January 2024

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CENTRE FOR THE
STUDY OF LIVING
STANDARDS

Closing the First Nations Education Gap in
Canada: Assessing Progress and Estimating the
Economic Benefits — An Update Using 2021
Census Data
Chris Haun
CSLS Research Report 2024-01

January 2024
Prepared for the Assembly of First Nations

Closing the First Nations Education Gap in
Canada: Assessing Progress and Estimating the
Economic Benefits — An Update Using 2021
Census Data
Abstract
This report first assesses key labour market gaps facing First Nations people in Canada
relative to non-Indigenous Canadians in 2021. It then estimates the economic benefits which
would accrue to First Nations people and Canadians generally if these gaps were to be closed.
Our primary focus is the educational attainment gap between the First Nations population and thenon-Indigenous population, though we also investigate gaps in employment rates and average
employment incomes, both conditional on educational attainment. This report updates a previous
study undertaken by the Centre for the Living Standards and published by the Assembly of First
Nations, repeating key exercises using newly-available data from the 2021 Canadian Census. We
find that significant progress has been made in closing gaps in employment rates andemployment incomes between the two populations since 2016. The educational attainment ofboth populations is found to have increased over the 2016-2021 period. However, nonIndigenous rates of improvement have outpaced First Nations rates of improvement, causing the
gap to widen slightly. Using detailed tabular data from Statistics Canada, we are able to simulate
the closure of these gaps both at the aggregate level and within age, gender, andprovince/territory categories. Ultimately, we estimate that the cumulative economic benefits
associated with closing the education gap over the 2021-2041 period could be as large as $233
billion, and that the cumulative economic benefits associated with closing all three gaps ofinterest over the same timeframe could be as large as $369 billion.

Closing the First Nations Education Gap in
Canada: Assessing Progress and Estimating the
Economic Benefits — An Update Using 2021
Census Data
Table of Contents
Executive Summary ................................................................................................................ iv
Introduction...............................................................................................................................1
Understanding the 2021 Census: Data Structure & Limitations ...........................................4a)Overview .........................................................................................................................5b)Overnight & Longitudinal Models ...................................................................................7c)Tabular vs. Microdata ......................................................................................................9d)

Variables ....................................................................................................................... 10

The State of the Gaps ............................................................................................................. 13a)

The Education Gap: Distributional Approach ................................................................. 14b)

The Education Gap: Average Years Approach ............................................................... 21c)

The Income Gap Conditional on Education .................................................................... 30d)

The Employment Rate Gap Conditional on Education ................................................... 37

Methodology – Overnight Model ........................................................................................... 41a)

Closing the Education Gap............................................................................................. 41b)

Closing the Income Gap Conditional on Education ........................................................ 43c)

Closing the Employment Rate Gap Conditional on Education ........................................ 45d)Closing All Three Gaps Simultaneously......................................................................... 46e)

Limitations & Assumptions ........................................................................................... 47

Methodology – Longitudinal Model ...................................................................................... 48
Results & Discussion ............................................................................................................... 59a)Overnight Model ........................................................................................................... 59i)

The Education Gap.................................................................................................... 62ii)

The Income Gap Conditional on Educational Attainment .......................................... 63iii) The Employment Rate Gap Conditional on Educational Attainment .......................... 65
ii

iv)
b)

Closing All Gaps Simultaneously .............................................................................. 66

Longitudinal Model ....................................................................................................... 67i)

Scenario 1: The Education Gap Fully Closes ............................................................. 74

ii)

Scenario 2: The Education Gap Closes Halfway ........................................................ 75iii) Scenario 3: The Conditional Employment Rate Gap .................................................. 76iv)

Scenario 4: The Conditional Income Gap .................................................................. 78v)

Scenario 5: All Gaps Close ........................................................................................ 79c)Comparing the Models................................................................................................... 80i)

The Closing of the Education Gap ............................................................................. 83

ii)

The Closing of the Conditional Income Gap .............................................................. 84iii) The Closing of the Conditional Employment Rate Gap.............................................. 85iv)

The Closing of All Three Gaps Simultaneously ......................................................... 87

Challenges in Closing the Gaps .............................................................................................. 88
Conclusion ............................................................................................................................... 90
References................................................................................................................................ 93iii

Closing the First Nations Education Gap in
Canada: Assessing Progress and Estimating the
Economic Benefits — An Update Using 2021
Census Data

Executive Summary
In February of 2023, the Assembly of First Nations (AFN) released a study done by theCentre for the Study of Living Standards (CSLS), leveraging data from the 2016 Census toassess the state of the educational attainment gap between First Nations people and nonIndigenous people in Canada. The study also investigated two related gaps in labour market
outcomes between the two populations: the gap in average employment income within
educational attainment categories (what we called the “employment income gap conditional on
education” or simply the “income gap conditional on education”) and the gap in employment
rates within educational attainment categories (what we called the “employment rate gap
conditional on education”). Finally, the study estimated the potential economic gains associatedwith closing these gaps based on two models of gap closure: the “overnight” model and the“longitudinal” model. The findings of the study were published in the form of a comprehensive
research report.
Since the release of the report, there has been considerable interest in extending ouranalysis of these gaps to include the 2016-2021 period. This report hence serves as an update to
the report published earlier this year on the educational attainment gap between First Nations
people in Canada and non-Indigenous Canadians. By leveraging recently released data from the2021 Census on the educational attainment and labour market outcomes of the two populations,
we are able to assess the progress made in closing key labour market gaps over the 2016-2021
period. We also provide updated estimates of the potential gains that would accrue to First
Nations people and Canadians generally if these gaps were to close.
Methodology
The methodological framework of this report closely follows that of our previous report,with some adjustments made to account for differences in the available data between the tworeports. To assess progress made in eliminating key labour market disparities between the First
Nations population and the non-Indigenous population, we mobilize aggregate data from
Statistics Canada tables on educational attainment as well as employment rates and average
employment incomes within educational attainment categories.

iv

In the overnight model of gap closure, we simulate the instantaneous closure of thesegaps in 2021 to estimate the potential economic benefits from closing the gaps, or viewed
differently, the significant opportunity costs incurred by Canadians from failing to close thesegaps. In the longitudinal model of gap closure, we envision these gaps closing gradually over the2021-2041 period.
To estimate the benefits of gap closure over this period, we leverage economic
projections developed by the CSLS alongside First Nations population projections produced by
Statistics Canada. Unlike the overnight model where we closed gaps between the two
populations at the aggregate level, in the longitudinal model, we close gaps only between First
Nations people and non-Indigenous people of the same gender, age group, and province/territoryof residence. Altogether, we consider five scenarios: the education gap closes fully, the education
gap closes halfway, the conditional employment rate gap closes, the conditional income gap
closes, and all gaps close simultaneously.
Economic gains in the longitudinal model are calculated by comparing key metrics likeGDP, employment, and labour productivity between any given gap closure scenario and abaseline projection where educational attainment progresses as it did in the 2016-2021 period.
Interestingly, our projections for First Nations GDP, employment and labour productivity in
2041 are slightly lower than those offered in our previous report. We attribute this primarily tothe fall in employment rates observed across both populations between the 2016 and 2021
Censuses: an effect which is further pronounced by the projection procedure we employ. There
are also some small differences in the categories of the Census educational attainment variable
between this report and our previous report. This too may contribute to the discrepancy.

The Education Gap
Since 2016, levels of educational attainment have progressed substantially for both First
Nations people and non-Indigenous people. Whereas First Nations people had 12.07 years ofeducation on average in 2016, they had 12.24 in 2021: a growth rate of 0.27% per year. This
represents a faster rate of improvement in educational attainment for the First Nations populationcompared to the 2011-2016 period (a growth rate of 0.25% per year)
The bulk of this improvement occurred at the top and bottom of the educational
attainment distribution. The proportion of the First Nations population with no educational
credential fell significantly (33% in 2021 vs. 38% in 2016) and conversely, the proportion with ahigh school diploma or equivalent credential rose (30% in 2021 vs. 25% in 2016). The
proportion of the population with a bachelor’s degree and the proportion with a university
certification above the bachelor level also grew steadily: a 1.2-point increase for the former(6.6% in 2021 vs. 5.4% in 2021) and a 0.5-point increase for the latter (2.4% in 2021 vs. 1.9% in2016).
However, rates of improvement were even faster for the non-Indigenous population; thislead to a slight widening of the education gap. In 2016, non-Indigenous people had 13.34 yearsv

of education on average; this figure grew to 13.53 years in 2021, implying a growth rate of
0.29% per year. Improvements generally occurred in the same categories as they did for First
Nations people, although progress was concentrated to an even greater degree at the top end of
the distribution. Assuming current trends improvement continue indefinitely, the more rapid rateof improvement within the non-Indigenous population means that the attainment levels of the
populations will never converge. However, if we make the simplifying assumption that theeducational attainment of the non-Indigenous population has hit a “ceiling” and does not
improve over time, we find convergence in 37 years.
The share of the non-Indigenous population with a bachelor’s degree increased from
15.9% in 2016 to 17.9% in 2021, while the share with a credential above the bachelor level rosefrom 8.0% to 9.5%. The largest relative gaps between the populations continue to occur in the“no educational credential” category, where the First Nations share is over two times as large as
the non-Indigenous share, and the bachelor’s and above bachelor’s categories, where the First
Nations share makes up 37% and 26% of the non-Indigenous share, respectively.

The Employment Income Gap Conditional on Education
The gap in average employment incomes has closed substantially, both in broad terms
and within educational categories. The absolute gap between the populations has fallen from
$13,370 in 2016 to just $9,869 in 2021. It should be noted that all monetary estimates in thisreport are provided in 2015 Canadian dollars. On average, First Nations people earned about
71% of what non-Indigenous people earned in 2016; that figure has risen to about 79% in 2021.
The improvements are even more stark within educational attainment categories.
Previously, the absolute gaps within categories ranged from just over $4,200 to about $10,600,
with First Nations earnings ranging from 83% to 88% of non-Indigenous earnings. In 2021, theabsolute gaps range from about $3,700 at the lowest to about $6,500 at the highest, with First
Nations earnings ranging from about 89% to 92% of non-Indigenous earnings. The “noeducational credential” category is an outlier in this respect; Statistics Canada reports that First
Nations average wages here have risen almost $9,000 in the 2016-2021 period. Furthermore, inthis category, the average First Nations wage as a proportion of the average non-Indigenous
wage has risen from 83% in 2016 to 123% in 2021: an inversion of the employment income gap.
The Employment Rate Gap Conditional on Education
There has been a similar degree of progress in closing the employment rate gap
conditional on education. Across both populations, employment rates have generally fallen since2016. This is likely due to the impacts of the pandemic, which were still being felt in May 2021,
when the Census was conducted. With that said, employment rates for First Nations people havefallen much less than those for non-Indigenous people, causing the employment rate gap toshrink significantly. In 2016, First Nations people experienced an overall employment rate of
46.8%: 13.7 points lower than the non-Indigenous figure (60.5%). In 2021, this figure fell to
46.3% -- a decrease of just 0.5 points. For comparison, the non-Indigenous figure fell 3.1 points
to 60.5%. Consequently, the overall gap between the populations fell to just 11.1 points.
vi

As with the employment income gap, the discrepancy between the populations is muchsmaller when controlling for educational attainment. In fact, looking within educational
categories, the gap falls to between 0.6 points and 5.5 points depending on the category. In 2016,absolute gaps within educational attainment categories ranged from 4.2 points, at the smallest(excluding categories where First Nations people experienced a higher rate than non-Indigenous
people), to 7.9 points, at the largest. These figures suggest that the employment rate gap has
improved in both broad terms and conditional on educational attainment. The largest gap byquite a significant margin continues to be found in the ”no educational credential” category
where, despite earning wages that are 123% of what non-Indigenous people earn, First Nations
people face an employment rate that is 5.5 points lower than what non-Indigenous people
experience (25% for First Nations people vs. 30.4% for non-Indigenous people).
The Overnight Model of Gap Closure
In the overnight model of gap closure, we envision the gap closing instantaneously in
2021. Gains are assessed by comparing key economic metrics like total employment income andtotal employment pre- and post-gap-closure. Within this approach, we find the following:•

The closure of the education gap is associated with an additional $5.5 billion in First
Nations employment income and 70,913 jobs for First Nations people.

•

The closure of the income gap is associated with an additional $1.3 billion in First
Nations employment income; notably, there are no employment gains under this scenario.

•

The closure of the employment rate gap is associated with $0.8 billion in additional
employment income for First Nations people and 26,061 additional jobs.

•

The closure of all three gaps simultaneously is associated with $7.7 billion in additional
First Nations employment income and 85,020 additional jobs for First Nations people. In
terms of estimated gains from gap closure, this is by far the most significant of the four
scenarios.

These estimates are generally comparable to those produced in our previous report, withsome key differences. The gains from closing the income and employment rate gaps haveattenuated somewhat, reflecting the progress made in closing the gaps since 2016. Conversely,
the gains from closing the education gap have grown slightly due to the widening of the gap
since 2016. The former effect seems to outweigh the latter though, given that the gains from the
all-gaps-closed scenario are found to be smaller here compared to our previous report.
The Longitudinal Model of Gap Closure
In the longitudinal model of gap closure, we simulate the gradual closing of gaps between
First Nations people and non-Indigenous people over the 2021-2041 period. Across the five
scenarios we consider, we find the following:

vii

•

The full closure of the education gap is associated with an additional $24.7 billion inFirst Nations GDP in 2041 and an additional 106,000 jobs for First Nations people in
2041. In this report, the labour share of GDP is assumed to be 0.5 based on its historicvalue in Canada. Thus, gains in First Nations employment income are estimated to beabout $12.3 billion under this scenario. This is significantly larger than the gain in
income estimated in the overnight model, chiefly because of population and real wage
growth between 2021 and 2041; Statistics Canada projects that the First Nations workingage population will nearly double between 2021 and 2041 and real wages are expected to
grow by about 23% in that time. Over the 2021-2041 period, the gradual closure of the
gap is associated with an estimated $233 billion in additional First Nations GDP and
1,046,000 additional job-years for First Nations people. A “job-year” represents a single
job for a single year, or a year’s worth of income for the First Nations population. The
annual growth rate of GDP over the 2021-2041 period increases from 1.71% per year in
the baseline scenario to 1.75% per year when the education gap closes fully. The annual
growth rate of employment rises from 0.95% to 0.97%. The annual growth rate of labour
productivity improves by the same margin, growing from 0.75% to 0.77%.

•

As one would expect, the half-closure of the education gap is associated with gains ofabout half the magnitude of the full-closure scenario; in 2041, this means an additional$12.3 billion in First Nations GDP and an additional 53,000 jobs for First Nations people.
Over the 2021-2041 period, the half-closure of the gap is associated with about $117
billion in additional First Nations GDP and an estimated 523,000 additional job-years forFirst Nations people. The annual growth rate of GDP over the 2021-2041 period
increases from 1.71% to 1.73%. The annual growth rate of employment rises from 0.95%
to 0.96%. Finally, the annual growth rate of labour productivity grows from 0.75% to0.76%.

•

The closure of the conditional employment rate gap is associated with $9.9 billion in
additional First Nations GDP as well as about 123,000 jobs for First Nations people.
Cumulatively, the closure of the gap is associated with $94 billion in additional output by
the First Nations population and 1,217,000 additional job-years for First Nations people.
These gains in employment from the closure of the employment rate gap are even larger
than those associated with the full closure of the education gap. Over the 2021-2041, theannual economic growth rate rises from 1.71% to 1.73% and the annual growth rate of
employment rises from 0.95% to 0.98%. However, the annual growth rate of labour
productivity falls from 0.75% to 0.74%, reflecting the fact that new First Nations
employment tends to be concentrated in lower educational categories, where wages andlabour productivity are relatively low.

•

The closure of the conditional employment income gap is associated with the smallest
economic gains of all the scenarios considered; in 2041, the closure of the gap is
associated with an additional $4.7 billion in First Nations GDP. Once again, there are no
gains in employment associated with this scenario. Cumulative gains in GDP over the2021-2041 period, though, are estimated to be about $45 billion. The annual GDP growthrate over the period rises from 1.71% to 1.72% while annual labour productivity growthover the period rises from 0.75% to 0.76%.
viii

•

The final scenario we consider sees the education gap, the conditional employment
rate gap, and the conditional employment income gap all close simultaneously overthe 2021-2041 period. Naturally, this scenario is associated with largest economic
benefits. In 2041, the closure of all three gaps is associated with an additional $39.1
billion in First Nations GDP and about 184,000 jobs for First Nations people. Over the2021-2041 period, the closure of the gaps is associated with $369 billion in additional
GDP and about 1,822,000 job-years compared to the baseline scenario. The annual
growth rate of GDP during the period rises from 1.71% to 1.77%. Annual employment
growth, meanwhile, rises from 0.95% to 0.99% and annual labour productivity growth
grows from 0.75% to 0.78%

Conclusion
In updating the exercises from our previous report using 2021 Census data, this reportconfirms that there are massive economic gains associated with the closure of key educational
and labour market gaps facing First Nations people in Canada. The economic gains reported here
are generally smaller than those estimated in the previous report, reflecting progress made since2016 in closing these gaps. Still, we find that the current rates of improvement in First Nations
educational attainment are insufficient to close the education gap between First Nations and nonIndigenous people. The findings here therefore reinforce the need for renewed action on the partof policymakers, community leaders, and ordinary Canadians to support First Nations educationand to engender a culture of lifelong learning.

ixClosing the First Nations Education Gap in
Canada: Assessing Progress and Estimating the
Economic Benefits — An Update Using 2021
Census Data1
Introduction
In February of 2023, the Assembly of First Nations (AFN) released a study done by theCentre for the Study of Living Standards (CSLS), leveraging data from the 2016 Census toassess the state of the educational attainment gap between First Nations people and nonIndigenous people in Canada, as well as associated gaps in wages and employment rates (AFN,
2023).2 The findings of the study were published in the form of a comprehensive report,
representing the most recent installment in a series of reports undertaken by the CSLS on thelabour market and educational gaps faced by Indigenous Peoples in Canada relative to nonIndigenous Canadians.3 Since the release of this report earlier this year, there has been
considerable interest in extending our analysis of these gaps to include the 2016-2021 period: adecidedly unusual period for the Canadian economy due to the onset of the COVID-19 pandemic
in early 2020.

1This report was written by Chris Haun under the supervision of Andrew Sharpe. They wish to thank Bert
Waslander, Tim Sargent, and AFN officials, particularly Randy Schmucker, for their thoughtful comments andfeedback on this report.
2This report uses the term “education gap” as shorthand for the “educational attainment gap between First Nations
and Non-Indigenous Canadians” for the sake of brevity.
3
In particular, the CSLS’s 2007 report “The Potential Contribution of Aboriginal Canadians to Labour Force,
Employment, Productivity and Output Growth in Canada, 2001-2017”, the 2009 follow-up report “The Effect ofIncreasing Aboriginal Educational Attainment on the Labour Force, Output and the Fiscal Balance”, and the 2015
report “Closing the Aboriginal Education Gap in Canada: Assessing Progress and Estimating the Economic
Benefits” which forms the methodological basis for this report.

