International Advisory Panel on Population and Development Republic of Moldova 2122 April 2016 Tom áš Sobotka Vienna Institute of Demography Austrian Academy of Sciences Wittgenstein Centre for Demography and Global Human Capital ID: 633446
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Fertility change in Central and Eastern Europe: towards a new model of reproduction?
International Advisory Panel on Population and Development – Republic of Moldova, 21-22 April 2016
Tomáš SobotkaVienna Institute of Demography (Austrian Academy of Sciences), Wittgenstein Centre for Demography and Global Human CapitalSlide2
European fertility divides, 1980s
Main demographic divisions and cleavages, East and West of Europe, 1980s
CEE contrasted with Western & Northern Europe: Family and marriage almost universal, voluntary childlessness rareEarly family formation (unplanned pregnancies, shotgun weddings)Limited cohabitation and non-traditional family formsPronatalist family policies (only limited effect), often limited birth control and little knowledge on contraception, widespread abortionRestricted
international migration (Iron Curtain was real…)
Both East & WestSlow population growth, long-term shift to sub-replacement fertility
Two-child family normSlide3
European divisions (broader geographical regions)
Map
creator: http://edit.freemap.jp/enEastern EuropeCentral Europe“German-speaking” countries
South-eastern Europe
Nordic countriesWestern Europe
Southern EuropeSlide4
Agenda
Fertility transformations after 1989Three key trends in reproductive behaviourUncertain numbers: Data
issues in Central & Eastern Europe (CEE) and in Moldova“Our nation is dying”: The policy debates and responsesDiscussion: The new CEE diversitySlide5
Fertility transformations after 1989
economistmom.comSlide6
The global spread of low fertility
Number of countries with
period TFRs below 2.1 births per womanSource: own elaboration based on UN Fertility Database, 2013 and national statistical officesSlide7
The „fertility collapse“ and its slow recovery
Period Total Fertility Rates, selected CEE countries, 1985-2015
Sources: Eurostat, Human Fertility Database, National statistical officesSlide8
Period Total Fertility in broad European regions:
North & West vs. South & Centre & East
Source: European Demographic Data Sheet 2014 (VID/WIC 2014)Slide9
Mean age of mother at first birth, 1950-2014
Netherlands and Spain compared with 7 CEE countries
Source: Human Fertility Database,
Eurostat, own computations, Russian Fertility Database, MD: computations by K.
Zeman partly based on Penina
et al. (2015)
CEE countriesSlide10
Mean age of mother at first birth, 1950-2014
Netherlands and Spain compared with 7 CEE countries
Source: Human Fertility Database,
Eurostat, own computations, Russian Fertility Database, MD: computations by K.
Zeman partly based on Penina
et al. (2015)Slide11
Estimating the influence of fertility postponement: Conventional and tempo-adjusted TFR
Sources:
European Demographic Data Sheet 2014 and 2016 (forthcoming)Tempo effect in the EU in 2012 estimated at -0.15 (TFR 1.57, adjTFR 1.72)Slide12
Cohort fertility trends and variation
Observed and projected completed cohort fertility
by regions, women born 1960-1979
Myrskylä, M., J. Goldstein, and Y. Alice Cheng. 2012. “New Cohort Fertility Forecasts for the Developed World: Rises, Falls, and Reversals.”
Popul. Dev. Rev. 39 (1): 31–56.Slide13
Childlessness
rankings: Top 5 and bottom
5 countriesEuropean Fertility Data Sheet 2015 (www.fertilitydatasheet.org) &Sobotka, T. 2016. “Childlessness in Europe: Reconstructing Long-Term Trends Among Women Born in 1900-1972.”Slide14
Rapid increase in one-child families
S. Basten, T. Frejka et al. 2016. “
Fertility and Family Policies in Central and Eastern Europe.” Forthcoming, Comparative Population Studies.
Share of women with a small family size (0 or 1), cohorts 1960 and 1970 (%)Slide15
The sharp rise of
non-marital childbearing (%)
Source:
Eurostat,
National statistical offices, Sobotka 2011Slide16
European Fertility Data Sheet
2015 (www.fertilitydatasheet.org)Slide17
Large education differences in fertility in CEE
Difference in family size of women with low and high education (children per woman, women born 1950-59)
European Fertility Data Sheet
2015 (www.fertilitydatasheet.org)Slide18
Ideal and intended family size in Europe strongly centered on having two children
Share of women with an ideal of having two children: European regions, 1979-2011
Sobotka, T. and É.
