Census Population Coverage Error: Results and Methods 

Colleen Clark 

Statistics Canada, Social Survey Methods Division, 

Census Coverage Studies Section, 120 Parkdale Avenue, Ottawa, Ontraio, Canada, K1S 2A3, 

Colleen.Clark@statcan.gc.ca

Keywords: Coverage error; census data quality; census coverage error; population estimates; 

undercoverage; undercount; census undercoverage; census undercount; overcoverage, overcount; census 

overcoverage; census overcount; coverage rates, record linkage; data quality 

1. Introduction

The 2006 Canadian Census of Population required the participation of the entire population of Canada, 

some 32.5 million people distributed over a territory of 9 million square kilometres. Although there are 

high quality standards governing the collection and processing of the data, it is not possible to eliminate all 

errors. Coverage errors are one of the most important types of error since they affect not only the accuracy 

of the counts of the various census universes, but also the accuracy of all of the census data describing the 

characteristics of these universes. There are two types of population coverage error. Population 

undercoverage refers to the error of the census excluding someone who should have been enumerated. 

Population overcoverage refers to the error of the census either enumerating someone more than once or 

including someone who should not have been enumerated. The latter is negligible in the Canadian context. 

The net impact of undercoverage and overcoverage on the size of a population of interest is known as 

population net undercoverage. Undercoverage is usually larger than overcoverage. 

Estimates of coverage error are produced only for the census population universe. Chart 1 gives the 

population undercoverage rate for the 1971 Census through to the 2006 Census, the population 

overcoverage rate and the population net undercoverage rate for the 1991 Census through to the 2006 

Census. As the chart shows, population coverage error is a growing data quality concern. Undercoverage, 

now at 4.26% for the 2006 Census, has more than doubled since 1981when it was 2.01%. Population 

overcoverage was first measured for the 1991 Census. Although overcoverage is the smaller coverage 

error, it has doubled since 1996. 

 Chart 1: 1971 Census to 2006 Census 

rates of population coverage error for Canada 

0.00

1.00

2.00

3.00

4.00

5.00

Census Year

Rate of 

population 

coverage error 

(%)

Undercoverage 1.93 2.04 2.01 3.19 3.43 3.18 3.95 4.26

Overcoverage 0.56 0.74 0.96 1.59

Net Undercoverage 2.87 2.44 2.99 2.67

1971 1976 1981 1986 1991 1996 2001 2006

Notes:

1. Blank cells indicate data not available.
2. Overcoverage was first measured for the 1991 Census. The increase from 1991 to 1996 is due in part 

to a change in methodology. 

Source: Statistics Canada, 1971 to 2006 Census Coverage Studies 

There are two post-censal studies that measured 2006 Census population coverage error. The Reverse 

Record Check (RRC) estimated population undercoverage while the Census Overcoverage Study (COS) 

estimated population overcoverage. The Dwelling Classification Survey (DCS), carried out during census 

processing, addresses coverage error from non-response dwellings and occupied dwellings classified in 

error as unoccupied. Census data are adjusted for this type of coverage error. Census data are not adjusted 

for population net undercoverage. Rather, estimates of net undercoverage are used in the production of the 

base population for Statistics Canada’s demographic estimates of population. Population estimates are 

used for calibration in many surveys such as the Canadian Labour Force Survey. Preliminary estimates of 

2006 Census population coverage error were released March 27, 2008. Because estimates of population net 

undercoverage directly impact transfer payments from the federal government to the provincial and 

territorial governments, a lengthy and detailed certification exercise with the provincial and territorial 

statistical focal points was carried out over the following four months. Some changes were subsequently 

made to the methodology for non-response adjustment in the RRC to arrive at the final estimates released 

on September 29, 2008. . 

This paper presents selected results and methodologies from the 2006 Census coverage studies. Section 2 

gives an overview of the 2006 Census methodology, lists some of the sources of coverage error and defines 

the measures used to quantify coverage error. An overview of the methodology of the RRC and the COS is 

in section 4. Section 5 presents census collation undercoverage, a new measure introduced for the 2006 

Census. Section 6 gives some concluding remarks. 

