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    Population and Family Estimation Methods at Statistics Canada

    Chapter 9
    Population estimates by age, sex, marital status and legal marital status

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    The analysis of population by age and sex is a fundamental aspect of most demographic studies. The age and sex structure of the population varies with time and place, while at the same time, demographic behaviour is often a function of age and sex. For example, mortality rates are much higher in the older age groups. High migration rates are associated with young adults, as they move for personal and economic reasons. Population estimates by age and sex are widely used by other divisions of Statistics Canada. For example, these estimates are used in the calculation of employment and unemployment rates and crime rates, which tend to vary according to age and sex distributions. The addition of marital status builds the foundation for studying other demographic phenomena such as marriage and divorce rates and changes in family structure. Government and private sector planning and policies are largely driven by the age, sex and marital status profiles of certain populations.

    Population estimates by age and sex are available at national, provincial, territorial, census division, census metropolitan area and economic region levels. The more detailed breakdown of these estimates by marital status or legal marital status is available only at the national, provincial and territorial levels. This chapter presents the methods used to produce population estimates disaggregated by age, sex, marital status and legal marital status.

    9.1 Postcensal population estimates by age and sex, Canada, provinces and territories

    9.1.1 Data sources and relevant concepts

    Postcensal estimates of population by age and sex are produced using the cohort-component approach. This is similar to the component method as used in the production of total population estimates, although additional data are required in its application. The data required for the cohort component method are related to demographic events (deaths, immigration, net non-permanent residents, emigration, returning emigration, net temporary emigration and interprovincial migration) that can be directly linked to persons belonging to the same birth cohort (i.e., persons who were born during the same period or year). Different components require different approaches, based on the nature of the data used to generate the estimates. Their respective chapters elaborate upon the manner in which the estimate for each component is distributed by age and sex.

    The data sources used in the production of the population estimates by age and sex are as follows:Note 1

    • Births and deaths using vital statistics;
    • Immigration and non-permanent residents using data from Citizenship and Immigration Canada (CIC);
    • Emigration distributed by age and sex using the data by five-year age group, sex, province and territory from T1FFNote 2 files adjusted for the coverage. We distribute these estimates by single year of age using Sprague coefficients;
    • Net temporary emigration distributed by age and sex using emigration distributions;
    • Returning emigrants distributed by age and sex using the most recent National Household Survey (NHS) data on mobility data one year ago, after excluding non-permanent residents and immigrants;
    • Interprovincial migration by age and sex derived from T1FF family file by Income Statistics Division and counts from the last available NHS (one-year mobility variable).

    9.1.2 Levels of estimates

    The difference between preliminaryNote 3 and final postcensal estimates lies in the timeliness of the components. When all the components are preliminary, the estimate is described as preliminary postcensal (PP). When they are all final, the estimate is referred to as final postcensal (PD). Any other combination of levels is referred to as updated postcensal (PR).

    9.1.3 Methods of estimation

    Postcensal estimates of population by age and sex are produced using the cohort component approach. This approach requires a slight modification of the component approach described in Chapter 1, but the overall principles are the same.

    Annual estimates

    Estimates of population by age and sex are published annually with July 1 as the reference date. To calculate these estimates, birth cohorts (those persons born during the same year) for both males and females separately, are used. The cohort-component approach factors in the aging of the cohorts over time. For example, persons aged 19 one year will be 20 years old the following year. The data required for the cohort-component method include demographic events such as births, immigration, emigration, net temporary emigration, returning emigration, non-permanent residents and interprovincial migration that can be directly linked to persons belonging to the same birth and sex cohorts.

    Demographers use a tool called a Lexis diagram (Figure 9.1) to aid in the linking of events to specific cohorts. Time is located on the horizontal axis (abscissa), while the vertical axis (ordinate) represents age. Specific cohorts are identified by the diagonals (lifelines) that cross the diagram. Using the cohort-component approach, demographic events are organized to follow these lifelines.

    Figure 9.1
    Transition from a distribution of demographic events by age and period to a distribution by age and birth cohort

    Figure 9.1 Transition from a distribution of demographic events

    Description for Figure 9.1

    Take, for example, those aged 19 as of July 1, 2006, who belong to the cohort born between July 1, 1986 and June 30, 1987 (inclusive). The demographic events experienced by this cohort during the estimation period are represented by triangles b and c.

    Under the cohort-component method, the equations for estimating annual population by single years of age and sex at the national, provincial and territorial levels are as follows:

    For each sex, by province and territory:

    At age 0:Note 4

    Equation 9.1:

