Second demographic transition: status questionis after 25 years

1. SDT articles and papers can be downloaded from
http://www.sdt.psc.isr.umich.edu
http://www.vub.ac.be/SOCO/Lesthaeghe.htm

2. A. Maslow’s pyramid of needs
1943
R. Inglehart’s postmodernism transition
2005
Life styles, fertility
derivative thereof,
SDT
Economic
Security, Child quality,
FDT

3. GNP per Capita
Survival
Major concern
Well-being
Major concern
First demographic
transition in fertility and
health/mortality : class
differentials dominant;
minor life style
differences within social
classes.
Second demographic transition in
household formation & fertility &
health/mortality: Major life style
differentials develop within social
strata.
Maslowian scale

4. Theoretical views on fertility in SDT countries since the 1970s
• 1970s & 80s : Easterlin & oscillating fertility.
• 1986 SDT Long term below replacement fertility due to
postponement of partnership, marriage and parenthood.
(Plurality of life styles).
• 1990s: Stochastic forecasting : No Social Sc. theory,
only mechanistic statistical extrapolation of distributions.
• 1990s: Bongaarts-Feeney : rediscovery of postponement
effect on period rates. Misinterpretations ! No modeling
of recuperation-phase.
• 2000: Still dominance of postponement – but occasional
stress on differential catching up. More stress on cohort
profiles (Lesthaeghe & Willems, Frejka & Sardon,
Sobotka)

5. Contrast first & second demographic
transitions
• FDT
• EARLIER MARRIAGE
• LOW + DECLINING
COHABITATION
• LOW DIVORCE
• HIGH REMARRIAGE
• FERTILITY CONTROL AT
HIGHER AGES
• DEFICIENT
CONTRACEPTION, PARITY
FAILURES
• DECLINING ILLEGITIMACY
• LOW CHILDLESSNESS
• SDT
• LATER MARRIAGE
• RISE COHABITATION, RISE
SINGLE LIVING
• RISE DIVORCE
• LOW REMARRIAGE
• FERTILITY
POSTPONEMENT
• EFFICIENT
CONTRACEPTION
• RISING EXTRA-MARITAL
FERTILITY
• HIGHER CHILDLESSNESS

6. Shifting fertility distributions
Postponement : differentials in date of onset
and in speed.
Recuperation : very different amounts, but
remarkably stable patterns of differentials.
Look at cohort fertility ( aggregate & by
parity) for the full view of the story

7. Source : D.J. vandeKaa, 2002

8. SDT2 index (attitudes and values dimension)
This index is based on the 1999/2000 results of the European Values Study,
published in Halman (2001). It is based on the responses in 29 countries to the
following questions and statements.:
“…how important it is in your life: leisure time” (LEISURE, % “very important”)
“How often do you spend time in church, mosque, or synagogue” (CHURCH, %
“every week”);
“Please use the scale to indicate how much freedom of choice and control you feel
you have over the way your life turns out?” (CONTROL, mean value on the scale
of 1 (=none control at all) to 10 (= a great deal of control));
“Do you think that a woman has to have children in order to be fulfilled or is this not
necessary?” (NEED_KIDS, % responses “not necessary”);
“Marriage is an outdated institution” (MARRIAGE, % “agree”);
“A job is alright, but what women really want is a home and children” (F_HOME, %
“agree strongly”);
“One does not have the duty to respect and love parents who have not earned it by
their behaviour and attitudes” (PAR_RESPECT, % “agree”);
“Do you approve or disapprove abortion (…) where a married couple does not
want to have any more children?” (ABORTION, % “approve”).
Several questions were not asked in all the participating countries; the SDT2 index
for these countries was based on the mean score of the responses to the
remaining items. Maximum, minimum and mean values of these indicators and the
assigned SDT scores are displayed in table AP-2.

