World Population Prospects The 2010 Revision · International seminar on Population Estimates and...

World Population Prospects

The 2010 Revision

Gerhard K. Heilig (Chief)

Patrick Gerland, Kirill Andreev, Nan Li, Danan Gu, Thomas Spoorenberg

Sarada Ravinuthala, Chandra Yamarthy, Neena Koshy

United Nations, Department of Economic and Social Affairs (DESA)

Population Division - Population Estimates and Projections Section

www.unpopulation.org

International seminar on Population Estimates and Projections: methodologies, innovations and estimation of target population applied to public policies

Latin American Population Association (ALAP) - Research Network on Population Estimates and Projections,

and National School of Statistics (ENCE) of the Brazilian Institute of Geography and Statistics (IBGE)

Rio de Janeiro (Brazil), 9 -11 November 2011

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Team

Chief

Gerhard K. Heilig

Population Affairs

Officer

Danan Gu

Population Affairs

Officer

Nan Li

Population Affairs

Officer

Thomas

Spoorenberg

Population Affairs

Officer

Kirill Andreev

Population Affairs

Officer

Patrick Gerland

Editorial Assistant

Neena Koshy

Information

Systems Assistant

Sarada

Ravinuthala

Information

Systems Assistant

Chandrasekhar

Yamarthy

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Mandate

Prepare the World Population Prospects Official United Nations population projections, used throughout the UN System

Recent revisions prepared every second year

Latest revision: 2010 (230 countries)

22 revisions since the early 1950s

Prepare the World Urbanization Prospects Estimates and projections of urban population for 230 countries

Estimates and projections of major urban agglomerations (about 5000)

Latest revision: 2009

Since 1988

Publish results, develop methodology Web sites, wall charts, CD-ROMs/DVDs, databases

Model life tables, probabilistic projections (Bayesian Hierarchical Model)

Develop specialized databases and software DemoBase, DemoData, DataArchive

Estimation and projection software, probabilistic models, data checking

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1

World Population Prospects: What we do

60% of Workload

Update and development of new

databases and software, server

and database maintenance, backup

Start of

WPP

Evaluation Adjustments

Data Collection

230 countries / areas

Uploading to Database

Calculation of Variants

Aggregation of Regions

Epidem. Modeling for AIDS Countries

3

CD-ROMs / DVDs

Online Database

Web Sites

Statistical Reports

Vol. 1, 2

Early Release Data

Wall Chart

25% of Workload

15% of Workload

Checking of Results

2

Methodological Report

(on web site)

Start of

WUP

Fixing of Errors

Data Collection, Estimation

Projection,

Aggregation, Checking

Output Production

0

Consulting / Feedback

Responding to clients

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Source: United Nations, Department of Economic and Social Affairs, Population Division (2011): World Population Prospects, the 2010 Revision. New York

0

1. Census data + post-enumeration surveys (from United Nations Demographic Yearbook database and directly from National Statistical Offices)

2. All available demographic and health surveys (DHS, DSS, MICS, WHS, etc.) for estimating fertility and mortality

3. Estimates from population and vital registers (from statistical reports of National Statistical Offices or their web sites)

4. Scientific reports and data collections (Human Mortality Database, child mortality estimates, etc.)

5. Data and estimates provided by other international agencies (CELADE, Regional Commissions, EUROSTAT, ESCAP, UNICEF, UNAIDS, WHO)

WPP data sources

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Methodology

The UN approach to estimating population

(by age and sex), fertility, mortality and migration

Availability & Data Quality

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Data Sources: Censuses (WPP2010) 1

Country / area

Year of last

census

Years since

last census Cayman Islands 1999 10

Iraq 1997 13

Turkmenistan 1995 14

Pitcairn 1992 18

Bosnia and Herzegovina 1991 18

Myanmar 1991 18

Uzbekistan 1989 20

Somalia 1986 23

Eritrea 1984 25

Dem. Rep. of the Congo 1984 25

Angola 1984 26

Afghanistan 1979 31

Lebanon 1943 67

Countries where last census was conducted

more than 10 years ago (as of 2010)

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0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

8,000

9,000

10,000

11,000

12,000

13,000

14,000

15,000

16,000N

ew

Zeala

nd

Neth

erlands

Fin

land

Bulg

aria

Hungary

Pola

nd

Norw

ay

Icela

nd

Denm

ark

Belg

ium

Fra

nce

Sw

eden

United S

tate

s o

f Am

erica

Austr

iaSw

itzerland

UK:

