United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Evaluation of Fertility Data Collected from Population Censuses United Nations Statistics Division

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 For two items that can be collected to obtain fertility statistics in census: Children ever born Recent births Discuss What information to collect What fertility indicators can be derived Possible quality issues related to each question Methods of data evaluation Outline of the presentation

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Children ever born – what information to collect? How many children has [this woman] had in her lifetime? (a) “Total number of sons living in the household”; (b) “Total number of sons living elsewhere”; (c) “Total number of sons born alive who have died before the census date”; (d) “Total number of daughters living in the household”; (e) “Total number of daughters living elsewhere”; (f) “Total number of daughters born alive who have died before the census date”. incl. all live births Could be elaborated into a number of questions Asked to all women

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 When is it used? Widely used for over 50 years Important for countries without complete birth registration Also important for countries with complete birth registration Study fertility by detailed socio-economic characteristics Children ever born – the use of What can we get? Parity distributionsAverage number of children ever born Age-specific fertility rateTotal fertility rate (TFR)

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Children ever born - Tabulation Age of women Number of children ever born CEB not stated Total women Total children born 01… … NS Total - Do not group the numbers of children, except for the last open category - Distinguish children ever born not stated from no children

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Children ever born – possible errors (1) Group A: Errors because of misunderstanding the question: -Mortality error: reported only children living rather than ever born -Non-resident error: overlooking ever born children living elsewhere -Marriage error: women not including her children born from previous marriage/not reporting children born out of wedlock Group B: Errors because of respondents’ lapse of memory or neglect: -Memory error: forgot some children, especially from older women Group C: Enumerators’ failure to reach individuals: -The not-at-home error: information provided by neighbors -Coverage error: omit an area or forgot to record the answer Group D: Recording error: -Childless women mis-classified into parity not stated

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Not all errors can be detected However, many steps can be taken to find inconsistencies, to understand better the data quality and to provide information for improvement in the next census Children ever born – possible errors (2)

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Children ever born – quality assessment Methods (1) -Initial assessment: -Any missing values in children ever born data? -Missing value for any relevant variables? (age of mother, sex of child, survival status of the child) -Comparing children ever born and children surviving data

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Children ever born – quality assessment Methods (2) -For tabulated data: -Sex ratio of children ever born consistent with national average of sex ratio at birth? -Check whether women with parity “not stated” are childless instead (El-Badry method) -Plausibility of data – graphics help and best with other sources -Average children ever born should increase with age (Group B error) – with constant or declining fertility assumption -Proportion of women by parity, for older age groups -Time plot of mean number of children ever born, based on multiple data sources (cohort analysis) -Age-specific fertility rates -TFR

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 P/F ratio method Usually used to adjust current fertility data derived from recent births question May also be used to assess the quality of both current (derived from recent births) and life time fertility data (derived from children ever born) Certain assumptions (discuss in more details later) Children ever born – quality assessment Methods (3)

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Children ever born – quality assessment examples (1) Any missing/implausible value for children ever born data? Source: Estimation of fertility from the 2001 South Africa census data, Tom A Moultrie & Rob Dorrington, Centre for Actuarial Research, University of Cape Town

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Children ever born – quality assessment examples (2) Comparing sex ratio at birth Data source: graph produced based on data from United Nations Demographic Yearbook

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Children ever born – quality assessment examples (3): Plot mean number of children ever born by age of women Data source: graph produced based on data from United Nations Demographic Yearbook

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Children ever born – quality assessment examples (4): mean children ever born from multiple sources Data source: graph produced based on data from United Nations Demographic Yearbook

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Children ever born – quality assessment examples (5): parity distribution for age group High level of 0 parity for older age group: 1950 and 1970 censuses: possible combined group of not stated parity with 0 parity group Flat curve: probably some form of mis-reporting, seems to be improving over time Mexican fertility survey: shape of the curve more plausible (although with small sample sizes) Source: Child survivorship estimation: methods and data analysis, Griffith Feeney, Asian and Pacific Population Forum, Vol. 5, Nos. 2-3, 1991

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Year = census yr – (age – 25) 1960 and 1970 censuses: an increase of fertility Erroneous data from 1980 census (conclusion was reached after comparing with data from other surveys) Children ever born – quality assessment examples (6): Cohort analysis of mean number of children ever born Source: Child survivorship estimation: methods and data analysis, Griffith Feeney, Asian and Pacific Population Forum, Vol. 5, Nos. 2-3, 1991

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Children ever born – quality assessment examples (7): Comparing age specific fertility rates Data source: graph produced based on data from United Nations Demographic Yearbook and Measure DHS country report

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Children ever born – quality assessment examples (8): Comparing total fertility rates Data source: graph produced based on data from United Nations Demographic Yearbook and Measure DHS country report