9. A strong SDT – fertility postponement link
Lithuania
Russia
Belarus
Bulgaria
Estonia
Slovakia
Romania
Latvia
Poland
Ireland
Czech Republic
Hungary
Portugal
Austria
Slovenia
Croatia
GreeceItaly
Spain
France
United Kingdom
Denmark
Germany
The Netherlands
Finland
Sw eden
0.0
1.0
2.0
3.0
4.0
5.0
6.0
7.0
8.0
9.0
1980 1985 1990 1995 2000 2005 2010
Year when mean age at first birth increased by 2 years
SDT2Index
SDT vanguard
SDT tail
Source: T. Sobotka 2008.

10. SOURCE : D.J. vandeKaa, 2002.
Recup
No or weak recup
Late start

11. But a positive association between SDT and period total
fertility : classic case of split correlation
Bulgaria
Poland
GreeceSlovakia
Luxembourg
The Netherlands
United Kingdom Finland
Denmark
France
Sweden
Lithuania
Latvia
Spain
Italy
Hungary
Austria
Estonia
Czech Rep.
Portugal
Germany
Russia
Croatia
Ukraine
Romania
Ireland
Iceland
Slovenia
Belarus
0
1
2
3
4
5
6
7
8
9
10
1.00 1.20 1.40 1.60 1.80 2.00 2.20TFR
SDTIndex
Figure 8a: SDT Index and TFR in 2004 (r=0.71)
All stronger recuperation countries
No or weak recup & late starters
Source of plot : Tomas Sobotka, 2008. Interpretation : Ron Lesthaeghe 2008.
1.50

12. for a < 30 for a > 30
dt(a) = dn(a)*kt dt(a) = dn(30)*kt + rn(a)*Rt
___________________________________________________________________________
dn(a): national standard age schedule of deviations in cumulated fertility compared to those of
benchmark cohort
dno(a): idem, if no recuperation after age 30
dt(a): age schedule of deviations from benchmark at any time t
dto(a): idem, if no recuperation after age 30 (= dn(30)*kt)
kt: "through scalar" at time t
kt = B/A = cumfertt(30) - cumfertb(30) / cumfertn(30) - cumfertb(30)
Rt: "relative recuperation scalar"
Rt = dt(30) - dt(50) / dn(30) - dn(50)
___________________________________________________________________________

13. Deficits CCFR Netherlands
-1000
-800
-600
-400
-200
0
200
<20 <20-24 <20-30 <20-34 <20-39 <20-44 <20-45+
Age Brackets and Baseline (1940-44)
Deficets,ThousandsofBirths
1945-1949
1950-1954
1955-1959
1960-1964
1965-1969
1970-1974
1975-1979
1980-1984
Deficits CCFR Portugal
-900
-800
-700
-600
-500
-400
-300
-200
-100
0
100
200
<20 <20-24 <20-30 <20-34 <20-39 <20-44 <20-45+
Age Brackets and Baseline (1940-44)
Deficets,ThousandsofBirths
1945-1949
1950-1954
1955-1959
1960-1964
1965-1969
1970-1974
1975-1979
1980-1984
TROUGH RECUP
PTFR(t+30) = A + B1*BaseCTFR(t=0) + B2*TROUGH(t) + B3*RECUP(t) + e
Trough = deficit in cumulated CASFR at age 30 compared to base
Recup = part of trough recuperated by age 40
Sample= all never communist European countries, baseline = cohort born 1940-44,
predicting PTFRs in period 1960-2005.
RESULT : baseCTFR only Rsq. = .505, baseCTFR + Trough Rsq= .673,
all 3 including Recup then Rsq= .793. Hence : RECUP IS ESSENTIAL.
ONLY countries dip below a TFR below 1.5 that have no or weak recuperation.
The “Bongaarts’ babies” have remained in his cupboard in a large number of
countries, and will stay there for as long as there is no recuperation of fertility after
age 30.

15. Source : E.J.C. Tu and X. Zhang, 2004

16. Postponmt + weak
or no recuperation
Postponement +
stronger recuperation
Less
postponement but
quantum drop

17. How do countries line up ?
SDT-based expectation very good when considering the postponement of
marriage and parenthood : high on SDT => earlier and stronger
postponement.
But TFR line-up goes the other way : high on SDT => higher TFR, no
“lowest-low fertility”.
Essential to distinguish between the postponement and catching up
effect. Latter now MAJOR determinant of national differentials in overall
fertility in “never Communist” Europe where SDT started earliest. Pure
postponement models are INADEQUATE.
Differential catching up will lead to differential childlessness as well.
Some SDT-values foster postponement, but some ( gender equity ones)
may be associated with low childlessness and better catching up at later
ages.

18. SDT and TFRs : inconsistent or double effect ?
Self-actualisation,
keeping open future.
Emancipation: gender
equity & division of
labour in family.
Organisation & policy aspects re
independence of young adults and
reduction opportunity costs (child
care facilities, schooling,
allowances & benefits), housing
opportunities.
SDT
Postponement
Recuperation
Overall fertility
+
+
_
+
Social & Economic
constraints: longer
education, deregulation
labour market etc

19. Former Communist Europe : Crisis or transition ?
Countries line up :
1. Countries that recovered best re real GDP recovery by 2000 have the larger
increases in mean ages at first marriage and at first birth. Contrary to crisis
hypothesis.
2. Countries that score highest on index of gender empowerment and on self-
realization ( Inglehart & Welzel ) have the highest increases in mean ages at
first birth. Consistent with SDT.
3. No other significant correlations with size drop TFR 1989-2000, or size
increase extra-marital fertility 1990-2000.
Social class differentials.
Greater / earlier rise of premarital cohabitation among lower educated or lower
socio-econ strata is by no means an indicator of the crisis hypothesis. This
feature is often found in other societies as well (e.g. Sweden and USA).
Historically: cohabitation was lower class feature in most societies.
Timing
Postponement trends in FCC’s often predate the 1989-Wende.

20. Former Communist Countries and Demographic change in the period 1989-
2000 : do they line up ?
Zero order correlations between indicators of economic performance,
indicators of Value orientations ( Inglehart & Welzel), and indicators of
demographic change.
Size Drop Size Rise in Size Rise in Mean Age:
in TFR extramar. Fert. 1st marr. 1st birth
Index recovery real GDP ’90=100 .283 ns .008 ns .665 * .622 *
Index recovery total employment ’89=100 -.408 ns .119 ns .078 ns .264 ns
Index recovery industrial output ’89=100 -.195 ns .011 ns .267 ns .165 ns
UN Index gender empowerment ca 2000 .139 ns -.010 ns .289 ns .581 *
Percent self-expressiveness ca mid-90s .065 ns -.250 ns .283 ns .517 *
Conclusion :
*Not much of a line up expected on the basis of the differences in strength of
economic recovery. Where there is a significant correlation (* at.05), it’s
reversed : best GDP-recovering countries have largest postponements.
*SDT based line up not convincing either, but significant correlations are at
least in line with expectations.
Sources : UNECE ESE 2002-1;Council of Europe, 2002; Inglehart & Welzel, 2005, UN Human Development Report.

21. Conclusions
• Stress on expressive values and individual autonomy, in tandem with
structural constraints, will either continue to shift fertility schedules to later
ages, or to the maintenance of such late schedules.
• However, by now pure postponement models have become inadequate;
differential recuperation now needs attention in advanced SDT-settings..
• Cohort fertility profles by parity (and by other covars such as education) give
crystal clear views of fertility differentials.
• Little or no wisdom from mechanical approaches.
• Recuperation differentials between countries are correlated with longer
histories of development in amenities, family support policies, gender roles,
intergenerational relations etc.
• The lower the scores on gender equity & symmetry in division of labour, and
the weaker the support structure (benefits, amenities, organisational
adaptation) for households with children, the weaker the degree of
recuperation.
• In SDT-countries weak recuperation means prolongation of TFRs below 1.5
children (with high but still varying degrees of childlessness)

22. Indicator of Gender
Empowerment ca 2000
and percentages
stressing
Self-expressive
Values mid 1990s:
country locations.
EVS & WVS data.
Inglehart & Welzel,
2005, p.283

24. The SDT views on Fertility, 1986-2009
Ron Lesthaeghe
Belgian Royal Academy of Science and University of Michigan.
K.Neels

25. •The graphs below show there is great postponement of births,
but that the extent to which fertility declines at young ages is
made-up later in life varies greatly.
•The regression analysis below uses 3 factors to predict the PTFRs
30 years after the birth of a cohort: Cohort Total Fertility Rate for
the baseline cohort, the trough parameter def (30), and the gap
reduction parameter def(40)-def(30).
•The cohort analysis is based on the
comparison of cumulated age-specific fertility
schedules for each cohort to that of the
benchmark cohort born 1940-44.
•Clearly, postponement is occurring, but not
all countries are recuperating from the deficit
of births at early ages.
• 50.5% of the variance in the PTFRs (1970-1990) is explained if the PTFRs
are regressed on the CTFRs of the baseline cohort (model 1). Adding the
level of the trough parameter (postponement effect, model 2), 67.3% of the
variation is explained. If the recuperation factor is also considered (model
3), 79.3% of the variance in PTFRs is explained.
•The graphs above plot the PTFR against the value predicted by the model,
showing that each model is a substantial improvement over the previous one.
•These results suggest that differential catching up is an important
determinant of PTFRs. Postponement is important to studies of fertility,
but so is “catching up.”
DeficitsCCFRFinland
-600
-500
-400
-300
-200
-100
0
100
<20 <20-24 <20-30 <20-34 <20-39 <20-44 <20-45+
Age Bracketsand Baseline (1940-44)
Deficets,ThousandsofBirths
1945-1949
1950-1954
1955-1959
1960-1964
1965-1969
1970-1974
1975-1979
1980-1984
DeficetsCCFRSpain
-1200
-1000
-800
-600
-400
-200
0
200
<20 <20-24 <20-30 <20-34 <20-39 <20-44 <20-45+
AgeBracketsandBaseline(1940-44)
Deficets,ThousandsofBirths
1945-1949
1950-1954
1955-1959
1960-1964
1965-1969
1970-1974
1975-1979
1980-1984
DeficitsCCFRNetherlands
-1000
-800
-600
-400
-200
0
200
<20 <20-24 <20-30 <20-34 <20-39 <20-44 <20-45+
AgeBracketsandBaseline(1940-44)
Deficets,ThousandsofBirths 1945-1949
1950-1954
1955-1959
1960-1964
1965-1969
1970-1974
1975-1979
1980-1984
DeficitsCCFRPortugal
-900
-800
-700
-600
-500
-400
-300
-200
-100
0
100
200
<20 <20-24 <20-30 <20-34 <20-39 <20-44 <20-45+
Age Bracketsand Baseline (1940-44)
Deficets,ThousandsofBirths
1945-1949
1950-1954
1955-1959
1960-1964
1965-1969
1970-1974
1975-1979
1980-1984
CATCHING UP
NOT CATCHING UP
*Countries with lowest-low fertility are those that have not
exhibited any catching up after age 30. Those countries with
PTFRs that have not fallen below 1.50 either have high baseline
CTFRs or clearly exhibit catching up.
Model 1 Model 2 Model 3
Gap Reduction -- -- -.917***
Trough Parameter -- .851*** 1.414***
Baseline CTFR 0.651*** .752*** 1.107***
Constant 318.361 371.068 -286.525
R Square 0.505 0.673 0.793
Regression ModelsCountries like
Belgium,
Denmark,
Finland, France,
the Netherlands,
Sweden
Countries
like
Austria,
Greece, ,
Italy,
Portugal,
Spain.
Analysis of Cohort Fertility Schedules by Age
.
Fertility data source: Council of Europe (2004) Recent Demographic Developments in Europe – 2004 Edition (CD).
(Council of Europe: Strasbourg, France).
For more information on postponement and catching up, see Lesthaeghe & Willems (1999), Lesthaeghe (2001), Frejka &
Calot (2001), and Sobotka (2003).