Engla

nd a

nd W

ale

sAustr

alia

Canada

Port

ugal

Japan

Italy

Czech R

epublic

Latv

iaBela

rus

Lithuania

Spain

Luxem

bourg

Germ

any,

Federa

l Republic

of

Ukra

ine

Esto

nia

Germ

an D

em

ocra

tic R

epublic

Panam

aIs

rael

Rom

ania

Russia

n F

edera

tion

Chile

Slo

vakia

Cuba

Syrian A

rab R

epublic

Slo

venia

Peru

Gre

ece

Haiti

Malta

San M

arino

Cypru

sVenezuela

(Bolivarian R

ep.

Azerb

aijan

Ecuador

Kyrg

yzsta

nBra

zil

Taiw

an,

Pro

vin

ce o

f Chin

aPhilip

pin

es

Republic

of

Kore

aPuert

o R

ico

Cost

a R

ica

Bolivia

Trinid

ad a

nd T

obago

Chin

a,

Hong K

ong S

AR

Fiji

Arm

enia

Form

er

Yugosla

via

Thailand

Gre

enla

nd

Uru

guay

Moro

cco

Germ

any

Mauritius:

Isla

nd o

f M

auritius

Irela

nd

Mexic

oIn

dia

Republic

of

Mold

ova

Form

er

Eth

iopia

Arg

entina

UK:

Scotland

Sin

gapore

Kazakhsta

nEth

iopia

UK:

Nort

hern

Ire

land

Nic

ara

gua

Hondura

sSain

t Lucia

Jord

an

Form

er

Czechoslo

vakia

Myanm

ar

United K

ingdom

Andorr

aIr

an (

Isla

mic

Republic

of)

Guate

mala

Egypt

Bahra

inJa

maic

aSri L

anka

Serb

ia a

nd M

onte

negro

Belize

Iraq

Colo

mbia

Barb

ados

Mozam

biq

ue

Tunis

iaG

uyana

Mala

ysia

: Penin

sula

r M

ala

ysia

Lesoth

oEl Salv

ador

Bots

wana

Seychelles

Bangla

desh

Mauritius:

Rodrigues

Buru

ndi

Turk

ey

Kuw

ait

Benin

Antigua a

nd B

arb

uda

Bru

nei D

aru

ssala

mD

om

inic

aSw

aziland

Mala

ysia

Gre

nada

Uzbekis

tan

Mala

wi

Cro

atia

Sain

t H

ele

na:

Trista

n d

aM

ali

Mauritius

Alg

eria

Chad

Mart

iniq

ue

Zim

babw

eIn

donesia

Sain

t Kitts

and N

evis

Pitcairn

Fre

nch P

oly

nesia

Georg

iaSolo

mon I

sla

nds

Kenya

Nig

er

Cape V

erd

eLao P

eople

's D

em

. Republic

Para

guay

Dem

. Rep.

of

the C

ongo

Guadelo

upe

Afg

hanis

tan

Lie

chte

nste

inTFYR M

acedonia

Faero

e I

sla

nds

Berm

uda

Réunio

nCam

bodia

Pakis

tan

Baham

as

Neth

erlands A

ntilles

Dom

inic

an R

epublic

Gam

bia

Chin

a,

Macao S

AR

Mald

ives

Tajikis

tan

Papua N

ew

Guin

ea

Chin

aSain

t Vin

cent

/ G

renadin

es

Mala

ysia

: Sabah

Nepal

Mala

ysia

: Sara

wak

Zam

bia

Mongolia

Monts

err

at

Alb

ania

New

Cale

donia

Mars

hall I

sla

nds

Tonga

Sudan

Kirib

ati

Cam

ero

on

Maurita

nia

Surinam

eLib

yan A

rab J

am

ahiriy

aYem

en

Burk

ina F

aso

Togo

Qata

rVie

t N

am

Sam

oa

Niu

eO

man

Vanuatu

Guin

ea

Madagascar

Rw

anda

UR o

f Tanzania

Centr

al Afr

ican R

epublic

Equato

rial G

uin

ea

Com

oro

sSaudi Ara

bia

Cook I

sla

nds

Bhuta

nCongo

Gabon

Sie

rra L

eone

Senegal

Nam

ibia

Aru

ba

Bosnia

and H

erz

egovin

aG

uin

ea-B

issau

Lib

eria

Nig

eria

South

Afr

ica

Côte

d'Ivoire

Mic

ronesia

(Fed.