    P (t+1) 0 = B (t,t+1) − D (t,t+1) −1 + I (t,t+1) −1 −( E (t,t+1) −1 +ΔT E (t,t+1) −1 )+R E (t,t+1) −1 +ΔNP R (t,t+1) −1 +Δ N (t,t+1) −1 MathType@MTEF@5@5@+= feaagKart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaamiuamaaDa aaleaacaGGOaGaamiDaiabgUcaRiaaigdacaGGPaaabaGaaGimaaaa kiabg2da9iaadkeadaWgaaWcbaGaaiikaiaadshacaGGSaGaamiDai abgUcaRiaaigdacaGGPaaabeaakiabgkHiTiaadseadaqhaaWcbaGa aiikaiaadshacaGGSaGaamiDaiabgUcaRiaaigdacaGGPaaabaGaey OeI0IaaGymaaaakiabgUcaRiaadMeadaqhaaWcbaGaaiikaiaadsha caGGSaGaamiDaiabgUcaRiaaigdacaGGPaaabaGaeyOeI0IaaGymaa aakiabgkHiTiaacIcacaWGfbWaa0baaSqaaiaacIcacaWG0bGaaiil aiaadshacqGHRaWkcaaIXaGaaiykaaqaaiabgkHiTiaaigdaaaGccq GHRaWkcqqHuoarcaWGubGaamyramaaDaaaleaacaGGOaGaamiDaiaa cYcacaWG0bGaey4kaSIaaGymaiaacMcaaeaacqGHsislcaaIXaaaaO GaaiykaiabgUcaRiaadkfacaWGfbWaa0baaSqaaiaacIcacaWG0bGa aiilaiaadshacqGHRaWkcaaIXaGaaiykaaqaaiabgkHiTiaaigdaaa GccqGHRaWkcqqHuoarcaWGobGaamiuaiaadkfadaqhaaWcbaGaaiik aiaadshacaGGSaGaamiDaiabgUcaRiaaigdacaGGPaaabaGaeyOeI0 IaaGymaaaakiabgUcaRiabfs5aejaad6eadaqhaaWcbaGaaiikaiaa dshacaGGSaGaamiDaiabgUcaRiaaigdacaGGPaaabaGaeyOeI0IaaG ymaaaaaaa@8C43@

    From 1 to 99 years:

    Equation 9.2:

    P (t+1) (a+1) = P t a − D (t,t+1) a + I (t,t+1) a −( E (t,t+1) a +ΔT E (t,t+1) a )+R E (t,t+1) a +ΔNP R (t,t+1) a +Δ N (t,t+1) a MathType@MTEF@5@5@+= feaagKart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaamiuamaaDa aaleaacaGGOaGaamiDaiabgUcaRiaaigdacaGGPaaabaGaaiikaiaa dggacqGHRaWkcaaIXaGaaiykaaaakiabg2da9Gqaaiaa=bfadaqhaa WcbaGaa8hDaaqaaiaa=fgaaaGccqGHsislcaWGebWaa0baaSqaaiaa cIcacaWG0bGaaiilaiaadshacqGHRaWkcaaIXaGaaiykaaqaaiaadg gaaaGccqGHRaWkcaWGjbWaa0baaSqaaiaacIcacaWG0bGaaiilaiaa dshacqGHRaWkcaaIXaGaaiykaaqaaiaadggaaaGccqGHsislcaGGOa GaamyramaaDaaaleaacaGGOaGaamiDaiaacYcacaWG0bGaey4kaSIa aGymaiaacMcaaeaacaWGHbaaaOGaey4kaSIaeuiLdqKaamivaiaadw eadaqhaaWcbaGaaiikaiaadshacaGGSaGaamiDaiabgUcaRiaaigda caGGPaaabaGaamyyaaaakiaacMcacqGHRaWkcaWGsbGaamyramaaDa aaleaacaGGOaGaamiDaiaacYcacaWG0bGaey4kaSIaaGymaiaacMca aeaacaWGHbaaaOGaey4kaSIaeuiLdqKaamOtaiaadcfacaWGsbWaa0 baaSqaaiaacIcacaWG0bGaaiilaiaadshacqGHRaWkcaaIXaGaaiyk aaqaaiaadggaaaGccqGHRaWkcqqHuoarcaWGobWaa0baaSqaaiaacI cacaWG0bGaaiilaiaadshacqGHRaWkcaaIXaGaaiykaaqaaiaadgga aaaaaa@866A@

    For 100 years and over:

    Equation 9.3:

    P (t+1) 100+ = P t 99+ − D (t,t+1) 99+ + I (t,t+1) 99+ −( E (t,t+1) 99+ +ΔT E (t,t+1) 99+ )+R E (t,t+1) 99+ +ΔNP R (t,t+1) 99+ +Δ N (t,t+1) 99+ MathType@MTEF@5@5@+= feaagKart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaamiuamaaDa aaleaacaGGOaGaamiDaiabgUcaRiaaigdacaGGPaaabaGaaGymaiaa icdacaaIWaGaey4kaScaaOGaeyypa0dcbaGaa8huamaaDaaaleaaca WG0baabaGaaGyoaiaaiMdacqGHRaWkaaGccqGHsislcaWGebWaa0ba aSqaaiaacIcacaWG0bGaaiilaiaadshacqGHRaWkcaaIXaGaaiykaa qaaiaaiMdacaaI5aGaey4kaScaaOGaey4kaSIaamysamaaDaaaleaa caGGOaGaamiDaiaacYcacaWG0bGaey4kaSIaaGymaiaacMcaaeaaca aI5aGaaGyoaiabgUcaRaaakiabgkHiTiaacIcacaWGfbWaa0baaSqa aiaacIcacaWG0bGaaiilaiaadshacqGHRaWkcaaIXaGaaiykaaqaai aaiMdacaaI5aGaey4kaScaaOGaey4kaSIaeuiLdqKaamivaiaadwea daqhaaWcbaGaaiikaiaadshacaGGSaGaamiDaiabgUcaRiaaigdaca GGPaaabaGaaGyoaiaaiMdacqGHRaWkaaGccaGGPaGaey4kaSIaamOu aiaadweadaqhaaWcbaGaaiikaiaadshacaGGSaGaamiDaiabgUcaRi aaigdacaGGPaaabaGaaGyoaiaaiMdacqGHRaWkaaGccqGHRaWkcqqH uoarcaWGobGaamiuaiaadkfadaqhaaWcbaGaaiikaiaadshacaGGSa GaamiDaiabgUcaRiaaigdacaGGPaaabaGaaGyoaiaaiMdacqGHRaWk aaGccqGHRaWkcqqHuoarcaWGobWaa0baaSqaaiaacIcacaWG0bGaai ilaiaadshacqGHRaWkcaaIXaGaaiykaaqaaiaaiMdacaaI5aGaey4k aScaaaaa@91B7@

    where

    (t,t+1) MathType@MTEF@5@5@+= feaagKart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaaiikaiaads hacaGGSaGaamiDaiabgUcaRiaaigdacaGGPaaaaa@3B8E@
    =
    interval between times t and t+1;
    a MathType@MTEF@5@5@+= feaagKart1ev2aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaamyyaaaa@36DD@
    =
    age;
    P (t+1) MathType@MTEF@5@5@+= feaagKart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaamiuamaaDa aaleaacaGGOaGaamiDaiabgUcaRiaaigdacaGGPaaabaaaaaaa@3AE7@
    =
    estimate of the population at time t+1;
    P t MathType@MTEF@5@5@+= feaagKart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaacbaGaa8huam aaDaaaleaacaWF0baabaaaaaaa@37F2@
    =
    base population at time t (census adjusted for CNUNote 5 or most recent estimate);
    B MathType@MTEF@5@5@+= feaagKart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaamOqaaaa@36BD@
    =
    number of births;
    D MathType@MTEF@5@5@+= feaagKart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaamiraaaa@36BF@
    =
    number of deaths;
    I MathType@MTEF@5@5@+= feaagKart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaamysaaaa@36C4@
    =
    number of immigrants;
    E MathType@MTEF@5@5@+= feaagKart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaamyraaaa@36C0@
    =
    number of emigrants;
    ΔTE MathType@MTEF@5@5@+= feaagKart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaeuiLdqKaam ivaiaadweaaaa@38FF@
    =
    net temporary emigration;
    RE MathType@MTEF@5@5@+= feaagKart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaamOuaiaadw eaaaa@3797@
    =
    number of returning emigrants;
    ΔNPR MathType@MTEF@5@5@+= feaagKart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaeuiLdqKaam OtaiaadcfacaWGsbaaaa@39DB@
    =
    net non-permanent residents;
    ΔN MathType@MTEF@5@5@+= feaagKart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaeuiLdqKaam Otaaaa@382F@
    =
    net interprovincial migration.

    Annual population estimates by single year of age and sex for persons aged 0 to 99, and 100 years and over are available from 2001 and onwards at the national, provincial and territorial level. Previously, the upper limit of the age category was 90 years and over.

    9.2 Intercensal population estimates by age and sex, Canada, provinces and territories

    Intercensal population estimates for reference dates between two censuses are produced following each census. They reconcile previous postcensal estimates with the new census counts after being adjusted for census net undercoverage (CNU). Like the total population by province or territory, intercensal population by age and sex are adjusted by distributing the error of closure uniformly across the age-sex cohorts. Refer to Chapter 1 for further details.

    9.3 Subprovincial postcensal and intercensal estimates by age and sex

    Postcensal population estimates by age and sex for census divisions (CDs) and census metropolitan areas (CMAs) are produced by applying the component method to each age-sex cohort in the base population, whereby the population is aged from year to year and the components are tabulated according to age and sex cohorts. A different method called the census division's (CD) aggregate method is used to produce population estimates by age and sex for economic regions (ERs). Descriptions of the methods used to estimate the populations by age and sex for CMAs, CDs and ERs are provided in Chapter 8. At the subprovincial level, annual population estimates by age and sex are available for ages 0 to 89 and ages 90 and over.

    Special methods for preliminary postcensal estimates by age and sex are applied for CDs, CMAs and ERs in Quebec and British Columbia. These methods and the approach used to derive intercensal estimates by age and sex at subprovincial levels are described in Chapter 8.

    9.4 Population estimates by age, sex, marital status and legal marital status, Canada, provinces and territories

    There are two series of population estimates by marital status, the main difference between them being the treatment of persons living in common-law unions. One of them is the series of estimates by legal marital status, i.e., a person's conjugal status under the law (for example, single, married, widowed or divorced). On the basis of this definition, people living common law are categorized by their legal marital status. If a person has never married and is living common law, he or she is regarded as single under this definition.