2. Coverage Error 

2.1 2006 Census Methodology 

Overall, the 2006 Census of Population moved from a decentralized, manual operation to a more 

centralized and automated one: Questionnaires were mailed by Canada Post Corporation in a majority of 

urban areas; the Address Register, which is updated by listing operations, provided the mailing addresses; 

and item non-response follow-up became centralized. Further, in some regions it was difficult to recruit 

enough staff. 

In the 2006 Census, about 98% of households were enumerated via self-enumeration. For the 70% of 

dwellings located in Mail Out areas Canada Post delivered a census questionnaire. In the List Leave areas, 

covering 28% of the dwellings, households received their questionnaire from an enumerator. The 

canvasser method, whereby a census enumerator visited a household and completed a questionnaire, was 

used for remote and northern areas of the country, on most Indian reserves, and in large urban downtown 

areas where there was a concentration of transient residents. For the first time, the 2006 Census offered all 

households in Canada the option of completing their questionnaire online. Approximately 18% of 

households responded via the Internet. 

As part of census processing, hot deck imputation was carried out to account for persons living in nonresponse dwellings and occupied dwellings classified in error as unoccupied. This procedure increased the 

number of occupied dwellings by 3.6% and decreased the number of unoccupied dwellings by 5.2%. 

Further, 70.9% of all dwellings classified as non-response were actually occupied. Imputation added 

571,521 persons to the census database, 1.81% of the census count of population. Compared to the 2001 

Census, a large increase in both the number of non-response dwellings and the number of misclassified 

dwellings resulted in doubling the number of persons imputed. 

2.2 Sources 

Coverage error reflects error on the part of the respondent and on the part of census operations. 

Undercoverage can occur in the first stage of the census if the list of dwellings constructed to cover the 

census dwelling universe is incomplete. Dwellings that have just been built are particularly difficult to list. 

Depending on the date that they are completed and the timing of the census frame update, there is a risk 
that a new dwelling may not be included in the census frame thereby contributing to undercoverage. 

Coverage errors can also be introduced during the processing stage when records for persons or households 

are erroneously created or cancelled. 

Coverage error is most likely to have occurred during the field collection stage. A respondent can 

erroneously omit someone whose usual place of residence, according to the census rules, is the dwelling. 

This is undercoverage. Conversely, a respondent can erroneously include someone whose usual place of 

residence is elsewhere. Overcoverage occurs if that person is listed at their usual residence or elsewhere. 

Examples of overcoverage include: (i) children whose parents have separate residences and each parent 

includes the children on their census form, (ii) persons who need to reside away from their family for 

reasons of work who are listed on their family’s form and also on the form for the dwelling they live in 

while working, and (iii) students away at school who are listed both by their roommates and their parents. 

These living arrangements may also result in undercoverage. Although efforts are made to enumerate 

homeless persons, the risk of undercoverage is higher for this population. As for many surveys, reduced 

respondent participation continues to be an issue for the census. This is evidenced by both increased nonresponse and increased undercoverage. 

 

An individual’s usual place of residence refers to the dwelling in which, as of May 16, 2006, a person lives 

most of the time. In most cases, it is easy to determine someone’s usual place of residence. However, 

there are a number of situations where the process is not elementary and special rules have been created in 

order to define an individual’s usual place of residence. Although the rules are set out in the census form, 

the list is long and there may be comprehension challenges for some respondents. 

2.3 Definitions 

If T is the true number of persons in the census target population and C is the published census count of 

the number of persons in the census target population, then the error in using C instead of T is 

N  T  C . This error, denoted as N , is net population coverage error. If U is population 

undercoverage denoting the number of persons not included in C who should have been, and O is 

population overcoverage denoting is the number of persons included in C who should not have been, then 

an estimate of T is given by Tˆ  C  Nˆ  C Uˆ  Oˆ

. Since undercoverage is more common than 

overcoverage, net population coverage error is stated as net undercoverage. Let us assume that 

overcoverage from persons included in C that are not in the census target population is zero (Empirical 

evidence from past coverage studies have shown this number to be very small.). Therefore, Oˆ

 is restricted 

to an estimate of the number of excess enumerations, usually duplicates. Census population coverage error 