Sta

tes o

f)Yem

en:

Form

er

Dem

. Yem

en

United A

rab E

mirate

sLebanon

Occupie

d P

ale

stinia

n T

err

.Is

le o

f M

an

Angola

Dem

. People

's R

ep.

of

Kore

aD

jibouti

Eritr

ea

Ghana

Monaco

Nauru

Pala

uSão T

om

é a

nd P

ríncip

eSom

alia

Turk

menis

tan

Tuvalu

Uganda

Fre

nch G

uia

na

Form

er

USSR

Channel Is

lands:

Guern

sey

Sain

t H

ele

na e

x.

dep.

Monte

negro

Serb

iaTim

or-

Leste

UR o

f Tanzania

: Zanzib

ar

UR o

f Tanzania

: Tanganyik

aW

este

rn S

ahara

Caym

an I

sla

nds

Coco

s (

Keeling)

Isla

nds

Turk

s a

nd C

aic

os I

sla

nds

British V

irgin

Isla

nds

Am

erican S

am

oa

Norf

olk

Isla

nd

United S

tate

s V

irgin

Isla

nds

Christ

mas I

sla

nd

2005-08

2000-04

1995-99

1990-94

1985-89

1980-84

1975-79

1970-74

1965-69

1960-64

1955-59

1950-54

Population statistics are sufficient for cohort component projection.

Projection benefits significantly from Census data.

Population statistics Insufficient for cohort component projection.

Projection can be done only with Census data.

Figure 2: Data Availability from Estimates.

Population in five-year age groups by sex: Number of data

points 1950-2008 in five-year intervals

Source: UNPD, DemoData. Chart by GKH.

Population statistics usually sufficent for cohort component projection.

Estimation often can be improved with Census data.

Register Data: Population by Age and Sex

Sufficient for cohort-component projection

Partially sufficient for cohort-component projection

Not sufficient for projection

≈ 2/3 of countries have insufficient

population estimates by age and sex

to establish consistent time-series

from 1950 to present

1

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Data Sources: Child Mortality Estimation (WPP2010) 1

Number of countries according to the most recent data available

Only countries with a population of 100,000 or more in 2009

61 Countries have child mortality information from before 2004

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Data Sources: Adult Mortality Estimation (WPP2010) 1



74 Countries have no information on adult mortality at all !

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Data Sources: Fertility Estimation (WPP2010) 1



62 Countries have only fertility information from before 2004

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Estimation of Population from Censuses 1

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Estimation of Population from Censuses 1

Under-reported migrant workers

Under-reported births

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Estimation of Total Population 1

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Estimation of Mortality: 1q0, 5q0 (Senegal) 1

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Estimation of Mortality: 5q0 (Senegal)

1950 1960 1970 1980 1990 2000 2010

0.0

0.1

0.2

0.3

0.4

0.5

A. Birth histories

UNPD Spline 1978 WFS1986 DHS1992-1993 DHS1997 DHS1999 DHS2000 MICS2005 DHS2008-2009 MICS

Saint-Louis (SEN), VRBamako (MLI), VR

Ouaga. (DSS)

Mauritius, VR

1950 1960 1970 1980 1990 2000 20100.0

0.1

0.2

0.3

0.4

0.5

B. CEB/CS

Fouta Toro (Maures)1960-1961 survey1978 WFS1986 DHS1992-1993 DHS1996 MICS1997 DHS1999 DHS2005 DHS2006 MICS2008-2009 MICS

1950 1960 1970 1980 1990 2000 2010

0.0

0.1

0.2

0.3

0.4

0.5

C. Household deaths

Fouta Toro (Toucouleurs & Peuls)Fouta Toro (Maures)

1950 1960 1970 1980 1990 2000 2010

0.0

0.1

0.2

0.3

0.4

0.5

D. Vital Registration

Mauritius (VR)BamakoDakarSaint-Louis

1950 1960 1970 1980 1990 2000 2010

0.0

0.1

0.2

0.3

0.4

0.5

E. Multiround survey

1970-1971 Multiround Survey1978-1979 Multiround SurveyDakarCentral valleyThienaha

