Income Research Paper Series
Exploring the reach of the Canada child benefit: Two coverage rate monitoring strategies

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Summary

A prerequisite for the eligibility and receipt of Canada’s many social benefit programs is participation in the tax system. Each year, as many as 1 in 10 Canadians do not file their taxes in a timely fashion and as a result miss out – at least temporarily – on benefits to which they could be entitled. The Canada child benefit (CCB), which replaced the Canada child tax benefit (CCTB) in July 2016, is a means-tested tax-free monthly government benefit program available to families with a registered child. This study looks at the CCB coverage using two coverage rate monitoring strategies. It supports ongoing work across several federal agencies to examine the reach of the tax and benefit system. This paper concludes that contrasting approaches to monitoring coverage rates provides important lessons for understanding the coverage of the CCB.

Introduction

Since 2016, important progress has been made to ensure hard-to-reach households are receiving the full benefits to which they are entitled. With as many as 1 in 10 Canadians not filing (Office of the Auditor General of Canada, 2022), there are still benefits being unclaimed or claimed quite late. The Canada child benefit (CCB)^Note  is one example. Despite potentially incomplete coverage, the CCB was attributed with lifting 782,000 children out of poverty between 2015 and 2020 (ESDC, 2022). To ensure existing programs, such as the CCB, are having the full impact for which they were designed, this paper monitors coverage of the CCB.

Two approaches that could be used to monitor the CCB program are the “participation rate approach” and the “take-up rate approach”.^Note  The first, the participation rate approach, used elsewhere at Statistics Canada, measures the proportion of the participating or ‘eligible’ families, such as immigrants receiving the benefit divided by the total population of immigrants living in Canada. The Canada Revenue Agency (CRA) uses a similar approach for the Indigenous populations living on and off reserves. The participation rate in these two cases is used to investigate specific sub-populations’ participation in the program.

The second approach, recommended by Employment and Social Development Canada’s (ESDC) Chief Data Office, is the take-up rate. This is defined as the ratio of the total number of beneficiaries who are in receipt of a benefit to the total number of individuals eligible for that benefit. Beneficiaries are defined as a parent that has received at least one CCB payment. This is used to estimate the total amount of benefit being left unclaimed. One limitation of this approach is that it ignores individuals who are considered ineligible.

This paper addresses this limitation by using, a third approach, the “population coverage rate approach” with children as the unit of analysis. This differs from previous approaches by incorporating both eligible and ineligible children into a statistic. The coverage rate is calculated by dividing the total number of children within the CCB administrative file by the total estimated population of children in Canada. Coverage rates are complemented by non-filing rates of parents and a combined indicator which incorporates both non-filing and children coverage estimates into a single indicator.

The next section will provide additional details of the methodology, data and indicators used in this analysis. It then provides results for benefit months between January 2019 and December 2022 for children under the age of 18.^Note  Finally, it discusses the strengths and weaknesses of each indicator, provides caveats in interpreting the results and lists potential areas of further study.

Method, data and key indicators

The key to assessing the reach of the CCB is to compare counts of children who are eligible for the benefit or excluded for high parental income to the total child population. This requires obtaining the best estimate of the child population. Children who were in joint custody were present twice in the CCB data, once with each parent, but were reweighted to only count once in total before calculating the coverage rates.

Current approaches using households or families as the unit of analysis could result in bias. Following the recommendation of a recent ESDC internal report, this leads to take children under 18 as the unit of analysis. The census is the best data to obtain accurate estimate of CCB coverage as it can provide the best estimates for the count of children whose parents received the CCB, the count of children eligible for the CCB, and the count of children in the population.

However, census data is only available every five years and cannot directly support timely information for monitoring the coverage. To overcome this problem, it is important to rely on CCB administrative sources to provide the necessary numerator (children known to the Canada Revenue Agency) for the coverage rate combined with Demographic Estimates drawn from other sources as the denominator.

Statistics Canada receives monthly CCB files which includes primary caregiver’s and their children’s information. For each, the CCB file contains date of birth, eligibility, sex, benefit entitlement, net income and filing status in previous year.