Uˆ Uˆ

can be usefully expressed as rates relative to the true population: Rˆ

U  100 *  100 * , 

Tˆ C  Nˆ

Oˆ Oˆ Nˆ Uˆ

Rˆ

 Oˆ 

O  100 *  100 * , and Rˆ

N  100 *  100 * . A positive net ˆ ˆ  T C  Nˆ  T  C  Nˆ



undercoverage rate indicates than undercoverage is larger than overcoverage; there are more people not 

included in the published census count C than there are excess enumerations. This has been, and 

continues to be, the experience of the Canadian census. For some domains of interest, however, there is net 

overcoverage where the number of persons missed is smaller than the number of excess enumerations. It is 

the goal of the census coverage studies to estimateU , O and N , the corresponding rates, and the standard 

errors of these estimates for a variety of geographic and demographic characteristics; most notably for each 

province and territory. 

3. Estimates 

Compared to the 2001 Census, coverage error has increased. The rate of undercoverage increased from 

3.95% (with a standard error (s.e.) of 0.13) to 4.26% (s.e. 0.17), and the rate of overcoverage increased 
notably from 0.96% (s.e. 0.05) to 1.59 (s.e. 0.01). Since the overcoverage rate increased more than the 

undercoverage rate, the estimated net undercoverage rate decreased from 2.99% (s.e. 0.14) in 2001 to 

2.67% (s.e. 0.17). It has been important to stress with users that even though net undercoverage is down, 

coverage error has increased because both undercoverage and overcoverage has increased. Even though 

there are high quality standards governing all census operations, changes in census methodology from 2001 

to 2006 may have a role in these increases. 

Chart 2 shows rates of population undercoverage by age and sex for Canada for the 1971 Census through to 

the 2006 Census. The demographic trends observed in 2006 continue historical trends. A profile of the 

person most likely to have been counted as undercoverage in the 2006 Census emerges from crosstabulations as male, between 18 and 34 years of age, and single. Mother tongue other than English or 

French (immigrants from non-English/non-French countries) is also important. The rate of undercoverage 

for men was almost twice the rate for women, 5.51% (s.e. 0.26) versus 3.04% (s.e. 0.23). For both men and 

women, undercoverage was highest for young adults aged 18 to 34. Among young adult males, 

undercoverage was over 10% for the 18-19 age group at 10.06% (s.e. 2.45), the 20 to 24 age group at 

12.21% (s.e. 1.12), and the 25 to 34 age group at 11.42% (s.e. 0.86). High undercoverage is also related to 

marital status, highest for single persons and separated persons.1

. 

Chart 2: 1971 Census to 2006 Census rate of population undercoverage 

by age and sex for Canada 

0.00

2.00

4.00

6.00

8.00

10.00

12.00

14.00

Census Year

Census Population 

Undercoverage Rate 

(%)

Males 2.27 2.46 2.37 3.75 3.95 3.89 4.90 5.51

Females 1.59 1.61 1.65 2.68 2.93 2.49 3.02 3.04

Males 20-24 4.97 5.99 6.03 10.36 8.98 6.48 11.68 12.21

Females 20 - 24 4.01 4.62 4.98 6.89 7.36 6.45 7.91 8.71

1971 1976 1981 1986 1991 1996 2001 2006

Source: Statistics Canada, 1971 Census to 2006 Census coverage studies. 

There are some demographic trends in overcoverage. Across the provinces and territories, overcoverage 

varied much less than undercoverage did. Overcoverage was only slightly higher for males than females, 

1.62% (s.e. 0.02) versus 1.56% (s.e. 0.01). Overcoverage is highest for children and young adults from age 

5 to 34 with the exception of the youngest children. The rate for those 0-4, 1.35% (s.e. 0.07), is similar to 

the rates for the 35+ group. Rates are highest for young adults aged 20-24 at 2.88% (s.e. 0.11). 

