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World Fertility Trends:
Empirical Evidence, Estimation and
Challenges
23–24 June 2016
WissenschaftsForum
Berlin, Germany
Kirill Andreev United Nations Population Division
Department for Economic and Social Affairs
Overview
• Role of UN Population Division
• Global Estimates and Projections of Fertility
• Empirical Evidence for Fertility Estimation
• Challenges
• A way forward
UN Population Division
• Population Division has always been a think tank carrying out research and producing scientifically sound information
• Population Division has also been a “service” institution, producing data resources and tools for demographers and information for the general public
• The Population Division serves as a Secretariat for the Commission on Population and Development. It provides supports for annual meetings and intergovernmental process.
Main Fertility-Related Activities
• Monitor fertility, marriage and family planning levels and
trends
• Analyze the relationship between fertility and development
• Provide global data on marriage, fertility and family planning
• Provide estimates for global monitoring of development goals (SDG): Adolescent birth rate: • Ages 10-14 years • Ages 15-19 years
Fertility Estimates and Projections
• Global coverage: 201 countries
• 5-year periods and 5-year age groups
• Estimation period 1950-2015 (approximate, depending on
data availability)
• Projection period 2015-2100 (input to global population
projections)
1.00
2.00
3.00
4.00
5.00
6.00
7.00
1950 1970 1990 2010 2030 2050 2070 2090
Tota
l Fer
tilit
y R
ate
Year
World Africa Asia
Europe Latin America and the Caribbean Northern America
Oceania
Fertility: Global Trends and Projections
Projections Estimates Fertility transition time • Sweden: 50 years • Latin America: 36 years • Asia: 42 years • Africa: 85 years
Mean Age at Childbearing: Global Trends and Projections
25
26
27
28
29
30
31
32
1950 1970 1990 2010 2030 2050 2070 2090
Mea
n A
ge a
t C
hild
bea
rin
g
Year
World Africa Asia
Europe Latin America and the Caribbean Northern America
Oceania
5.00
5.50
6.00
6.50
7.00
7.50
8.00
8.50
1950 1970 1990 2010 2030 2050 2070 2090
Stan
dar
d d
evi
atio
n
Year
World Africa Asia
Europe Latin America and the Caribbean Northern America
Oceania
Standard Deviation of Age Schedule of Fertility
Challenges
Fertility Estimation
• Data from all sources
• Assessment of data quality
• Estimation approach
• Cohort component method with estimated fertility inputs
Estimation Methods
• Direct estimates (VR and population estimates)
• Direct estimates (birth histories from household surveys)
• Direct and adjusted estimates (recent births in censuses)
• Reverse survival and OWC methods
• Estimates based on cumulative fertility histories (CEB)
Sweden: Ideal Case
1.5
1.7
1.9
2.1
2.3
2.5
2.7
2.9
1940 1950 1960 1970 1980 1990 2000 2010 2020
Tota
l Fe
rtili
ty R
ate
Year
NSO
WPP
Australia: Revisions of National Fertility Estimates
1.50
1.60
1.70
1.80
1.90
2.00
2.10
2.20
1970 1975 1980 1985 1990 1995 2000 2005 2010 2015
Tota
l Fer
tilit
y R
ate
Year
2011
2012
1
1.2
1.4
1.6
1.8
2
2.2
2.4
2.6
1980 1985 1990 1995 2000 2005 2010 2015
To
tal F
ert
ility
Ra
te
Year
WPP RHS2010 (OCM) RHS2010 RHS2005 RHS1999 Direct_DYB Eurostat.20150811
Georgia: VR vs. Surveys
Surveys
VR
5
6
7
8
9
1950 1960 1970 1980 1990 2000 2010 2020
To
tal F
ert
ility
Ra
te
Year WPP NSO 2009 MIS,D-BH 2011 DHS,D-BH 2011 DHS,X-BH2006 DHS,D-BH 2006 DHS,X-BH 2002 Census,D-RB 2002 Census,A-RB 2000-2001 DHS,D-BH2000-2001 DHS,X-BH 1995 DHS,D-BH 1995 DHS,X-BH 1991 Census,D-RB 1991 Census,A-RB1988-1989 DHS,D-BH 1988-1989 DHS,X-BH 1969 Census,A-RB 1969 Census,D-RB 1959 Census,A-RB1959 Census Report
Uganda: Censuses vs. Surveys (no-VR)
Direct estimates from surveys
Adjusted estimates from censuses
Direct estimates from censuses
5
5.5
6
6.5
7
7.5
1950 1960 1970 1980 1990 2000 2010 2020
To
tal F
ert
ility
Ra
te
Year
WPP 2013-2014 DHS,X-BH 2013-2014 DHS,D
2010 MICS 2007 DHS,X-BH 2007 DHS,D
2001 MICS 1995 MICS,OWC 1984 Census
1975-1976 EDOZA,BH 1975-1976 EDOZA 1955-57 Survey, Adj
Spline (GCV) Spline (p=0.01)
The latest UNPD estimate for 2010-2015
Spline estimates
The only empirical data point below the 2010-2015 estimate
+0.5 child difference
Dem. Rep. Of Congo: What is the Current Fertility Level? (no recent census)
Empirical Fertility Data: 2015 World Fertility Data http://www.un.org/en/development/desa/population/publications/dataset/fertility/wfd2015.shtml
• About 140,000 data points (TFR, ASFRs and MAC) • Online plots of empirical data and estimates (all indicators and countries) (1809 charts)
CHALLENGES: Sustainable Data Collection
• Demographic Year Books (DYB) and internal databases. DYB is available via data.un.org (UN data portal)
• NSO online databases and web services • Microdata, VR or birth histories • Eurostat • HFD and HFC
• Manual download (e.g. no SQL or web service access to data.un.org) • Variable / Incomplete meta information • Often no assessment of data quality (e.g. data.un.org – re-publishing) • Little information on population estimates: intercensal or postcensal?
Adjusted or not adjusted? How consistent with the reported births? • Limitations to access to micro data • Harmonization of data
Sources
Challenges
CHALLENGES: Data Gaps
A country is classified as a country with “gaps in fertility data” if there are no empirical data for at least one decade since 1950 or for the period 2010 and later.
4
2
18
36
25
10
95
9
0
20
4
26
47
106
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Oceania
Northern America
Latin America and the Caribbean
Europe
Asia
Africa
World
No Gaps Gaps
CHALLENGES: Timely VR-based Data A country is classified as a country with “timely VR-based data available” if the latest empirical point is available for the period 2010 or later and birth registration in a country is at least 90%.
5
2
20
38
27
7
99
8
0
18
2
24
50
102
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Oceania
Northern America
Latin America and the Caribbean
Europe
Asia
Africa
World
Timely VR-based data available Not available
A Way Forward? • Improved methodology for estimates and automated process of
estimation:
o Total fertility, age-specific fertility rates
o Single year of age and single calendar year
o Uncertainty around fertility estimates
o Age-specific fertility rate for ages 10-14 (SDG reporting)
• Comprehensive and (possibly) automated data collection and
updates of fertility databases
• Better online dissemination of fertility levels and trends with
interactive graphics, indicator-specific and country profiles for the
general public
• Improving collaboration (regional commissions, UN agencies,
national statistical offices and research organizations)
unpopulation.org