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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.
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World Population ProspectsThe 2010 RevisionGerhard K. Heilig (Chief)Patrick Gerland, Kirill Andreev, Nan Li, Danan Gu, Thomas SpoorenbergSarada Ravinuthala, Chandra Yamarthy, Neena Koshy United Nations, Department of Economic and Social Affairs (DESA)Population Division - Population Estimates and Projections Sectionwww.unpopulation.org5 May 2011
WPP preparation process: Overview Estimation of population, fertility, mortality and migration Probabilistic projection of total fertility Projection of life expectancy Projection of migration Table of content 0 1 2 3 4 Source: United Nations, Department of Economic and Social Affairs, Population Division (2011): World Population Prospects, the 2010 Revision. New York
Team Chief Gerhard K. Heilig Population Affairs Officer Danan Gu Population Affairs Officer Kirill Andreev Population Affairs Officer Patrick Gerland Population Affairs Officer Nan Li Population Affairs Officer Thomas Spoorenberg Editorial Assistant Neena Koshy Information Systems Assistant Sarada Ravinuthala Information Systems Assistant Chandrasekhar Yamarthy
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
World Population Prospects: What we do 0 Start of WPP Start of WUP Projection, Aggregation, Checking Output Production Data Collection, Estimation 1 2 3 Data Collection230 countries / areas Uploading to Database Calculation of Variants Early Release Data CD-ROMs / DVDs EvaluationAdjustments Aggregation of Regions Online DatabaseWeb Sites Checking of Results Epidem. Modelingfor AIDS Countries Fixing of Errors Statistical ReportsVol. 1, 2 60% of Workload Consulting / Feedback Wall Chart Methodological Report (on web site) 15% of Workload Responding to clients Update and development of new databases and software, server and database maintenance, backup 25% of Workload
Basic Concept: Cohort-Component Projection 0 This diagram illustrates the basic concept of a cohort component population projection as well as a method of consistency checking. It shows two census populations: 1960 and 1970. When the estimated fertility for the inter-censual period is applied to 1960 female population age 15-49, it should produce the children age 0-10 in the census population of 1970. The population age 10-100+ in the 1970 census, on the other hand, should be equivalent to the population age 0-95 from the 1960 census with the inter-censual mortality applied. Mortality (Migration) Parents Fertility Children Source: United Nations, Department of Economic and Social Affairs, Population Division (2011): World Population Prospects, the 2010 Revision. New York
Uncertainty of Projections 0 Minimal uncertainty (adult mortality) Cohort Some uncertainty (second generation fertility, child mortality) Little uncertainty(first generation fertility, child mortality) Period / Year Age Source: United Nations, Department of Economic and Social Affairs, Population Division (2011): World Population Prospects, the 2010 Revision. New York
Census data + post-enumeration surveys(from United Nations Demographic Yearbook database and directly from National Statistical Offices) All available demographic and health surveys(DHS, DSS, MICS, WHS, etc.) for estimating fertility and mortality Estimates from population and vital registers(from statistical reports of National Statistical Offices or their web sites) Scientific reports and data collections(Human Mortality Database, child mortality estimates, etc.) Data and estimates provided by other international agencies(CELADE, Regional Commissions, EUROSTAT, ESCAP, UNICEF, UNAIDS, WHO) WPP data sources 0 Source: United Nations, Department of Economic and Social Affairs, Population Division (2011): World Population Prospects, the 2010 Revision. New York
Projection Period: 2015 - 2100 Medium Fertility Variant based on medianof probabilistic fertility projections Extended Model Life Tables (UN-MLT 2010) BaseYear 1950 for most countries (no back-projection) WPP2010: What is new? 0 1 2 3 4 Source: United Nations, Department of Economic and Social Affairs, Population Division (2011): World Population Prospects, the 2010 Revision. New York
1 Methodology The UN approach to estimating population (by age and sex), fertility, mortality and migrationAvailability & Data Quality Source: United Nations, Department of Economic and Social Affairs, Population Division (2011): World Population Prospects, the 2010 Revision. New York
Register Data: Population by Age and Sex 1 ≈ 2/3 of countries have insufficient population estimates by age and sex to establish consistent time-series from 1950 to present Sufficient for cohort-component projection Partially sufficient for cohort-component projection Not sufficient for projection Source: United Nations, Department of Economic and Social Affairs, Population Division (2011): World Population Prospects, the 2010 Revision. New York
Data Sources: Child Mortality Estimation (WPP2008) 1 Number of countries according to the most recent data available Only countries with a population of 100,000 or more in 2009 Source: United Nations, Department of Economic and Social Affairs, Population Division (2011): World Population Prospects, the 2010 Revision. New York
Data Sources: Adult Mortality Estimation (WPP2008) 1 Number of countries according to the most recent data available Only countries with a population of 100,000 or more in 2009 Source: United Nations, Department of Economic and Social Affairs, Population Division (2011): World Population Prospects, the 2010 Revision. New York