Considering marital status, overcoverage was high for single persons 

In order to route clerical flow during the 2006 COS, a code was developed classifying the type of 

overcoverage. Households who moved around Census Day and were enumerated at two addresses 

accounted for 20% of the persons who were involved in multiple enumerations. Another 20% was from 

identical households who were either at the same address or very close such as next door. This outcome 

may indicate a problem in census operations. The next largest group was children whose parents do not 

live in the same household who are listed once with each parent. These persons accounted for 16.9% of 

overcoverage. Another 12% is for students or young adults newly away from home, and 11% is for 

 

1

Single persons are those who report that they are not legally married and are not in a common-law relationship.
persons in two dwellings where the members of the first are a subset of the members of the second 

household. This is the first time that such data were available for analyzing overcoverage. Since 

classification of overcoverage cases was done on a trial basis and designed for work flow, the data only 

provide some trend information. However, it is reassuring to see that the data, except for a small number of 

cases where there was not enough data, easily fit the coding scheme, and, that overcoverage is coming from 

the types of living situations we had expected. 

4. Methodology 

The 2006 Census coverage studies differ from the 2001 Census coverage studies. This was the first time 

that the names of persons listed on all of the census forms were available electronically on the census 

response database (RDB). This greatly increased the efficiency of coverage studies since matching could 

include the name and not be restricted to just demographic characteristics. Indeed, the measurement of 

overcoverage was undertaken by a new study, the Census Overcoverage Study, specifically designed to 

exploit the use of an individual’s name for identifying overcoverage. 

4.1 Reverse Record Check 

Canada is divided into 10 provinces and 3 territories. The territories are the sparsely-populated northern 

regions. In the Revere Record Check (RRC), a random sample of individuals representing the 2006 Census 

target population was taken from frames independent of the census. For the provinces, this consisted of a 

list of persons enumerated in the 2001 Census, a sample of persons missed in the 2001 Census, a list of 

intercensal births from provincial birth registries, and, from to federal administrative data, a list of 

intercensal immigrants and a list of persons who are not Canadian citizens but have a permit to temporarily 

reside in Canada such as students, workers, and refugee claimants. The frame for each territory is the 

territorial health care file. The 2006 RRC sample consisted of 67,813 persons in the provinces and 86,460 

persons in the territories. 2

 

In 2001, the RRC measured both undercoverage and a component of overcoverage. The introduction of the 

COS meant that the RRC no longer needed to measure any overcoverage. The RRC methodology was 

consequently changed so that not all cases were sent for field collection thereby significantly reducing field 

costs. The first step after selecting the sample was to search the RDB data from the survey frame and 

various update sources such as taxation data. If the search resulted in locating the selected person on the 

RDB, collection was not required. The exception was a sample of those that had been found. This sample 

was used to estimate some parameters of the non-response adjustment model. 

When the selected person was not found, a telephone interview via computer-assisted telephone 

interviewing (CATI) out of the regional offices (ROs) was conducted to collect further information to 

declare the individual as in scope or not in scope for the census, and when in scope, to provide further data 

for searching. Including the sample for the non-response adjustment model, an interview was achieved for 

84.2% of the 20,114 cases sent to the ROs. 

Estimates of population undercoverage are based on persons in the RRC sample who were classified 

‘Missed’. These persons have been found to be in scope for the 2006 Census but no evidence of 

enumeration in the 2006 Census could be found in the Response Database. Nationally, there were 5,431 

Missed sampled persons in the provinces and 676 Missed sampled persons in the territories On a weighted 

basis, the Missed represented 8.28% of the national sample Following classification of each person in the 

sample as Enumerated, Missed, or Out of Scope3

, design weights were adjusted to account for nonresponse whereby the total design weight of the non-respondents was shared among a group of respondents 

 

2

The large sample size in the territories is because a different methodology is used. The sample frames were first 

matched to the entire census database. Matches were classified as Enumerated if they were found in the same territory 

or out of scope if they were found elsewhere. All of the matched persons from the sample frames were included in the 

RRC sample with a weight of one. An additional sample was selected from the non-matches. 