1This report hence serves as an update to the report published earlier this year on the
educational attainment gap between First Nations people in Canada and non-Indigenous
Canadians. 4 By leveraging recently released data from the 2021 Census on the educational
attainment of the two populations, we are able to assess the progress made in closing the
educational attainment gap over the 2016-2021 period, as well as gaps in employment rates andaverage employment incomes, both conditional on educational attainment. Finally, we also
provide updated estimates of the potential gains that would accrue to First Nations people andnon-Indigenous people generally if these gaps were to close.
Although substantial progress has been made in improving the employment income andemployment rate gaps experienced by the First Nations population, we find that since 2016, thegap in educational attainment between the First Nations and non-Indigenous populations has
actually widened. This is because, although both populations have seen growth in average levelsof educational attainment over the 2016-2021 period, the educational attainment of nonIndigenous people has simply improved more since 2016 than it has for First Nations people. As
a result, we still find that there are immense economic benefits associated with the closure of thethree key gaps between the First Nations and non-Indigenous populations.
In the overnight model, we envision these gaps closing instantaneously in 2021, giventhat the best available data on the educational attainment, employment earnings, and employment
rates of First Nations and non-Indigenous people come from the 2021 Canadian Census; data on
these variables for 2022 and 2023 is not available at this time. We estimate that the closing of theeducation gap is associated with gains of $5.5 billion in additional employment income and

4

The comparison here does not include other Indigenous groups in order to focus on the situation for the First
Nations population in Canada. The non-Indigenous group does not include any Indigenous persons or peoples.

2

about 71,000 additional jobs for First Nations people.5 These estimates are larger than thosepresented in our previous report. The simultaneous closure of all three gaps of interest,
meanwhile, is associated with gains of $7.7 billion in additional employment income and about
85,000 additional jobs for First Nations people. These figures are somewhat smaller than thosepresented previously, reflecting how gaps in employment income and employment rates haveshrunk substantially since 2016. These figures are best interpreted as the substantial opportunity
costs which the Canadian economy incurred in 2021 by failing to fully close these gaps.
In the longitudinal model, we project these gaps closing gradually over the 2021-2041
period.6 Within this framework, we estimate that the full closure of the education gap is
associated with an additional $24.7 billion in GDP and a further 106,000 jobs for First Nations
people in 2041. These estimates are calculated by comparing key economic variables like GDP
and employment between a scenario where the education gap in 2041 is fully closed and abaseline projection where the education gap progresses as it did between 2016 and 2021. Overthe 2021-2041 period, the closing of the gap is estimated to generate a total of $233 billion in
cumulative GDP gains and an additional 1 million job-years of employment for the First Nations
population. This manifests as an improvement in the annual economic growth rate for the 20212041 period from 1.71% in the baseline to 1.75% when the education gap closes. In the scenario
where all three gaps of interest close simultaneously over the 2021-2041 period, the gains rise5

All monetary estimates in this report are expressed in 2015 Canadian dollars. This is to facilitate comparison with
our earlier report, for which estimates were also expressed in 2015 Canadian dollars, as incomes reported in the2016 Census were earned in 2015. Still, readers can multiply the monetary estimates presented by 108.2% toproduce figures in 2020 dollars (Statistics Canada, 2023). Similarly, estimates can be multiplied by 111.8% for 2021
dollars, and by 119.4% for 2022 dollars (Statistics Canada, 2023).
6
The 2021-2041 timeframe is chosen due to limitations in the available data. Detailed data on educational
attainment, average employment incomes, and employment rates by sex, age, and province in the two populations isunavailable for 2022 and 2023. We are also limited in our ability to extend the time period, given that thelongitudinal model relies on First Nations population projections produced by Statistics Canada which, at the time ofwriting, have yet to be updated beyond 2041.

3

dramatically. We estimate that this scenario is associated with an additional $39.1 billion in GDP
and about 184,000 jobs for First Nations people in 2041. Over the 2021-2041, the closure of thethree gaps is associated with cumulative gains of $369 billion in GDP and 1.8 million additional
job-years for First Nations people. This raises the annual economic growth rate for Canada inthis period by 0.6 percentage points to 1.77%: an extremely significant improvement in thegrowth trajectory of the country.
The remainder of the report is structured as follows. The second section offers an indepth description of the 2021 Census data which underpins our analysis in this report. In
particular, we recount the unique circumstances surrounding the administration of the 2021
Census and make note of areas where the data differs from the 2016 Census data employed in
our previous report. The third section utilizes this data to assess the state of the three key gaps
between the First Nations and non-Indigenous populations, gauging the progress made in closing
these gaps over the 2016-2021 period. The fourth and fifth sections describe our methodologies
for the overnight and longitudinal models of gap closure respectively. The sixth section presents
the results of the overnight and longitudinal models, with a final subsection comparing results
between the models. A final section concludes.

Understanding the 2021 Census: Data Structure & Limitations 7
Like our earlier report on the subject, this report relies on data from the Canadian Census
to assess the state of the educational attainment gap between First Nations people and nonIndigenous people in Canada, as well as the related gaps in employment rates and average
employment incomes (AFN, 2023). In our previous report, the most recent Census available was7

Unless another source is provided, all information in this section is sourced from the 2021 Census Guide (Statistics
Canada, 2021a).

4

the 2016 Census; hence, our analysis was based on the state of the gaps in 2016. Using aggregate
measures of educational attainment and labour market performance as well as individual-level
microdata from the 2016 Census, we were able to estimate the economic benefits which would
accrue to First Nations people and Canadians generally if these gaps were to be closed.
Beginning in February 2022, Statistics Canada began to release data products from the2021 Census. These releases were staggered throughout the year and curated around particular
topics or themes. Requisite data on First Nations people and education became available in Fall
2022 (Statistics Canada, 2021b). Hence, we were not able to integrate data from the 2021 Census
into our previous work. At the time of writing this report, all of the data and highlight tables
relating to the 2021 Census have now been released, although the individual-level Public Use
Microdata File (PUMF) will not be made available until Fall 2023 or later. Nevertheless, there issufficient data available for us to update the analysis from our previous report on the educational
and labour market gaps facing First Nations people.
In many ways, the structure of this data is extremely similar, if not identical, to the datafrom the 2016 Census, and as a result, there is great overlap with the previous report in the typeof data we mobilize and the manner in which we use it. With that said, there are a number of key
ways in which our data strategy here differs from our approach previously, particularly withrespect to the lack of a PUMF and the use of detailed cross-tabular data as a substitute. In thefollowing section, we explore these differences and provide an overview of the data employedthroughout the report.

a) Overview

5The 2021 Census was conducted in May and June of 2021 with a reference date of May
11.8 Occurring in the midst of the COVID-19 pandemic, the 2021 Census faced a number ofchallenges relating to the collection of data. Households were given the option of completing thecensus either online, on paper, or over-the-phone. About 84% of private dwellings chose tosubmit the form online: a significant increase from just over 68% in 2016. For some collective
dwellings, and in some cases of non-response by households, in-person enumerators weredispatched to collect data. As a rule, Statistics Canada strived to keep data collection contactlesswherever possible. When necessary, the agency used administrative data to impute responses forareas with insufficient data. Notably, all income data collected for the 2021 Census was sourced
directly from Canada Revenue Agency records: a first time for the Canadian Census. This
procedure was successful both in reducing the burden on respondents and in improving data
quality.
Despite these unprecedented circumstances, the quality of the 2021 Census data remains
quite high. The national response rate was 96.9% for the short-form survey and 95.7% for the
long-form survey; only slightly lower than in 2016, when the response rates were 97.4% and96.9%, respectively. Although response rates were high nationally, they were substantially lower
in areas which were particularly difficult to access during the pandemic. As such, data reliability
is lower in some smaller aggregation areas in Northern Canada, in remote communities, and in
Indigenous communities. Indeed, the number of incompletely enumerated reserves andsettlements rose substantially, from 14 in 2016 to 63 in 2021. In the majority of cases, this wasdue to logistical issues stemming from the pandemic and natural events (e.g. forest fires),however in a number of cases, these communities did not grant Statistics Canada permission to

8

Labour force data (ex. whether an individual is employed, unemployed, or not in the labour force) is based on thereference week of May 2nd to May 8th, 2021 (Statistics Canada, 2022d).

6

conduct enumeration activities. As a result, the frequency with which Statistics Canada was
required to impute missing data rose for the short-form census compared to the 2016 Census. For
the long-term census, the imputation rate rose for some questions and fell for others, relative to
2016. The former is attributable to the aforementioned drop in response rates compared to 2016.
The latter, meanwhile, is a result of the increased prevalence of online census form submissions,
given that forms completed online have generally been less likely to contain missing or invalid
information.

b) Overnight & Longitudinal Models
The specific census data which we mobilize in this report takes on a different form foreach of the two models of gap closure we employ. The overnight model of gap closure, which
envisions the gaps closing instantaneously in 2021, makes use of aggregate measures of
educational attainment for the national First Nations and non-Indigenous populations, as well as
aggregate employment rates and average employment incomes by educational attainment
category. This data is sourced directly from 2021 Census data tables available online. However,since the employment incomes reported in the 2021 census are measured in 2020 dollars (giventhat they are reported for the year 2020), these estimates must be rebased into 2015 dollars toallow comparison with data from the 2016 Census. To do this, we acquire the annual average allitems Consumer Price Index for 2020 (137.0) and 2015 (126.6) (Statistics Canada, 2023).
Dividing the 2015 CPI by the 2020 CPI gives us a rebasing factor of 92.41, indicating that theprice level in 2015 was about 92% of the price level in 2020. In other words, 1 Canadian dollar
in 2020 is equal to about 0.92 Canadian dollars in 2015 in terms of purchasing power. In order to7

find employment incomes in 2015 dollars, we simply multiply the 2020 figures by this rebasing
factor.
The longitudinal model of gap closure, meanwhile, simulates the gradual closure of thegaps over the 2021-2041 period. Estimates are obtained by producing projections of theCanadian economy and comparing these projections across a handful of different scenarios, witheach scenario utilizing different assumptions about how key gaps will progress between 2021
and 2041. A core distinction between the two models is that, while the overnight model closes
the employment rate and employment income gaps within educational categories at the
population level, the longitudinal model closes these gaps within groups defined by educational
attainment, age group, gender, and province/territory of residence. In other words, in thelongitudinal model, the conditional employment rate and employment income gaps are identified
by comparing First Nations and non-Indigenous people of the same age group, gender, andprovince/territory of residence. This is done to create a more accurate comparison between the
populations and to produce a more causal understanding of the effect of being First Nations on
an individual’s labour market performance.
Naturally, this more detailed approach requires more granular data, and in particular, data
which includes the gender, province/territory of residence, and approximate age of respondents.
In our previous report, the 2016 Census PUMF was utilized to this end, given that it features
highly detailed data on the census responses provided by individual Canadians. The
aforementioned age-gender-province/territory-education bins were constructed by aggregating
the individual-level data from the PUMF based on the values for these four variables.
With no PUMF available at the time of writing, we must take a slightly different
approach. Although the data tables viewable online on the Statistics Canada website are quite8

limited in detail, highly granular and much more flexible versions are available in the publicly
available .IVT files provided for each table. Using the Beyond 20/20 Professional Browser
program, the underlying data can be manipulated to produce complex cross-tabulations of many
variables.9 By filtering employment income and employment rate data based on the population ofinterest (First Nations or non-Indigenous), educational attainment level, age group, gender, andprovince-territory of residence, we are able to re-create the same set of bins which we used in thelongitudinal model of our previous report.10 However, in a sense, we are using the opposite
approach; rather than aggregating up from individual-level data, we are disaggregating downfrom national data. While the resulting data structure across these approaches is fundamentallyvery similar, there are some significant implications to this change in data preparation.

c) Tabular vs. Microdata
Census data in both PUMF form and cross-tabular form undergo a number of cleaning
and re-organizing procedures by Statistics Canada to ensure high levels of reliability andconfidentiality. However, given the differing structures and applications of the two forms of data,
there is some variance in these procedures and this can manifest in discrepancies between results

9

It is important to note that this cross-tabular data structure used for the longitudinal model of gap closure is derived
from the same tables as the higher-level data used in the overnight model. The difference lies a) in the level ofaggregation and b) in the variables used to define the groups that are ultimately compared to estimate the gains fromgap closure. However, as discussed in the “Tabular vs. Microdata” subsection, there are still small discrepancies
between the two levels of aggregation as a result of data cleaning and organizational choices.
10
There are some differences in the exact bins created due to changes in the categories available for certain
variables. These differences are discussed in detail later in this section. With that said, there is a great level ofcomparability between the bins created here and the bins created in our previous report, given that the underlying
variables are essentially very similar.

9derived from the different forms.11 Most notably, the Census 2021 cross-tabulations employ
rounding procedures to all cell values to protect the anonymity of respondents.12
While this has little impact at the national level, it has a more material effect on thelongitudinal model, where the number of individuals occupying a given age-sexprovince/territory-education bin, particularly for the First Nations population, can be extremely
small. The number of First Nations women in the territories in a given age group with auniversity degree above the bachelor level, for example, is never more than 50 and is 0 in manycases, according to the cross-tabular data. In such cases, rounding to the nearest multiple of 5 caninfluence the calculation of within-bin employment rates and average employment incomes. Thiscan hence influence the size of the gaps closed and ultimately our estimates for the magnitude ofbenefits which might result from gap closure. Still, we estimate the impact of these rounding
procedures to be small.

d) Variables
Following below is a list of the census variables which we are interested in for the
analysis provided in this report:-

Educational Attainment-

Employment Rates (# of employed persons / working age population)

11

Also of note is the fact that individual-level Census microdata only contains a proportion of total Census
respondents: 2.7% of respondents in the case of the 2016 PUMF. Responses are also anonymized through a variety
of procedures, including the construction of some synthetic respondents. Given that the total number of Census
respondents is extremely large, this sample is substantial and remains broadly representative of the Canadian
population. In contrast, the tabular data includes all Census respondents and therefore may be more representative insome respects than the individual-level microdata.
12
This means that disaggregated values do not always add up to the total aggregated values. For example, the total
First Nations working-age population in Canada in 2021 according to top-level Census data is 764,750. The same
statistic calculated by summing the population within each age-gender-province/territory-education bin, gives a totalof 763,840: a discrepancy of 910 individuals.

10-

Employment Incomes (for the year 2020)-

Employment (# of employed persons during reference week of May 2nd to May 8th,
2021)

-

Working Age Population (15+)-

Gender-Age Group-

Province/Territory of ResidenceThis set of variables is almost identical to those which were mobilized in the previous report,with the sole exception of gender, which has replaced the sex variable employed previously.
In prior censuses, respondents were exclusively asked for their sex and information ongender identity was not collected (Statistics Canada, 2017a; 2022c). Transgender and non-binary
individuals were instructed to simply choose the sex which they felt represented them best. In
2021, the Canadian Census separated sex and gender into two distinct concepts for the first time.
Respondents were asked both for their sex assigned at birth as well as their gender identity: avariable which now included a non-binary category in addition to male and female. This gendervariable is now presented in Statistics Canada census data tables in lieu of the sex variable.
However, in the interests of protecting the anonymity of census responses, the coding of thevariable in these tables has remained almost identical to the previous sex variable, featuring only
two categories: “Male+” and “Female+”.13 Any non-binary respondents have been distributed
into these two categories using an undisclosed “statistical method” (Statistics Canada, 2022a).
For these reasons, some caution should be exercised in comparing the estimates of thelongitudinal method between this report and our earlier report, given that our previous analysis

Results by gender are sometimes presented in this report using the “Male” and “Female” terminology. It should be
noted that these category names actually refer to the “Men+” and “Women+” categories described here.
13

11

involved controlling for sex and we instead control for gender in this report, which we view as
the best available substitute for the sex variable. Still, these two variables represent distinct
concepts and the relationship between them is not entirely clear, given the lack of a clear
sex/gender dichotomy in the 2016 Census questions and the absence of detail on how exactly the“Men+” and “Women+” categories are defined.
Although the remaining variables of interest have largely maintained the same concepts,
there have been several changes to the categories available which readers should note. Thesechanges pertain to the educational attainment variable, which measures the highest educational
credential received or completed by an individual. The 2016 Census data tables employed in theovernight model of the previous report feature a “University certificate, diploma or degree above
bachelor’s level” category. The 2021 Census data tables employed in both models of gap closurefor this report do not feature such a category, and hence it must be assembled manually by
combining four smaller categories.14 Moreover, the 2016 PUMF contained categories breaking
down the “College, CEGEP, or other non-university certificate or diploma” category into 3
separate categories with varying program lengths. These three smaller categories were used in
the longitudinal model of our previous report. However, such categories do not exist in the 2021
Census data tables. The longitudinal model in this report therefore only features a single category
for non-university certificates and diplomas, and thus only considers 7 educational attainment
categories as opposed to the 9 considered in our previous report. This slight methodologicaldifference contributes to differences between this report and our earlier report with respect to the14

A similar procedure was required in the longitudinal model of the previous report.

12

projections and estimated benefits of gap closure offered in the longitudinal model.15 Still, we
estimate the impact of this change to be small.

The State of the Gaps 16
Over the 2016-2021 period, the Canadian economy underwent significant transformation,with important implications for both the First Nations population and the non-Indigenous
population. Most obviously, in 2020, the global community was plunged into a worldwide
pandemic caused by the outbreak and propagation of the COVID-19 virus, and Canada was notspared from this turmoil. Policymakers instituted unprecedented public health measures leading
to sharp contractions in economic activity. The Canadian economy also underwent novel
structural changes such as the widespread adoption of tele-work and work-from-home schemes
and the onset of lasting labour shortages due to decreased labour force participation amongcertain groups. Some of these impacts were transitory, while others had deeper and more longlasting effects. The pandemic was, of course, far from the only economic event in this period.
New policies were introduced, like the federal price on carbon, while others, such as the
Canadian Environmental Assessment Act, were revised or repealed (Government of Canada,
2023a; 2023b); some longer-term trends, like rising levels of immigration into Canada, continued
mostly unabated, while others, like the persistent low-inflation environment of prior decades,
were disrupted by social and economic shocks (Government of Canada, 2023c; Statistics
Canada, 2022b).

15

This is a consequence of how employment and employment income are defined. See Footnotes 20 and 24 foradditional detail.
16
This section draws heavily on the “Understanding the Gaps” section of our previous report to explain and define
the gaps of interest (AFN, 2023).

13

For all of these reasons, it is of great interest to update our previous work on the
educational and labour market gaps faced by First Nations people in Canada. To this end, thefollowing section presents 2021 Census data on the educational attainment and labour market
performance of the First Nations population in Canada relative to the Canadian non-Indigenous
population. In short, although the average educational attainment of both populations has grown
substantially, greater rates of improvement within the non-Indigenous population have widened
the overall educational attainment gap between the two populations. Despite this, the First
Nations population has experienced significant gains in average employment incomes andemployment rates over the 2016-2021 period, and gaps in wages and rates of employment
between the two populations have reduced substantially.

a) The Education Gap: Distributional Approach
Of the three gaps considered in this report, the education gap is the most straightforward
in concept. It simply refers to the observation that, on average, First Nations peoples in Canada
tend to attain a lower level of education within their lifetime compared to non-Indigenous people
in Canada. However, the measurement of this gap is somewhat complicated. In this report, weoffer two measurement approaches: the distributional approach, which compares the proportionof both working-age populations which has a given level of educational attainment, and theaverage years approach, which estimates the number of years of education that the average
individual in each population has received and compares the resulting figures. We begin byassessing the state of the education gap through a distributional lens.