The population of children can be estimated from multiple sources. The Demographic Estimates^Note  program and the births^Note  file of the Vital statistics, enable estimation of two basic coverage rates: the coverage rate by Demographic Estimates and coverage rate by Vital statistics^Note  . Children were classified as Canadian born by either having non-immigrant parents or having immigrant parents where the child’s date of birth is past the date of immigration.

The Demographic Estimates program creates postcensal population estimates, by using coverage studies of a representative sample of individuals, accounting for natural growth of the population and net migration. This is an estimate for all children currently residing in Canada. One of the benefits of this data source is that it is released quarterly in a timely manner and data are available upon request for monthly reference points. This source estimates all individuals living within Canada at a given reference date and would also include immigrants, permanent residents, and temporary residents. It contains characteristics such as age, sex, and province or territory of residence and would include newcomers to Canada and exclude children known to have died or moved away.

The Vital statistics birth file registers all births that occur within Canada during a given year (although in rare cases births are not registered). This is an estimate for all children born in Canada. Any births outside Canada are excluded from the birth files.^Note  The file contains information about the location of birth, date of birth, sex of the child, the mother’s place of residence and does not account for any children born elsewhere who may now be living in Canada.

Indicators

Indicator A: coverage rate of children

Two coverage rates mentioned above take the children in the CCB who are eligible or ineligible due to having high-income parents divided by the total population using each population estimate. This is represented in Figure 1 by the red circle divided by the grey circle in the Venn diagram below. This represents the proportion of the child population (or births) which is known to Canada Revenu Agency (CRA) at any point in time. Children unknown to CRA could arise from parents not applying for CCB at birth registration, or parent(s) not registering children upon arrival in Canada.^Note 

Indicator B: non-filing rate of parents

Non-filing rates are useful complements to the two basic coverage rate estimates. This second indicator measures the proportion of children known to CRA whose parent(s) have not yet filed divided by all known children represented in Figure 1 by the calculation of C / C+D. This statistic represents the proportion of parents who have not filed a return, even if this might be interrupting their receipt of entitlements.

Indicator C: coverage rate of parents

The final indicator considers both the registering aspect and the filing aspect by considering the proportion overall of the child population who are entitled and receiving the benefit or have been excluded from receipt for having high income. This combines the two effects of not registering the children and not filing and should provide an idea of the total impact of barriers in these two mechanisms. However, it is not a true measure of who would certainly be entitled had they registered and filed as some of them may yet be excluded under the high family adjusted net income constraint.

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The three indicators and two population definitions (Demographic Estimates and Vital statistics (birth)) provide six different ways of monitoring the coverage of the CCB within the child universe. The dimensions explored and contrasted here are the benefit month, the child birth month (or birth cohort) and child age (either in months or years). It is important to note that there are numerous other dimensions that it would be desirable to consider for differences in the indicators. However, the methods presented in this paper hinge on the dimensions of interest being present on both the CCB administrative file and the births or Demographic Estimates. For example, some elements of geography and age of parents would be possible but many sociodemographic concepts of interest would not be feasible unless using different methods. Table A.1 in the appendix summarizes these 6 coverage indicators. They will be addressed one by one after a general review of overall non-filing rates.

Non-filing rates of families with registered children

Differences in the eligible CCB population are observable over the year and between sociodemographic groups. Table 1 shows the month-to-month changes in the count and implicit filing rates for families with at least one eligible child. The number of families grows slightly from 3,636,060 to 3,643,190 over the course of the 2021-2022 program year, representing a +0.2% increase.

It is not self-evident that the number of eligible families would grow. Each month several children age out of the program or pass away, and their family becomes ineligible if they were the last eligible child, and some, emigrating from Canada, also become ineligible. On the flip side, several join the program over time such as families with newborns and immigrants to Canada. Variations in the average number of children per family could also influence the total. Following the loosening of pandemic restrictions, international migration drove most of the 2.7% population growth seen in 2022, the highest level since 1957 (Statistics Canada, 2023a). This source could also help explain why the number of families with at least one eligible child was mostly growing between 2021 and 2022.