3 A detailed classification of 12 codes was used to code both the results of searching and the groupings required for the 

non-response adjustment model. 
most like the non-respondents in their propensity to respond, a characteristic highly correlated with the 

probability of being classified Missed. 

It should be noted that the RRC used an early version of the Response Database. Consequently, there are 

some persons classified as Missed who are included in the final census database. Some enumerations were 

deemed too incomplete, usually invalid name date, to be used by the RRC (RRC Incomplete 

Enumerations). The sampled person’s Census Day Address may point to a dwelling that contains imputed 

enumerations. Last, there were some enumerations added to the census database after the data were 

extracted to create the RRC database. The size of these groups is shown in Table 4. 

Table 1 shows the number of persons sent for CATI collection and the number for whom collection was 

completed. Overall, 84.2% of the sample sent for collection resulted in an interview. Table 2 gives the 

Frame Sent Completed

% 

completed

2001 Census 12,680 10,943 86.3

Missed 1,456 1,204 82.7

Births 802 708 88.3

Immigrants 1,473 1,171 79.5

NPR 1,485 957 64.4

Health Care Files 2,218 1,961 88.4

Total 20,114 16,944 84.2

Source: Statistics Canada, 2006 Reverse Record Check.

Table 1: 2006 RRC Completion counts by sampling 

frame for Canada

Provinces 

Territories

unweighted distribution of the RRC sample by 

classification. ‘Listed’ and ‘Mobile’ are process 

metadata used for forming the weight adjustment 

groups for non-response adjustment. Listed means 

that the sampled person could be classified without 

resort to collection data. Mobile means that the 

sampled person’s Census Day Address was an 

address uniquely supplied by collection. Note that 

non-response refers to having sufficient date from 

all sources, of which one may be collection, to 

classify the sampled person as either Enumerated, 

Missed, or Out of Scope. Despite the field 

completion rate of 84.2%, data from other sources 

meant that there was sufficient information to 

assign one of these classifications to 98.0% of the 

sample. 

Classification

Number of 

persons % of sample 

Enumerated 141,782 91.90

Listed1

141,333 91.61

Not listed 449 0.29

Missed 6,107 3.96

Listed 745 0.48

Not listed mobile 1,847 1.20

Not listed not mobile 3,515 2.28

Out of Scope 6,384 4.14

Listed 2,485 1.61

Not listed 783 0.51

Non-response 3,116 2.02

Total 154,273 100

1

Includes 84,980 for the territories sample.

Source: Statistics Canada, 2006 Reverse Record Check

Table 2: 2006 RRC sample classification for 

Canada 

4.2 Census Overcoverage Study (COS) 

Table 3 gives the components of the 2006 Census 

estimate of population overcoverage for Canada 

Overcoverage is measured in two steps. Step 1 used 

exact matching to identify overcoverage. Step 2 used 

probabilistic record linkage with the aid of Statistics

Canada’s Generalized Record Linkage System 

(GRLS). In Step 1 the 2006 Census database is 

matched to a partial list of persons who should have 

been enumerated constructed from administrative data 

sources, mostly taxation files. This list had high 

coverage and had been, where possible, unduplicated. 

Exact matching was done using name (treated), sex, 

and birth date: 64.68% of the RDB resulted in a 1:1 

match, 1.76% M:1. 0.05% M:M, and 33.25% resulted 

in no match indicating undercoverage (known) in the 

admin files. Records from the RDB who matched to 

more than one record on the admin files were 

automatically declared as overcoverage with a weight 

of one. Clerical review of a sample of matches 

revealed that a modest number of them were false matches from persons who were clearly different. 

Estimates were subsequently adjusted. 