14

Table 1: Educational attainment for Working-age (15+) First Nations vs. non-Indigenous, 2021
High school
No educational diploma or
credential
equivalent

Total
First Nations
Working AgePopulation

Non-university
certificate or
diploma

University
below
bachelor's

Bachelor's
degreeUniversity
abovebachelor level

254,330

228,045

66,525

129,600

17,38550,355

18,515

33.3%

29.8%

8.7%

16.9%

2.3%

6.6%

2.4%

4,501,045

7,691,690

2,515,865

5,465,705

866,285

5,193,450

2,753,840

15.5%

26.5%

8.7%

18.9%

3.0%

17.9%

9.5%

Absolute Gap (NonIndigenous less First
Nations)-17.7pp-3.3pp

0.0pp

1.9pp

0.7pp

11.3pp7.1pp

First Nations as aproportion of NonIndigenous

214.2%

112.4%

100.2%

89.9%

76.1%

36.8%

25.5%

Proportion
Non-Indigenous
Working AgePopulation
Proportion

764,750

Apprenticeship ortrades certificate/
diploma

28,987,880

Relative Gap (1 - First-114.2pp-12.4pp-0.2pp10.1pp23.9pp63.2pp74.5ppNations as Proportionof Non-Indigenous)
Note: *pp = percentage points, negative numbers represent categories which First Nations people are more likely to occupy than non-Indigenous people
Source: Statistics Canada. Table 98-10-0451-01 Labour force status by highest level of education, Indigenous identity, age and gender: Canada, provinces andterritories, census metropolitan areas and census agglomerations with parts.

15

Table 2: Educational attainment for Working-age (15+) First Nations vs. non-Indigenous, 2016

Total

High school
No educational diploma or
credential
equivalent

Apprenticeship ortrades certificate/
diplomaNon-university
certificate or
diploma

University
below
bachelor's

Bachelor's
degreeUniversity
abovebachelor
level

First Nations
Working AgePopulation

691,405

Proportion

264,425

175,315

67,480117,785

15,52037,67013,210

38.2%

25.4%

9.8%

17.0%

2.2%

5.4%

1.9%

4,827,400

7,253,640

2,669,080

5,327,705

786,105

4,365,815

2,188,355

17.6%

26.5%

9.7%

19.4%

2.9%

15.9%

8.0%

-20.6pp

1.1pp

0.0pp

2.4pp

0.6pp

10.5pp6.1pp217.2%

95.8%

100.3%

87.7%

78.3%

34.2%

23.9%

-117.2pp

4.2pp-0.3pp12.3pp21.7pp65.8pp76.1ppNon-Indigenous
Working AgePopulation
Proportion
Absolute Gap (NonIndigenous less First
Nations)
First Nations as aproportion of NonIndigenous
Relative Gap (1 - First
Nations as Proportionof Non-Indigenous)

27,418,100

Note: *pp = percentage points, negative numbers represent categories which First Nations people are more likely to occupy than non-Indigenous people
Source: Statistics Canada, 2016 Census of Population, Statistics Canada Catalogue no. 98-400-X2016178.

16

Table 1 presents the educational attainment distribution for the First Nations and nonIndigenous working-age populations in Canada as observed in the 2021 Census. Under the
distributional approach, the education gap manifests as the gap in the proportion of the two
populations which occupy any given educational attainment category. The data presented inTable 1 indicates clearly that there were substantial gaps in the educational attainment levels of
the two populations in 2021. Table 2, meanwhile, presents the same distributions as observed in
the 2016 Census and as provided in our previous report, allowing us to compare the withincategory gaps over time and gauge whether progress has been made in closing them.

Box 1: Measuring the Education Gap — The Distributional Approach
We call this manner of measuring and analyzing the education gap the distributional
approach. In observing the distribution of educational attainment—the highest educational degree or
certification one has achieved—within the two populations, we see the share of each population
which falls into any given bin. We can then identify individual bins where the difference between theshares in the two populations is significant. The advantage of this approach is that it yields a series ofcategory-specific gaps rather than one aggregate gap. This increased granularity allows us to see
precisely which educational categories either population is concentrated in, and therein develop abetter understanding of the nature of the gap. The trade-off to this precision comes in the form oftractability though; comparing these gaps over time is cumbersome and the results of this approach
are more difficult to grasp and visualize than an approach which produces a single gap.

As we observed in our previous report, gaps in educational attainment are concentrated at
the top and bottom of the educational attainment distribution; the three categories in the middleof the educational attainment distribution – “apprenticeship or trades certificate/diploma”, “nonuniversity certificate or diploma”, and “university below bachelor’s” – do not show particularly
large gaps between the two populations, nor has there been significant movement in these17

categories since 2016. The largest disparity between the two populations occurs in the “noeducational credential” category; about 33% of the First Nations population reports having nosuch credential compared to only about 16% of the non-Indigenous population. In other words,
working-age First Nations people are more than twice as likely as non-Indigenous people to haveno educational credentials. Compared to 2016 though, the gap in this category has closed
somewhat in both absolute terms (20.6 percentage point difference in 2016 vs. 17.7 percentage
points in 2021) and relative terms (First Nations proportion as 217.2% of the non-Indigenous
proportion in 2016 vs. 214.2% in 2021).17 Still, the gap in this category remains very substantial.
In contrast, the gap in the “high school diploma or equivalent” category has actuallygrown since 2016. However, interpreting this change is not so simple. The proportion ofworking-age First Nations people occupying this category has increased somewhat, from 25.4%
in 2016 to 28.9%. in 2021. The proportion of the working-age non-Indigenous population,
meanwhile, has stayed essentially static at 26.5%. As such, the direction of the gap in thiscategory has reversed from 2016 to 2021; where previously non-Indigenous people were more
likely to report a high school diploma or equivalent as their highest level of education, now First
Nations people are more likely to do so. Furthermore, the absolute size of the gap has actuallygrown since 2016, from 1.1 percentage points in 2016 to 3.3 percentage points in 2021. In one
sense, this reversal is a positive development for the First Nations population; given thesubstantial fall in the proportion of First Nations with no educational credentials at all, it seems
that this represents an upward movement for the population in terms of educational attainment.

17This decrease in the relative size of the gap may seem unexpectedly small compared to the more substantial
reduction in the absolute size of the gap. It is important to note that there are two effects at play here: the reductionin the share of First Nations people in the category and the reduction in the share of non-Indigenous people in the
category. If the non-Indigenous share were to remain the same, the effect on the relative size of the gap would bemuch more pronounced.

18

At the same time, the “high school diploma or equivalent” category still represents a relatively
low level of educational attainment. Hence, all else equal, it would not be particularly
encouraging to see a substantial gap develop in this category and in this direction, given that it
would suggest First Nations people are not moving forward to attain even higher levels of
education.
The “bachelor’s degree” category continues to be a site of considerable disparity between
the two populations in 2021. Only 6.6% of the First Nations population reported having abachelor’s degree as their highest credential compared to 17.9% for the non-Indigenous
population: a gap of 11.3 percentage points, with non-Indigenous people being almost threetimes as likely as First Nations people to occupy this category. Both populations have seen
growth in this category. The proportion of First Nations people occupying the category has
grown by about 1.2 percentage points or about 22% since 2016. On the other hand, theproportion of non-Indigenous people in the category grew by 2.0 percentage points or about
13%. As such, the relative gap between the two populations in this category has shrunk – theFirst Nations proportion is about 37% in 2021 compared to 34% in 2016 – though the absolute
gap has risen by 0.8 percentage points (11.3 in 2021 vs. 10.5 in 2016).
Similar trends are observed in the “university above bachelor level”: a category that
includes certificates and diplomas above the bachelor level, as well as medical, dental andveterinarian degrees, master’s degrees, and earned doctorates. In 2021, 2.4% of First Nations
people have a credential in this category, up about 21% since 2016. However, such credentials
are still much more common in the non-Indigenous population, with about 9.5% of nonIndigenous people having a certificate, diploma, or degree of this kind: a 19% increase since2016. As we observed in the bachelor’s degree category, though the gap between the populations

19

has slightly fallen in relative terms, it has grown in absolute terms, from about 6 percentage
points in 2016 to 7 percentage points in 2021.

Chart 1: First Nations Educational Attainment Shares as a Proportion of nonIndigenous Shares (Age 15+), 2016 & 2021

250%

217.2%

214.2%

200%

2016
150%
95.8% 112.4%

100%

2021
100.3%
100.2%

87.7% 89.9%

78.3% 76.1%

34.2% 36.8%

50%

23.9% 25.5%

0%
No educational
credential

High school
diploma or
equivalent

Apprenticeship Non-university
or trades
certificate orcertificate/
diploma
diploma

University
below
bachelor's

Bachelor's
degreeUniversity
above bachelor
level

Sources: a) Statistics Canada. Table 98-10-0451-01 Labour force status by highest level of education, Indigenous identity, age and gender: Canada,
provinces and territories, census metropolitan areas and census agglomerations with parts; b) Statistics Canada, 2016 Census of Population, Statistics
Canada Catalogue no. 98-400-X2016268.

Chart 1 depicts the share of First Nation individuals in each educational attainment
category as a proportion of the same share in the non-Indigenous population for both 2016 and2021. The chart thus reflects the relative gap in each category. As the chart shows, there is afairly consistent pattern across the educational attainment categories, where the size of the First
Nations share relative to the non-Indigenous share tends fall lower as the educational attainment
category becomes higher. In fact, the pattern becomes even more consistent in 2021 with thesubstantial increase in the proportion of the First Nations population occupying the “high school
20diploma or equivalent” category. The chart confirms a few key observations from our analysis
above. In particular, we can see that the movements in the distribution between 2016 and 2021
occur mostly at the very bottom, in the no credential and high school categories, and at the very
top, in the bachelor’s and university above bachelor categories.

b) The Education Gap: Average Years Approach

Table 3: Average Years of Education for First Nations vs. non-Indigenous, 20062021
Gap(absolute)

Average Years of Education

2006
2011
changecompound annual
growth rate
2016changecompound annual
growth rate2021
changecompound annual
growth rate
2006-2021 periodchangecompound annual
growth rate

First Nations as
proportion of
non-Indigenous(4)

Gap(relative)(5) = 1.00 (4)First Nations
11.72
11.93
0.20

Non-Indigenous
13.00
13.23
0.22

1.28
1.30
0.02

90.16%
90.15%-0.01pp9.84pp9.85pp

0.34%
12.07
0.15

0.34%
13.34
0.11

0.35%
1.26
-0.04

90.53%
0.38pp

9.47pp

0.25%
12.24
0.16

0.16%
13.53
0.19

-0.63%
1.29
0.03

90.45%-0.08pp9.55pp

0.27%

0.29%

0.46%

0.51

0.53

0.01

0.29%

0.26%

0.06%

0.29ppNote: pp = percentage point
Sources: a) Statistics Canada. Table 98-10-0451-01 Labour force status by highest level of education, Indigenous identity, age andgender: Canada, provinces and territories, census metropolitan areas and census agglomerations with parts; b) Statistics Canada, 2016
Census of Population, Statistics Canada Catalogue no. 98-400-X2016178; c) Statistics Canada, 97-560-XCB2006036, 2006; d) Statistics
Canada, 2011 National Household Survey, Statistics Canada Catalogue no. 99-012-X2011044.

Table 3 presents the results of the average years approach of measuring educational
attainment for the 2006, 2011, 2016, and 2021 censuses as well as measures of the gap in
attainment between the First Nations and non-Indigenous populations for each year. The table21

also offers rates of improvement in the average years of education between each census year. We
estimate that the average First Nations person in 2021 has 12.24 years of education: an increaseof 0.16 years compared to 2016. The average non-Indigenous person in 2021 is estimated to havereceived 13.53 years of education, indicating an increase of 0.19 years compared to 2016. Thisimplies a gap of 1.29 years–marginally higher than the gap of 1.26 years recorded in 2016.
Essentially, the average educational attainment of both populations increased significantly
between 2016 and 2021, however the rate of improvement for non-Indigenous people wasslightly higher over the period (0.29% annually for non-Indigenous people compared to 0.27%
annually for First Nations people). As a result, the First Nations average years of education as aproportion of the non-Indigenous figure – a measure which had increased substantially over theprevious period – fell from 90.53% in 2016 to 90.45% in 2021. Still, it should be noted that therate of improvement in educational attainment for First Nations people actually grew between
the previous period and the 2016-2021 period, from 0.25% to 0.27%. The non-Indigenous rate of
improvement increased substantially more though, rising from 0.16% in the 2011-2016 period to
0.29% in the 2016-2021 period. With that said, the rates of improvement for both populations
still do not live up to the high rates recorded for the 2006-2011 period.

22Box 2: Measuring the Education Gap — The Average Years Approach
We call this the average years approach to measuring the education gap. Each educational
category is assigned a single value representing the expected number of years of schooling required toobtain that credential. The average years of education of a population is derived simply by taking thearithmetic mean of each individual’s assigned years of education value. This allows us to describe thegap as the simple difference in the average years figure between the two populations. The coding
scheme of the average years variable is described below:
Educational Attainment Category

Assigned Value

No certificate, diploma or degree

10 years

Secondary (high) school diploma or equivalency

12 yearscertificate
Apprenticeship or trades certificate or diploma

13 years

College, CEGEP or other non-university certificate or

14 years

diploma
University certificate or diploma below bachelor level

15 years

Bachelor's degree

16 years

University certificate, diploma or degree above bachelor

18 yearslevel
The advantage of this approach is that, unlike the distributional approach, it produces a single
numerical measurement of the education gap that is simple to transform or compare over time. Thisusability comes at the price of precision, however. As the mean is a very narrow representation of its
underlying distribution, the measure produced by this approach tells us little about the shape of theeducation gap. Indeed, it is conceivable that two very distinct distributions of educational attainment
might produce the same average years of education value, indicating no education gap at all, evenwhen the distributional approach suggests significant category-specific gaps. Knowing that the
average years of education in a population is 14, for example, does not tell us anything about the
spread of individuals across categories. The distribution could be polar, with individuals either
occupying the very low or the very high categories but largely avoiding the middle categories.
Alternatively, the distribution could be tightly clustered around the middle categories, with very few
individuals inhabiting either end of the range. Fundamentally, the mean does not provide us withenough information to distinguish between these two
23 distributions.

Table 4: Trends in Convergence of Average Educational Attainment Levels, 20062021
First Nations Average
Years of Education
Growth Rate
0.29%
0.27%

Scenario
2006-2021 trend
2016-2021 trend
2006-2021 trend
holding NI
0.29%
constant
2016-2021 trend
holding NI
0.27%
constant
Estimates from Previous Report0.25%
2011-2016 trend
2011-2016 trends
w/ static NI levels

0.25%

Non-Indigenous
Average Years of
Education
Growth Rate
0.26%
0.29%

Non-Indigenous (NI) Education…
Grows
Grows

Years toConvergence461
No convergence

No Growth

Stays at 2021 levels

35

No Growth

Stays at 2021 levels

37

0.16%

Grows

117

No Growth

Stays at 2016 levels

40

Sources: a) Statistics Canada. Table 98-10-0451-01 Labour force status by highest level of education, Indigenous identity, age and gender: Canada,
provinces and territories, census metropolitan areas and census agglomerations with parts; b) Statistics Canada, 2016 Census of Population, Statistics
Canada Catalogue no. 98-400-X2016178; c) Statistics Canada, 97-560-XCB2006036, 2006; d) Statistics Canada, 2011 National Household Survey, Statistics
Canada Catalogue no. 99-012-X2011044.

Table 4 leverages the estimated rates of improvement in average years of education toproject the future progression of the educational attainment gap under a number of different
scenarios. As shown in Table 3, the rate of improvement for the non-Indigenous population
between 2016 and 2021 exceeded the rate of improvement for the First Nations population
during the same period. Given that the non-Indigenous population already receives more years ofeducation on average, this implies that, should these trends continue into the future, theeducation levels of the two populations will never converge.
This is a significant change from our findings when conducting the same exercise using
the 2011-2016 trends in educational attainment, as we did in our previous report. Extrapolatingbased on these rates finds convergence in average years of education after 117 years – still an
extremely long time to be sure, but certainly less bleak than the results found when using 20162021 rates of improvement. This reflects the fact that the First Nations average years of24

education grew significantly faster during the 2011-2016 period than the average years ofeducation for the non-Indigenous population (0.25% for First Nations people vs. 0.16% for nonIndigenous people). As another point of comparison, convergence is found to happen after an
estimated 461 years when using the longer-term rates of improvement for the 2006-2021 period.
Again, over this period, growth in the First Nations average years of education outpaces growthin the non-Indigenous figure, though the difference is less stark in this case (0.29% for the First
Nations population vs. 0.26% for the non-Indigenous population).
Admittedly, this assumption of constant rates of improvement is somewhat unrealistic.
Within the educational attainment categories used by the Canadian Census, there is a highest
category and thus a ceiling to attainment; there is no educational attainment level above the“university above bachelor’s” category and 18 years is the maximum years of education an
individual can possess As such, it seems likely that a highly-educated population like the nonIndigenous population should at some point confront a limit to educational attainment growth; as
more individuals move into higher and higher educational attainment categories, this leaves lessfor growth in the population as a whole. Moreover, there will always be a need for individuals
with lower levels of education in the workforce. At a certain point, one would expect thisdynamic to manifest in diminishing rates of improvement for the non-Indigenous population.
Given that the First Nations population starts a markedly lower level of average educational
attainment, this ‘ceiling effect’ would not impact First Nations rates of improvement, allowing
for the First Nations population to ‘catch up’ and the gap to close.
An alternative framework attempts to capture this idea of diminishing returns to growthin educational attainment growth by assuming that the non-Indigenous population has alreadyreached a ceiling. Under this scenario, the average years of education for First Nations people25continues to improve at the rate observed over the 2016-2021 period, but the average years ofeducation for the non-Indigenous population remains static at 2021 levels. Under such a
scenario, the gap in average years of education is closed in 37 years. This is slightly lower thanour estimate 40 years in the previous report, reflecting small improvement in the First Nations
rate of improvement from the 2011-2016 period to the 2016-2021 period. Ultimately, neither ofthese frameworks provides a particularly realistic projection of gap closure. Rather, they areintended as upper and lower bounds, calculated using extreme assumptions about how the gap in
educational attainment between the two populations might progress. Still, they provide a stark
look at the possible persistence of the educational attainment gap, should policymakers andcommunity leaders not take substantial action to improve levels of educational attainment within
the First Nations population.

26

27

Table 5: Average Employment Income for Working Age (15+) First Nations People vs. non-Indigenous People,
2020 (2015 dollars)

TotalHigh school
No educational diploma or
credential
equivalent

Apprenticeshipor trades
Non-university
certificate/certificate or
diploma
diploma

University below Bachelor'sbachelor's
degreeUniversity above
bachelor level

First Nations$36,927$30,162$29,164$41,140$40,105$42,286$55,122$70,889

Non-Indigenous$46,796$24,544$32,898$44,282$45,059$46,389$61,544$77,018

Absolute Gap(Non-Indigenous
less First
Nations)

9,869- 5,618

3,733

3,142

4,953

4,103

6,422

6,129

78.9%

122.9%

88.7%

92.9%

89.0%

91.2%

89.6%

92.0%

21.1pp-22.9pp11.3pp

7.1pp

11.0pp

8.8pp

10.4pp8.0pp

First Nations as
a proportion of
Non-Indigenous
Relative Gap (1 First Nations as
Proportion of
Non-Indigenous)

Note: pp = percentage point; employment incomes in the 2021 Census are reported for the year 2020; average employment income is calculated for all individuals who
had a positive, non-zero employment income in 2020.
Sources: a) Statistics Canada. Table 98-10-0427-01 Employment income statistics by Indigenous identity and highest level of education: Canada, provinces andterritories, census metropolitan areas and census agglomerations with parts; b) Statistics Canada. Table 18-10-0005-01 Consumer Price Index, annual average, notseasonally adjusted.

