1

Childlessness: a further look at cohort estimates based on survey

time-series data

Máire Ní Bhrolcháin*, Eva Beaujouan*, and Mike Murphy**

* Centre for Population Change, University of Southampton

** Department of Social Policy, London School of Economics

2

Outline

• Where have all the children gone?

• Possible explanations

• Identifying missing own children

• Revised childbearing history

• Validation

• Sources of misreporting

• Conclusions and future work

3

Where have all the children gone?

Proportion childless (weighted) according to the GHS birth histories, by age and birth cohorts

Cohort

change in % childless 40-44 to 55-59

1935-39 + 3.9

1940-44 + 5.91945-49 + 7.31950-54 + 4.0 (to 50-54)

4

Explaining these findings

Potential sources of bias• migration• mortality• institutionalisation• changing differential response rates• changing item non-response• change in sample design• respondent fatigue? forgetting? deliberate

misreporting?

5

Using household data to identify own children

Own children in household identified via

• relationship code

• gap of 16+ years in age

Matches between birth history and own children identified

Own children identified who were not declared in the fertility history

6

Presence in household of own children not recorded in fertility history, by women’s self-reported fertility

a. by declared parity b. among childless by age

Revise the fertility history

Merge undeclared own children into original history to generate revised fertility history [checks]

Validated against sources internal and external to GHS

8

Intra-cohort change in percent childless by survey year, original and revised fertility histories

Cohort 1945-49

0

5

10

15

20

25

30

1984 1989 1994 1999 2004

Survey year

%

original

revised

Cohort 1950-54

0

5

10

15

20

25

30

1984 1989 1994 1999 2004Survey year

%

9

Proportion childless by age and birth cohort, revised histories. GB: cohorts 1935-39 to 1970-74, weighted

0

20

40

60

80

20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59

Age group

%

1935-39

1940-44

1945-49

1950-54

1955-59

1960-64

1965-69

1970-74

10

Annual TFR based on original and revised fertility histories & vital registration. GB, 1979-2007, weighted

1.0

1.5

2.0

2.5

19711974

19771980

19831986

19891992

19951998

20012004

2007

Year

Child

ren

for

1000

wom

en

TFR revisedTFR GBTFR original

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% with undeclared child(ren) among self-reported childless women by age and interview mode

Laptop self-completion

0

10

20

30

40

50

60

1994

1995

1996

1998

2000

2001

2002

2003

2004

2005

-07

Survey year

%

12

Potential number of questions within FI before fertility history

0

20

40

60

80

100

1979 1983 1986 1990 1994 1998 2000

minmax

13

Questions in Family Information section

Illustration

A woman with one disrupted cohabitation + one marriage with

premarital cohabitation + 2 stepchildrenwould have to answer 24

questions before she fills in the birth history among which 7 dates…

0

10

20

30

40

50

current marr hist cohabhist

SFA

minmax

5 x 8 3 x 7 2 x 7

Interviewer instructions

Up to 1996, interviewers instructed to code the “ever had a baby” question as “yes” without asking if this was evident from household composition and step/foster/adopted children question

Instruction absent in 1998, though “Ask or record” on questionnaire 1998-2007

No instructions available 2000-

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Quality of GHS fertility data: implications

Policy• estimates of true birth order• indirectly, estimates of childlessness

demographic, social care

• study of lone parent familiesResearch• demographic research on fertility and

family

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Conclusions and future directions

Careful monitoring by subject specialistsNeed to validate survey fertility historiesLaptop self-completion may *reduce* rather

than improve data qualityReconsider respondent burdenFertility history sensitive? or cohabitation

history? Future work: estimating childlessness

imputation of births?

17

Acknowledgments

Analysis based on the CPC GHS time series datafile constructed in collaboration with Dr Ann Berrington and with the assistance of Mark Lyons Amos.

We thank ONS and General Lifestyle Survey Branch for their help with various questions about the data.