siblings or twins.

  • 3. Instrumental variables method (IV):

  • variables are correlated with schooling but not

  • correlated with omitted third variables, such as

  • ability, inherited genetic traits, and time

  • preference.


Instrumental Variable (IV)

  • Y = X B + U

  • OLS is biased when U is correlated with X

  • Use an IV Z for X

  • βIV = (Z’X)-1 (Z’Y)

  • βIV is consistent when Z satisfies two conditions:

  • 1) Z is uncorrelated with U

  • 2) Z is correlated with X


Instrumental Variable (IV)

  • Random encouragement designs:

  • 1. To test the effect of flu vaccine on flu:

  • The IV (the letter) is randomly assigned,

  • but not the treatment (flu vaccine).

  • 2. Distance to hospital with operating facilities

  • as an IV for surgery in heart attacks.

  • 3. Distance to school as an IV for schooling

  • 4. Policy Reforms


How to find IV?

  • 1.Lleras-Muney (2005), Compulsory Education

  • Laws from 1915 to 1939

  • US Censuses of Population for 1960, 1970, 1980

  • The effect of education on mortality

  • 2. Arendt (2005), Compulsory School Reform in

  • Denmark in 1958 and 1975

  • The impact of schooling on self-rated health

  • 3. Spasojevic (2003), 1950 Swedish

  • Comprehensive School Reform.


Difference-in-Difference (DD)Estimators

  • “Natural Experiments” Actual policy changes to identify the effects of policies on outcomes

  • DD: to compare outcomes before and after a policy change for a group affected by the change (Treatment Group, T) to a group not affected by the change (Control Group, C).

  • DD = [E(Y1 ︳T) – E(Y0︳T)] –

  • [E(Y1 ︳C) – E(Y0︳C)]

  • Yi, t = α+ β2 Time + β3 Treatment

  • + β4 (Time* Treatment) + ui,t


DD:

  • Meyer, Bruce D. (1995), “Natural and Quasi-experiments in Economics,” Journal of Business and Economic Statistics, 13(2), 151-161.

  • Angrist, Joshua D. and Alan B. Krueger (1999), “Empirical Strategies in Labor Economics,” Handbook of Labor Economics.

  • MIT, Harvard:

  • Jonathon, Gruber

  • Duflo, Esther


前言

  • 探討主題:Does the parents’ attainment of education affect the health of their children?

  • 研究困難:Unobserved characteristics that affect both the parents’ education levels and the health of their children.

  • 本文實證方法:Compulsory schooling laws in Taiwan affects the levels of Parental education, but is uncorrelated with children’s health


?

本文大綱

  • 1968年臺灣九年國民義務教育

  • Data and sample

  • Effect of 1968-Reform on Education

  • Effect of Parental Education on child health outcomes


研究背景:1968年延長九年國民義務教育

  • Extended from 6 years to 9 years

  • 140 new high schools were opened

    • Number of junior high schools per thousand primary school graduates increased from 0.8 (1967-1968 academic year) to 1.3 (1968-1969 academic year)

    • The percentage of primary school graduates who entered junior high school increased from 56% (1967-1968 academic year) to 77% (1968-1969 academic year)

  • Intensity of school construction varies across regions.


(每1000位國小畢業生中國中的數目)

Junior High Schools per Thousand Primary School Graduates Source: Ministry of Education, Educational Statistics of Republic of China.


(每位國小畢業生進入國中的比例)

Number of First Year JH Students to Number of Primary School Graduates

Source: Ministry of Education, Educational Statistics of Republic of China.


ProgramIntensity in 1968

(1968年新設國中數目佔1967年每1000 位12歲至14歲學童的比率)

* Program intensity is defined as number of new junior high schools in 1968

per thousand children ages 12-14 in 1967.