28

Table 6: Average Employment Income for Working-Age (15+) First Nations People vs. non-Indigenous, 2015
(2015 dollars)No
educational
credential

High school
diploma or
equivalent

Apprenticeshipor trades
certificate/
diploma$33,079$21,260$28,170$39,549$46,449$25,526$33,960

13,370

4,266

71.2%

28.8pp

Total
First Nations
Non-Indigenous
Absolute Gap(NonIndigenous lessFirst Nations)First Nations as
a proportion of
Non-Indigenous
Relative Gap (1- First Nations
as Proportion of
NonIndigenous)

Non-university
certificate or
diploma

University
below
bachelor's

Bachelor's
degreeUniversity
abovebachelor level$38,570$41,509$52,997$68,480$45,072$45,805$47,710$62,485$79,110

5,790

5,523

7,235

6,201

9,488

10,630

83.3%

83.0%

87.7%

84.2%

87.0%

84.8%

86.6%

16.7pp17.0pp12.3pp15.8pp13.0pp15.2pp13.4ppNote: pp = percentage point; employment incomes in the 2016 Census are reported for the year 2015; average employment income is calculated for all individuals who
had a positive, non-zero employment income in 2015.
Source: Statistics Canada, 2016 Census of Population, Statistics Canada Catalogue no. 98-400-X2016268.

29c) The Income Gap Conditional on Education
The income gap conditional on educational attainment is defined as the difference in the
average employment incomes earned by First Nations people and non-Indigenous people withthe same level of educational attainment. As we observed in our previous report, First Nationsindividuals earn lower incomes on average than non-Indigenous individuals in addition to having
a lower average level of educational attainment. In 2020, the average employment income forFirst Nations people was $36,927 while the average employment income for non-Indigenous
people was $46,796: an absolute gap of $9,869, with First Nations people earning 78.9 percent ofwhat non-Indigenous people earn, on average.18
The core variable which we are most interested in as we grapple with this gap in earnings
is the level of educational attainment. As seen in the previous subsection, the distribution of
educational attainment differs between First Nations people and non-Indigenous Canadians, and
it is likely, given the positive relationship between education and earnings, that differing levelsof education between the two groups is the primary driver of the income gap we observe. For thisreason, we are not particularly interested in the aggregate income gap as we estimate thepotential economic benefits of boosting the labour market performance of First Nations people.
Rather, we are interested in the income gap conditional on, or controlling for, the level of
education. Put simply, we are asking: what is the difference between the earnings of First
Nations individuals and non-Indigenous individuals when we only compare individuals with thesame level of educational attainment?

18

Although these figures are sourced from the 2021 Census, income data in the Census is always reported for theprior year. Hence, the gaps measured here are for 2020.

30

Table 5 shows the income gap conditional on each level of education in 2020.19 When
comparing within educational categories, the income gap is apparent in all categories except for
the “no educational credential” category where the average employment income earned by First
Nations people actually exceeds what is earned by non-Indigenous people. This category is astark outlier however, as average non-Indigenous earnings exceed average First Nations earnings
in every other category. Notably, the absolute gap is highest within the highest educational
attainment categories, although the relative gap is fairly consistent across the distribution. The
highest absolute gap is observed in the “bachelor’s degree” category where First Nations people
earn $6,422 less on average than non-Indigenous people. Conversely, the smallest absolute gap
occurs in the “apprenticeship or trades certificate/diploma” category where First Nations people
earn $3,142 less on average than their non-Indigenous counterparts. The largest relative gap
occurs in the “high school diploma or equivalent” category where the average employment
income for First Nations people is a little less than 89% of the average employment income
earned by First Nations people. The category with the smallest relative gap is again the“apprenticeship or trades certificate/diploma” where First Nations people earn about 93% ofwhat non-Indigenous people earn on average.

19

Gains in First Nations average employment incomes between 2015 and 2020 should be interpreted with somecaution. Some degree of the improvement in employment incomes for First Nations people may simply reflectchanges in reporting behaviour and collection procedures. Notably, in 2019, the Canada Revenue Agency introduced
the T90 form to capture income earned by First Nations people that is tax-exempt under the Indian Act. As a result,official income statistics from 2015 and 2020 are not perfectly comparable. The decision to use administrative tax
and benefit data to derive income statistics may also contribute to the discrepancy, but only to the extent that it
affects data on First Nations earnings differently than data on non-Indigenous earnings. Finally, the observed gains
in average employment income might not be representative of the situation of the typical First Nations person; gains
in median employment income over the period were generally less substantial, and among those with “noeducational credential”, the median income remains higher for non-Indigenous people than for First Nations people.
This indicates that employment income gains may have been concentrated towards the top of the First Nations
income distribution, distorting the average. Altogether, these factors suggest that the true income gap remains larger
than is shown in Table 5 and hence that our estimates for the gains from gap closure are likely to be underestimates.

31

Excluding the “no educational credential” category, the First Nations population tends toearn between 88% and 92% of what non-Indigenous people earn when controlling for
educational attainment. Similarly, the absolute gap within categories ranges from about $3,700 toabout $6,500 when we control for educational attainment. These figures are substantially lower
compared to the aggregate gap across categories, in which First Nations earn only 78.9% of what
their non-Indigenous counterparts earn and face an absolute gap of $9,869. The fact that the sizeof the gap falls so substantially when we control for educational attainment is a testament to theparamount importance of educational attainment in reducing the employment income gap
between the two populations; based on these figures, between 35% and 62% of the aggregate
employment income gap is attributable to differences in educational attainment across the two
populations.
For comparison, Table 6 presents the income gap conditional on level of education in
2015. Here, the aggregate gap in average employment incomes between the two populations is$13,370. Over the 2015-2020 period, this gap has fallen by an impressive 26.2%. Again, when
educational attainment is controlled for, the gap we observe in average employment income
between the two populations becomes considerably smaller. Across educational categories, First
Nations people in 2015 are found to make 71.2% of what non-Indigenous people make.
However, when we compare within educational attainment categories, First Nations people arefound to enjoy an average employment income that is between 83% and 88% percent of theaverage employment income of non-Indigenous Canadians. In 2020, this has improved by about
4 to 5 percentage points for most educational attainment category: a very significant
improvement in the income gap conditional on educational attainment over the 2015-2020
period.

32

The largest within-category improvement between 2015 and 2020 occurs in the “noeducational credential” category where First Nations average employment income has increasedby almost $9,000 and the direction of the gap has actually reversed. Again, this category is anextreme outlier though. The next largest improvement in absolute terms occurred in the“university above bachelor level” category where the First Nations average wage increased by$2,419 over the 2015-2020 period; the absolute gap closed by even more in this category due tothe non-Indigenous average wage falling in real terms. In relative terms, the next mostsubstantial improvement occurs in the “apprenticeship” category where the First Nations average
wage as a proportion of the non-Indigenous average wage rose from 87.7% in 2015 to 92.9% in
2020: an improvement of 5.2 percentage points.
Overall, the aggregate average employment income gap has seen a significant decrease
between 2015 and 2020. The within-category gaps have also decreased for all levels of
educational attainment, and hence, the employment income gap conditional on education has
closed substantially. It is worth noting that employment incomes were affected by the pandemic
and subsequent lockdown measures, with working hours, and thus employment incomes,
impacted for many individuals. For the pandemic to have modified the income gap though, itwould have had to affect First Nations persons in a distinct manner relative to non-Indigenous
persons. This might be plausible if the two populations exhibited significantly different working
behaviours at the time of pandemic (e.g. one population was more likely to work in-person andin-office). Nevertheless, the gains observed over the 2015-2020 period suggest meaningfulprogress has been made in closing the disparity in earnings faced by First Nations people relative
to non-Indigenous people and in equalizing labour market conditions across the two populations

33

more broadly. Further action is still required though, as evidenced by the substantial gap thatremains in the average earnings of the two populations.

34

Table 7: Employment Rates for Working Age (15+) First Nations People vs. non-Indigenous People, 2021

Total

No
educational
credential

High school
diploma or
equivalent

Apprenticeshipor trades
certificate/
diplomaNon-university
certificate or
University below Bachelor's
diplomabachelor's
degreeUniversity
abovebachelor level

First Nations
Working Age Population

764,750

254,330

228,045

66,525

129,600

17,38550,355

18,515

Employed Persons
Employment Rate

354,005
46.3%

63,46025.0%

109,280
47.9%

38,985
58.6%

80,92062.4%

10,53560.6%

36,71072.9%

14,115
76.2%

Working Age Population 28,987,880
Employed Persons 16,641,270
Employment Rate
57.4%

4,501,045
1,369,065
30.4%

7,691,690
3,914,550
50.9%

2,515,865
1,563,200
62.1%

5,465,705
3,536,395
64.7%

866,285
529,93061.2%

5,193,450
3,715,905
71.5%

2,753,840
2,012,225
73.1%

Non-Indigenous

Absolute Gap (NonIndigenous less First
Nations)

11.1pp

5.5pp

3.0pp

3.5pp

2.3pp

0.6pp

-1.4pp-3.2ppFirst Nations as aproportion of NonIndigenous

80.6%

82.0%

94.2%

94.3%

96.5%

99.1%

101.9%

104.3%

Relative Gap (1 - First
Nations as Proportion of
Non-Indigenous)

19.4pp18.0pp

5.8pp

5.7pp

3.5pp

0.9pp

-1.9pp-4.3ppNote: pp = percentage point
Source: Statistics Canada. Table 98-10-0451-01 Labour force status by highest level of education, Indigenous identity, age and gender: Canada, provinces and territories,
census metropolitan areas and census agglomerations with parts

35

Table 8: Employment Rates for Working Age (15+) First Nations People vs. non-Indigenous People, 2016

Total

No
educational
credential

High school
diploma or
equivalent

Apprenticeshipor trades
certificate/
diplomaNon-university
certificate or
University below Bachelor's
diplomabachelor's
degreeUniversity
abovebachelor level

First Nations
Working Age Population

691,405

264,425

175,315

67,480117,785

15,52037,67013,210

Employed Persons

323,685

67,635

91,11538,71577,34010,07028,645

10,160

Employment Rate

46.8%

25.6%

52.0%

57.4%

65.7%

64.9%

76.0%

76.9%

Working Age Population 27,418,100

4,827,400

7,253,640

2,669,080

5,327,705

786,105

4,365,815

2,188,355

Employed Persons 16,592,130

1,617,050

4,178,585

1,736,750

3,722,625

500,535

3,238,840

1,597,750

60.5%

33.5%

57.6%

65.1%

69.9%

63.7%

74.2%

73.0%

13.7pp

7.9pp

5.6pp

7.7pp

4.2pp

-1.2pp-1.9pp-3.9pp

77.4%

76.4%

90.2%

88.2%

94.0%

101.9%

102.5%

105.3%

22.6pp23.6pp

9.8pp

11.8pp

6.0pp-1.9pp-2.5pp-5.3ppNon-Indigenous

Employment Rate

Absolute Gap (NonIndigenous less First
Nations)
First Nations as aproportion of NonIndigenous
Relative Gap (1 - First
Nations as Proportion of
Non-Indigenous)

Note: pp = percentage point
Source: Statistics Canada, 2016 Census of Population, Statistics Canada Catalogue no. 98-400-X2016267.

36d) The Employment Rate Gap Conditional on Education
First Nations people tend to experience rates of employment which are substantially lower
than those experienced by non-Indigenous people.20 The conditional employment rate gap isdefined as the difference in the employment rates experienced by First Nations people and nonIndigenous people with the same level of educational attainment. The employment rate of agiven population can be expressed as 𝐸/𝑊𝐴, where 𝐸 represents the number of employedpersons within the population and 𝑊𝐴 represents the number of working-age individuals within
the population. It expresses the population that is presently employed as a proportion of thebroader population that could be employed. As such, it is sometimes interpreted as a sort ofcomposite measure, capturing both the rate of unemployment and the rate of labour force
participation within a given population. 21 Both factors are expressed through 𝐸, the numerator of
the equation. Holding the size of the population constant, as unemployment rises, logically, the20

There are two primary ways of measuring employment using the data provided by the 2021 Census. Most
obviously, we can use the number of employed people. This number is based on a Census question which asks
respondents if they worked during the week that the Census was conducted (May 2nd to May 8th in 2021). Thisapproach may thus exclude seasonal workers or people who, for whatever reason, did not work during the reference
week, but were working at other points in the year. This method yields an employment rate of 57.1% for Canadiansin 2021. The other, broader approach classifies any person who reports a non-zero sum for their employment income
as employed, though this is for the year 2020, as employment incomes in the Census are reported for the year prior.
This method yields an employment rate of 69.6% for Canadians. While the first approach may suffer from being too
limited, this approach risks being overly inclusive. Individuals who worked even a single hour within a year will beclassified as employed, occupying the same category as individuals who work 40 hours a week year-round. For thisreport, we have chosen to use the first approach, referring to the employment rates and numbers provided by
Statistics Canada. This approach is certainly not without its flaws, however we feel it is a better approximation of
long-term employment, which is the form of employment we are most interested in.
21
The employment rate of a population can be decomposed as follows:𝑒=𝐸
𝐿 − 𝑈 𝑃 ∗ 𝑊𝐴 − 𝑈 (𝐸 + 𝑈) − 𝑈
=
=
=
𝑊𝐴
𝑊𝐴
𝑊𝐴
𝑊𝐴

where e is the employment rate, E is the number of employed persons in the population, WA is the working age
population (the number of individuals above 15 years old in this context), L is the labour force or the number ofpeople who are either working or actively looking for work, U is the number of unemployed persons in the
population, and P is the labour force participation rate of the population or the proportion of the working age
population that is in the labour force.

37

number of employed persons should fall, and the employment rate therein. Similarly, as the
proportion of the population who are working or looking for work (i.e., the ‘labour force’) rises,
the number of employed persons is also likely to rise, with the employment rate to follow. The
employment rate captures both of these dimensions and it can therefore be a useful tool formeasuring the labour market performance of a population in broad terms.
Table 7 presents measures of the employment rate gap between First Nations peoples andnon-Indigenous Canadians for each level of educational attainment in 2021. First Nations people
experienced an overall employment rate of 46.3% while non-Indigenous people experienced arate of 57.4%: an absolute gap between of 11.1 percentage points, with First Nations people
experiencing a rate that is 80.5 percent of the non-Indigenous rate. However, this aggregate gap
is significantly higher than what we observe within educational attainment categories. When
comparing between First Nations people and non-Indigenous people of the same educational
attainment level, the gap in employment rates ranges from 0.6 percentage points to 6 percentage
points, depending on the category. This suggests that differences in the educational attainment of
the two populations are responsible for between 46% and 95% of the overall absolute gap in
employment rates between the two populations. The same relationship is observed when using
relative measures of the gap. When we do not control for educational attainment, theemployment rate experienced by First Nations peoples is 80.6 percent of the rate experienced by
non-Indigenous Canadians. However, when we control for the level of educational attainment,
the employment rate of First Nations peoples as a percentage of non-Indigenous Canadians is
between 82.0 percent and 104.3 percent. Overall, the difference in educational attainment
between the two populations is found to be a significant driver of the overall gap in employment
rates.

38

As expected, First Nations people face lower rates of employment than non-Indigenous
people in most educational categories. The largest within-category gap in employment rates isfound in the “no educational credential”, where despite earning significantly higher wages thannon-Indigenous people, First Nations people face an employment rate that is 5.5 points lower
than the non-Indigenous figure. This is also the largest gap in relative terms, with the First
Nations rate making up just 82% of the non-Indigenous rate. Still, across the educational
attainment distribution, a fairly consistent pattern can be seen where within-category gaps tend tobe smaller at higher educational categories, with the gap outright reversing at the highest
categories. That is to say, First Nations people with a credential at or above the bachelor level
actually experience higher rates of employment than non-Indigenous people. This reinforces our
finding from our previous report that increased educational attainment is instrumental in
reducing the aggregate employment rate faced by First Nations people. These categories withreversed gaps, though, are likely a product of distributional differences in age across the two
populations. The average age of the First Nations population is significantly lower than that of
the non-Indigenous population and this holds true at the highest levels of educational attainment,with highly educated First Nations people being younger on average than highly-educated nonIndigenous Canadians (Statistics Canada, 2022e). Individuals tend to become less inclined towork as they approach retirement age, and individuals in these categories are more likely to beadvanced in age, having completed many years of schooling. Hence, it seems likely that thisdifference in the demographic characteristics of the two populations is driving the inverted gap
that we observe in the top two educational categories.
Table 8 presents data on the conditional employment rate gap from 2016. Since 2016,
rates of employment have fallen for both the First Nations population and non-Indigenous

39

population. This is likely due to the impacts of the pandemic, which were still being felt in May
of 2021, when the 2021 Census was conducted. With that said, the effect is more pronounced for
non-Indigenous people; the employment rate for non-Indigenous people has fallen by 3.1 points
since 2016, while the First Nations rate has fallen by just 0.5 points. As a result, the aggregate
gap in employment rates, which was 13.7 points in 2016, has closed by about 19%. Similar
progress has been seen within educational attainment categories -- in particular, the three lowest
educational categories. The gap in the “no educational credential”, for example, has seen adecrease in the gap of 2.4 percentage points, from 7.9 points in 2016 to 5.5 points in 2021. The
second lowest level, the “high school diploma or equivalent” category, has seen a decrease of 2.6
percentage points, from 5.6 points to 3.0 points. The “apprenticeship or trades
certificate/diploma” category has seen the largest decrease in the conditional employment rategap, falling by 4.2 points since 2016, from 7.7 points to 3.5 points. In contrast, in the top three
categories – where First Nations people had experienced a higher employment rate than theirnon-Indigenous counterparts in 2016 – the gap has shrunk somewhat, moving in the direction ofparity between the populations.
Overall, the employment rate gap between the two populations has improved
significantly over the 2016-2021 period, both in aggregate and within educational attainment
categories. Although employment rates have fallen for both populations, they have generally
fallen farther for non-Indigenous people, and as a result, the gap has shrunk meaningfully. It is
possible that these gains are due, in part, to the pandemic. However, this would require the First
Nations population and the non-Indigenous population to be impacted in systematically different
ways by the pandemic shocks. In any case, First Nations people continue to experience
employment rates that are generally lower than those experienced by non-Indigenous people,

40

indicating that there is still significant work to do in equalizing labour market conditions acrossthe two populations.

Methodology – Overnight Model 22
As with our previous report, a core objective of this report is to estimate the economic
benefits that would accrue a) to First Nations people and b) to Canadians generally if these threegaps – the educational attainment gap, the conditional income gap, and the conditional
employment gap -- were to be closed. As part of this estimation process, we will assess theimpact of closing each of the three gaps individually, as well as the cumulative impact of closing
all three gaps simultaneously. The primary metric which we use to estimate these benefits is thetotal employment income generated by the closure of a gap. Total employment income is simply
the sum of the earnings from employment of all individuals in a population, usually a national
economy; it has a close relationship with output, with the growth rates of the two measures being
inextricably linked. Moreover, total employment income comprises about half of GDP. Our
methodology for these estimates is fairly simple, and this section outlines the specific procedure
we perform to simulate the closing of each gap as well as for all three gaps simultaneously.

a) Closing the Education Gap
Our definition of closing the education gap entails adjusting the share of the First Nations
population in any given educational attainment category in such a way that it exactly matches theshare of the non-Indigenous population in that category. This results in the average years of
22

This section draws heavily on the methodology section of our previous report, given the great similarity between
the reports in methods used (AFN, 2023). Descriptions of methodological procedures are altered where necessary toreflect changes to the estimation strategies used.