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Children ever born – quality assessment examples (9): El-Badry method AgeFemale pop.Childless women (%) Women who have unknown number of children (%) 15+1,483, , , , , , , , , , , , Unknown2, Data source: United Nations Demographic Yearbook, Burundi 1990

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Children ever born – quality assessment examples (9): El-Badry method (cont.) Data source: United Nations Demographic Yearbook, Burundi 1990

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 % women with not stated # of children = * % childless women (linear regression)   32% of the real childless cases were reported as “number of children not given” El-badry method: Failure of enumerators to make entries of zero: Errors in recording childless cases in population censuses, JASA, Vol. 56, No. 296, 1961 Children ever born – quality assessment examples (9): El-Badry method (cont.)  real childless women = observed childless women / (1- 32%)

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Children ever born – quality assessment examples (10) Using the P/F ratio method Rational: -Compare cumulative fertility level derived from current fertility data F(trusting the distribution but not level) and life time fertility data P (trusting the overall level but assumes under-reporting varies by age) -The method is typically used to adjust current fertility level (may be generated from recent births question in census or birth data from civil registration) -However the method is also used to assess the quality of children ever born data and sometimes, the age reporting of mother Current fertility data: Births in the last 12 months (from censuses or civil registration) Life time fertility data: Children ever born in the life time of women

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Assumptions: Constant proportion of under-reporting of current fertility for all age groups Increasing under-reporting of parity (children ever born) by age of women Constant fertility (relaxed by a modification of the original P/F ratio method) Children ever born – quality assessment examples (10) Using the P/F ratio method (cont.)

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Children ever born – quality assessment examples (10): P/F ratio method (cont.) Data source: Manual X, Bangladesh 1974 census Typical P/F ratio, relative good data

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Typical “look” of P/F ratios: -Similar level of P/F ratios for age groups 20-24, and P/F ratios becomes smaller for older ages Deviation from the above typical pattern: indicates either violations of the assumptions or different patterns of under-reporting -Example 1: a rising trend in the P/F ratios by age of women: fertility could have been decreasing in the past -Example 2: a declining trend in the P/F ratios by age of women: fertility could have been increasing or that reported data on children ever born suffer from progressively increasing omissions of children as age of women increases -Example 3: large fluctuation in P/F ratios may reflect either differential coverage by age or selective age misreporting of women Children ever born – quality assessment examples (10): P/F ratio method (cont.)

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Recent births - basics How? Date of birth of last child born alive (preferred question) OR Births in the last twelve months (to a woman) or in the household However, The questions are subject to under-reporting of births Age of women during the census to be adjusted to age at giving birth (usually year) What can we get? Age specific fertility rate and TFR

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Recent births – Possible errors Reporting errors: Enumerator’s error “reference period error”: uncertain of the date of birth vs the reference period Proxy respondent Births reported not including: Women had a birth recently but died before the census Household had a birth recently but the household dissolved before the census Not significant in most cases, however could become an issue when many deaths occurred in a short period (HIV/AIDS)

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Recent births – assessment (1) Methods Initial assessment: any missing values in data? (month/date/year of births) Missing data for any relevant variables? (age of mother, sex of child, survival status of the child) For tabulated data: Sex ratio at birth consistent with national average? Plausibility of data – graphics help and best with other sources Age-specific fertility rate TFR

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Recent births – assessment (1) Methods (cont.) -Compare with civil registration data on live births -P/F ratio method to compare with children ever born data for coverage

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Recent births – assessment (2): any missing values? Source: Estimation of fertility from the 2001 South Africa census data, Tom A Moultrie & Rob Dorrington, Centre for Actuarial Research, University of Cape Town

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Recent births – assessment (3): Comparing age-specific fertility rate patterns Source: Graph created using data from United Nations Demographic Yearbook; 2000 Census of Population, Social and Economic Characteristics of Population, State Institute of Statistics, Turkey; Measure DHS Final Report Turkey 1998 and 2003

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Recent births – assessment (4): Comparing TFR Source: Graph created using data from United Nations Demographic Yearbook; 2000 Census of Population, Social and Economic Characteristics of Population, State Institute of Statistics, Turkey; Measure DHS Final Report Turkey 1998 and 2003

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Recent births – assessment (6): Comparing TFR Yes under-estimated: but may reflect recent fertility pattern; adjusting for under-count and will be useful for sub-national and small area fertility estimates. How to adjust: use household survey data Only source for small area Date of last birth data better quality than births in the last 12 months

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Illustration of using MortPak FERTPF for indirect estimates of fertility – input data

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Illustration of using MortPak FERTPF for indirect estimates of fertility – results

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Thank you!