Econometric Method:

  • 控制組/對照組: children over/under the age of 11 in 1968

  • Validation of our strategy:

    • The higher the program intensity is, the larger the effect of education reform

    • Program intensity was independent with initial schooling levels


Enrollment Rate

Program

Enrollment Rate in 1966 vs. Program Intensity Source: Ministry of Education, Educational Statistics of Republic of China.


Program

Percentage of Workers in Agriculture in 1967 vs. Program Intensity Source: The data on percentage of workers in agriculture are from the Taiwan Agricultural Yearbook.


Data and Sample

  • Birth and death certificates, 1978-1999, total 22 years

  • Sample Size: 5,576,868~6,099,832.

  • Child Health outcomes include the probabilities of:low/very low birth weight(less than 2500 grams/1500 grams), pre-maturity, mortality,etc.

  • Sample: women or men satisfying these:

    • Between 1- and 20-years old in 1968

    • Between 22- and 45-years old when they or their wives gave birth in 1978-1999


Effect of 1968 Education Reform on Education

  • Basic approach:

  • Sijt is the number of years of formal schooling completed by mother (or father) i born in city/county j with her/his child born in year t.

  • Indices: i: mother (or father), j: city/county, t: year

  • C: cohort dummies,

  • P: program intensity,

  • T: treatment group dummy,

  • R: region of birth(city/county),

  • Y: year dummies, 1978 is an omitted year

19

19

1979

l =1979


β (

)

)

β (

Effects of Education Reform on Parents’ Educational Attainment (Basic Approach)


1968年九年國教對個人教育成就的影響:

  • Education reform not only has a positive impact on the educational attainment of the treatment groups, but also has a larger impact for the younger women.

  • The 12-14 year-olds may not be a pure control group.

  • Education reform has a bigger impact on father’s educational attainment than on mother’s.

  • Education reform had a larger impact on the education of younger fathers.


1968年九年國教對個人教育成就的影響(續):

  • Full specification: replace P x T by P x C(Program Intensity)

  • Coefficient series {bk}:

    • decreases sharply when k=13 (13 years old in year 1968)

    • fluctuates near 0 when k=14 ~ 19

    • all positive for k=0 ~ 11, and decreases from 0 to 11

1999

19

k=1979

l=1979


Mothers

Fathers

Coefficients of the Interactions between the Age in 1968

and Program Intensity in the Years of Schooling Regression


1968年九年國教對教育成就的影響

  • Restricted Estimation: assume bk=0 when k ³15.

  • We delete the cohort aged 12-14 from our sample.

  • The F-ratios are 15.73 and 16.96 for mother’s and father’s samples, respectively, when the enrollment rate and the percentage of agricultural share are employed as regressors.

  • for every junior high school constructed per 1000 children between the ages of 12 and 14,

    • Mothers 0-5, 6-11: receive 1.0 and 0.72 additional years

    • Fathers 0-5, 6-11: receive 0.84 and 0.77 additional years


Effect of Parental Education on Child Health Outcome

  • Basic approach in the first stage

    • Under OLS estimation, higher parental educational attainments significantly reduce the risk of all adverse health outcomes (prematurity, etc.)

    • Under the 2SLS estimation, mother’s years of schooling shows significant impacts only on low and very low birthweight and prematurity.

    • Under the OLS estimation, father’s years of schooling has similar effect as mother’s.

    • Under 2SLS, father’s years of schooling has smaller effect as mother’s.


Effects of Parental Schooling on Child Health Outcomes:

OLS and TSLS (Basic Approach in the First Stage)


Effect of Parental Education on Child Health Outcome

  • Restricted estimation in the first stage

    • Similar to previous results except that father’s years of schooling reduces infant and postneonatal mortality.


Effects of Parental Schooling on Child Health Outcomes:

OLS and TSLS (Restricted Estimation in the First Stage)


Further questions:

  • 1. Control group, treatment group

  • Age:

  • 2. Clustering

  • 3. Group data regression

  • Weights?

  • 4. Mother’s education vs. Father’s education


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