41

education, as calculated in this study, becoming identical across both populations. To simulate
the closure of the education gap, we simply replace the proportion of First Nations people in any
given educational attainment category with the proportion of non-Indigenous people in thatcategory. To produce an estimate of the economic benefits of that change, we compare the total
employment income of a) First Nations people and b) Canadians before and after the closure of
the gap. This entails recalculating the total employment income of First Nations people using the
average earnings by category of educational attainment (Table 5), and the non-Indigenous
educational attainment shares (Table 1).
We first estimate the total employment income of First Nations individuals before theclosure of the gap by multiplying the number of employed First Nations individuals in eacheducational category by the average employment income in that category.23 To calculate total
employment income after the closure of the gap, we simply repeat this exercise using the
educational attainment shares for the non-Indigenous population in lieu of the First Nations
shares. Total employment and employment income are then calculated using the employment
rates and average employment incomes for First Nations people in each educational category.24.
By subtracting the post-closure total employment income from the pre-closure figure, we canquantify the economic benefit of closing the gap. We can also add the change in total

23

This process of calculating this pre-closure total employment income figure is the same for all four scenarios. For
this reason, its calculation is omitted from our description of the procedures used to close the other gaps.
24This estimation process involves the use of both the employment rate in a given educational attainment category
and the mean employment income in a given educational attainment category. It should be noted that these two
metrics are not directly comparable; the employment rate is calculated by including only those individuals whoreported working during the Census reference week, while the mean employment income is calculated for all
individuals who reported a non-zero sum of employment income. In other words, they are calculated using different
definitions of employment. The mean employment income for the group counted as employed by the 2021 Census(and therein represented in the employment rate) is likely higher than the mean employment income used in ourestimation.

42

employment income for First Nations people to the pre-closure total employment income for
Canadians generally to find the new total employment income for the country post-closure.25
Another way of estimating the economic benefits of closing the gap is quantifying thenumber of jobs created by the movement of First Nations individuals into higher categories of
educational attainment. Employment rates tend to be higher in these categories compared tolower categories. As such, when we close the education gap—an adjustment which moves manyFirst Nations people to higher educational categories—many First Nations individuals begin toenjoy higher rates of employment. In aggregate, this change in the effective employment rate
experienced by the First Nations population means a greater number of employed First Nations
people.26b) Closing the Income Gap Conditional on Education
The closure of the income gap conditional on education entails a similar albeit much
simpler process. To produce an estimate of the total employment income27 for the First Nations
population post-closure, we simply multiply the pre-closure number of employed First Nations
people in each educational attainment category by the average employment income for non-25

The calculation of pre-closure total employment income for all Canadians follows a very similar procedure to thecalculation of pre-closure total employment income for the First Nations population. The number of employedindividuals in each educational category is multiplied by the average employment income for Canadians by the total
number employed.
26
Both of these approaches of quantifying the benefits of closing the education gap assume that the movement ofFirst Nations individuals between educational categories does not affect the labour market conditions in thosecategories. Namely, we assume that the average employment income and the employment rate remain constant at
pre-closure levels. While this is not an entirely reasonable assumption, we posit that the real effects on theseparameters would be insignificant given the small size of these movements relative to the size of the Canadian
population in any given category.
27
It should also be noted that the jobs approach to quantifying economic benefits is not applicable to the closure of
the income gap. First Nations individuals are not moving between categories nor is the employment rate gap being
closed, and as such, the First Nations population does not enjoy a higher effective employment rate (neither in theaggregate nor in specific categories). The only economic benefits accruing as a result of closing the conditional
income gap are the gains in income which all employed First Nations people experience; there are no gains in
employment.

43

Indigenous individuals in that category. Finally, as in the previous section, we can subtract the
pre-closure total employment income from the post-closure figure to produce an estimate of thechange in total employment income resulting from the income gap closure.
It is important to note that the closure of the income gap within educational categories
does not constitute a closing of the aggregate income gap; that is to say, even after closing theincome gap conditional on education, First Nations people will still earn less on average thannon-Indigenous people. This is a consequence of differences in the distribution of educational
attainment levels between the First Nations and non-Indigenous populations. The aggregate
average employment income figure can be thought of as a weighted average of the average
employment income figures for each educational category. This function can be expressed in thefollowing form:𝑛̅𝑒𝑌 = ∑(𝑎𝑐 𝑌̅ 𝑒 𝑐 ),𝑐=1

where 𝑌̅ 𝑒 is the aggregate average employment income of a population, 𝑌̅ 𝑒 𝑐 is theaverage employment income of educational attainment category 𝑐, 𝑎𝑐 is a weight representing
the proportion of the working-age population which occupies category 𝑐, and 𝑛 is the number ofeducational attainment categories. When we close the income gap conditional on education, weare replacing the average employment income of First Nations people in a given category withthe same figure for non-Indigenous people; essentially, we are equalizing 𝑌̅ 𝑒 𝑐 across the two
populations. This is not sufficient to eliminate the aggregate income gap however, as the
distribution of individuals across educational categories will still vary between First Nations andnon-Indigenous people. Thus, the values of 𝑎𝑐 will still vary between the populations anddisparity will remain between the aggregate average employment incomes (𝑌̅ 𝑒 ) of First Nations
44

people and non-Indigenous Canadians. In order for the aggregate income gap to fully close, boththe income gap conditional on education and the education gap would need to close.28 Under
these circumstances, both 𝑎𝑐 and 𝑌̅ 𝑒 𝑐 would be equalized across the two populations, leading toa convergence of 𝑌̅ 𝑒 for First Nations and non-Indigenous people, and a full closure of theaggregate income gap.

c) Closing the Employment Rate Gap Conditional on Education
The closure of the employment rate gap conditional on education also follows a fairly
simple process. The working-age population of First Nations people in each educational category
is multiplied by the non-Indigenous employment rate in that category. This produces the numberof employed First Nations people in each educational category, which is then multiplied by theaverage employment income for First Nations people in that category. Once again, this provides
us an estimate of the total employment income post-closure for First Nations people, which canthen be compared to the pre-closure figure to produce the estimated change in total employment
income as a result of the gap closure.29 We can also estimate the number of jobs generated by theclosure of the conditional employment rate gap as an additional way of quantifying the economic
benefits. To do so, we compare the pre- and post- closure number of employed First Nations
people in each category and sum the differences.

28

We will perform this operation in our fourth and final scenario where all three gaps are closed simultaneously.
There are several educational categories in which First Nations people actually enjoy a higher employment rate
than non-Indigenous individuals. In these categories, we will not close the disparity in employment rates between
the two groups, given that replacing the First Nations employment rate with the non-Indigenous rate would actually
be economically harmful. Alternatively, we could replace the non-Indigenous employment rate with the higher
Indigenous employment rate, therein boosting the economic performance of non-Indigenous individuals, however
we feel this is not germane to the goal of this report. We have instead chosen to leave the First Nations employment
rate as is in these categories.
29

45

As with the closure of the conditional income gap, the closure of the conditional
employment rate gap is not sufficient to eliminate the aggregate employment rate gap. The
aggregate employment rate for a given population can be expressed as:𝑛

𝐸 = ∑(𝑎𝑐 𝐸𝑐 ),𝑐=1

where 𝐸 is the aggregate employment rate for a population, 𝐸𝑐 is the employment rate
within a given educational attainment category 𝑐, 𝑎𝑐 is a weight representing the proportion of
the population which occupies category 𝑐, and 𝑛 is the number of educational attainment
categories. Closing the employment rate gap within educational categories equalizes 𝐸𝑐 acrossthe First Nations and non-Indigenous populations, however the values of 𝑎𝑐 remain distinct for
the two groups. In order for the aggregate employment rate gap to close fully, both theconditional employment rate gap and the education gap need to close. 30d) Closing All Three Gaps Simultaneously
The procedure for estimating the benefits of closing all three gaps simultaneously is very
similar to the process for estimating the benefits of closing the education gap. The distinction isthat at every step we now use the parameters of the non-Indigenous population rather than theFirst Nations population: an adjustment that allows us to produce a portrait of the Canadian
economy if First Nations people were to enjoy the same level of educational attainment, the same
income conditional on education, and the same employment rate conditional on education as
non-Indigenous Canadians.

30

Again, we will perform this exercise in the final scenario as described in the following subsection.

46

We begin by closing the education gap. We do so by multiplying the total working age
population of First Nations people by the proportion of the non-Indigenous working age
population in each educational category. This yields the number of working-age First Nations
people in each category if the distribution of educational attainment for First Nations people was
identical to the distribution for non-Indigenous Canadians. We then close the conditional
employment rate gap by multiplying the number of working-age First Nations people in eachcategory by the non-Indigenous employment rate in that category, yielding the number of
employed First Nations people in each category. Finally, we close the conditional income gap.
By multiplying the number of employed First Nations people in each category by the average
employment income of non-Indigenous Canadians in that category and summing these figures,
we produce the total employment income for the First Nations population post-closure. Again,
one way we can quantify the economic benefits of closing all three gaps is by subtracting thepre-closure total employment income of First Nations people from the post-closure figure.
Alternatively, we can calculate the number of new jobs produced by subtracting the preclosure number of employed First Nations people in each category from the post-closure number.
The factors driving this job creation process are a) the greater employment rate which many First
Nations people now enjoy simply by virtue of having a higher level of educational attainmentand b) the greater employment rate which most First Nations people enjoy now that employment
rates in every category have converged to the rates enjoyed by non-Indigenous Canadians.

e) Limitations & Assumptions
All four of these scenarios follow what we call the overnight model of gap closure. Thatis, they envision the three major gaps between First Nations people and non-Indigenous
Canadians closing instantaneously or ‘overnight’. This assumption exists to clearly identify and47draw attention to the gaps that currently exist. The closing of these gaps will take years, if not
decades, and will likely require substantial policy interventions. Moreover, this is hardly an
innocuous assumption given that the absolute and relative sizes of both populations, as well otherkey parameters like real wage rates and employment rates, are expected to change significantly
over this time period. As such, the findings of this model should not be regarded as an exact
simulation of the economic outcomes that will arise should these gaps truly be closed. Rather,
they should be viewed as initial estimations of the magnitude of benefits which might accrue toFirst Nations people and Canadians generally, should policymakers and community leaders
pursue such goals. Alternatively, the results of the overnight model might be interpreted as thebenefits forgone or the costs incurred in 2021 by not closing these gaps in educational attainment
and labour market performance between the two populations. That is, the results here offer aportrait of the more prosperous First Nations economy which could have been realized had thesegaps been closed at the time of the 2021 Census.

Methodology – Longitudinal Model 31
Whereas the “overnight” model of gap closure detailed in the previous section envisions
these labour market gaps closing instantaneously, the longitudinal approach imagines the gaps
closing gradually over the course of a 20-year period (2021 to 2041). In doing so, it leverages
population projections produced by Statistics Canada and economic projections produced by the
CSLS to develop estimates of key economic indicators for the First Nations population over thisperiod (Statistics Canada, 2021c; Arif, 2022). Moreover, through the use of individual-level
Census microdata, we are able to control for the demographic characteristics of individuals and31

This section draws heavily on the methodology section of our previous report, given the great similarity between
the reports in methods used (AFN, 2023). Descriptions of methodological procedures are altered where necessary toreflect changes to the estimation strategies used.

48

project their future economic performance in terms of wages, output, labour productivity, andemployment.32 Compared to the overnight model, which uses aggregate level data, this approachallows us to produce more accurate and more detailed estimations of the impacts of these labour
market gaps on the First Nations population and the Canadian economy.
Within this model, we consider six different scenarios – one baseline scenario and fivegap closure scenarios (Scenario 1 to Scenario 5) – each with their own set of assumptions about
how the labour market gaps experienced by the First Nations population might change anddevelop by the year 2041. Table 9 presents a summary of how we define each of these scenarios.
For each scenario, we produce estimates of key economic indicators, namely, employment,
employment income, contribution to GDP, and labour productivity.33 By comparing theseestimates between scenarios, we are able to develop an understanding of the gains which may
accrue to First Nations people and Canadians generally if these disparities are partially orcompletely eliminated.

This report uses the term “productivity” interchangeably with “labour productivity”, as this is the only form of
productivity we discuss. We calculate labour productivity as total output divided by total employment; as such, theconcept is always expressed in 2015 Canadian dollars per employed person.
33
Employment income and output are closely linked concepts. Historically, the labour share of income (theproportion of output which accrues to labour in the form of employment income) has been about 0.5 in Canada. As
such, we estimate GDP or output to be two times employment income in the longitudinal model.
32

49

Table 9: Scenario Definitions
Scenario

Description

AssumptionsFirst Nations
Educational
Attainment in 2041

First Nations
Employment
Rates in 2041

First Nations Wages
in 2041

Baseline

Projected based on 20162021 rates ofimprovement for First
Nations; "business as
usual"

Equal to First
Nations
employment rates in
2021

Equal to First Nations
employment incomesin 202034, assuming
annual growth of 1%

1

Full Closure of
the Education
Gap

Same as projectededucational attainment of
non-Indigenous
population in 2041; noeducational attainment
gap in 2041

Equal to First
Nations
employment rates in
2021

Equal to First Nations
employment incomesin 2020, assuming
annual growth of 1%

2

Half Closure of
the Education
Gap

Equal to the average ofthe baseline projections
for First Nations and nonIndigenous populations;half of gap in baseline iseliminatedEqual to First
Nations
employment rates in
2021

Equal to First Nations
employment incomesin 2020, assuming
annual growth of 1%

3

Closure of the
Employment
Rate Gap

Projected based on 20162021 rates ofimprovement for First
Nations; "business as
usual"

Equal to nonIndigenous
employment rates in2021; gap closed

Equal to First Nations
employment incomesin 2020, assuming
annual growth of 1%

4

Closure of the
Income Gap

Projected based on 20162021 rates ofimprovement for First
Nations; "business as
usual"

Equal to First
Nations
employment rates in
2021

5

Closure of All
Three Gaps
(Educational
Attainment,
Employment
Rate, Income)Same as projectededucational attainment of
non-Indigenous
population in 2041; noeducational attainment
gap in 2041

Equal to nonIndigenous
employment rates in2021; gap closed

34

Equal to nonIndigenous
employment incomesin 2020, assuming
annual growth of 1%;
gap closed
Equal to nonIndigenous
employment incomesin 2020, assuming
annual growth of 1%;
gap closed

These are the employment incomes reported for First Nations people in the 2021 census. However, they represent
incomes earned in the year 2020.

50

The baseline scenario, which we use as a benchmark when analyzing the other five
scenarios, assumes that the level of educational attainment among First Nations will continue tochange at the same rate as it did between the 2016 and 2021 censuses. 35 In our previous report,
we projected educational attainment for the two populations using the rates of change inattainment categories for the 2006-2016 period.36 Given that the primary objective of this reportis to assess the impact of the 2016-2021 period on the state of the educational and labour market
gaps facing First Nations people, we have elected to use rates calculated for the 2016-2021
period. In terms of creating a data product that builds upon our previous work and prioritizes
contemporaneousness, we feel this approach provides the most utility.37 During the 2016-2021
period, the disparity in attainment between the First Nations population and the non-Indigenous
population closes in some categories and widens in others. This baseline scenario is produced byobserving the rates of change in each educational category between 2016 and 2021 andextrapolating those rates over the 2016-2041 period. The rate of change for each of these

35

Specifically, we calculate the compound annual growth rate required to achieve the change between 2016 and2021 in the proportion of the First Nations population which occupies any of the nine educational attainment
categories. For example, if the proportion of First Nations people with a bachelor’s degree as their highest
certification was 10% in 2016 and 20% in 2021, we would calculate that as a 200% change over the 2016-2021
period. The corresponding compound annual growth rate would then be 14.9%. Given that the proportion occupyingsome educational attainment categories falls over this period, these rates can be greater than or less than zero.
36
An alternative approach to projecting educational attainment levels is to take the first difference over the period
and derive an average annual change in each educational attainment category. These absolute annual changes canthen be applied repeatedly to estimate the future educational attainment levels of the two populations. For thisreport, we follow with the approach originally used in Calver (2015) and produce projections for each population
using the growth rates of the shares in each educational attainment category. We do not expect that the use of thisalternative approach would have a significant impact on our results.
37
The question of which period to use as the basis for our educational attainment projections is an interesting one
and one that has no single answer. Using the 2006-2016 period as we did in the previous report excludes recent
trends in educational attainment growth and thus negates the very objective of this report. Using the 2006-2021
period allows us to include recent trends but at the cost of rigidity; the impact on our projections of recent trends is
downplayed due to size of the period included. Given that educational attainment trends can change significantly
from period to period, the idea of including more years of data here does not necessarily create a better projection.
Using the 2011-2021 period would give us the same 10-year window as our previous report, however we would not
feel comfortable basing our projections so heavily on the anomalous 2011 Household Survey, which unlike astandard census, was not mandatory for Canadians to complete. Ultimately, we feel that using the 2016-2021 periodaligns most closely with the goals of this report. However, we are able to provide the results for the other approaches
mentioned upon request.

51

categories is presented in Table 10, alongside historical and projected levels of educational
attainment. Ultimately, this approach sees the education gap between the population widen insome categories compared to 2021. 38
The outcome of this projection procedure closely resembles what we found in ourprevious report. Both groups become more educated over time, however in many respects the
gap in educational attainment widens. For the First Nations population, gains mainly occur asindividuals move out of the “no certificate” category, and into the “high school” category. In
fact, based on 2016-2021 trends, we project that in 2041, almost half of First Nations people(47.2%) will hold a high school diploma (or an equivalent) as their highest credential. There are
significant gains in the “bachelor” and “university above bachelor” categories as well; theproportion of First Nations individuals with a bachelor’s degree as their highest credential nearly
doubles relative to 2021 (6.6% to 11.6%), and the proportion with a credential above thebachelor level more than doubles (2.4% to 5.2%). In fact, relative to their starting proportions in
2021, the growth experienced by the First Nations population exceeds the growth experienced by
the non-Indigenous population in key categories like “bachelor” and “university above38

It should be noted that the methodology used for these projections involves a standardization process which
affects the results in considerable ways. After applying the historical rates of growth to each educational attainment
proportion to estimate the future proportion of individuals in that category, these proportions no longer sum to
100%. As such, a normalization process must be applied to both the non-Indigenous educational distribution as wellas the First Nations educational distribution in order to return the sum of the proportions back to 100%. Given thatthe unnormalized total differs between the two populations as a result of the different levels of growth in educational
attainment which each population experiences, the educational attainment distributions are scaled down by distinct
factors, with the factors representing the average level of growth across all the education categories. Consequently,
any individual proportion does not solely represent the level of growth projected for that category, but also theaverage level of growth expected for each educational category in the population. This generates some unintuitive
results in some cases; for example, the “high school” category in the non-Indigenous population has a positive,
albeit very small growth rate between 2016 and 2021. However, because this growth rate is so small relative to othercategories, the projected share occupying the category in 2041 actually falls compared to 2021. For these reasons,caution should be exercised in interpreting these projected proportions, especially when comparing the proportions
across the two populations. Still, they represent broad-level movements in educational attainment, and for the
purposes of estimating key economic indicators like employment incomes, contributions to GDP, and levels of
employment, we hold that these projections are meaningful.

52bachelor”. In relative and absolute terms, the proportion of the working-age population with noeducational credential also falls significantly faster for the First Nations population than the nonIndigenous population. Despite these very significant gains, the absolute gains experienced inthese categories are generally greater for the non-Indigenous population than for the First
Nations population, and as such the absolute gap grows in many categories under this baseline
scenario. This is also true for the gap in the average years of education for the two populations,which grows from a gap of about 1.29 years in 2021 to about 1.53 years in 2041.