The number of families who did not meet the filing requirements declines systematically during every program year generating a declining intra-year non-filing rate. The number of these families declined by more than two thirds from 411,850 for July 2021 to 115,860 by June 2022. This represented an 8.1 percentage points (pp) decline in the rate over the 11-month period. Despite individuals failing to file by the deadline, many people do complete their filing and consequently get any benefits owed as the program year progresses. Since the CCB payments have a retroactive feature, not everyone may feel a strong incentive to file on time, raising the question, “Is it problematic that people are not filing on time? Which of the rates is most useful for different analyses?”

On the second question, annual rates have the potential to underestimate the true number of people that eventually receive the CCB, depending on the month used in calculation. A higher rate of receipt would be found in June compared to July and the beginning of the program year.^Note  The differences equal the number of late filers who receive retroactive payments after completing their tax return. As there are no penalties for late filing, if no taxes are owed, it’s unclear how to address the seasonal patterns.

The families eligible for CCB universe are not evenly distributed among all sociodemographic groups. Table 2 summarizes these differences in non-filing rate^Note  and population proportions in the CCB and the income tax returns (T1). This preliminary coverage evaluation of subpopulations of interest shows that age, gender, and geography play an important role in determining filing behavior.

It is not immediately obvious that the amount of the benefit mirrors the filing rate as seen by widely ranging supplementary benefits between provinces and territories.^Note  However, additional analysis is required to untangle the various factors in determining filing rates, benefit amounts and poverty alleviation.

Finally, these rates are calculated using only those who are known to CRA to be parents, and it is therefore difficult to fully understand the true non-filer population for parents of children unknown to CRA and consequently assess the full extent of the population missing out on potential benefits. The following indicators provide a jumping off point and work to alleviate this problem. 

Indicator A: coverage rate of children known to CRA

Starting to examine the different indicators, the coverage rate of children known to CRA as share of the total count of children is presented. This shows the completeness of registration based on two sets of data: Demographic Estimates and Vital statistics. Not all benefit months or birth months are presented together on the first two charts for visual clarity. Different months were chosen to help the reader keep the two separate populations of analysis clear: July/June benefit months and March birth cohorts are visualized (the month of March was chosen arbitrarily, July and June mark the beginning and end of the program year).

A.1 Coverage rate using Demographic Estimates

Younger individuals, in this case those under 1 year of age have lower rates of coverage, however as it aggregates to single-year-of-age level some of the variation between the 1 month and 11 months-old children seen in the next graph is hidden. This could mean that coverage rates of the CCB for the youngest children is improving when comparing by demographics. The second notable observation is that total coverage rate for children between 1 to 5 years old is at about 96%. There is no clear pattern between years, but it seems that the coverage rate increases slightly as older children are considered in this range.

Chart 1 start

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A.2 Coverage rate using Vital statistics

Chart 2 graphs the coverage rate based on Vital statistics for 10 March birth cohorts between 2012 and 2021. It averages at roughly 95% for those children over 1 year old. This means that the proportion of Canadian-born children integrated into the system is relatively stable.

The second important observation is for all March cohorts, newborn children between the age of 1 and 12 months have lower coverage rates. It is as low as 20% in 2019 for 1 month old children. Two possible explanations for this are processing times of registration paperwork and parents registering late potentially by waiting until next tax season before registering their baby for the CCB. Since, the payments are retroactive, in some cases several years from entitlement dates, there isn’t a major financial penalty for late filing or registration.  

Chart 2 start

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Reversing the age and benefit dates in Table 3 to represent the age profile observed for a few benefit months shows this trend more clearly. For newborn children the CCB requires that parents file their taxes and register the newborn to receive the benefits. In the case of children under 1 year old, the variation within the coverage rate is best explained by a lag in registration dates of the newborn. The coverage rate for 12-month-old is like the entire child population at about 95%. Between 2019 and 2022 1 month old children fluctuate about 20%, with lows at 3% in June 2021 and highs of 30% in late 2021.

The 2-month-old group increases from a low of 60% in 2019 to as much as 70% in 2022. This means between 60% and 70% of children are registered by the time CRA processes the data for the month after they turn 2 months old. Most individuals register their newborn shortly after birth, but it can take time for the registration to make its way through the system and the CCB payments are computed many days earlier than the start of the month.