Beaujouan
. 2014. “Two is best? The persistence of a two-child family ideal in Europe.”
Population and Development Review
40(3): 391-419.Slide19
Fertility intentions in Europe
Remarkable
lack of variation, two-child family norm almost universal
Also
no systematic variation by social status, very little difference between men and women
Mean intended family size of men and women aged 25-29, selected European countries, 1990s (FFS survey) and 2000s (GGS survey)
Mean, women
1990s (15 countries): 2.18
2000s (10 countries): 2.16
GGS and FFS data
analysed
by
Éva
Beaujouan
Slide20
Three key trends in reproductive behaviourSlide21
1. A shift away from abortion & towards more efficient contraception
Czech Republic:
Total induced abortion rate (abortions per woman) and % of women aged 15-44 using the contraceptive pill, 1985-2007
Source: UZIS (2012) and Czech Statistical OfficeSlide22
2. Rapid fall in teenage childbearing
Teenage fertility rate (births per 1000 women aged 15-49), selected countries, 1990 and 2014
:
Source: Eurostat (2016); Human Fertility Database (2016)Slide23
3. Falling frequency of „shotgun marriages“
Share of first marriages preceded by pre-marital conception (in %), 4 countries, 1950-2006
:
Source: Sobotka and
Toulemon
(2008: Figure 7)Slide24
Uncertain numbers:Data issues in CEE and in MoldovaSlide25
CEE: outmigration and biased population data
Population change since the 1990s:
Massive outmigration in many countries; Moldova, Baltic States, Bulgaria, eastern Germany losing 15-25% of their population
Rough estimate of net migration loss, without Russia: 9-13 million in 1989-2013 out of pop. 212 mill (including eastern Germany); 7-11 million without eastern GermanyConsequences for demographic dataOutmigration undercounted and underestimated in most countries
Statistical agencies struggle with trying to provide reliable data on age & sex distribution; frequent revisions (esp. after population censuses)Frequent Inconsistencies: de jure vs. de facto
(actual) population; including or excluding births to citizens abroadPopulation estimates highly uncertain and often upward biasedDemogr. Indicators: numerator – denominator biasSlide26
Moldova: biased population data
Particularly strong mismatch between actual and
de jure
populationStrong outmigration to EU countries and Russia
Underreported; citizens living abroad still mostly included in population structure estimates (de jure concept instead of the “usual residence” concept commonly applied in the EU)Population data were not adjusted to the actual population after the 2004 and 2014 Censuses
Affects especially women and men of reproductive ages Fertility underestimated: birth data mostly include children born in Moldova; population data also most of the citizens abroad
Recent effort to estimate “true” pop. structure and mortality by sex & age:
O. Penina, D. Jdanov, P. Grigoriev. 2015. “Producing reliable mortality estimates in the context of distorted statistics: the case of Moldova.” MPIDR Working Paper WP 2015-011.Slide27
Producing alternative fertility estimates for Moldova
Penina
, Jdanov &
Grigoriev’s (2015) population estimates for 1990-2014 can be sued to produce alternative fertility estimates for MoldovaBirths by age and birth order as observed in population registerPopulation: excluding Moldovan citizens living abroad
using Penina et al. (2015) dataActual births in MD matched with the actual population in MD
Key assumption: Most of the births to MD citizens abroad not reported in MD vital statistics. If this assumption violated, the presented results would provide upward-biased estimates
Thank you to Krystof Zeman (VID) for computing the data presented hereSlide28
Estimated number of women aged 15-50
Data source:
O. Penina, D. Jdanov, P. Grigoriev. 2015Slide29
Estimated period Total Fertiltiy Rates, officail and elternative estimate
Data source: Population:
O. Penina, D. Jdanov, P. Grigoriev. 2015. Live births: Nat. Bureau of Statistics of the Republic of Moldova. Computations by Krystof Zeman.Slide30
Interpretation, consequences
Initial (official) estimates:
Moldova has alongside Bosnia and Portugal the lowest TFR in Europe (2014), deep below EU averageNo significant fertility recovery after 2000
New estimates:Moldova has above-average TFR in Europe, slightly above the EU level (1.57)Significant increase in fertility in 2002 (1.43) to 2009 (1.70), similar to many other CEE countries
Thank you to
Krystof Zeman (VID) for computing the data presented hereSlide31
Interpretation, consequences
Total fertility rate 1985-2014: Official dataSlide32
Interpretation, consequences
Total fertility rate 1985-2014: Official data vs. alternative estimatesSlide33
“Our nation is dying
”: The policy debates and responses
Source:somatosphere.netSlide34
Many governments think fertility is too low
Government view on fertility level and government policy on fertility in 22 countries ever reaching a period total
fertility
of 1.40 or
below, 1996-2011
Source:
Sobotka 2013; based on UN reports &
UN World Population Policy Database; http://esa.un.org/PopPolicy/about_database.aspx Slide35
Public family & population policy discussions: different ideological underpinning
Demography high in political agenda in CEE
Family policies: the previous ones partly collapsing or abandonedPolicy reorientation often driven by ideological considerations & perceived need to lower government expenditures1990s: declining childcare availability; shift to the more “traditional” support of the prolonged stay of mothers at home
Policy turbulences; lacking coherence, frequent changesHungary: the least “effective” family policies?