53

Table 10: Proportion of Working Age Population (15+) in Educational
Attainment Categories by Year and Scenario 39
First Nations

No credential
High School
Apprenticeship/Trades
Non-University
Certificate/Diploma
University below
Bachelor
Bachelor
University above
Bachelor
Total
Average Years of
Education

2006

2011

2016

2021

CompoundAnnualGrowthRate (20162021)

Projected
2041 atCurrent
Rates(baseline)

Education
Gap Half
Closes by
2041

Education
Gap
ClosesFully by
2041

48.4%
19.9%
10.4%

42.6%
22.9%
10.6%

38.2%
25.4%
9.8%

33.3%
29.8%
8.7%

-2.8%
3.3%
-2.3%

15.7%
47.2%
4.5%

12.1%
35.8%
4.8%

8.6%
24.5%
5.0%

13.2%

14.8%

17.0%

16.9%

-0.1%

13.7%

14.5%

15.2%

2.9%

2.8%

2.2%

2.3%

0.3%

2.0%

2.6%

3.2%

3.7%

4.5%

5.4%

6.6%

3.9%

11.6%

18.9%

26.2%

1.5%

1.8%

1.9%

2.4%

4.9%

5.2%

11.3%

17.4%

100.00%100.00%100.00%100.00%-100.00%100.00%100.00%

11.72

11.93

12.07

12.24

-

12.84

13.60

14.37

Projected
2041 atCurrent
Rates(baseline)

Education
Gap Half
Closes by
2041

Education
Gap
ClosesFully by
2041

Non-Indigenous

No credential
High School
Apprenticeship/Trades
Non-University
Certificate/Diploma
University below
Bachelor
Bachelor
University above
Bachelor
Total
Average Years of
Education

2006

2011

2016

2021

CompoundAnnualGrowthRate (20162021)

23.1%
25.7%
10.8%

19.4%
25.6%
10.8%

17.6%
26.5%
9.7%

15.5%
26.5%
8.7%

-2.5%
0.1%
-2.3%

8.6%
24.5%
5.0%

-

-

17.4%

18.3%

19.4%

18.9%

-0.6%

15.2%

-

-

4.5%

4.5%

2.9%

3.0%

0.8%

3.2%

-

-

11.9%

13.6%

15.9%

17.9%

2.4%

26.2%

-

-

6.7%

7.7%

8.0%

9.5%

3.5%

17.4%

-

-

100.00%100.00%100.00%100.00%-100.00%

-

-

13.00

13.23

13.34

13.53

-

14.37

-

-

39

This table updates a similar table (Table 2) presented in Part II of our previous report. Some numbers havechanged slightly due to the different educational attainment categories present in the 2021 Census data. Namely,
there is only one category representing non-university certificate/diploma programs as opposed to three.

54

Scenario 1 sees the educational attainment gap between First Nations people and nonIndigenous people close completely. Under this scenario, the First Nations population is assumed
to have the same educational attainment distribution as the non-Indigenous population in 2041.40
For example, if 20% of the non-Indigenous population in 2041 is projected to occupy the“bachelor’s degree” category, this scenario assumes that the same proportion of the First Nation
population will occupy the “bachelor’s degree” category in 2041. This assumption is made foreach of the seven educational categories which we investigate 41. It is essential to note that the
gap which is being closed is the gap between the projected 2041 First Nations population and the
projected 2041 non-Indigenous population, not the gap between the two populations in thepresent day.
In Scenario 1, gains in 2041 are estimated by calculating key economic indicators likeGDP, employment, total employment income, and productivity, and comparing these indicators
to the baseline scenario. The compound annual growth rates of GDP and employment over the2021-2041 period are then calculated using observed GDP in 2021 and our estimates for 2041
GDP and employment after the education gap has closed. By applying these compound annual
growth rates to GDP and employment in 2021, we can find GDP and employment in each of theintervening years and trace out the growth path of the Canadian economy as the gap closes. Thisapproach models gap closure as a linear process, where benefits grow at a constant annual rate
throughout the 2021-2041 period. Cumulative benefits are then estimated by comparing GDP
and employment in each year between the gap closure scenario and the baseline scenario. This40

Non-Indigenous levels of educational attainment in 2041 are projected using the same methodology described in
the baseline scenario for the First Nations population (see Table 2).
41
Only seven categories are used for the longitudinal model compared to nine in the previous report. This is because
the categories breaking down credentials from non-university institutions like colleges and CEGEP based onprogram length are not available in the tabular data employed in this report. Such categories were also not available
in the tabular data in 2016 and were only present in the PUMF file.

55

estimation framework remains consistent throughout the longitudinal model, although theunderlying assumptions regarding gap closure differ between scenarios.
Scenario 2, meanwhile, envisions the educational attainment gap closing only “halfway”. Functionally, this means that, rather than assuming the educational attainment of First
Nations people in 2041 will be equal to that of non-Indigenous people in 2041,42 we assume that
the First Nations educational attainment distribution will be the average of the projected 2041
distributions for First Nations people and non-Indigenous people. For each educational category(ex. “high school”), we estimate the proportion of the First Nations population in that categoryby taking the arithmetic mean of a) the projected proportion of First Nations in that category in
2041 in the baseline scenario, and b) the projected proportion of non-Indigenous people in thatcategory in 2041. In other words, half of the gap in the baseline scenario is eliminated under
Scenario 2. In this way, this scenario represents a sort of middle-ground between Scenario 1,
where First Nations educational attainment in 2041 is made equal to non-Indigenous levels of
educational attainment, and the baseline scenario. Although smaller in scale and effect than
Scenario 1, this “half-way” scenario likely represents a more realistic, albeit still optimistic,
assumption about the progression of First Nations educational attainment vis-à-vis nonIndigenous educational attainment. In 2041, many individuals who have completed theireducation and are in the workforce today will still be in the workforce. As such, the full closureof the educational attainment gap would require that today’s young First Nations people attainextremely high levels of education in order to ‘balance out’ the presence of older First Nations

42

We define equality in educational attainment as the two populations occupying each educational attainment
category in identical proportions. For example, if 25% of the non-Indigenous population has a bachelor’s degree as
their highest certification, equality in educational attainment would mean that 25% of the First Nations population
also has a bachelor’s degree as their highest certification. This is only an example of one category though; for theeducational attainments of the two populations to be equal, this would need to be true for all nine educational
categories.

56

people who are, on average, less educated than non-Indigenous individuals of the same age. The
half-closed scenario, meanwhile, more or less represents a future in which today’s young First
Nations people attain the same levels of education as today’s young non-Indigenous people: aproposition which, though a lofty goal in itself, is much more achievable.
For Scenario 3, we turn our attention to another labour market gap experienced by First
Nations people in comparison to non-Indigenous people: the conditional employment rate gap.
This is the observation that, even when matched up based on demographic and educational
characteristics, First Nations people tend to experience lower rates of employment than nonIndigenous people. In the overnight model, we are interested in the employment rate gap
conditional on educational attainment – that is, the disparity in employment rates between First
Nations people and Indigenous people of the same level of educational attainment. However,with the use of more detailed cross-tabular census data, we are able to control for differences insex, province/territory of residence, and age group, in addition to educational attainment. For thesake of brevity, we will refer to this gap as simply the conditional employment rate gap. We
describe each combination of these four variables as a “bin” containing the number of First
Nations individuals that matches that combination of characteristics. For example, one bin,which might be called “Quebec females 35-44 years old with a high school education”, contains
all female First Nations persons in Quebec between the ages of 35 and 44 who have a highschool diploma or an equivalent as their highest educational certification. Given that economic
indicators like rates of employment and average incomes vary greatly across these four variables,
and we are primarily interested in labour market disparities which occur solely because of one’s
status as a First Nations person or a non-Indigenous person, we feel it is best to observe the gaps
within bins, rather than across whole populations. Under this scenario, we assume that the57

educational attainment of the First Nations population is the same as in the baseline scenario,
however in calculating levels of employment, income, and output, we utilize the non-Indigenous
employment rate for each bin (each age-sex-province-educational attainment combination). In
this way, we envision the employment rate gap between the First Nations and non-Indigenous
populations fully closing.
Scenario 4 envisions the conditional income gap closing by 2041. Like the conditional
employment rate gap, the conditional income gap refers to the observation that, even for
individuals of the same sex, province/territory of residence, age group, and educational
attainment level, employed First Nations individuals tend to earn less on average in employment
income than non-Indigenous individuals.43 To simulate the closing of this gap, we follow asimilar procedure to the previous scenario. We assume that the First Nations population in 2041
has “baseline” levels of educational attainment, however, when we calculate employment,
income, and output, we utilize the non-Indigenous average employment income per employedperson for each bin (each age-sex-province-educational attainment combination). By doing so,
we are able to produce estimates of key economic indicators under the assumption that theconditional income gap has closed fully.
Finally, for Scenario 5, we essentially combine Scenarios 1, 3, and 4 in order to simulate
the closure of all three major labour market gaps simultaneously. We assume that First Nations
people in 2041 have the same level of educational attainment as non-Indigenous people areprojected to have, and furthermore, when calculating, employment, income, and output, we use
the non-Indigenous employment rate and average employment income for each bin (each age-

43

Employment status in this context refers to whether an individual had positive, non-zero employment income in2020, as this is the group over which average employment income is calculated.

58

sex-province-educational attainment combination). In doing so, we simulate a future in which all
three gaps have been fully closed; one in which First Nations individuals experience largely thesame labour market outcomes as non-Indigenous CanadianResults & Discussiona) Overnight Model
Table 11 presents the results of the overnight model of gap closure under four different
scenarios: the education gap closes, the income gap conditional on education closes, theemployment rate gap conditional on education closes, and a final scenario where all three gaps
close simultaneously. These figures represent the estimated economic benefits which would
accrue to First Nations people and Canadians generally if the key gaps between the First Nations
and non-Indigenous populations were to close instantaneously or ‘overnight’ in 2021. Table 12
presents analogous figures from Part I of our previous report, recording the benefits of overnight
gap closure that we estimated based on 2016 Census data. We now move to discuss the resultsfrom each gap closure scenario in turn.

59

Table 11: Estimated Economic Benefits by Gap Closure Scenario, Overnight Approach, 2021

Measures of Economic Benefit

Gap Closure Scenario

Closing
Education Gap
Closing Income
Gap
Conditional on
Education
Closing
Employment
Rate Gap
Conditional on
Education
Closing All
Three Gaps
Simultaneously

New
Employment
from gap
closure(# of jobs)

First Nations
share of
Canadian
employment
before gap
closureFirst Nations
share of
Canadian
employment
after gap
closureTotal
Canadian
Employment
Income preclosure(millions)

Total
Canadian
Employment
Income postclosure(millions)

Change in
Total
Employment
Income(millions)

Change in FN
Total
Employment
Income(percentchange)Change in
Canadian
Total
Employment
Income(percentchange)70,913

2.04%

2.44%

$804,820$810,359$5,538

41.3%

0.69%

NA

2.04%

2.04%

$804,820$806,117$1,297

9.7%

0.16%

26,061

2.04%

2.19%

$804,820$805,656

$835

6.2%

0.10%

85,020

2.04%

2.52%

$804,820$812,485$7,664

57.1%

0.95%

Note: All monetary estimates provided in 2015 Canadian dollars.
Source: CSLS Estimates

60

Table 12: Estimated Economic Benefits by Gap Closure Scenario, Overnight Approach, 2016 (Estimates from
Previous Report)

Measures of Economic Benefit

Gap Closure Scenario

Closing
Education Gap
Closing Income
Gap
Conditional on
Education
Closing
Employment
Rate Gap
Conditional on
Education
Closing All
Three Gaps
Simultaneously

New
Employment
from gap
closure(# of jobs)

First Nations
share of
Canadian
employment
before gap
closureFirst Nations
share of
Canadian
employment
after gap
closureTotal
Canadian
Employment
Income preclosure(millions)

Total
Canadian
Employment
Income postclosure(millions)

Change in
Total
Employment
Income(absolute)(millions)

Change in FN
Total
Employment
Income(percentchange)Change in
Canadian
Total
Employment
Income(percentchange)68,469

1.88%

2.27%

$793,564$798,562$4,998

44.8%

0.63%

NA

1.88%

1.88%

$793,564$795,596$2,032

18.2%

0.26%

41,759

1.88%

2.12%

$793,564$794,681$1,117

10.0%

0.14%

94,783

1.88%

2.42%

$793,564$802,202$8,638

77.5%

1.09%

Note: All monetary estimates provided in 2015 Canadian dollars.
Source: CSLS Estimates

61

i)

The Education Gap

The closure of the educational attainment gap between the First Nations and nonIndigenous populations is found to produce the most significant gains of the three individual
gaps which we consider. In total, the closure of the gap is associated with over $5.5 billion in
additional employment income for the First Nations population, representing a 41% increase in
the total employment income earned by First Nations people in Canada. This would also
represent a 0.69% increase in total Canadian employment income. Significant gains in
employment are also associated with the closure of the education gap. We estimate that the First
Nations population would enjoy about 71,000 additional jobs post-gap-closure. This would raise
the share of total Canadian employment comprised by employed First Nations – what we call theFirst Nations employment share – from 2.04% to 2.44%.
As anticipated by our observation that the educational attainment gap between the two
populations had widened since 2016, the estimated gains from the overnight closure of theeducation gap have increased compared to the estimates offered in our previous report.
Previously, we had estimated gains in total First Nations employment income of just under $5
billion – this figure grows by more than half a billion when performing the exercise with 2021
census data. Similarly, we had previously estimated employment gains of about 68,000
additional jobs: a figure which is found to about 2,000 jobs higher when using 2021 data. Theselarger absolute gains are also generally reflected in the relative measures of economic gain that
we provide. As a proportion of total Canadian employment income, the gains estimated in thisreport are 0.06 percentage points higher than those estimated in our previous report (0.69% using
2021 Census data vs. 0.63% using 2016 Census data). Similarly, the increase in the First Nations
employment share that we observe when the education gap closes is slightly higher in these62

updated estimates (0.40 percentage points here vs. 0.39 percentage points in previous report).
Interestingly though, the gains in total employment income as a proportion of total First Nations
employment income have fallen from 44.8% in our previous estimates to 41.3% in our updated
estimates. This reflects the fact that, as observed in the “State of the Gaps” section of this report,
the First Nations population has experienced tremendous growth in wages over the 2016-2021
period; the average real wage for First Nations people has increased by 11.6% since 2016, while
the real average wage for non-Indigenous average wages has grown by less 1% over the same
period. As such, although the estimated gains from the overnight closure of the education gap
have grown substantially compared to our previous report, the total employment income of theFirst Nations population has grown even faster. Therefore, even though estimated gains in
employment income have grown in absolute terms compared to our previous report, this specificmeasure of relative gain has decreased somewhat.

ii)

The Income Gap Conditional on Educational Attainment

In terms of the estimated income gains associated with gap closure, the closure of theincome gap conditional on educational attainment is found to be the second most important of
the three individual gaps we consider. In total, the closure of the gap is associated with about$1.3 billion in additional employment income: a substantial increase to be sure, but significantly
smaller than the gains associated with the closure of the education gap. This represents a 9.7%
increase in First Nations total employment income and a change in total Canadian employment
income of 0.16%. There are also no employment gains associated with the closure of this gap.
This is because the closure of the conditional income gap is defined as the equalization of theaverage earnings per employed person conditional on education across the First Nations and non-63

Indigenous populations. It does not entail any altering of the employment rates faced by First
Nations people – the source of employment gains when we close the conditional employment
rate gap – nor does it move individuals to higher educational categories where they might enjoy
higher rates of employment – the source of employment gains when we close the education gap.
The gains we estimate from the closure of the conditional income gap here aresubstantially smaller than the gains we estimated from our previous report. Based on the data
available in the 2016 Census, we had previously estimated total employment income gains ofabout $2 billion. The gains estimated based on 2021 Census data, meanwhile, are about $735
million or 36% smaller. However, this is very much expected given just how much theemployment income disparities between the two population have shrunk since 2016; naturally,
with smaller gaps to close, the benefits from gap closure are much smaller. Notably though, as aproportion of First Nations total employment income, these gains have fallen even more sharply
compared to our previous estimates, decreasing by about half (9.7% in this report vs. 18.2% in
our previous report). This reflects the same dynamic observed when estimating the gains fromclosing the education gap; the impressive growth that the First Nations population has
experienced in average employment incomes and employment rates has boosted total First
Nations employment income substantially compared to 2016. As a result, the drop from ourprevious report in the estimated benefit of closing the income gap is magnified in this measure of
relative gain. The numerator in the calculation – the absolute gain in First Nations employment
income – has fallen, while the denominator in the calculation – the total employment income of
the First Nations population – has grown very substantially. The result is a drop in relative gainthat is larger than what we observe when looking at the absolute economic gains.

64

iii)

The Employment Rate Gap Conditional on Educational Attainment

Closing the employment rate gap conditional on educational attainment is associated withthe smallest income benefits of the three individual gaps we consider in the overnight model.
Gains in employment income from the closure of the conditional employment rate gap are
estimated to be about $0.8 billion, representing a 6.2% increase in total First Nations
employment income and a 0.1% increase in total Canadian employment income. Again, whilethese gains are certainly meaningful, they do not compare to the estimated gains accrued fromthe closure of the education gap, which we estimate to be about 7 times larger. In terms ofadditional employment, the closure of the conditional employment rate gap is associated with
about 26,000 additional jobs for First Nations people: a change which would boost the First
Nations employment share from 2.04% to 2.19%.
As with the conditional income gap, the gains estimated from this gap closure scenario
are significantly smaller compared to the gains we estimated in our previous report. Previously,
we had estimated employment income gains of about $1.1 billion. Our updated estimate
represents a decrease of $0.3 billion or about 25% compared to our previous findings based on
2016 Census data. Still, the differential between reports here is smaller than for the conditional
income gap. Our estimates for the gains in employment from the closure of the gap, meanwhile,fell by about 16,000 jobs or 37%. As noted with the conditional income gap, these changes in theestimated gains associated with gap closure reflect the substantial amelioration of the gaps overthe 2016-2021 period. Moreover, for similar reasons as described above, the relative gains,expressed as a proportion of total First Nations employment income, have fallen quite
substantially compared to our previous report (6.2% here compared to 10.0% in our previous
report).