Indicator B: children with non-filing or late-filing parent(s)

Once the child has been registered and parents have filed, to maintain eligibility, the parents must file each subsequent year. This next indicator looks at the share of the child population known to CRA with non-filing parents. This reveals the number of parents that may file late and/or do not file entirely in subsequent years and represents a second barrier to obtaining benefits.

B.1 Children with non-filing parent(s) using Demographic Estimates

Looking at non-filing rates for parents of children living in Canada between 2020 and 2022 shows that non-filing rates are very low for all age categories between 1 and 5. There are between 1.0% and 2.0% of non-filers by June of each year. These numbers jump to 5.8% for the month of July reflecting the late filing of individuals who missed the April tax date and are late to register their children. It seems to show that as children age the filing rate of parents declines slightly, however without more complex analysis it is difficult to draw any conclusion disentangling the role that the pandemic and a variety of other factors play for this specific cohort.

Chart 3 start

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B.2 Children with non-filing parent(s) using Vital statistics

The rates of Canadian-born children with non-filing parents have been increasing slightly across the March-born cohorts. The annual late filing pattern emerges again in the graph below with the peak for the March 2012 birth cohort jumping from under 3% to 10% as they age from 124 to 125 months old. On the flip side, the troughs gradually increase to between 2 and 4% non-filers depending on the age of the child in question. It does appear that the non-filing rate is slightly higher for 96 months and 108 months children compared to 12- and 24-month-old children. One explanation for this could be that non-filing rates are decreasing for more recent parents, or a second possibility could be that as children age, their parents become less reliant on the benefit (or more aware that late filing has no lasting consequence) or for other reasons find it harder to file by deadline.  

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Indicator C: coverage rate of parents

The final indicator combines lags in registration and the non-filing behavior to construct the proportion of children with parents who are entitled to CCB (or are excluded because of high income). This combines the two effects previously investigated and shows both the coverage rate and yearly non-filing impacts in the same graph. One could also call it the registered child with filing parents rate. This approach resembles approaches relying on families as the unit of analysis but with a child-based unit of analysis.

C.1 Children with entitled to CCB or high-income parent(s) using Demographic Estimates

Using Demographic Estimates shows eligibility for kids over 1-year-old is more standard across time with notable dips in July of each year. From the peak in June to the trough in July there is a 9 pp decline in the proportion of filers. As the program filing requirement shifts to the next fiscal year, the parents of 9% of the children have not yet filed and see their benefits interrupted. There are differences of 3 pp between the parents of 1 year old and 5-year-old children, shown below by the gap between the red dots and the green dots.

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C.2 Children with entitled to CCB or high-income parent(s) using Vital statistics

The final indicator examines the coverage of children with filing parents against the population of children. Most children have been registered for CCB and have parents who file in time for CRA to calculate entitlements for the new program year to start (87% for July 2021). As the program year progresses, this rises as more parents file their taxes (to 94% by June 2022). It will drop back down in July as the new tax return becomes required. These patterns were not easily observable with the population data due to the lack of monthly distinctions.  

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Chart 7 examines the pattern from the perspective of 1 year age increments. There is clear periodic variation every year. These are attributable to the beginning of each new program year in July when people who have not filed the previous year become ineligible until they complete the filing requirement. The COVID-19 pandemic period included several changes to program requirements like a 3-month filing grace period before being cut-off from benefits. This contributed to a 3-month shift in the July dip and a less pronounced dip occurred in October, once the contingency payments expired.

Some years have larger drops in July and the distance from the trough to the peak is bigger. The filing rate for parents connected to CCB children was higher in 2019 at 87.2% compared to 85.5% in 2022. Finally, the distance between trough and peak varies from year to year, however as the previous graph shows, it seems that the peak filing rate reaches between 94% and 95% each year. 

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Discussion

This final section compares and analyses the two data sets (Demographic Estimates and Vital statistics) and the three indicators (A: child known to CRA coverage rate, B: children with non-filing parents rate and C: children with entitled to CCB or high-income parents rate). Each approach shines light on a different aspect of the CCB coverage and looks at some of the benefits and limitations of each. All together these provide new opportunities to monitor the CCB benefit system in Canada.