    The other is the series of estimates by marital status, i.e., a person's de facto conjugal status. For example, a person who reports being legally widowed and is living with another person as a couple but is not married to that person will be counted as common law in the marital status series and widowed in the legal marital status series.

    Separate estimates for legal and de facto marital statuses at the national, provincial and territorial levels are available from 1991 onwards. However, estimates for the marital status exist since 1971. Estimates of marital statuses are not produced for subprovincial levels.

    9.4.1 Definition of different groupings by marital status or legal marital status

    Marital status refers to the conjugal status of a person. In demographic estimates, a distinction is made between legal marital status and marital status. The distinction between the two definitions lies in the concept of who is considered married. A person's legal marital status is determined by law. Common-law partners are not legally married to each other, thus are considered single, divorced or widowed according to their legal marital status. Separated couples are considered legally married under both concepts.

    The following definitions represent those used by Statistics Canada for legal marital status and marital status, respectively.

    Legal marital status refers to the marital status of the person under the law. Estimates are presented in the following categories: single, legally married, separated, widowed or divorced.

    Table summary
    This table displays the results of Legal marital status (appearing as column headers).
    Legal marital status
    Single (never legally married) Includes persons who have never married (including all persons less than 15 years of age). Those who live with a common-law partner are included in this category.
    Married (and not separated) Includes persons whose opposite- or same-sex spouse is living, unless the couple is separated or a divorce has been obtained. Also included are persons in civil unions.
    Separated Includes persons currently legally married but who are no longer living with their spouse (for any reason other than illness, work or school) and have not obtained a divorce. Those who live with a common-law partner are included in this category.
    Widowed Includes persons who have lost their legally-marriedspouse through death and have not remarried. Those who live with a common-law partner are included in this category.
    Divorced Includes persons who have obtained a legal divorce and have not remarried. Those who live with a common-law partner are included in this category.

    Marital status indicates the conjugal arrangement of a person. Estimates are presented in the following categories: single, married (including persons living common-law and persons who are separated), widowed or divorced. Common-law status refers to whether the person aged 15 or over is living with a person of the opposite sex or of the same sex as a couple but is not legally married to that person. It includes situations where the members of such a couple are living apart temporarily because of illness, work or school.

    Table summary
    This table displays the results of Marital Status (appearing as column headers).
    Marital status
    Single (never legally married) Includes persons who have never married (including all persons less than 15 years of age). Those who live with a common-law partner are not included in this category.
    Married (and not separated) From 1971 to 1990, the category married (and not separated) includes persons whose opposite- or same-sex spouse is living, unless the couple is separated or a divorce has been obtained. Also included are persons in civil unions and common-law unions. As of 1991, legally married persons are included in this category; persons living with a common-law partner are no longer included in the married category. For the legal marital status, common-law unions are found in each of the categories other than married. For marital status, they constitute a separate category.
    Separated Includes persons currently legally married but who are no longer living with their spouse (for any reason other reasons than illness, work or school) and have not obtained a divorce. Those who live with a common-law partner are not included in this category.
    Living in common law Includes persons who are living with a person of the opposite sex or of the same sex as a couple but who are not legally married to that person. It includes situations where the members of such a couple are living apart temporarily because of illness, work or school.
    Widowed Includes persons who have lost their legally-married spouse through death and who have not remarried. Those who live with a common-law partner are not included in this category.
    Divorced Includes persons who have obtained a legal divorce and have not remarried. Those who live with a common-law partner are not included in this category.

    9.5 Postcensal population estimates by marital status and legal marital status

    In the past, the Demography Division used the component method to produce population estimates by marital status and legal marital status. Since marriage and divorce data is no longer available, the division had to modify its estimation method. As the overall picture of marital status evolves slowly, the division has opted to use proportions taken from the census. For every census, a series of proportions by age, sex, marital status and legal marital status will be produced. They will be kept constant for the entire postcensal period and will be applied to the annual population estimates by age and sex.

    9.5.1 Censal population estimates

    The base numbers used to create the proportions come from census counts by age, sex, marital status and legal marital status readjusted for CNU and a particular adjustment made for the population aged 15 to 19 years. For more information regarding the CNU, please refer to Chapter 2.

    9.5.1.1 Adjustment for those aged 15 to 19 years

    For the past few censuses, we have realised that the census numbers for marital status adjusted for CNU for the 15 to 19 year age group overestimate the number of persons widowed, divorced or married. Comparisons with other data sources, such as vital statistic files (to determine a person's age when they were married or divorced), or Citizenship and Immigration Canada files (to determine the marital status of immigrants or non-permanent residents) do not corroborate the higher counts found in the census. As a result, we decided to include an adjustment for this particular age group.

    In order to do so, we use the latest postcensal estimates (July 1st, 2006) that we obtained using the components method in order to correct the adjusted census counts.

    We calculate a series of weights for marital status estimates, and another for legal marital status for persons married, separated, divorced and widowed for each age between 15 and 19 years, for both sexes and for each province and territory.