65

iv)

Closing All Gaps Simultaneously

The final scenario which we simulate in the overnight model is one where all three
individual gaps – the educational attainment gap, the income gap conditional on educational
attainment, and the employment rate gap conditional on educational attainment – are closed
simultaneously. As one might expect, this scenario is associated with the largest gains of all the
scenarios we consider in the overnight model. In total, we estimate that the simultaneous closureof all three gaps is associated with an increase in First Nations employment income of $7.6
billion: a magnitude of benefit that is about $2 billion or 38% larger than what we estimate forthe closure of the education gap alone. This represents a 57% increase in total First Nations
employment income and a 0.95% increase in total Canadian employment income. The associatedgains in employment are similarly impressive, with an estimated 85,000 additional jobs for First
Nations post-closure and a boost in the First Nations employment share from 2.04% to 2.52%.
Notably, the employment income gains from this scenario are essentially equal to the sumof the employment income gains from the individual gap closure scenarios. On the contrary, thegains in employment are markedly smaller than the sum of gains from the individual scenarios.
This is a consequence of the sequence in which we close the three gaps in this final scenario andthe fact that the employment rate gap shrinks at higher levels of educational attainment. Whenclosing all three gaps simultaneously, we begin by closing the education gap, before proceeding
to close the conditional employment rate gap and ultimately the conditional income gap. This
process moves First Nations individuals into higher educational attainment categories than theywould have inhabited in the scenario where only the conditional employment rate gap closes.
These higher educational attainment categories tend to feature smaller gaps in employment rates
between the First Nations and non-Indigenous populations. As such, the gains from closing the66

conditional employment rate gap in this final scenario tend to be smaller than they would be if
only the conditional employment rate gap closed and not the education gap alongside it.
Compared to the estimates offered in our prior report, the gains presented here aremodestly smaller. Previously, based on 2016 Census data, we had estimated employment income
gains of about $8.6 billion. Our current estimate of $7.7 billion therefore represents a decrease ofabout $1 billion or about 11%. A similar differential is observed for the estimated gains in
employment from closing all gaps simultaneously. Again, our estimates presented here arelower, in this case by 10% or about 10,000 jobs. The reason for this follows from our analysis of
the individual gap closure scenarios. Although the size of the education gap has increased, andtherein the benefits of closure as well, the conditional employment income and employment rate
gaps have closed considerably. These two trends have conflicting effects on the size of gains
from the all-gaps-closed scenario. Still, given that the gains have dropped considerably comparedto our previous estimates, it seems that the effect of smaller employment rate and income gaps
outweighs the effect of a larger education gap.

b) Longitudinal Model
Table 13 and 14 presents our estimates for the economic benefits accrued for various gap
closure scenarios under the longitudinal model of gap closure. We consider five scenarios in
total. In each scenario, the relevant gaps close gradually over the course of the 2021-2041 period.
The scenarios we consider are: the education gap fully closes, the education gap closes halfway,
the conditional employment income gap closes, the conditional rate gap closes, and a final
scenario where all three individual gaps close simultaneously. All measures of benefit are67

calculated by comparing the scenario of interest with baseline projections of key economic
indicators like GDP, employment, and labour productivity for the 2021-2041 period.
Table 13 presents estimates for the economic benefits accrued in 2041, the final year of
the gap closure process. Table 14, meanwhile, compares the estimates developed using 2021
Census data with estimates from our previous report based on 2016 Census data. These results
are somewhat analogous to the results produced by way of the overnight model, in that theyquantify the benefits of gap closure accrued within a single year of the gap closure scenario.
Notably though, the figures here represent the results of closing the projected gaps in 2041 andnot the gaps observed in the 2021 Census. Moreover, the employment income and employment
rate gaps in this context are conditional not just on educational attainment but also on gender,
age group and province/territory of residence.
In contrast, Table 15 presents estimates for the cumulative economic benefits across theentire 2021-2041 period from the gradual closure of the relevant gaps in each scenario. Table 16compares these results with those produced for our previous report using 2016 Census Data.
Gains in these tables are calculated by comparing projected GDP and employment each year
between the relevant gap closure scenario and the baseline projections. The differences in thesevariables which develop each year are then summed across the entire period. This long-term
approach to measuring the benefits of gap closure also allows to quantify the effect of eachscenario on the annual growth rates of GDP, employment, and labour productivity.
We now move to discuss the results for each gap closure scenario in turn. Interestingly,
the projections for First Nations GDP, employment, and labour productivity in 2041 aresomewhat lower than those produced in our last report. The baseline projected GDP contributionof First Nations people in 2041, for example, is estimated to be $64.4 billion: a little under $468billion less than the $68.3 billion in GDP that we estimated in the same exercise in our previous
report. We interpret this as stemming mainly from the fall in employment rates observed
between the 2016 and 2021 Censuses. This effect is further pronounced by the application ofFirst Nations population and educational attainment projections to the year 2041, and inparticular, the manner in which different population weights are attached to different bins by
these projections. Different age-sex-province/territory-educational attainment bins are estimatedto experience different levels of growth in the period leading up to 2041 (2021-2041 for thisreport, 2016-2041 for the previous report). In particular, the bins which have experienced more
drastic drops in employment between 2016 and 2021 seem to experience greater projected rates
of population growth. What results is an aggregate First Nations employment rate for ourbaseline 2041 projection that is meaningfully lower than in our previous report (49.0% in thisreport vs. 51.3% in the previous report). As mentioned in the “Understanding the 2021 Census”
section, there are also slight differences in the educational attainment categories considered in
the longitudinal model between this report and our previous report. This inconsistency may also
contribute to the discrepancy observed here, though we estimate the impact to be small.

69

Table 13: Main Longitudinal Results Based on 2021 Census Data,
Projections for First Nations in 2041 by Scenario

Baseline
Scenario

Education
Gap Closes

Education
Gap Half
ClosesEmployment
Rate Gap
ClosesIncomeGap
ClosesAll Three
Gaps
Close

1

2

3

4

5

GDP Gains (2015 dollars)
Total FN Contribution
to GDP (billions)

64.4

89.1

76.8

74.3

69.1

103.5

% change over baseline

-

38.3%

19.2%

15.4%

7.3%

60.7%

Total GDP (billions)% change over baseline

3,081
-

3,106
0.80%

3,094
0.40%

3,091
0.32%

3,086
0.15%

3,120
1.27%

Employment Income Gains (2015 dollars)
Total FN Employment
Income (billions)% change over baseline
Total Canadian
Employment Income(billions)% change over baseline

32.2

44.5

38.4

37.2

34.6

51.8

-

38.3%

19.2%

15.4%

7.3%

60.7%

1,541

1,553

1,547

1,546

1,543

1,560

-

0.80%

0.40%

0.32%

0.15%

1.27%

Employment Gains (# of jobs)
Total FN Employment(thousands)

643

749

696

766

643

827

-

16.4%

8.2%

19.1%

0.0%

28.7%

23,284

23,38923,337

23,40723,284

23,468

-

0.45%

0.23%

0.53%

0.00%

0.79%

Labour Productivity Gains (2015 dollars per worker)
FN Labour Productivity
100,164
118,978
110,285
97,032

107,523

125,122% change over baseline

-

18.8%

10.1%

-3.1%

7.3%

24.9%

Aggregate CanadianLabour Productivity

132,340

132,796

132,569

132,068

132,543

132,967% change over baseline

-

0.35%

0.17%

-0.21%

0.15%

0.47%

% change over baseline
Total Canadian
Employment(thousands)% change over baseline

Source: CSLS Estimates

70

Table 14: Main Longitudinal Results by Report & Census Data Year, Point
Estimates for Benefits in 2041 by Gap Closure
Education Gap
Education Gap
Employment
ClosesHalf Closes
Rate Gap Closes
12
3
Gains in First Nations Contribution to GDP (2015 dollars)

Scenario
Previous reportbased on 2016
CensusCurrent reportbased on 2021
CensusAbsolute
Change (billions)% change overbaseline
Absolute
Change (billions)% change overbaseline

Income Gap
Closes4

All Three Gaps
Close
5

30.2

15.1

11.1

8.7

48.4

44.2%

22.1%

16.3%

12.7%

70.9%

24.7

12.3

9.9

4.7

39.1

38.3%

19.2%

15.4%

7.3%

60.7%

Gains in First Nations Employment Income (2015 dollars)Previous reportbased on 2016
CensusCurrent reportbased on 2021
CensusAbsolute
Change (billions)% change inbaseline
Absolute
Change (billions)% change overbaseline

15.1

7.6

5.6

4.3

24.2

44.2%

22.1%

16.3%

12.7%

70.9%

12.3

6.2

5.0

2.4

19.6

38.3%

19.2%

15.4%

7.3%

60.7%

Gains in First Nations Employment (# of jobs)
Previous reportbased on 2016
CensusCurrent reportbased on 2021
CensusAbsolute
Change(thousands)% change overbaseline
Absolute
Change(thousands)% change overbaseline

105

52

139

0

188

15.5%

7.8%

20.7%

0.0%

27.8%

106

53

123

0

184

16.4%

8.2%

19.1%

0.00%

28.7%

Gains in First Nations Labour Productivity (2015 dollars per worker)
Absolute
25,182
13,497-3,654
12,847
Previous report
Changebased on 2016
% change overCensus
24.9%
13.3%
-3.6%
12.7%
baseline
Absolute
18,814
10,122-3,132
7,359
Current report
Changebased on 2021
% change overCensus
18.8%
10.1%
-3.1%
7.3%
baseline
Source: CSLS Estimates

71

34,11333.7%
24,95924.9%

Table 15: Main Longitudinal Results Based on 2021 Census Data, Cumulative
Gains Over 2021-2041 Period

Baseline
Scenario

Education
Gap
Closes

Education
Gap Half
ClosesEmployment
Rate Gap
ClosesIncomeGap
ClosesAll Three
Gaps
Close

3

4

5

1
2
GDP Projections (2015 dollars)
Total GDP (billions)% change overbaseline

54,905

55,13855,021

54,99954,95055,274

-

0.42%

0.21%

0.17%

0.08%

0.67%

Employment Projections (# of job-years)
Total Canadian
Employment(thousands)% change overbaseline

445,573446,619446,096446,790445,573447,395

-

0.23%

0.12%

0.27%

0.00%

0.41%

Effect on Annual GDP Growth
Annual GDP GrowthRateabsolute change% change overbaseline

1.71%

1.75%

1.73%

1.73%

1.72%

1.77%

-

0.04pp0.02pp0.02pp0.01pp0.06pp

-

2.37%

1.19%

0.96%

0.46%

3.75%

Effect on Annual Employment Growth
Annual Employment
Growth Rateabsolute change% change overbaseline

0.95%

0.97%

0.96%

0.98%

0.95%

0.99%

-

0.02pp0.01pp0.03pp0.00pp0.04pp

-

2.41%

1.21%

2.80%

0.00%

4.19%

Effect on Annual Labour Productivity Growth
Annual Productivity
Growth Rateabsolute change% change overbaseline
Source: CSLS Estimates

0.75%

0.77%

0.76%

0.74%

0.76%

0.78%

-

0.02pp0.01pp-0.01pp0.01pp0.02pp

-

2.31%

1.16%

-1.37%

1.03%

3.16%

72

Table 16: Main Longitudinal Results by Report & Census Data Year, Cumulative
Estimates for Benefits of Gap Closure Over 2021-2041 Period
Education Gap
Education Gap
Employment
ClosesHalf Closes
Rate Gap Closes
1
2
3
Cumulative Gains in GDP (2015 dollars)

Scenario
Previous reportbased on 2016
CensusCurrent reportbased on 2021
CensusAbsolute Change(billions)% change overbaseline
Absolute Change(billions)% change overbaseline

Income Gap
Closes4

All Three Gaps
Close
5

286

143

105

82

457

0.52%

0.26%

0.19%

0.15%

0.83%

233

117

94

45

369

0.42%

0.21%

0.17%

0.08%

0.67%

Cumulative Gains in Employment (# of job-years)
Previous reportbased on 2016
CensusCurrent reportbased on 2021
CensusAbsolute Change(thousands)% change inbaseline
Absolute Change(thousands)% change overbaseline

1,035

518

1,379

0

1,857

0.23%

0.12%

0.31%

0.00%

0.42%

1,046

523

1,217

0

1,822

0.23%

0.12%

0.27%

0.00%

0.41%

Effect on Annual GDP GrowthPrevious reportbased on 2016
CensusCurrent reportbased on 2021
CensusAbsolute Change(percentage
points)Absolute Change(percentage
points)Previous reportbased on 2016
CensusCurrent reportbased on 2021
CensusAbsolute Change(percentage
points)Absolute Change(percentage
points)Previous reportbased on 2016
CensusCurrent reportbased on 2021
CensusAbsolute Change(percentage
points)Absolute Change(percentage
points)0.05pp0.02pp0.02pp0.01pp0.08pp0.04pp0.02pp0.02pp0.01pp0.06ppEffect on Annual Employment Growth
0.02pp0.01pp0.03pp0.00pp0.04pp0.02pp0.01pp0.03pp0.00pp0.04ppEffect on Annual Labour Productivity Growth
0.03pp0.01pp-0.01pp0.01pp0.04pp0.02pp0.01pp-0.01pp0.01pp0.02ppSource: CSLS Estimates

73

i)

Scenario 1: The Education Gap Fully Closes

The estimated gains from the full closure of the education gap under the longitudinalmodel are substantial. Using projections based on 2021 Census data, we find that the closure of
the gap is associated with an additional $24.7 billion in GDP in 2041 for the First Nations
population (Table 14), boosting the 2041 First Nations contribution to GDP by 38%, from about$64 billion in the baseline projection to over $89 billion when the gap closes (Table 13). The
closure of the gap is also associated with $233 billion in cumulative GDP gains over the 20212041 period (Table 16): an increase of 0.42% in total GDP over the period, which manifests as a0.04 percentage point increase in the annual economic growth rate, from 1.71% to 1.75% (Table
15). The significance of gains in the annual growth rates of key variables like GDP, employment,
and productivity is hard to overstate. These changes represent improvements in the growthtrajectory of the country, the fruits of which will manifest annually and compound over time.
Hence, even small changes in these rates represent important economic benefits. Still, the gains
here are somewhat lower than the $30 billion in additional 2041 GDP and $286 billion in
cumulative GDP gains that we estimated in our previous report, but they nonetheless representvery large gains in output and income for the First Nations population.
The gains in employment are similarly impressive. We estimate that the full closure of
the education gap is associated with an additional 106,000 jobs for First Nations people in 2041,
representing a 16.5% increase in total First Nations employment in 2041 and 0.45% increase intotal Canadian employment in 2041. Over the 2021-2041 period, the closing of the gap is
associated with about 1,046,000 additional yearly incomes for First Nations people or “jobyears” as we call them (one job for one year). In total, this improves the annual growth rate ofCanadian employment for the period by 0.02 percentage points, from 0.95% annually to 0.97%74

annually. These estimates are actually slightly larger, in both absolute and relative terms,
compared to the estimates offered in our previous report, with the estimated gains in employment
being about 1,000 jobs and 11,000 job-years larger in the exercise performed here.
Total First Nations labour productivity, measured as annual output per worker is also
found to improve significantly in this scenario, from about $100,000 per worker in the baseline
projections for 2041 to about $119,000 when the education gap closes fully: an improvement of
18.8%. This causes the annual growth rate of Canadian labour productivity over the 2021-2041
period to rise from 0.75% to 0.77%: a significant gain given the slow rates of productivity
growth that Canada has seen in recent years. These gains are about 25% smaller than thoseestimated in the previous report; in our previous projections we had found gains of about$25,000 in First Nations labour productivity in 2041. Labour productivity is essentially a ratio of
total output to total employment, and hence, the decrease in First Nations labour productivity
between the two reports is a result of both a) the smaller gains in output and b) the larger gains in
employment that we observe here relative to the previous report.

ii)

Scenario 2: The Education Gap Closes Halfway

As one would expect, the benefits from closing the education gap halfway over the 20212041 period are about half as large as the estimated benefits from closing the education gap
completely. We estimate a total increase in 2041 First Nations GDP of about $12 billion and anincrease in cumulative GDP over the 2021-2041 period of about $117 billion. In relative terms,
this is an increase in 2041 First Nations GDP of about 19% and an increase in cumulative 20212041 GDP of about 0.21%. Altogether, this manifests as a 0.02 percentage point increase in theannual growth rate of GDP over the 2021-2041 period. These figures are again somewhat

75smaller than those estimated in our previous report, with 2041 GDP and cumulative GDP gains
being about 13% and 19% smaller, respectively.
Employment gains from the half-closing of the education gap are found to be significant
as well, with gains in 2041 employment estimated at about 53,000 jobs and cumulative gains
over the 2021-2041 period estimated at about 523,000 job-years. This represents an increase in
the annual rate of Canadian employment growth of 0.01 percentage point. Again, these gains areslightly larger compared to those we found in our previous report. The half-closing of theeducation gap is also associated with around a $10,000 or a 10.1% increase in labour
productivity, augmenting the annual rate of labour productivity growth by 0.01 percentage
points. These gains in labour productivity are slightly smaller than those found in the previous
report for this scenario.

iii)

Scenario 3: The Conditional Employment Rate Gap

The closing of the conditional employment rate gap is, too, associated with very
substantial gains. We estimate that the closing of the gap would generate about $9.9 billion in
additional First Nations output in 2041: an increase of about 15% over the baseline projections.
Furthermore, over the 2021-2041 period, we estimate that the closing of the gap would generate
an additional $94 billion in cumulative GDP, boosting total cumulative GDP over the period by
0.17% and raising the annual GDP growth rate by 0.02 percentage points to 1.73% annually.
These estimates are largely comparable to those offered in the previous report, albeit slightly
attenuated. For example, previously we had estimated gains in 2041 GDP of $11.1 billion; thisfigure has fallen by about 11%.

76

The most impressive gains from the gradual closing the conditional employment rate gap
are related to the additional employment generated for the First Nations population. In all, theclosing of the gap is associated with 123,000 additional jobs for First Nations people and about
1,200,000 additional yearly incomes or job-years for the First Nations population. Worth notingis that these gains in employment are the largest of all of the individual gap closure scenarios -even larger than those found when closing the full education gap. This would seem to indicate
that, despite closing substantially over the 2016-2021 period, the conditional employment rate
gap continues to be an important source of disparity between the First Nations and nonIndigenous populations. These gains manifest as a 0.03 percentage point increase in annual
employment growth, bringing the annual growth rate of Canadian employment from 0.95% peryear to 0.98% per year. These gains, despite their impressive size, are again slightly smaller thanthose estimated in our previous report.
Finally, as a result of these massive gains in employment being paired with more modest
gains in output, the labour productivity of First Nations people actually falls by almost $3,000 orabout 3.6% compared to baseline. This pushes the annual rate of labour productivity growth
down by 0.01 percentage points. What we are observing here is a sort of composition effect;
existing First Nations workers are not individually becoming less productive. Rather, the largest
gaps in employment rates between the First Nations and non-Indigenous populations tend tooccur within lower categories of educational attainment. As such, most of the gains in
employment that we see when we close the conditional employment rate gap in this scenario
stem from jobs added in these lower categories, where workers tend to be less productive. The
measures of labour productivity expressed here find the labour productivity of the average First
Nations worker by distributing total First Nations output across the total number of First Nations

77

workers. With the addition of these low-productivity jobs, the ‘average’ First Nations worker isless productive than in the baseline scenario. Notably though, the fall in First Nations labour
productivity found here is smaller than what we found in our previous report, implying that theimbalance between added output and added employment is less severe here.

iv)

Scenario 4: The Conditional Income Gap

Although still meaningful, the impacts from closing the conditional income gap are thesmallest among all the scenarios considered by a significant margin. The closure of the gap is
associated with an additional $4.7 billion in GDP in 2041 and $45 billion in additional
cumulative GDP over the 2021-2041 period, representing a 7.3% increase over baseline GDP in
2041 and a 0.08% increase in cumulative output over the gap closure period. This is reflected as
a 0.01 percentage point increase in the annual economic growth rate for the 2021-2041 period.
While Scenario 4 was also found to be of least impact among the scenarios considered in ourprevious report, the gains reported here are markedly smaller than the gains found previously.
Before we had estimated about $8.7 billion in additional output in 2041: a figure which has
fallen by about $4 billion. Similarly, we had projected cumulative gains of $82 billion in GDP in
our prior report: a magnitude of benefit almost twice as large as what we find here. With that
said, this is hardly cause for concern as these lower estimated benefits are a natural consequenceof the significant progress made in closing the income gap between the 2016 and 2021 Censuses.
Notably, there are no employment gains to the closure of the conditional income gap, as
there is no change to the employment rates facing the First Nations population (see Methodology
section for a more detailed explanation). However, as a result, the gains in output seen heretranslate directly into gains in First Nations labour productivity. Essentially, the numerator in thelabour productivity calculation – total output – is growing, while the denominator – total
78

employment – remains static. Consequently, when the conditional income gap closes, weobserve about a $7,000 increase in the average output of First Nations workers and a 0.01
percentage point increase in the annual growth rate of Canadian labour productivity. These gains
are again somewhat smaller than what we observed in our previous report.

v)

Scenario 5: All Gaps Close

In this scenario, we simulate the simultaneous closure of the education gap, theconditional income gap, and the conditional employment rate gap. As such, the gains from this
scenario are by far the most significant among the five scenarios we consider in the longitudinalmodel. Altogether, we estimate that the simultaneous closure of all three gaps is associated withan increase in 2041 First Nations GDP of about $39 billion: a staggering 60.7% increase overbaseline. Furthermore, over the 2021-2041 period, we estimate that the simultaneous closure of
the three gaps is associated with an increase in cumulative GDP of about $369 billion or 0.67%
over baseline. In total, this augments the annual growth rate of GDP for the 2021-2041 period
from 1.71% in the baseline scenario to 1.77% when all gaps. Despite the massive size of thesegains, it is worth acknowledging that these estimates are substantially lower than their analogues
in the previous report. Estimated gains in 2041 GDP totalled to about $48 billion in the previous
report; the gains found here thus represent a decrease of $9.3 billion or about 19%. Similarly,
cumulative gains in GDP over the 2021-2041 period were estimated to be about $457 billion
previously. The estimate offered here is $88 billion, or again, about 19% smaller compared toour previous report.
Gains in employment from the simultaneous closure of three gaps are equally impressive.
We estimate that the scenario is associated with an increase in First Nations employment of
about 184,000 jobs: about a 29% increase over baseline. Across the 2021-2041 period, we also79see about an increase in total job-years of about 1,800,000 or 0.41% over baseline. This
manifests in a 0.04 percentage point increase in the annual growth rate of Canadian employment
over the 2021-2041 period, boosting it from 0.95% per year in the baseline projections to 0.99%
per year. These estimates are largely comparable to the estimates from our previous report.
These immense gains in output and employment contribute to a substantial increase inFirst Nations labour productivity relative to baseline. In total, output per First Nations worker
rises by about $25,000 or 25% relative to the baseline projections. This brings First Nations
labour productivity up to $125,122 per worker or about 94% of the Canadian average ($132,967
per worker): a significant improvement from the baseline, where First Nations labour
productivity was just over 75% of the Canadian figure. This is reflected in the annual labour
productivity growth for the 2021-2041 period, which rises from 0.75% per year to 0.78% per
year. Compared to our previous estimates, this jump in labour productivity is somewhat
attenuated although still very substantial. In our prior report, we had estimated an increase inFirst Nations labour productivity of about 34,000 and hence, our estimates in this report
represent a decrease of about 27%.

c) Comparing the Models
Table 17 presents the relative gains in First Nations employment and income associatedwith each gap closure scenario for both the overnight model and the longitudinal model. On
balance, the estimated gains from the longitudinal model follow closely with the gains estimatedthrough the overnight model, though given the distinct methodologies used for each approach,there are some key differences in the findings of the two models. For example, the estimatedgains from gap closure in 2041, which we produce through the longitudinal model, tend to belarger in absolute terms than the gains estimated in the overnight model. This is largely because80

of changes in the First Nations population and the Canadian labour market which occur in the
20-year period from 2021-2041.