Demographic Estimates

The Demographic Estimates include all children living in Canada at a given time. While this has important advantages over the Vital statistics data, it can also include children who may not be eligible for the Canadian tax and benefit system such as certain temporary residents. The sociodemographic granularity is more limited than the Vital statistics data. This can be seen in that the estimates do not breakdown by age in months making the potential precision lower than the Vital statistics.

Although timeliness is an issue, the Demographic Estimates – which are released every quarter – are more frequent than the Vital statistics. A second timeliness issue is that the demography data is based on the census with coverage studies. This means that the further away from the census year, which is only conducted every 5 years, the less accurate the estimates could be. Finally, it does not include data by month of age, but instead provides perspective on benefit month in question, which may have added benefit for CRA as it could provide information from the perspective of program delivery.

An advantage of Demographic Estimates over Vital statistics is the inclusion of immigrants and children who are temporary residents. By incorporating all individuals living in Canada, coverage is based on the geographic boundary of Canada as opposed to coverage tied to births.

Vital statistics

The Vital statistics program only accounts for children born in Canada and has limited timeliness. The tradeoff is in improved data granularity through the availability of birth month and some sociodemographic information. The potential population relevant to CCB monitor is broader than children born in Canada. One consequence is that the limitation to capture the mobility of individuals for both Canadians and foreign nationals is limited.

For example, Canadians who give birth outside of Canada may not be registered and in certain circumstances children born in Canada are not registered. Secondly, recent immigrants or temporary workers who bring young children into Canada may be missed when measuring coverage rates through Vital statistics. Finally, this mobility issue limits applicability further away from the birth month in question.

This highlights a second limitation in the timeliness and reference period of the data. Firstly, the Vital statistics data is only released once a year. Secondly, the data shows that children are often not registered in their first year and as such there can be multiyear delays before the data are fully accurate for the number of births in a given period. In addition, the further away from the birth year, and partly connected with issues of mobility, inaccuracies of administrative data and non-filing, the estimates become less accurate for older children. This could explain why Chart 4 suggests that the non-filing rate increases as the children grow older.

Despite these two drawbacks, the increased granularity level of the data through using the birth month and sociodemographic information drawn from administrative data is a valuable improvement. This increases the ability of measuring coverage rates from the perspective of the recipient as it uses the child’s birthday to define the reference period. This means helping to identify patterns in the first year of life. 

Children known to CRA coverage rates

The child coverage rate provides an idea of the entire population that is being measured whether that is Canadian births or children living in Canada. It includes additional individuals than those that receive or should be eligible to receive the benefits and could help CRA identify to what degree they are successfully categorizing those that are eligible and those that are ineligible. As has been shown, this is particularly valuable in looking at newborns where indicator A.1. Coverage rate (Demographic Estimates) is the more informative compared to A.2 Coverage rate (Vital statistics), which is restricted to year-over-year changes.

Children with non-filing parents rate

When looking at monthly variations due to a policy change or broader economic developments with short time series, the non-filing rate for B.1 Children with non-filing parent(s) (Demographic Estimates) or B.2 Children with non-filing parent(s) (Vital statistics) would both be extremely helpful depending on the perspective one is looking at. B.1 may be more helpful from the perspective of recipients and the rate at which newborns are registered. Whereas the B.2 focuses on the ebb and flow of filing that occurs year over year. It shows the sensitivity of those monthly flows based on benefit month to policy changes as was demonstrated by the shift due to pandemic contingency payments and catch up at filing following its end.

Children with entitled to CCB or high-income parents rate

The parental filing rate of children in the CCB combines these two measures. This approach to parental filing rate is similar to other approaches looking at household level analysis. This provides an interesting perspective into the patterns of recipients that are not captured by the other indicators. However, since more thorough analysis of recipients has been conducted elsewhere, this was not emphasized in this report. Its main benefit here is that it provides a combined picture of both non-filing and child coverage rate in including the non-filing dips into the coverage rate as seen in Chart 6.