    Equation 9.4:      Weigh t ex a  =  P ex a ∑ ex P ex a MathType@MTEF@5@5@+= feaagKart1ev2aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaam4vaiaadw gacaWGPbGaam4zaiaadIgacaWG0bWaa0baaSqaaiaadwgacaWG4baa baGaamyyaaaakiaaysW7cqGH9aqpcaaMe8+aaSaaaeaacaWGqbWaa0 baaSqaaiaadwgacaWG4baabaGaamyyaaaaaOqaamaaqafabaGaamiu amaaDaaaleaacaWGLbGaamiEaaqaaiaadggaaaaabaGaamyzaiaadI haaeqaniabggHiLdaaaaaa@4E58@

    where

    a MathType@MTEF@5@5@+= feaagKart1ev2aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaWcqaaaaaaaaa Wdbiaadggaaaa@3708@
    =
    Age going from 15 to 19 years;
    ex MathType@MTEF@5@5@+= feaagKart1ev2aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaamyzaiaadI haaaa@37DE@
    =
    Marital status or legal marital status for category x. The value of x representing persons either married, separated, divorced or widowed;
    P MathType@MTEF@5@5@+= feaagKart1ev2aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaamiuaaaa@36CC@
    =
    Postcensal population estimates derived from the components method given the marital status or legal marital status.

    As we don't have postcensal estimates from the components method for separated persons, we must make an additional adjustment for persons married and separated.

    The weight for married persons is calculated as follows:

    Equation 9.5:

    If
    Cen A M+S a  = 0; MathType@MTEF@5@5@+= feaagKart1ev2aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaam4qaiaadw gacaWGUbGaamyqamaaDaaaleaacaWGnbGaey4kaSIaam4uaaqaaiaa dggaaaGccaaMe8Uaeyypa0JaaGjbVlaaicdacaGG7aaaaa@42A4@

    Weigh t M a  =  Cen A M 15−19 Cen A M+S 15−19  *  P M+S a ∑ ex P ex a MathType@MTEF@5@5@+= feaagKart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaam4vaiaadw gacaWGPbGaam4zaiaadIgacaWG0bWaa0baaSqaaiaad2eaaeaacaWG HbaaaOGaaGjbVlabg2da9iaaysW7daWcaaqaaiaadoeacaWGLbGaam OBaiaadgeadaqhaaWcbaGaamytaaqaaiaaigdacaaI1aGaeyOeI0Ia aGymaiaaiMdaaaaakeaacaWGdbGaamyzaiaad6gacaWGbbWaa0baaS qaaiaad2eacqGHRaWkcaWGtbaabaGaaGymaiaaiwdacqGHsislcaaI XaGaaGyoaaaaaaGccaaMe8UaaiOkaiaaysW7daWcaaqaaiaadcfada qhaaWcbaGaamytaiabgUcaRiaadofaaeaacaWGHbaaaaGcbaWaaabu aeaacaWGqbWaa0baaSqaaiaadwgacaWG4baabaGaamyyaaaaaeaaca WGLbGaamiEaaqab0GaeyyeIuoaaaaaaa@642B@
    If not
    Weigh t M a  =  Cen A M a Cen A M+S a  *  P M+S a ∑ ex P ex a MathType@MTEF@5@5@+= feaagKart1ev2aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaam4vaiaadw gacaWGPbGaam4zaiaadIgacaWG0bWaa0baaSqaaiaad2eaaeaacaWG HbaaaOGaaGjbVlabg2da9iaaysW7daWcaaqaaiaadoeacaWGLbGaam OBaiaadgeadaqhaaWcbaGaamytaaqaaiaadggaaaaakeaacaWGdbGa amyzaiaad6gacaWGbbWaa0baaSqaaiaad2eacqGHRaWkcaWGtbaaba GaamyyaaaaaaGccaaMe8UaaiOkaiaaysW7daWcaaqaaiaadcfadaqh aaWcbaGaamytaiabgUcaRiaadofaaeaacaWGHbaaaaGcbaWaaabuae aacaWGqbWaa0baaSqaaiaadwgacaWG4baabaGaamyyaaaaaeaacaWG LbGaamiEaaqab0GaeyyeIuoaaaaaaa@5E2E@

    The weight for separated persons is calculated as follows:

    Equation 9.6:      Weigh t S a =   P M+S a ∑ ex P ex a  − Weigh t M a MathType@MTEF@5@5@+= feaagKart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaaeaaaaaaaaa8 qacaWGxbGaamyzaiaadMgacaWGNbGaamiAaiaadshapaWaa0baaSqa a8qacaWGtbaapaqaa8qacaWGHbaaaOGaeyypa0JaaiiOaiaacckada WcaaWdaeaapeGaamiua8aadaqhaaWcbaWdbiaad2eacqGHRaWkcaWG tbaapaqaa8qacaWGHbaaaaGcpaqaa8qadaaeqbqaaiaadcfapaWaa0 baaSqaa8qacaWGLbGaamiEaaWdaeaapeGaamyyaaaaaeaacaWGLbGa amiEaaqab0GaeyyeIuoaaaGccaaMe8UaeyOeI0IaaGjbVlaadEfaca WGLbGaamyAaiaadEgacaWGObGaamiDa8aadaqhaaWcbaWdbiaad2ea a8aabaWdbiaadggaaaaaaa@59ED@

    After obtaining the weights, we calculate the adjustment for each status.