Table 17: First Nations Income and Employment Effects by Gap Closure Scenario
and Model Used, Percentage Change over Baseline
Scenario 1 (Full
Education)
First Nations Employment Income
41.27%
Overnight
38.32%
LongitudinalFirst Nations Employment
20.03%
Overnight
16.45%
Longitudinal
Source: CSLS Estimates

Scenario 2 (Half
Education)

Scenario 3(Employment
Rate Gap)

Scenario 4(Income Gap)

Scenario 5 (AllGaps)

19.16%

6.23%
15.41%

9.66%
7.35%

57.11%
60.72%

8.22%

7.36%
19.13%-

24.02%
28.66%In this period, we project that the First Nations working-age population almost doubles,from 764,750 in 2021 to 1,313,000 in 2041. Hence, the gains from closing any of the gaps tend
to be larger in the longitudinal model simply due to the larger population and workforce which isaffected by any given gap closure scenario. As an example, holding all else equal, a $1,000
increase in the average employment income earned by First Nations is more impactful, in
absolute terms, for a large population than a small one. Imagine a small population of only 10
individuals with a total employment income of $100,000 (Population A) and a larger populationof 100 with a total employment income of $1,000,000 (Population B). The average employment
income in both populations is $10,000; all individuals work and earn a wage in this hypotheticalscenario. If both populations experience a $1,000 increase in the average wage earned byworkers, that manifests as a gain of $10,000 for Population A ($1,000 increase on average for 10
people = $10,000) and a gain of $100,000 for Population B ($1,000 increase on average for 100

81

people = $100,000). In both populations, total employment income rises by 10%, but theabsolute size of the gain in Population B is larger thanks to the larger population. A similar
dynamic is observed between the First Nations population in 2021 and the projected First
Nations population in 2041, and hence the absolute gains from the longitudinal model of gap
closure tend to be larger than those produced in the overnight model.
Another factor contributing to systematically higher gains in the longitudinal modelcompared to the overnight model is that the longitudinal model projects substantial real wage
growth in the 2021-2041 period. Based on projections developed by the CSLS, we assume that
real growth in wages will be equal to about 1% annually, in line with projected productivity
growth. Over the period, this results in the wages of First Nations and non-Indigenous people
growing by 23% compared to the wages used in the overnight model.44 In absolute terms, thismeans that the absolute size of the gaps, and hence the gains from closing the gaps, will haveincreased by 23%, even if all other variables, including the relative size of the gap has stayed thesame.45 For all of these reasons, it is generally more interesting and appropriate to compare
relative measures of gain between the two models. We now move to describe in greater depth
how the results of the two models compare to one another.

44

The wages provided in the 2021 Census are for the year 2020. As such, the assumed rate of annual real wage
growth is compounded 21 times to obtain wages in 2041.
45
It is important to note that the phenomenon described here does not refer to changes in the price level between thetwo periods. All income data presented and mobilized in this report is in 2015 dollars, unless explicitly statedotherwise. Hence, changes in price levels between different period have already been taken into consideration.
Rather, this phenomenon stems from real wage growth – change in wages after adjusting for changes in the pricelevel.

82

i)

The Closing of the Education Gap

Of the three individual gaps explored across the models, the education gap is found to be
the most impactful in terms of potential benefits from closure in both the overnight model andthe longitudinal model. Within the framework of the overnight model, we find that the closing of
the education gap is associated with a 41.3% increase in total First Nations employment income(Table 17).46 Repeating the exercise using the longitudinal model, we estimate that the income
gains from closing the gap represent a 38.3% increase in the total employment income of First
Nations: a comparable albeit slightly smaller figure. This seems to suggest that the returns to
educational attainment in terms of higher average wages and higher employment rates are lesssubstantial once we control for additional variables like age group, gender, and province/territoryof residence in the longitudinal model.
A similar story is seen with the employment gains associated with the closure of theeducation gap. In the overnight model, new employment as a proportion of existing First Nations
employment is about 20%, while the same figure for the longitudinal model is about 16%. The
gains from closing the education gap stem from individuals earning more and experiencing
higher employment rates as they are moved to higher educational attainment categories. As such,the smaller gains in the longitudinal model compared to the overnight model suggest that returns
to additional educational attainment become somewhat attenuated when we control for additionalvariables. Specifically, it implies that some of what we had previously observed as differences inlabour market outcomes between attainment categories was really the result of unobserved

46

Given that the overnight model does not provide estimates for the gains in GDP (output) associated with each gap
closure scenario, we focus primarily on employment and employment income in comparing the results of the twomodels. Since we make the assumption that the labour income share for Canada is 0.5 (i.e., half of national income
accrues to labour), relative gains are identical for employment income and GDP in the longitudinal model. As such,though we do not discuss gains in output specifically, they are implicitly reflected in the comparison conducted here.

83differences in the age, gender and province/territory characteristics of individuals within eacheducational attainment category.

Box 3: Estimating Returns to Educational Attainment
Consider the following hypothetical: imagine that men and women are equally likely to attain abachelor’s degree, but that men are much more likely to attain a degree above the bachelor level. On
the surface, it will seem that individuals with a degree above the bachelor level earn significantly moreon average than individuals who have a bachelor’s degree as their highest credential. Part of thisdifference in average earnings is simply reflecting the fact that men tend to earn higher wages than
women, all else equal, and that individuals with a degree above the bachelor level are more likely to bemen.
If we were to compare only between individuals of the same gender, the difference in earnings
across the two attainment categories would likely be less dramatic. This difference would also moreclosely reflect the benefit an individual would receive from improving their level of educational
attainment (i.e., the causal effect of educational attainment on labour market outcomes). We do notaccount for these types of demographic differences in the overnight model, however we do control forthe age, gender, and province/territory of residence of respondents in the longitudinal model. As such,the estimated returns to educational attainment differ between the two models. The gains fromclosing the education gap therefore differ as well, since they reflect the returns accruing to First
Nations individuals as they are moved to higher educational attainment categories.

ii)

The Closing of the Conditional Income Gap

A similar discrepancy arises between the estimated gains from closing the conditional
income gap across the two models. In the overnight model, the closure of the gap is associatedwith a 9.7% increase in the total employment income earned by the First Nations population.
Meanwhile, under the longitudinal model, the same figure drops to 7.3%. While the 2.4

84percentage point difference between the measures does not appear too substantial in itself, it
becomes somewhat more noteworthy when considering the already small magnitude of the gains
compared to other scenarios. This differential between the models indicates that the employment
income gap between First Nations people and non-Indigenous people of the same educational
attainment level becomes smaller once we control for gender, age group, and province/territoryof residence. Once again, this suggests that the income gap conditional on education that we
observed earlier in this report was partially a result of differences in the frequency of age,gender, and province/territory characteristics between First Nations people and non-Indigenous
people of the same level of attainment.

iii)

The Closing of the Conditional Employment Rate Gap

In contrast to the previous two gaps, the benefits from the closure of the conditional
employment rate gap grow in magnitude when the additional controls added in the longitudinalmodel. Whereas the overnight model estimates gains in total First Nations employment incomeof about 6.2% when the conditional employment rate gap is closed, the longitudinal model
estimates that the closure is associated with much more substantial gains of 15.4% relative tobaseline. Measures of relative gains in employment tell a similar story. Within the overnightmodel, the closing of the conditional employment rate gap is associated with gains in
employment of about 7.4%. However, using the longitudinal model, this measure rises to an
estimated increase of 19.1%: the largest increase in employment of all three individual gap
closure scenarios. In contrast, while the gains in employment are substantial in the overnightmodel, they are less, in both relative and absolute terms, than the employment gains accrued
when the education gap is closed. The differential between the two models again underscores85

that controlling for additional variables in the longitudinal model can drastically affect the size ofthe gap being closed. In this case though, controlling for age, gender, and province/territory ofresidence enlarges the conditional employment rate gap massively. This suggests that theconditional employment rate gap observed earlier in the report actually masks some deeper
disparities between the First Nations and non-Indigenous populations with respect to theemployment rates they faced in 2021. Specifically, it tells us that the distribution of age, gender,
and province/territory characteristics between the two populations made the gap appear smaller
than it otherwise would have, if the two populations had been identical on these dimensions.
Across both the longitudinal and overnight models, the all-gaps-closed scenario was, as
one would expect, the most significant scenario in terms of gains for employment and income. In
the overnight model, we estimate that the closure of the gap is associated with an 57.1% increase
in total First Nations employment income. We found comparable gains in the longitudinalmodel, estimating a 60.7% increase in total First Nations employment income in 2041 when all
gaps are closed. Here, the gains from the longitudinal model are higher than those from theovernight model, even when using relative measures. This tracks with our previous observations
that controlling for additional variables in the longitudinal model can widen or shrink the gaps
being closed, depending on the distribution of demographic characteristics across the First
Nations and non-Indigenous populations. Given that the gains from the all-gaps-closed scenario
are larger in the longitudinal model compared to the overnight model, controlling for thesevariables seems to have enlarged the underlying gaps.
One might expect that the discrepancy between the two models in the individual gap
closure scenarios would sum to equal the discrepancy between the two models when the three
scenarios are combined, and this holds fairly true. In total, the discrepancies across the three86

individual scenarios sum to a difference of about 3.8 percentage points. This is driven by small
negative discrepancies (i.e., the longitudinal model gains are smaller than the gains in theovernight model) for the closure of the education gap and the closure of the conditional income
gap, and a strong positive discrepancy (i.e., the longitudinal model gains are larger than theovernight gains) in the case of the gains from closing the conditional employment rate gap. This
matches up very closely with the observed discrepancy in the all-gaps-close scenario of about 3.6
percentage points between the longitudinal and overnight models. Additionally, when discussing
the results from the all-gaps-close scenario in the overnight model, we noted that the sum of bothabsolute and relative gains across the three individual scenarios matched the gains seen in the allgaps-closed scenario. The same dynamic is observed here; absolute and relative gains in income
from the three individual scenarios equal almost exactly the absolute and relative gains in the allgaps-closed scenario.

iv)

The Closing of All Three Gaps Simultaneously

In terms of benefits to employment from the all-gaps-closed scenario, the gains we findin the longitudinal model again outstrip the gains we find in the overnight model. Using theovernight model, we estimate gains in employment of about 24%. However, with thelongitudinal model, we find gains of about 29%: a difference of about 5 percentage points. This
tracks with our previous observation that the employment rate gap becomes substantially larger
once we control for age, gender, and province/territory of residence. Still, this discrepancy inemployment gains is larger than the discrepancy we find between the two models with respect toincome gains. However, this makes some sense; with respect to relative gains in employment,
the closing of the conditional income gap has no effect here. Compare this to our discussion of87

income gains, where the conditional income gap shrunk when we controlled for additionalvariables in the longitudinal, leading to smaller gains in the longitudinal model compared to theovernight model. Without this moderating effect, the relative employment gains from closing all
gaps are meaningfully larger in the longitudinal model than the overnight model, stemming
primarily from the larger employment rate gap that arises once we control for additionalvariables. With that said, when looking at employment benefits, the gains from the individual
gap closure scenarios do not sum to equal to the total estimated gains in the scenario: anobservation that holds true for both the longitudinal and overnight models. This likely reflects adynamic that we discussed earlier in this section; as the education gap closes, individuals are
moved to higher educational attainment categories where the employment rate gap tends to besmaller compared to lower categories. As a result, when both the education gap and theconditional employment rate gap close together, this, all else equal, has somewhat of a shrinking
effect on the effective gap in employment rates that we close compared to when we only closethe conditional employment rate gap.

Challenges in Closing the Gaps
While the main objective of this report has been to estimate the magnitude of benefits
which would follow if the educational attainment gap, and the related gaps in employment rates
and employment incomes, were to close, it must be acknowledged that the closing of these gaps
is extremely challenging and far from straightforward, given the large proportion of the First
Nations population that is already in the labour force and unlikely to pursue further education. It
would not be sufficient for First Nations youth to attain the same average level of educational
attainment as non-Indigenous youth going forward to 2041. Rather, First Nations youth would
need to stay in school longer and achieve higher levels of attainment than non-Indigenous youth88

in order to balance out the lower levels of attainment of previous generations. Future researchmight seek to map out exactly what this process of closure might require by breaking down
educational attainment trends by age group and making assumptions regarding the lifelong
educational attainments of different groups.
The half-closure of the education gap may be more attainable within the 2021-2041
timeframe. As noted in the “State of the Gaps” section of the report, the educational attainment
level in the non-Indigenous population is a moving target, improving every year, sometimes at afaster rate than the First Nations figure, as was the case in the 2016-2021 period. This iscomplicated by the high level of immigrants which Canada accepts each year, the majority ofwhich are economic immigrants accepted based on their skillset (Government of Canada, 2023c).
These immigrants are often highly-educated, and hence the average non-Indigenous level of
educational attainment can also move upward thanks to this compositional effect.
The bottom-line is that the closure of the educational attainment gap between the First
Nations population and the non-Indigenous population requires the development of a welldesigned and comprehensive action plan to address the disparity on multiple fronts. Identifying
such a strategy is beyond the scope of this report, but we do wish to highlight some areas offocus and offer a few key means of achieving parity in educational attainment between First
Nations people and non-Indigenous people. Reasons for high-school drop-out rates for First
Nations people need to be addressed. Targeted investments into educational staff andinfrastructure on-reserve might help to address this by instilling in young First Nations students astronger appreciation for school and a lifelong drive to learn. Such policies could help students
develop a strong base of knowledge and skills early on and enhance their overall educational

89

experience: outcomes which would pay long-term dividends by making them more likely tocomplete secondary school and pursue additional education.
Post-secondary education, in particular university, needs to be strongly emphasized andencouraged. This might be aided by the increased provision of First Nations-specific skills,
training, and degree programs which emphasize Indigenous knowledge systems and target skills
and subjects tailored to the specific needs of communities and Nations. Scholarships and funding
opportunities represent an important tool to this end as well, given the substantial socioeconomic
barriers that confront many First Nations people with interests in higher education.
In order to address the historically lower levels of educational attainment within the First
Nations population, any action plan must also integrate and promote a principle of lifelong
learning – of returning to school later in life and continually upgrading one’s skills. Such a
principle would make equalizing educational attainment levels across the populations much morefeasible (albeit still challenging) by encouraging improvement at all levels of the First Nations
population and not just for the cohort still in school. All of these efforts might be further
bolstered by an increased number of well-educated role models within First Nations
communities: figures who would set a high standard of achievement, promote the value of
education, and exemplify the principle of lifelong learning.

Conclusion
Our analysis in this report finds that, although significant progress has been made inclosing the employment income and employment rate gaps faced by First Nations people in
Canada relative to non-Indigenous Canadians, the educational attainment gap between the two
populations has actually grown since 2016. The educational attainment of the First Nations
90

population did improve since 2016, growing from 12.07 years on average in 2016 to 12.24 years
on average in 2021. However, the educational attainment of the non-Indigenous population grewfaster, from 13.34 years on average in 2016 to 13.53 years in 2019. As a result, the gap between
the two populations grew from 1.26 years, on average, in 2016 to 1.29 years in 2021. Similarly,
as a proportion of the average years of education in the non-Indigenous population, the average
years of education within the First Nations population fell from 90.53% in 2016 to 90.45% in
2021.
Because of this, the estimated gains from closing the gaps in educational attainment andlabour market performance facing First Nations people are still extremely significant. Using theovernight model of gap closure, we estimate that the closure of the education gap in 2021 is
associated with $5.5 billion in additional employment income and an additional 71,000 jobs forFirst Nations people. This rises to $7.7 billion in employment income gains and an additional
85,000 jobs in the scenario where all three gaps – the educational attainment gap, theemployment income gap conditional on education, and the employment rate gap conditional on
education – close simultaneously in 2021.
An even larger magnitude of benefit is found when simulating the closure of key
gaps by way of the longitudinal model. In total, we estimate that the full closure of the education
gap over the 2021-2041 period is associated with an additional $24.7 billion in GDP for First
Nations in 2041 as well as 106,000 additional jobs for the First Nations population in 2041.
Across the entire period, we estimate that the closure of the gap is associated with $233 billion in
cumulative GDP gains and a cumulative gain of 1 million job-years for the First Nations
population compared to our baseline projection. This augments the annual economic growth rateof Canada over the 2021-2041 period from 1.71% to 1.75%. The gains are, as one might expect,91found to be even larger under a scenario where all three gaps close simultaneously. Altogether,
we estimate that the simultaneous closure of all three gaps over the 2021-2041 period is
associated with gains of $39.1 billion in additional GDP and 184,000 additional jobs for First
Nations in 2041. Over the entire period, we estimate cumulative gains of about $369 billion in
total GDP and 1.8 million additional yearly incomes for the First Nations population.
Consequently, the annual Canadian economic growth rate would rise from 1.71% to 1.77%.
Ultimately, this report finds that, though there has been substantial progress made in
improving the on-the-ground realities of First Nations people in Canada, there is still asubstantial amount of work to do. The educational attainment gap and the lack of success inameliorating it over the 2016-2021 period is of particular concern; if current trends continue, it ispossible this gap may never close. Still, as demonstrated in this report, there are immense
economic benefits – to say nothing of the humanitarian benefits -- which would accrue not just toFirst Nations people, but to Canadians more broadly, if these gaps were to close. However, as
evidenced by the generally slow pace of progress in closing the education gap, it seems very
unlikely that such an outcome will come to pass without intentional action and intervention on
the part of all Canadians. Indeed, the complete closing of the gaps facing First Nations people
will likely require consistent, concerted efforts from policymakers and community leaders to
support First Nations education and to engender a culture of lifelong learning.

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