1950 1960 1970 1980 1990 2000 20100.0

0.1

0.2

0.3

0.4

0.5

F. Demographic Surveillance Sites

OuagadougouBandafassiFakao-PalmarinFakaoMlompNiakharN'gayokhèmePeul BandePaos-Koto

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Estimation of Mortality: 45q15 (Senegal)

1950 1960 1970 1980 1990 2000 2010

0.1

0.2

0.3

0.4

0.5

0.6

A. Derived from 5q0 and relational model

UNPD (CD-N)Timaeus/SahelCD-SouthCD-North

Loess reg.Spline

UNPD

Saint-Louis (SEN), VR

Bamako (MLI), VROuaga. (DSS)

Mauritius, VR

1950 1960 1970 1980 1990 2000 2010

0.1

0.2

0.3

0.4

0.5

0.6

B. Household deaths

Fouta Toro (Toucouleurs & Peuls)1988 Census

1950 1960 1970 1980 1990 2000 2010

0.1

0.2

0.3

0.4

0.5

0.6

C. Intercensal survival

1960-1971 surveys1972-1982 census estimates1978-1988 census1982-1992 census estimates1992-2002 census estimates

1950 1960 1970 1980 1990 2000 2010

0.1

0.2

0.3

0.4

0.5

0.6

D. Maternal orphanhood

1986 DHS (at marriage)1986 DHS1986 DHS (=> marriage)1988 Census1992-1993 DHS2005 DHS

1950 1960 1970 1980 1990 2000 2010

0.1

0.2

0.3

0.4

0.5

0.6

E. Siblings

1992-1993 DHS2005 DHSDHS-Siblings (pooled analysis)

1950 1960 1970 1980 1990 2000 2010

0.1

0.2

0.3

0.4

0.5

0.6

F. Vital Registration

Mauritius (VR)BamakoDakarSaint-Louis

1950 1960 1970 1980 1990 2000 2010

0.1

0.2

0.3

0.4

0.5

0.6

G. Multiround survey

1970-1971 Multiround Survey1978-1979 Multiround SurveyDakar

1950 1960 1970 1980 1990 2000 2010

0.1

0.2

0.3

0.4

0.5

0.6

H. Demographic Surveillance Sites

OuagadougouBandafassiFakaoMlomp

NiakharN'gayokhèmePeul BandePaos-Koto

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Estimation of Fertility: TFR (Senegal)

1950 1960 1970 1980 1990 2000 2010

23

45

67

8

Observed (weighted)

1957 Middle Senegal (D)1957 Middle Senegal (I)

1957 Middle Senegal (D-A)1960-61 survey (D)

1960-61 survey (D-A)1970-71 EDN (D)1978 WFS (D)

1978 WFS (D-A)1986 DHS (D)1986 DHS (D-A)

1988 census (D)1992-93 DHS (D)

1992-93 DHS (D-A)1997 DHS (D)

1997 DHS (D-A)1999 ESIS (D)

1999 ESIS (D-A)MICS-MD (D)2002 census (D)

2002 census (D-A)2005 ESIS (D)2005 ESIS (D-A)

2006 MIS (D)2008-2009 MIS (D)

WPP08 Loess regression

Cubic Spline

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Estimation of Fertility: ASFR (Bangladesh) 1

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Estimation of Fertility: ASFR (Bangladesh)

Lines are weighted cubic spline and loess regression trends

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Methodology: The UN approach to

projecting total fertility

A Bayesian Hierarchical Model (BHM) based on

bi-logistic decline curves of fertility

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Model of fertility decline

0.00

0.02

0.04

0.06

0.08

0.10

0.12

0.14

1 2 3 4 5 6 7 8 9 10

Children per woman

Fe

rtili

ty d

eclin

e

Fast/Fast Fast/Slow Slow/Slow

Model: Bi-logistic function to estimate the rate of fertility decline

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1

2

3

4

2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100

Year

Child

ren p

er

wom

an

Fast/Fast Fast/Slow Slow/Slow Floor

1

2

3

4

5

6

7

8

2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100

Year C

hild

ren p

er

wom

an

Fast/Fast Fast/Slow Slow/Slow Floor

Projections: Fertility

A. From high to low fertility

B. From medium to 1.85

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Model of fertility decline

Model: Bi-logistic function to estimate the rate of fertility decline

1 2

1 2

1 2

( )(81) (81)