    Equation 9.7:

    If
    Adjustmen t ex a  = Weigh t ex a  *  ∑ ex Ce n ex a  − Cen A ex a  > 0 Set equal to 0 MathType@MTEF@5@5@+= feaagKart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGceaqabeaaqaaaaa aaaaWdbiaadgeacaWGKbGaamOAaiaadwhacaWGZbGaamiDaiaad2ga caWGLbGaamOBaiaadshapaWaa0baaSqaa8qacaWGLbGaamiEaaWdae aapeGaamyyaaaak8aacaaMe8Uaeyypa0JaaGjbV=qacaWGxbGaamyz aiaadMgacaWGNbGaamiAaiaadshapaWaa0baaSqaa8qacaWGLbGaam iEaaWdaeaapeGaamyyaaaak8aacaaMe8UaaiOkaiaaysW7peWaaybu aeqal8aabaWdbiaadwgacaWG4baabeqdpaqaa8qacqGHris5aaGcca WGdbGaamyzaiaad6gapaWaa0baaSqaa8qacaWGLbGaamiEaaWdaeaa peGaamyyaaaak8aacaaMe8UaeyOeI0IaaGjbVlaadoeacaWGLbGaam OBa8qacaWGbbWdamaaDaaaleaapeGaamyzaiaadIhaa8aabaWdbiaa dggaaaGccaaMe8UaeyOpa4JaaGjbVlaaicdaaeaacaqGtbGaaeyzai aabshacaqGGaGaaeyzaiaabghacaqG1bGaaeyyaiaabYgacaqGGaGa aeiDaiaab+gacaqGGaGaaGimaaaaaa@7976@
    If not
    Adjustmen t ex a  = Weigh t ex a  *  ∑ ex Ce n ex a  − Cen A ex a MathType@MTEF@5@5@+= feaagKart1ev2aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaaeaaaaaaaaa8 qacaWGbbGaamizaiaadQgacaWG1bGaam4CaiaadshacaWGTbGaamyz aiaad6gacaWG0bWdamaaDaaaleaapeGaamyzaiaadIhaa8aabaWdbi aadggaaaGcpaGaaGjbVlabg2da9iaaysW7peGaam4vaiaadwgacaWG PbGaam4zaiaadIgacaWG0bWdamaaDaaaleaapeGaamyzaiaadIhaa8 aabaWdbiaadggaaaGcpaGaaGjbVlaacQcacaaMe8+dbmaawafabeWc paqaa8qacaWGLbGaamiEaaqab0WdaeaapeGaeyyeIuoaaOGaam4qai aadwgacaWGUbWdamaaDaaaleaapeGaamyzaiaadIhaa8aabaWdbiaa dggaaaGcpaGaaGjbVlabgkHiTiaaysW7caWGdbGaamyzaiaad6gape Gaamyqa8aadaqhaaWcbaWdbiaadwgacaWG4baapaqaa8qacaWGHbaa aaaa@68A2@

    where

    a MathType@MTEF@5@5@+= feaagKart1ev2aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaWcqaaaaaaaaa Wdbiaadggaaaa@3708@
    =
    Age going from 15 to 19 years;
    ex MathType@MTEF@5@5@+= feaagKart1ev2aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaamyzaiaadI haaaa@37DE@
    =
    Marital status or legal marital status for category x. The value of x representing persons either married, separated, divorced or widowed;
    P MathType@MTEF@5@5@+= feaagKart1ev2aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaamiuaaaa@36CC@
    =
    Postcensal population estimates derived from the components method given the marital status or legal marital status;
    M MathType@MTEF@5@5@+= feaagKart1ev2aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaamytaaaa@36C9@
    =
    Married persons;
    S MathType@MTEF@5@5@+= feaagKart1ev2aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaam4uaaaa@36CF@
    =
    Separated persons;
    CenA
    =
    Census counts adjusted for CNU.

    For people that are single, we sum the adjustment for the other statuses and we change the sign from negative to positive in order to maintain the coherence of the data by age and sex. In other words, the adjustment redistributes people from the other marital statuses and adds them to the count of single persons.

    Subsequently, this adjustment is applied to the census counts adjusted for CNU (CenA).

    Regardless of the adjustments performed, the coherence between the marital status estimates and those for legal marital status must be assured in order to obtain the censal estimates. The difference between marital status estimates and legal marital status estimates must always be inferior or equal to 0 for statuses other than married. This difference can be explained by the fact that persons living in common law are redistributed from their legal marital status in order to create the common-law category under marital status.

    The censal estimates by marital status and legal marital status are used to calculate the intercensal and postcensal estimates.

    9.6 Postcensal population estimates by marital status and legal marital status

    9.6.1 Estimation methods

    In order to estimate the postcensal population estimates by age, sex, marital status and legal marital status we need the censal estimates by age, sex, marital status and legal marital status (adjusted for CNU and a demographic adjustment for those aged 15 to 19 years) and the postcensal estimates by age and sex.