Conclusion

This paper has described three new indicators using two different data sources, the Demographic Estimates and Vital statistics, to provide new insights on the coverage rates of the CCB using children as the unit of analysis. A first series of coverage rates were calculated by dividing the total number of children within the CCB administrative file by the total estimated population of children in Canada.  Additionally, the coverage rates were augmented by using information on non-filing rates of parents as well as incorporating both non-filing and children coverage estimates into a single indicator.

Two major insights can be learned from this report. First, the newborn filing rate is quite low but catches up to the rest of the population by the time the child is 1 year old. The added granularity of the Canadian-born analysis helps understand the less than 1 year population and make contrasts of new arrivals and others. This means that the CCB program is integrating the newborns into the program in a timely way after registration. Second, the monthly aspects of the CCB program, encourages analysis to take the benefit month into account when calculating coverage rates and to be explicit about the period chosen.

There are still caveats and limitations to this analysis. They could help interpret the limits of these conclusions. First are the recurring differences between coverage and entitlement rates calculated here for CCB and those calculated for other benefit programs. Given that the size of the CCB benefit is a substantial incentive to file, one would expect filing rates of parents (filing being one of the requirements to be eligible to CCB) to be slightly higher than what is seen in this paper.

Another caveat is that administrative data are always incomplete when it comes to identifying and evaluating reasons which may drive people not to participate – either by not registering or not filing. Some of the reasons would include: lack of knowledge or information, difficulty navigating the program, mistrust of government or political statement, and absence of need. Despite the inherent limitations of using administrative data, coverage rates can provide a valuable picture.

Thirdly, in this analysis the Children’s special allowances (CSA) population was excluded. One of the objectives of the CCB is to reduce child poverty and evaluating the effectiveness of the program is limited when some vulnerable children are excluded. One possible explanation for this data related limitation is convenience in organizing information by benefit program as opposed to by child population. However, there is the possibility of including them in future research by adjusting some of this work with counts from CSA products.

Finally, tax filing is shown to have variations in terms of the month of filing in the case of individuals filing late and in terms of how old children are. The structure of the file also offers a five month longer window for filing than seen typically with the filing vintage from late December used in other research.  Every year CRA processes many returns for different years: in 2022 processing season, they processed 31.3 million returns but only 29.5 million were for the 2021 tax year (Government of Canada, 2025). The remainder were for previous years.

There are many possible areas of research that can be used to improve the reach and evaluation of the CCB and overcome some of the limits of this paper. A few potential areas are:

1. Sociodemographic analysis: through the incorporation of administrative such as the Vital statistics, greater granularity of data could be explored, which may help understand the type of individuals and families that are filing and those that are not. Work is currently being done to investigate immigrants and Indigenous Populations, but more can be done.
2. Contrasting across provinces and territories would be another approach of interest, potentially incorporating economic modeling to better disentangle the relationship between regional factors and supplementary benefits specific to each province or territory.
3. A longitudinal study could also see if each year it is the same people who late-file (maybe the self-employed who have a later filing date) and eventually catch up. A study could answer whether intermittent filing lapses are driven by life events (for example, births, moves to different cities and job loss, divorces, or other trauma). These assessments could suggest different intervention strategies.
4. Pathways into and out of the benefit system: related to the longitudinal studies, understanding how the benefits flow for children with families that experience changes due to death, divorce or mobility could shed light on how less consistent families are accessing the benefits and ensuring those that require the benefits are receiving them.
5. Microdata linkage could contribute to a richer sociodemographic profile of the population not known to CRA and better understanding of the populations. For example, in the 2021 Census, about 48,000 children were not linked to any administrative record and appeared unknown to CRA. Sociocultural characteristics could be observed for this population.

Finally, the objective of assessing the coverage rate and take-up rate is to determine if the exact thresholds and eligibility requirements of the policy are being met. However, there is an argument to be made that assessment of the threshold and eligibility requirements should be examined through the lens of policy working to alleviate child poverty in Canada. Moving from the take-up rate to a coverage rate works towards this by exploring both those that are eligible and ineligible for a benefit. More work can be done to examine the impact of potential changes in these eligibility requirements on the full realization of ending child poverty in Canada.

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Appendix