capturing the impact of demographic processes on social

IntroductionPreliminary analysis

Combining information using simulationConclusion and discussion

Capturing the impact of demographicprocesses on social stratification in education

in Germany

Maarten L. Buis

Institut für SoziologieEberhard Karls Universität Tü[email protected]

Maarten L. Buis Capturing the impact of demographic processes on social stratification in education in Germany



Outline

Introduction

Preliminary analysis

Combining information using simulation

Conclusion and discussion




Inequality of Educational Opportunity versusReproduction of Educational Categories

I Inequality of Educational Opportunity use a sample of theoffspring, while reproduction must use a sample parents

I Reproduction includes indirect effects throughdemographic processes:

I Inequality of Educational Opportunity → How close is acountry to the meritocratic model?

I Reproduction of Educational categories → What are thelong term processes that shape the structure of society?




Reproduction of educational categories anddemographic processes

mother’seducation

Offspring’seducation

father’seducation

# siblings

+

− −

+ +




Challenges

I Estimation requires a sample of mothers who havechildren who finished their education.

I This is not a common design.I The most recent cohort that can be studied was born

approx. 60 years ago.I Alternative is to reconstruct such a dataset using

simulation:I It is possible to use a wider range of datasources.I Extrapolation to more recent cohorts is natural within this

framework.




Challenges


I This is not a common design.

I The most recent cohort that can be studied was bornapprox. 60 years ago.

I Alternative is to reconstruct such a dataset usingsimulation:

I It is possible to use a wider range of datasources.I Extrapolation to more recent cohorts is natural within this

framework.




Challenges



approx. 60 years ago.

I Alternative is to reconstruct such a dataset usingsimulation:


framework.




Challenges




simulation:


framework.




Challenges




simulation:I It is possible to use a wider range of datasources.

I Extrapolation to more recent cohorts is natural within thisframework.




Challenges




simulation:I It is possible to use a wider range of datasources.I Extrapolation to more recent cohorts is natural within this

framework.




Outline

Introduction







Mother’s education → Father’s education

mother’seducation


father’seducation

# siblings

+

− −

+ +





Data & MethodsI Collected as part of the program “Sociology and the Study

of the Life Course”.I Cohorts born in 1920 1930 1940 1950 1955 1960 1964

1971I 4,231 observations (350 – 850 observations per cohort)I retrospective reconstruction of the life course.I Ordered logit of Father’s education on Mother’s education,

year of birth of the mother, and interaction betweenmother’s education and year of birth.





2

5

10

20

40

80

odds

rat

io

1920 1930 1940 1950 1960 1970

year of birth

women’s educationmedium versus lowerhigher versus lower




Father’s education → Offspring’s education

mother’seducation


father’seducation

# siblings

+

− −

+ +





Data & MethodsI Life History Study and ALLBUS 2006 and 2008I ALLBUS is a general survey, approx. 2,000 observations

per surveyI Not a sample of mothers but a sample for offspring.I Ordered logit of Offspring’s education on Father’s and

Mother’s education, number of siblings, offsrping’s year ofbirth.

I Interactions of year of birth with Father’s and mother’seducation and number of siblings.





1

2

5

10

odds

rat

io

1920 1940 1960 1980

year of birth

father’s educationmedium versus lowerhigher versus lower




Mother’s education → Offspring’s education

mother’seducation


father’seducation

# siblings

+

− −

+ +




Mother’s education → Offspring’s education

1

2

5

10

odds

rat

io

1920 1940 1960 1980

year of birth

mothers’s educationmedium versus lowerhigher versus lower




Mother’s education → Fertility

mother’seducation


father’seducation

# siblings

+

− −

+ +





Data & MethodsI Life history StudyI Discrete time event history modelI predicted hazards are calibrated using register data





.5

1

1.5

2

2.5

fert

ility

rat

e

1920 1940 1960 1980

year of birth

educationlowermiddlehigher




Number of siblings → Offspring’s education

mother’seducation


father’seducation

# siblings

+

− −

+ +





Data & MethodsI Life history study and ALLBUSI number of siblings in ALLBUS are imputed





.75

1

1.5

odds

rat

io

1920 1940 1960 1980

year of birth




Outline

Introduction







Simulation

I Start with 5,000 women each in cohorts 1920 1930 19401950 1955 1960.

I Assign them an educationI Assign them children given their cohort and educationI Assign them a partner (or not) with a level of educationI Assign an education to the offspring given Mother’s and

Father’s education, year of birth, and number of siblings.I Analyze the simulated datasetI One can study the impact of differential fertility and

homogamy by creating counterfactual scenarios wherethese don’t exist.




Simulation


I Assign them an education

I Assign them children given their cohort and educationI Assign them a partner (or not) with a level of educationI Assign an education to the offspring given Mother’s and






Simulation


I Assign them an educationI Assign them children given their cohort and education

I Assign them a partner (or not) with a level of educationI Assign an education to the offspring given Mother’s and






Simulation


I Assign them an educationI Assign them children given their cohort and educationI Assign them a partner (or not) with a level of education

I Assign an education to the offspring given Mother’s andFather’s education, year of birth, and number of siblings.

I Analyze the simulated datasetI One can study the impact of differential fertility and





Simulation



Father’s education, year of birth, and number of siblings.

I Analyze the simulated datasetI One can study the impact of differential fertility and





Simulation



Father’s education, year of birth, and number of siblings.I Analyze the simulated dataset

I One can study the impact of differential fertility andhomogamy by creating counterfactual scenarios wherethese don’t exist.




Simulation








Resutls

5

10

20

40

80

odds

rat

io

1920 1930 1940 1950 1960

year of birth of the mother

differential fertilityand homogamyno differential fertilityno homogamyno differential fertilityand no homogamy




Outline

Introduction







Conclusion

I Indication for a substantial indirect effect of mother’seducation on the offspring’s education through the Father’seducation.

I Evidence for an indirect effect through the number ofsiblings is mixed.




What’s next?

I Confidence building in the simulation

I Comparison with empirically observed cohortsI Add more dataI Quality control (certification and verification scripts)

I historical trends rather than counterfactual scenariosI international comparison




What’s next?

I Confidence building in the simulationI Comparison with empirically observed cohorts

I Add more dataI Quality control (certification and verification scripts)





What’s next?

I Confidence building in the simulationI Comparison with empirically observed cohortsI Add more data

I Quality control (certification and verification scripts)I historical trends rather than counterfactual scenariosI international comparison




What’s next?

I Confidence building in the simulationI Comparison with empirically observed cohortsI Add more dataI Quality control (certification and verification scripts)





What’s next?


I historical trends rather than counterfactual scenarios

I international comparison




What’s next?




capturing the impact of demographic processes on social

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