    The postcensal estimates by age and sex are distributed by marital status and legal marital status given the distribution of the censal estimates in the following way:

    Equation 9.8:      P t a, s, ml, m  =  C E α a, s, ml, m ∑ ml, m C E α a, s, ml, m  * PA S t a, s MathType@MTEF@5@5@+= feaagKart1ev2aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaamiuamaaDa aaleaacaWG0baabaGaamyyaiaacYcacaaMc8Uaam4CaiaacYcacaaM c8UaamyBaiaadYgacaGGSaGaaGPaVlaad2gaaaGccaaMe8Uaeyypa0 JaaGjbVpaalaaabaGaam4qaiaadweadaqhaaWcbaGaeqySdegabaGa amyyaiaacYcacaaMc8Uaam4CaiaacYcacaaMc8UaamyBaiaadYgaca GGSaGaaGPaVlaad2gaaaaakeaadaaeqbqaaiaadoeacaWGfbWaa0ba aSqaaiabeg7aHbqaaiaadggacaGGSaGaaGPaVlaadohacaGGSaGaaG PaVlaad2gacaWGSbGaaiilaiaaykW7caWGTbaaaaqaaiaad2gacaWG SbGaaiilaiaaykW7caWGTbaabeqdcqGHris5aaaakiaaysW7caGGQa GaaGjbVlaadcfacaWGbbGaam4uamaaDaaaleaacaWG0baabaGaamyy aiaacYcacaaMc8Uaam4Caaaaaaa@77CA@

    If the denominator is null for age a, we will use age a-1.

    where

    P t a, s, ml, m MathType@MTEF@5@5@+= feaagKart1ev2aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaamiuamaaDa aaleaacaWG0baabaGaamyyaiaacYcacaaMc8Uaam4CaiaacYcacaaM c8UaamyBaiaadYgacaGGSaGaaGPaVlaad2gaaaaaaa@4356@
    =
    Postcensal estimates on July 1 of year t, for age a, sex s, legal marital status ml and marital status m;
    C E α a, s, ml, m MathType@MTEF@5@5@+= feaagKart1ev2aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaam4qaiaadw eadaqhaaWcbaGaeqySdegabaGaamyyaiaacYcacaaMc8Uaam4Caiaa cYcacaaMc8UaamyBaiaadYgacaGGSaGaaGPaVlaad2gaaaaaaa@44B9@
    =
    Censal estimates on date α MathType@MTEF@5@5@+= feaagKart1ev2aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaeqySdegaaa@3796@  for age a, sex s, legal marital status ml and marital status m;
    PA S t a, s MathType@MTEF@5@5@+= feaagKart1ev2aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaamiuaiaadg eacaWGtbWaa0baaSqaaiaadshaaeaacaWGHbGaaiilaiaaykW7caWG Zbaaaaaa@3DA9@
    =
    Postcensal estimate on July 1 of year t, for age a and sex s.

    The possible combinations of legal marital status by marital status are:

    Table summary
    This table displays the results of The possible combinations of legal marital status by marital status. The information is grouped by Legal marital status (appearing as row headers) and Marital status (appearing as column headers).
    Legal marital status Marital status
    Single Single
    Single and living in common law
    Married Married
    Separated Separated
    Separated and living in common law
    Widowed Widowed
    Widowed and living in common law
    Divorced Divorced
    Divorced and living in common law

    We can derive two series of population estimates, one by marital status and the other by legal marital status. People living in common law are derived by finding the sum of people living in common law in each of the categories. As is done with censal population estimates, we must be sure to maintain coherence between the two series.

    9.6.2 Levels of estimate

    As was previously mentioned, the components method is no longer used to produce population estimates by marital status. Rather, these estimates are based on the marital status proportions taken from the Census and the population estimates by age and sex, which in turn were produced using the components method. Therefore, the difference between the preliminary and final postcensal population estimates by marital status or legal marital status can be found in the revision level of the components that were used to estimate the population by age and sex. If all the components are preliminary, we obtain preliminary postcensal estimates (PP). If they are all final components, the estimates become final postcensal (PD). For any other combination, we have updated postcensal estimates (PR).

    9.7 Intercensal population estimates by marital status and legal marital status

    The production of intercensal estimates by age and sex is done by distributing the error of closure across age and sex cohorts. For a description on the calculation and distribution of the error of closure, see Chapter 1.

    Adjusted census distributions by age, sex, marital status and legal marital status from the two most recent censuses are used to derive intercensal estimates of population by marital status and legal marital status. The census distributions are linearly interpolated to obtain the required series of distributions. The interpolated distributions are then applied to the intercensal population estimates by age and sex to obtain estimates by age, sex, marital status and legal marital status.