Eastern and SE Europe: the return of explicit pronatalismRussia, Ukraine, Belarus: strong support for 2nd & higher-order births (RUS: “maternal capital”; UKR: high childcare allowances)
BG: nationalistic discussion on “Bulgaria’s collapse” coloured by strong anti-Roma sentiments (Kotzeva & Dimitrova 2014)Slide36
Selected policy trends in the EU-CEE countries after 2000
EU policies: also motivated by “enabling” people to fulfill their fertility intentions; not explicitly
pronatalist A slow expansion of public childcare coverage for children below age 3 (EU target to achieve at least 33% coverage in each country) Shorter, but better paid parental leave, with remuneration up to 100% of the previous wage (Estonia, Poland). Stimulating earlier return to employment Flexible leave arrangements: more flexibility in selecting leave period, “multispeed leave” (Czech
Republic) Tax rebatesEastern Europe: Cash support to
newborns and children: childcare allowances in Ukraine, “maternity capital” established at the time of child’s birth (second births in Russia)Slide37
SOURCE: Vanhuysse, P. 2013.
Intergenerational Justice in Aging Societies. A Cross-national Comparison of 29 OECD Countries
.
Gütersloh: BertelsmannStiftung, p. 27. www.sgi-network.org/pdf/Intergenerational_Justice_OECD.pdf
The elderly bias in social spending, OECD, 2007-8
Most pro-elderly biased countries: Poland, Greece, Italy, Slovakia, Czech Rep., Portugal, Slovenia, Austria,
EBiSS
>5Slide38
Discussion:The new CEE diversity?Slide39
The new model of reproduction?
Common trends across the region: Fertility decline in the 1990s and partial “recovery” in the 2000s; declining significance of marriage for reproduction; two-child family ideal; fall in early pregnancies and childbearing; “postponement transition”
Also persistent traditional gender attitudes and (mostly) negative attitudes to childlessness
Diversity, cross-country differences: First birth timing, extra-marital childbearing, one-child families, teenage fertility
Low fertility matter of concern, but migration often the key driver of population declineSlide40
Data issues: The importance of accounting for migration & consistent data concepts and definitions
Uncertain data, biased estimates
A need of adopting consistent concepts and definitions of resident population and corresponding vital statistics
A need to improve migration statistics and estimates to provide up-to-date statistics on population & demographic indicators
Proper evaluation of population trends impossible without solid dataSlide41
The importance of education transition
Rapid rise in tertiary education enrollment across the region, esp. among women
A key “explanation” of postponed family formation & lower fertility
Large education gradient in family size
Also more effective contraceptive use
Gender gap in tertiary education at age 30-34, Europe 2011
Source: VID/Wittgenstein Centre 2014: European Demographic Data Sheet 2014Slide42
tomas.sobotka@oeaw.ac.at
Work on this presentation was funded by the European Research Council under the European Union’s Seventh Framework Programme (FP7/2007-2013) / ERC Grant agreement n° 284238 (EURREP).
EURREP website:
www.eurrep.org