Step 2 matched the RDB Step 1 non-matches to the entire RDB using probabilistic record linkage. GRLS 

identified matches that were close but not exact. Each match was assigned a weight indicating the 

‘closeness’ of the pair. Matches above a specified threshold were, as for Step 1, automatically declared 

overcoverage. Matches below a second specified threshold were automatically declared as not being 
Estimated number of persons 

with multiple enumerations 270,824

Standard error 955

Step 2 overcoverage 

above upper 

Number of persons with 

multiple enumerations 55,423

Estimated number of persons 

with multiple enumerations 180,523

Standard error 3,001

Estimated number of persons 

with multiple enumerations 506,770

Standard error 3,001

Estimated number of persons 

with multiple enumerations 515,715

Standard error 3,207

Source: Statistics Canada, 2006 Census Overcoverage Study,

Final estimate of 

overcoverage 

(applying AMS 

adjustment.)

Table 3: Components of 2006 Census estimate of population 

overcoverage for Canada

Step 1 overcoverage

Step 2 overcoverage 

between thresholds

Total COS 

overcoverage

overcoverage. Between the two 

thresholds, a sample was taken. 

These pairs of potential 

duplicates were clerically 

reviewed using names and 

various demographic 

characteristics including 

household composition in order 

to determine whether or not 

overcoverage had occurred. As 

part of evaluating the COS, an 

independent study was conducted 

to measure overcoverage. The 

2006 Automated Match Study 

repeats a methodology carried out 

since overcoverage was first 

measured for the 1991 Census. 

Comparison of COS cases and 

AMS cases revealed that that 

some types of overcoverage were 

not included in the AMS. COS estimates were adjusted using the AMS estimates for the overcoverage not 

covered by the COS. Table 3 gives the amount of overcoverage identified in Step 1, in Step 2 from pairs 

above the threshold and pairs between the thresholds, the total COS overcoverage, and the adjusted COS 

estimates. 

Component 

Number of 

perons

MHAT: Missed from RRC 2,846,000 

X: Netted out factor 1,462,000

 for imputed persons 933,000 

 for late enumerations 106,000 

 for RRC Incomplete Enumerations 423,000 

UHAT = MHAT - X 1,384,000 

OHAT: Overcoverage from COS 516,000 

NHAT = UHAT – OHAT 869,000 

C 31,613,000 

C + NHAT 32,482,000 

Table 4: Components of Estimated Population 

Coverage Error for Canada

Source: Statistics Canada, 2006 Census Coverage 

Studies.

4.3 Estimation 

Table 4 gives the components of the estimated 

population coverage error for Canada. The 

estimate of population undercoverage, Uˆ

, is 

constructed from the results of the RRC and 

census data as follows Let Mˆ

 = estimate of the 

number of persons in the RRC target population 

determined to be in the 2006 Census target 

population who have not been enumerated. Mˆ

is the sum of the final weights of persons 

classified as Missed. Let X = number of 

persons included in C that cannot be identified 

in the RRC as enumerated such as persons 

whose Census Day Address is a dwelling for 

which imputation was done during census 

processing. ThenUˆ  Mˆ  X . At the national 

level, X was about half of Mˆ

. This is a notable increase from 2001 when X , identified as the netted 

out factor in Table 5, was only about a third of Mˆ

. The increase is due to an increase in both the number 

of non-response dwellings and the number of misclassified dwellings that resulted in doubling the number 

of persons imputed. 
5. Persons not enumerated 

Each census count C is composed of two elements: C  E  I where E  the number of 

enumerations (This is the number of people who were listed on all census forms.4

), and I  the number of 

imputed persons. This is an estimate of the number of persons missed in non-response dwellings and/ or 

misclassified occupied dwellings. Undercoverage, therefore, is a subset of all persons who were not listed 

on a census form but should have been. It does not include those were not enumerated either because no 

completed census form was returned for the dwelling (non- response dwelling) or the dwelling did not 

receive a form because they were erroneously classified as unoccupied (misclassified occupied dwelling). 

An estimate of the true number of persons in the census target population T is given by 

Tˆ  C  Nˆ  C Uˆ  Oˆ  E  I Uˆ  Oˆ. This formulation of Tˆ has three components: 

 

1. E = the number of number of persons who were listed on a census form; 

2. Oˆ

 = an estimate of the number of excess enumerations5; and 

3. I Uˆ

 = an estimate of the number of persons who were not listed on a census form who should have 

been. 