1 exp[ ( )] 1 exp[ ( )]m m

k kP t

Ln Lnt t t t

t t

Parameter Slow/Slow Fast/Slow Fast/Fast

k1 ............... -0.11 -0.16 -0.25

Δt1.............. 5.03 4.34 4.01

tm1 .............. 5.77 5.06 5.17

k2 ............... 0.15 0.22 0.31

Δt2.............. 2.75 3.02 4.32

tm2 .............. 3.21 3.52 3.94

In probabilistic fertility projection: Parameters values are replaced

by distributions. Some 100,000 trajectories of fertility decline are

calculated by sampling from these parameter distributions.

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Fertility models and empirical data

-0.3

-0.2

-0.1

0

0.1

0.2

012345678910

Average annual decline in TFR

Total Fertility

Average annual TFR decline

Fast/Fast

Fast/Slow

Slow/Slow

China

Iran

Mexico

Poland

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BHM: A fertility transition model

Phase I: Not modeled.

Phase II: Fertility transition, modeled by

Bayesian Hierarchical Model (BHM)

Phase III: Modeled with a first order

autoregressive time series model [AR1],

with its mean fixed at the approximate

replacement-level fertility of 2.1

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2 BHM: A fertility transition model

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2 BHM: Bi-logistic functions and TF projections

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2 Probabilistic Projection of Population: Niger

Based on estimates from WPP2010; probabilistic fertility, deterministic mortality

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2 Probabilistic Projection of Population: Nigeria


Total Population Population age 15-64

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2 Probabilistic Projection of Population: Japan



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2 Probabilistic Projection of Population: Ukraine



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Methodology: The UN approach to

projecting life expectancy

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Models for projecting life expectancy at birth

Illustration of the double-logistic function (based on a curve from Japan).

The left plot illustrates the double-logistic function of 5-year gains in life

expectancy. The right plot is a time-series of life expectancy, e(0), with

gains modeled according to the double-logistic function

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Models for projecting life expectancy at birth 3

Illustration of the double-logistic function (based on a curve from Japan).

The left plot illustrates the double-logistic function of 5-year gains in life

expectancy. The right plot is a time-series of life expectancy, e(0), with

gains modeled according to the double-logistic function

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UN Model: Five-year gains in life expectancy at birth (in years): Male

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

27.5 32.5 37.5 42.5 47.5 52.5 57.5 62.5 67.5 72.5 77.5 82.5 87.5 92.5

e(0)

5-y

ea

r g

ain

s

Very fast (p90)

Fast pace (p75)

Medium Pace (m)

Slow pace (p25)

Very slow (p10)

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UN Model: Five-year gains in life expectancy at birth (in years): Female

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

27.5 32.5 37.5 42.5 47.5 52.5 57.5 62.5 67.5 72.5 77.5 82.5 87.5 92.5

e(0)

5-y

ea

r g

ain

s

Very fast (p90)

Fast pace (p75)

Medium Pace (m)

Slow pace (p25)

Very slow (p10)

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Projections: Mortality models and empirical data

Male: average annual gain in e0 at a given e0

-0.3

-0.1

0.2

0.4

0.6

0.8

1.0

35 40 45 50 55 60 65 70 75 80 85

year

Average annual gain

Oman

Norway

Japan

Very fast (p90)

Fast pace (p75)

Medium Pace (m)

Slow pace (p25)

Very slow (p10)

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Probabilistic mortality projection

ctct

iidc

ctc

l

lg

ctctcyg

tcl

tcl

tCctc

l

offunction smoothed ,0Normal~

,Normal Truncated~

Fcn Logistic Double param 6)|(

)|,

(,1,

6

,

.

.

period time countries; ,...,1;expectancylife,

Data:

• Male life expectancy at birth from 1950 through 2005;

• Estimates from UN World Population Prospects (WPP2006)

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Data Checking 5

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DemoData: Empirical Database 5

Different Data Sources

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Thank You !

www.unpopulation.org

World Population Prospects The 2010 Revision · International seminar on Population Estimates and...

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Transcript of World Population Prospects The 2010 Revision · International seminar on Population Estimates and...