Data Sources: Fertility Estimation (WPP2008) 1 Number of countries according to the most recent data available Only countries with a population of 100,000 or more in 2009 Source: United Nations, Department of Economic and Social Affairs, Population Division (2011): World Population Prospects, the 2010 Revision. New York
Estimation of Population from Censuses 1 Source: United Nations, Department of Economic and Social Affairs, Population Division (2011): World Population Prospects, the 2010 Revision. New York
Estimation of Population from Censuses 1 Under-reported migrant workers Under-reported births Source: United Nations, Department of Economic and Social Affairs, Population Division (2011): World Population Prospects, the 2010 Revision. New York
Estimation of Total Population 1 Source: United Nations, Department of Economic and Social Affairs, Population Division (2011): World Population Prospects, the 2010 Revision. New York
Estimation of Total Population 1 Source: United Nations, Department of Economic and Social Affairs, Population Division (2011): World Population Prospects, the 2010 Revision. New York
Estimation of Total Population 1 Source: United Nations, Department of Economic and Social Affairs, Population Division (2011): World Population Prospects, the 2010 Revision. New York
Estimation of Mortality: 1q0, 5q0 (Senegal) 1 Source: United Nations, Department of Economic and Social Affairs, Population Division (2011): World Population Prospects, the 2010 Revision. New York
Estimation of Mortality: 5q0 (Senegal) 1 Source: United Nations, Department of Economic and Social Affairs, Population Division (2011): World Population Prospects, the 2010 Revision. New York
Estimation of Mortality: 45q15 (Senegal) 1 Source: United Nations, Department of Economic and Social Affairs, Population Division (2011): World Population Prospects, the 2010 Revision. New York
Estimation of Fertility: TFR (Senegal) 1 Source: United Nations, Department of Economic and Social Affairs, Population Division (2011): World Population Prospects, the 2010 Revision. New York
Estimation of Fertility: ASFR (Bangladesh) 1 Source: United Nations, Department of Economic and Social Affairs, Population Division (2011): World Population Prospects, the 2010 Revision. New York
Estimation of Fertility: ASFR (Bangladesh) 1 Lines are weighted cubic spline and loess regression trends Source: United Nations, Department of Economic and Social Affairs, Population Division (2011): World Population Prospects, the 2010 Revision. New York
Data Quality Assessment (based on WPP2006) 1 Source: United Nations, Department of Economic and Social Affairs, Population Division (2011): World Population Prospects, the 2010 Revision. New York
No recent census available (latest census 10 or more years ago) Only headcount of census was published. Population by age and sex was not published. No data on fertility and mortality were available from the census (such as children ever born, children born during 12 months prior to enumeration, deaths during 12 month prior to enumeration). Censusdiverts significantly from previous population trends. Census population by age and sex cannot be reproduced from the previous census by using inter-censal statistics or estimates on births, deaths, and migration. Examples: Turkey 2007 register-based census; Bangladesh 2001 population census; Equatorial Guinea, 2001 census Obviously manipulatedcensus counts, such as in countries, where the published census count is exactly 300,000 or grossly overestimated to meet a particular, politically relevant threshold (such as 1 million).Examples: 1983 census of Equatorial Guinea; 1969 census of Bhutan. Conclusion: Data Problems 1 Source: United Nations, Department of Economic and Social Affairs, Population Division (2011): World Population Prospects, the 2010 Revision. New York
Divergencesin fertility databetween different official sources, such as differences between statistical data published by various ministries.Example: In China, fertility estimates range from 1.38 for 2006 (2006 National Sample Survey on Population Changes) to 1.8 for 2007 (Statement by Dr. Hao Linan, Director-General for International Cooperation of the National Population and Family Planning Commission of China at the General Debates of the 41st Session of the UN commission on Population and Development. New York, 8 April 2008). Divergences in mortality estimates (under-five mortality, infant mortality) from different sources, such as vital registers, surveys, censuses as documented by UNICEF Incomplete geographical coverage of censuses and surveys due to armed conflicts or other problemsExample: Democratic Republic of the Congo, Sri Lanka (Tamil Region), Sudan (Darfur) Lack of meta-information and quality measures for census and survey data. Post-enumeration survey for census was not carried out or results are not available. Sampling plan for population survey is not available. No information about representativity of survey. Conclusion: Data Problems 1 Source: United Nations, Department of Economic and Social Affairs, Population Division (2011): World Population Prospects, the 2010 Revision. New York
Incompatibility of subsequent census counts due to change of enumeration method, such as register-based data collection. Examples: Turkey 2007 address-based census, Brazil Incompatibility of subsequent census counts due to change of definitions, such as the change from de-facto population to de-jure population. Incompatible definitions: resident populationExamples: Hong Kong, Singapore, Qatar Highly disputed statistical data on mortality, fertility or migration due to war, civil war, natural disaster. Unlikely sex ratios at birth.Examples: Mortality estimates of Iraq during embargo and war; China’s “missing girls” Extremely volatile population changes within short periods due to (labor) migration, particularly in countries where a large percentage or even the majority of the de-fact population is foreign labor migrants.Examples: Qatar Conclusion: Data Problems 1 Source: United Nations, Department of Economic and Social Affairs, Population Division (2011): World Population Prospects, the 2010 Revision. New York