    The calculations are as follows:

    Equation 9.9:      I P t a,s,ml,m  = [ C E α a,s,ml,m ∑ ml,m C E α a,s,ml,m  + ( t−α β−α ) × ( C E β a,s,ml,m ∑ ml,m C E β a,s,ml,m  −  C E α a,s,ml,m ∑ ml,m C E α a,s,ml,m ) ] × I P t a,s MathType@MTEF@5@5@+= feaagKart1ev2aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaamysaiaadc fadaqhaaWcbaGaamiDaaqaaiaadggacaGGSaGaam4CaiaacYcacaWG TbGaamiBaiaacYcacaWGTbaaaOGaaGjbVlabg2da9iaaysW7daWada qaamaalaaabaGaam4qaiaadweadaqhaaWcbaGaeqySdegabaGaamyy aiaacYcacaWGZbGaaiilaiaad2gacaWGSbGaaiilaiaad2gaaaaake aadaaeqbqaaiaadoeacaWGfbWaa0baaSqaaiabeg7aHbqaaiaadgga caGGSaGaam4CaiaacYcacaWGTbGaamiBaiaacYcacaWGTbaaaaqaai aad2gacaWGSbGaaiilaiaad2gaaeqaniabggHiLdaaaOGaaGjbVlab gUcaRiaaysW7daqadaqaamaalaaabaGaamiDaiabgkHiTiabeg7aHb qaaiabek7aIjabgkHiTiabeg7aHbaaaiaawIcacaGLPaaacaaMe8Ua ey41aqRaaGjbVpaabmaabaWaaSaaaeaacaWGdbGaamyramaaDaaale aacqaHYoGyaeaacaWGHbGaaiilaiaadohacaGGSaGaamyBaiaadYga caGGSaGaamyBaaaaaOqaamaaqafabaGaam4qaiaadweadaqhaaWcba GaeqOSdigabaGaamyyaiaacYcacaWGZbGaaiilaiaad2gacaWGSbGa aiilaiaad2gaaaaabaGaamyBaiaadYgacaGGSaGaamyBaaqab0Gaey yeIuoaaaGccaaMe8UaeyOeI0IaaGjbVpaalaaabaGaam4qaiaadwea daqhaaWcbaGaeqySdegabaGaamyyaiaacYcacaWGZbGaaiilaiaad2 gacaWGSbGaaiilaiaad2gaaaaakeaadaaeqbqaaiaadoeacaWGfbWa a0baaSqaaiabeg7aHbqaaiaadggacaGGSaGaam4CaiaacYcacaWGTb GaamiBaiaacYcacaWGTbaaaaqaaiaad2gacaWGSbGaaiilaiaad2ga aeqaniabggHiLdaaaaGccaGLOaGaayzkaaaacaGLBbGaayzxaaGaaG jbVlabgEna0kaaysW7caWGjbGaamiuamaaDaaaleaacaWG0baabaGa amyyaiaacYcacaWGZbaaaaaa@B63C@

    where

    I P t a,s,ml,m MathType@MTEF@5@5@+= feaagKart1ev2aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaamysaiaadc fadaqhaaWcbaGaamiDaaqaaiaadggacaGGSaGaam4CaiaacYcacaWG TbGaamiBaiaacYcacaWGTbaaaaaa@3F83@
    =
    Intercensal population estimates at date t for age a, sex s, legal marital status ml and marital status m;
    C E α a,s,ml,m MathType@MTEF@5@5@+= feaagKart1ev2aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaam4qaiaadw eadaqhaaWcbaGaeqySdegabaGaamyyaiaacYcacaWGZbGaaiilaiaa d2gacaWGSbGaaiilaiaad2gaaaaaaa@4018@
    =
    Censal population estimates at date α MathType@MTEF@5@5@+= feaagKart1ev2aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaeqySdegaaa@3796@  for age a, sex s, legal marital status ml and marital status m;
    C E β a,s,ml,m MathType@MTEF@5@5@+= feaagKart1ev2aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaam4qaiaadw eadaqhaaWcbaGaeqOSdigabaGaamyyaiaacYcacaWGZbGaaiilaiaa d2gacaWGSbGaaiilaiaad2gaaaaaaa@401A@
    =
    Censal population estimates at date β MathType@MTEF@5@5@+= feaagKart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaeqOSdigaaa@3797@  for age a, sex s, legal marital status ml and marital status m;
    α MathType@MTEF@5@5@+= feaagKart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaeqySdegaaa@3795@
    =
    Date for the first census (Census at the beginning of the period);
    β MathType@MTEF@5@5@+= feaagKart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaeqOSdigaaa@3797@
    =
    Date for the second census (Census at the end of the period);
    t MathType@MTEF@5@5@+= feaagKart1ev2aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaamiDaaaa@36F0@
    =
    Date of the intercensal estimate on July 1 of year t;
    I P t a,s MathType@MTEF@5@5@+= feaagKart1ev2aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaamysaiaadc fadaqhaaWcbaGaamiDaaqaaiaadggacaGGSaGaam4Caaaaaaa@3B4E@
    =
    Intercensal population estimate on July 1 of year t, for age a and sex s.

    We can derive two series of population estimates, one by marital status and the other by legal marital status. People living in common law are derived by finding the sum of people living in common law in each of the categories. As is done with postcensal population estimates, we must be sure to maintain coherence between the two series.

    Notes

    Date modified: