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Ready, Willing and Able : The preconditions of demographic innovation

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Title: Ready, Willing and Able : The preconditions of demographic innovation


1
Ready, Willing and Able The preconditions of
demographic innovation
  • Ron Lesthaeghe
  • and
  • Camille Vanderhoeft, Karel Neels, Lisa Neidert,
    Didier Willaert.
  • VU Brussels University of Michigan.

2
RWA origins Princeton European Fertility
Transition
  • Findings Fertility control emerged in wide
    variety of circumstances, and leads and lags were
    not adequately predicted by classic factors of
    structural modernization ( Urbanization,
    industrialization, mortality decline )
  • A. J. Coale (1973) fell back on three conditions
    .

3
R and W and A
  • Ready new behavior must be advantageous
    (conscious cost/benefit calculus)
  • Willing new behavior must be ethically
    acceptable (religious and moral legitimacy)
  • Able there must be technical means for its
    realization ( material, legal, organizational,
    often at macro level)

4

COALES PRECONDITIONS FOR DEMOGRAPHIC INNOVATION
  • READY ECONOMICALLY ADVANTAGEOUS
  • WILLING CULTURALLY ACCEPTABLE
  • ABLE MEANS AVAILABLE

S R and W and A
The slowest moving condition can become a
bottleneck.
5
From 3 conditions to a dynamic model
(Lesthaeghe-Vanderhoeft 2001 conceptualization)
  • Shifting/overtaking distributions of resp. R,W
    and A in a population over time
  • The distribution of minima is what matters.
  • No longer an opposition between the economics and
    the sociology of behavior.
  • RWA can lead to Verhulsts logistic growth curve

6

Not ready, not willing, not able
Fully ready,willing and able
7

Si Min. (Ri,Wi, Ai)
Example 1 the upper tails of the three
distributions are already in the zones with
values greater than 0.5, yet nobody will adopt
the new form of behavior
Example 2 For 85, ability is no longer the
problem, and 50 is convinced of the advantages
of the new form. Yet, less than a quarter will
adopt it. Reason slow adaptation of
willingness is producing a bottleneck.
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From a first to a second demographic transition
in Europe remarkable spatial continuities in
Belgium and France . WHY ???
René Magritte (1895-1967) La Condition
Humaine, 1935, Simon Spierer Collection, Geneva.
10

(a) Speed of the marital fertility transition
(b) Secularization (1919)
Nation. level 55
Nation. level 51
? 70 55 - 69 40 - 54 lt 40
? 70 55 - 69 40 - 54 lt 40
(c) Births out of wedlock (1992)
(d) Unmarried cohabitation (1991
Nation. level 0.39
Nation. level 7.0
0.52 - 0.63 0.40 - 0.51 0.26 - 0.39 0.15 - 0.25
8.5 - 12.0 7.1 - 8.4 4.5 - 7.0 2.9 - 4.4
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How can such strong geographical continuity from
FDT to SDT be accounted for ? 1. Same
bottleneck condition produces similar maps. In
both transitions the willingness-factor (
cultural acceptability, legitimation) seems to
have been the slowest moving distribution. As a
result, the demographic maps continue to be
shaped by the cultural evolution. 2. Regional
subcultures surviving on the basis of stable
networks. Despite the passage of time and years
of migration, regional subcultures must have
survived, and must have maintained their relative
position with respect to the willingness factor.
14
RWA and regression techniques
  • Covariates with strong predictive power in
    regression analyses with cross-sectional data
    mainly point out which condition is the slowest
    moving one. The conclusion that the process is
    driven by economic resp. cultural factors because
    the best performing covariates are of an economic
    resp. cultural nature is erroneous.

15
Anything like that in the USA ?
  • A geography of willingness ?

16
F
NL
NJ
CT
AR
US
US
MA
17
2 basic demographic dimensions
  • Dimension 1 high abortion rates, higher
    frequencies cohabitation hhlds and same sex
    cohabitants, postponement in fertility schedule
    Non-hisp. White population, sustained
    sub-replacement fertility, low teenage fertility
    (white and non-white) typical Second
    demographic transition features.
  • Dimension 2 high teenage fertility ( black
    white), high non-marital fertility, high divorce
    (already since the 60s), grandparents hhlds resp
    for grandchildren older pattern typical for US
    ( not W. EU )

18
USA 50 states Demographic dimension
1indicators and best correlates
  • Demogr. Dimension 1 indicators (factor loadings)
  • Abortions p 1000 L Births 80 .92
  • Abortions p 1000 L Births 92 .91
  • Abort. rate p 1000 w 15-44 96 .86
  • hhlds same sex adults 00 .80
  • NHWhites TFR 02 -.72
  • hhlds families -.64
  • NHWhites Fertility postponm.02 .64
  • hhlds Cohabitation 00 .56
  • NHWhites Fert rate 15-19 02 -.54
  • second demographic transition dimension
  • families married couples, married couples
    children, parent children
  • NHW Non-hispanic whites
  • Best correlates of demographic dimension 1 (corr.
    coeff.)
  • vote Bush -.84
  • pop Metropolitan 00 .64
  • pop Metropolitan 62 .62
  • Disp. Pers. Income level 01 .60
  • pop. Catholic 02 .50
  • pop 25 with BA 90 .50
  • pop Evangelical 02 -.56
  • workers unionized .47
  • Disp. Pers. Income 80 .45
  • Plus estimate of Mormons in Utah

19
Relationship between the Second demographic
Transition Dimension in the US 50 states and the
Vote for Bush 2004 (r -.88)
20
USA 50 states demographic dimension 2
Indicators and best correlates
  • Demographic dimension 2 best correlates (corr.
    coeff.)
  • pop 30 livrespons.grandch. .84
  • pop. in Poverty 98-00 .68
  • pop 25 Hi School grads 90 -.63
  • vote Nixon (McGovern) 72 .57
  • vote Goldwater (Johnson) 64 .57
  • Evangelical 2000 .56
  • Disp. Pers. Income 01 -.55
  • pop 25 with BA 90 -.55
  • pop Black 00 .52
  • pop NHWhite 90 -.49
  • Plus estimate Mormon pop Utah
  • Demographic dimension 2 best indicators (factor
    loadings)
  • Births to teenagers 00 .87
  • Median age at first birth 02 -.80
  • Births to unmarried w. 00 .77
  • NHWhites teenage fert. rate 02 .74
  • Divorce per 1000 pop. 90 .71
  • Births to unmarried w 90 .69
  • Divorce per 1000 pop 62 .61
  • NHWhites fert. Postpnmt 02 -.57
  • Ratio of Sum ASFRs 30 / Sum ASFRs 20-29

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Conclusions
  • RWA model potent framework for the study of
    innovations.
  • Flexible (any condition can lead or lag) gt open
    to historical, contextual influences.
  • Stops narrow disciplinary interpretations,
    invites broad social sciences perspectives.
  • Ties in with diffusion literature (eg contagion),
    with systems analysis (eg growth curves)
  • Not limited to demographic or behavioral
    innovations.
  • Antidote to mechanistic, purely numerical
    extrapolations

30

And thats why I like this Magritte .....
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