2 Methodology: The UN approach to projecting total fertility A Bayesian Hierarchical Model (BHM) based on bi-logistic decline curves of fertility Source: United Nations, Department of Economic and Social Affairs, Population Division (2011): World Population Prospects, the 2010 Revision. New York
0.14 0.12 0.10 0.08 Fertility decline 0.06 0.04 0.02 0.00 10 9 8 7 6 5 4 3 2 1 Children per woman Fast/Fast Fast/Slow Slow/Slow Model of fertility decline 2 Model: Bi-logistic function to estimate the rate of fertility decline Source: United Nations, Department of Economic and Social Affairs, Population Division (2011): World Population Prospects, the 2010 Revision. New York
4 8 7 6 3 5 Children per woman Children per woman 4 2 3 2 1 1 2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100 2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100 Year Year Fast/Fast Fast/Slow Slow/Slow Floor Fast/Fast Fast/Slow Slow/Slow Floor Projections: Fertility 2 A. From high to low fertility B. From medium to 1.85 Source: United Nations, Department of Economic and Social Affairs, Population Division (2011): World Population Prospects, the 2010 Revision. New York
Model of fertility decline 2 Model: Bi-logistic function to estimate the rate of fertility decline 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. Source: United Nations, Department of Economic and Social Affairs, Population Division (2011): World Population Prospects, the 2010 Revision. New York
Fertility models and empirical data 2 Source: United Nations, Department of Economic and Social Affairs, Population Division (2011): World Population Prospects, the 2010 Revision. New York
BHM: A fertility transition model 2 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 Source: United Nations, Department of Economic and Social Affairs, Population Division (2011): World Population Prospects, the 2010 Revision. New York
BHM: A fertility transition model 2 Source: United Nations, Department of Economic and Social Affairs, Population Division (2011): World Population Prospects, the 2010 Revision. New York
BHM: A fertility transition model 2 Source: United Nations, Department of Economic and Social Affairs, Population Division (2011): World Population Prospects, the 2010 Revision. New York
BHM: Bi-logistic functions and TF projections 2 Source: United Nations, Department of Economic and Social Affairs, Population Division (2011): World Population Prospects, the 2010 Revision. New York
Probabilistic Projection of Population 2 Based on estimates from WPP2008; probabilistic fertility, deterministic mortality Source: United Nations, Department of Economic and Social Affairs, Population Division (2011): World Population Prospects, the 2010 Revision. New York
Probabilistic Projection of Population 2 Source: United Nations, Department of Economic and Social Affairs, Population Division (2011): World Population Prospects, the 2010 Revision. New York
3 Methodology: The UN approach to projecting life expectancy Source: United Nations, Department of Economic and Social Affairs, Population Division (2011): World Population Prospects, the 2010 Revision. New York
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 Source: United Nations, Department of Economic and Social Affairs, Population Division (2011): World Population Prospects, the 2010 Revision. New York
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 Source: United Nations, Department of Economic and Social Affairs, Population Division (2011): World Population Prospects, the 2010 Revision. New York
Models for projecting life expectancy at birth 3 Source: United Nations, Department of Economic and Social Affairs, Population Division (2011): World Population Prospects, the 2010 Revision. New York
Models for projecting life expectancy at birth 3 Source: United Nations, Department of Economic and Social Affairs, Population Division (2011): World Population Prospects, the 2010 Revision. New York
Projections: Mortality models and empirical data 3 Source: United Nations, Department of Economic and Social Affairs, Population Division (2011): World Population Prospects, the 2010 Revision. New York
Probabilistic mortality projection 3 • Data: • Male life expectancy at birth from 1950 through 2005; • Estimates from UN World Population Prospects (WPP2006) Source: United Nations, Department of Economic and Social Affairs, Population Division (2011): World Population Prospects, the 2010 Revision. New York
WPP2008 / P-WPP: e0 male 3 Source: United Nations, Department of Economic and Social Affairs, Population Division (2011): World Population Prospects, the 2010 Revision. New York
4 Methodology: The UN approach to estimating and projecting net-migration Source: United Nations, Department of Economic and Social Affairs, Population Division (2011): World Population Prospects, the 2010 Revision. New York
Estimation of net-migration (based on WPP2008) 4 2005-2010 On a continental scale, migration is a very small demographic component as compared to fertility and mortality Source: United Nations, Department of Economic and Social Affairs, Population Division (2011): World Population Prospects, the 2010 Revision. New York