Jane Waldfogel

October 14, 2014

The comparability challenge:

Lessons from cross-national

research in developed countries

Funding from NICHD,

Russell Sage Foundation,

& Sutton Trust.

Overview

• Drawing on cross-national research on

socioeconomic status (SES) and child

development in 4 developed countries

(Bradbury, Corak, Waldfogel, &

Washbrook), I will discuss

challenges/lessons related to:

- comparability & harmonization

- transparency & sensitivity

Research questions

• Do socioeconomic status (SES) gaps in

school readiness, and the factors that

explain them, differ across countries?

• Do these gaps widen or narrow after

school entry, and does this vary across

countries?

The challenge

• To answer these questions, we need

comparable measures of SES, child

outcomes, and other predictors/covariates

• But datasets don’t always use same

measures

• So what can we do?

• Tension between best measures vs. most

comparable ones

• Important to be clear about how data are

harmonized and also how sensitive results

are to decisions about

Measurement of SES

(e.g. income or education)• Income

- Continuous or banded? Gross or net?

Includes near-cash/in-kind transfers?

Equivalized?

• Be clear how it’s being defined and how

it’s being made comparable

• We use income quintiles because they

have a similar meaning across countries

• But one might also be interested in

absolute income or other measures (e.g.

poverty)

Measurement of SES

• Parental education

- Mother’s? Father’s? Years of schooling?

Education completed? Certificate

obtained?

• Again, need to be clear how it’s measured

• We use education of most highly educated

parent and 3 ISCED categories that are

comparable across our 4 countries

• We report how/why we created those

categories and how sensitive results are

Measurement of child

development• We need measures of child cognitive

development, behavior, and health

• Sometimes same measure is used across

2+ countries, but rarely all 4

• So we look at each measure and choose

the ones that are most consistent

(sometimes this involves creating our own

measure)

• We report the sensitivity of our results to

using different measures

Other covariates

• We also need measures for key predictors

other than SES – variables such as

parenting, parental health/mental health,

etc.

• Often, this means using the lowest

common denominator – rather than the

rich variables available in some datasets –

but this is a necessary trade-off to ensure

comparability.

• But again we report how/why we did this,

and report how sensitive results are

Comparing SES gaps in US and

UK• Using data from ECLS-B (US) and

ALSPAC (UK), Liz Washbrook and I

examined SES gaps in school readiness

• We divided families into income quintiles

and examined bottom-middle (Q1-Q3) and

top-middle (Q5-Q3) gaps in comparable

cognitive outcomes

• We found sizable SES-related gaps in

school readiness (vocabulary) in both

countries, but larger at the top in US than

UK

Comparing SES gaps in school

readiness in US & UK

Decomposing factors

associated with gaps in the two

countries• We next used the rich data from the US &

UK cohort studies to examine factors

explaining gaps

• To play a role in explaining gaps, a factor

must

- Differ between income groups

- Have an effect on the outcome

• Our decomposition analysis shows which

factors are most consequential, pointing to

an important role for parenting in both

countries

Trajectories after school entry

• We would like to know what happens to

these gaps once children are in school

• Do the gaps widen, narrow, or hold

constant?

• Katherine Magnuson, Liz Washbrook, and

I examined this for US and UK, using data

on reading from ECLS-K and ALSPAC

SES gaps after school entry in

US

SES gaps after school entry in

UK

Gaps in the 4 countries

• In recent work funded by Russell Sage

Foundation, we used 4 longitudinal datasets:

- AU (LSAC), CA (NLSCY), UK (MCS), US

(ECLS-K)

• We follow children from school entry to at

least age 11, analyzing whether SES-related

gaps widen, hold constant, or narrow, and

relating differences in gaps across countries

to differences in family resources & policy

contexts

Gaps in the 4 countries

• We find gaps are largest in US, and UK,

and smallest in Australia and Canada

• We are also able to estimate how much of

the gaps at age 11 are already present at

age 5, and how much develops during the

school years

• We find that most of the gap in US is

already present at school entry, more so

than in the other countries

Key findings

• Achievement gaps at school entry differ

across countries, mirroring differences in

adult social mobility – with larger gaps in

US & UK than AU & CN

• The evolution of the gaps after school

entry also differs across countries, likely

reflecting the continuing influence of family

factors as well as differences in school

factors

Key lessons in terms of

comparability• It’s important to get the harmonization right

- You have to invest considerable

time/resources in harmonizing data

- You may want to consult others on this

• It’s also important to be transparent

- Be clear what decisions you made and

why

- Be clear how sensitive results are to

alternatives

What’s next?

• Examining gaps at school entry, and

evolution of gaps after school entry, in

additional countries

• Examining changes in gaps for

succeeding cohorts, both within and

across countries

References

• Bradbury, Bruce, Miles Corak, Jane Waldfogel, & Elizabeth

Washbrook (2012). “Inequality during the Early Years: Child

Outcomes and Readiness to Learn in Australia, Canada, United

Kingdom, and United States.” In John Ermisch, Markus Jantti, and

Timothy Smeeding (eds). From Parents to Children: The

Intergenerational Transmission of Advantage. New York: Russell

Sage Foundation.

• Bradbury, Bruce, Miles Corak, Jane Waldfogel, & Elizabeth

Washbrokk (under review). Too many children left behind: A cross-

national perspective on the US achievement gap. New York:

Russell Sage Foundation.

• Magnuson, Katherine, Jane Waldfogel, & Elizabeth Washbrook

(2012). “The Development of SES Gradients in Skills during the

School Years: Evidence from the United States and England.” In

John Ermisch, Markus Jantti, and Timothy Smeeding (eds). From

Parents to Children: The Intergenerational Transmission of

Advantage. New York: Russell Sage Foundation.

References

• Waldfogel, Jane & Elizabeth Washbrook (2011). “Income-Related

Gaps in School Readiness in the United States and United

Kingdom.” In Timothy Smeeding, Robert Erikson, and Markus Jantti

(eds). Persistence, Privilege, and Parenting: The Comparative Study

of Intergenerational Mobility. New York: Russell Sage Foundation.

• Waldfogel, Jane & Elizabeth Washbrook (2011). “Early Years

Policy.” Child Development Research 2011: 1-12.

• Washbrook, Elizabeth, Jane Waldfogel, Bruce Bradbury, Miles

Corak, & Ali Akbar Ghanghro (2012). “The Development of Young

Children of Immigrants in Australia, Canada, the United Kingdom

and the United States.” Child Development 83(5): 1591-1607.