 

The last component,I Uˆ , estimates the number of persons missed in the census for any reason.

6

 Let us 

define I Uˆ  as census population collection undercoverage, denoted by A. The estimate of census 

population collection undercoverage is Aˆ  I Uˆ  and the corresponding estimate of the rate of census 

ˆ 

ˆ

A I Uˆ 

population collection undercoverage rate, R is: Rˆ  100 *  100 * 

A A

. Since net census  Tˆ ˆ 

 C  N 

collection undercoverage can be defined by subtracting overcoverage Oˆ

 from Aˆ., 

Tˆ  C  Nˆ  E  I Uˆ  Oˆ  E  Aˆ  Oˆ. Although net collection undercoverage cannot be 

applied to census counts to adjust for coverage error, Aˆ

 and Rˆ

A

 provides a broader picture of how well 

the census was able to enumerate its target population. Since there may be bias introduced whenever the 

data of one household is copied to represent the data of another household, as is done in WHI, collection 

undercoverage also provides analysts with a baseline and another measure of census data quality. 

Collection undercoverage was introduced for the 2006 dissemination of estimates of census coverage error. 

It has been well received by those concerned with census operations as ‘comprehensive’ and ‘clarifying’ 

and by those using census data as ‘quantifying a new element of data quality.’ The national 2006 Census 

net collection undercoverage rate was estimated to be 7.13%. This means that the 2006 Census achieved an 

enumeration, consisting of being listed on a census form only once, for 92.87% of its target population. 

This compares to 95.74% of the target population included in the 2006 Census count of 31,612,897 

persons. The difference between the two rates is that persons living in non- response dwellings and persons 

living in occupied dwellings erroneously classified as unoccupied are included in the former (100 - net 

collection undercoverage rate) but not the latter (100 - net undercoverage rate) . The 2001 Census 

achieved an enumeration for 94.17% of its target population compared to 97.57% of the target population 

included in the 2001 Census count of 30,007,094 persons. Since net undercoverage diminished from 2001 

 

4

It is possible that some of the persons listed on the form may not appear in the final census database. So, in the 

strictest sense, ‘enumeration’ is used here to represent persons listed on the form who appear in the final census 

database. 

5 Cases of overcoverage usually involve duplicate enumerations where one person is listed on firms for two different 

dwellings. There are a very small number of cases where someone is listed more than twice. 

6

The distinction is in the interpretation of the word ‘missed’. When speaking of undercoverage, ‘missed’ specifically 

excludes those not listed on a form who should been who were imputed for. 
to 2006, 2.99% to 2.67%, the decrease in the census net collection undercoverage rate is due to the increase 

in the number of non-response dwellings and misclassified occupied dwellings. 

6. Conclusion 

Census population coverage error increased from 2001 to 2006. Undercoverage, collection undercoverage 

and overcoverage all increased notably. There is evidence that some part of the overcoverage may be from 

census operations. The 2006 Census coverage studies implemented a number of important improvements 

resulting in measures of coverage error that are less biased and more precise. The new methodology for 

measuring overcoverage was successful while revealing a number of areas for improvement for 2011. 

Limiting the RRC to just the measurement of undercoverage reduced the need for collection and thereby 

the cost. Respondent and interviewer burden were reduced by focusing collection on cases more likely to 

have be classified Missed. 

The methodology of the 2011 Census implements collection by waves, a new process for identifying 

unoccupied dwellings, and a new field management system. Online collection will be offered in more 

areas and the take up is expected to be larger. There is a risk of reducing net undercoverage in the 2011 

Census, not from increasing overcoverage but from increasing non-response. Net undercoverage for one 

province, for example, in the 2006 Census was, at 0.8%, close to zero because of high non-response and 

misclassified occupied dwellings. Steps are being taken in the 2011 Census to address the misclassification 

of occupied dwellings as unoccupied. Work has already begun on the 2011 coverage studies. Major 

changes in methodology are not planned. One area of consideration is to include household characteristics 

in COS matching. In the RRC, there is potential to increase the use of administrative data to further reduce 

the need for collection.