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CENTRE FOR THE
STUDY OF LIVING
STANDARDSTHE HUMAN DEVELOPMENT INDEX IN CANADA:RANKING THE PROVINCES AND TERRITORIESINTERNATIONALLY, 2000-2015: AN UPDATEJames Uguccioni, Andrew Sharpe and Richard Beard
CSLS Research Report 2017-06
August 2017

1

The Human Development Index in Canada:
Ranking the Provinces and Territories
Internationally, 2000-2015: An Update
Abstract
We develop internationally comparable estimates of the Human Development
Index (HDI) for the Canadian provinces and territories over the 2000-2015 period. The
HDI is a composite index composed of three dimensions (life expectancy, education andincome) measured by four indicators (life expectancy at birth, average years of education,
expected years of schooling and GNI per capita). We first replicate the Canadian estimatesfrom the most recent Human Development Report (HDR) using data from Statistics
Canada. Next, we generate estimates for the provinces and territories following the same
methodology and using the same Canadian data sources. We make these estimatesinternationally comparable by scaling each province or territory’s estimate to Canada’s inthe most recent HDR. This allows the provinces and territories to be ranked in the mostrecent HDR international rankings for all four component variables as well as the overall
HDI. The highest HDI score in 2015 among the provinces and territories belongs to bothAlberta and Ontario, which would be tied for fifth in the international rankings. The lowest
ranking region is Nunavut, which would be in 45th place. Overall, our report highlights thediverse human development experiences of Canadians that are concealed by Canada’s
overall HDI.

2

The Human Development Index in Canada:
Ranking the Provinces and Territories
Internationally, 2000-2015: An Update
Table of Contents

Abstract ........................................................................................................................................... 2
Table of Contents ............................................................................................................................ 3
List of Tables .................................................................................................................................. 4
List of Exhibits................................................................................................................................ 4
List of Charts................................................................................................................................... 5
Executive Summary ........................................................................................................................ 6
Introduction..................................................................................................................................... 8
I. The Human Development Index.................................................................................................. 9
II. Replicating the most recent HDR’s Estimates for Canada ...................................................... 12
A. Life Expectancy ................................................................................................................... 12
B. Education.............................................................................................................................. 13
i. Average Educational Attainment....................................................................................... 13
ii. Expected Years of Schooling............................................................................................ 16
C. Income.................................................................................................................................. 19
D. Overall Human Development Index .................................................................................... 20
III. Estimates of the Human Development Index for the Canadian Provinces andTerritories...................................................................................................................................... 21
A. Life Expectancy ................................................................................................................... 22
B. Education.............................................................................................................................. 25
i. Average Years of Education .............................................................................................. 25
ii. Expected Years of Schooling............................................................................................ 27
C. Income.................................................................................................................................. 30
D. Overall Human Development Index .................................................................................... 33
IV. Future Research with the Human Development Index ........................................................... 35
V. Conclusion ............................................................................................................................... 36
References..................................................................................................................................... 38

3

The Human Development Index in Canada:
Ranking the Provinces and Territories
Internationally, 2000-2015 : An Update
List of Tables
Table 1: Life Expectancy at Birth, Canada, 1980-2015................................................................ 12
Table 2: Estimated Average Educational Attainment, Canada, Persons aged 25 and over,
1980-2015 ..................................................................................................................................... 14
Table 3: School Attendance by age group, Canada, 2000-2015................................................... 19
Table 4: Expected Years of Schooling, Canada, 1980-2015 ........................................................ 20
Table 5: GNI per capita, PPP adjusted 2011 US dollars, Canada, 1980-2015 ............................. 20
Table 6: CSLS Replication of the Official Human Development Index Estimate for
Canada, 2015................................................................................................................................. 21
Table 7: Life Expectancy Estimates and Index, Canada and the Provinces/Territories,
1990, 2000, 2011, and 2015.......................................................................................................... 22
Table 8: Life Expectancy Rank, Canada and the Provinces/Territories, 2000, 2005, 2011,
and 2015........................................................................................................................................ 24
Table 9: Average Educational Attainment Estimates and Index, Canada and theProvinces/Territories, 2000, 2005, 2011, and 2015 ...................................................................... 25
Table 10: Average Educational Attainment Rank, Canada and the Provinces/Territories,
2000, 2005, 2011, and 2015.......................................................................................................... 28
Table 11: Expected Years of Schooling Estimates and Index, Canada and theProvinces/Territories, 2000, 2005, 2011, and 2015 ...................................................................... 28
Table 12: Expected Years of Schooling Rank, Canada and the Provinces/Territories, 2000,
2005, 2011, and 2015.................................................................................................................... 30
Table 13: Gross National Income per capita Estimates and Income Index, Canada and theProvinces/Territories, 2000, 2005, 2011, and 2015 ...................................................................... 31
Table 14: Gross National Income per capita Rank, Canada and the Provinces/Territories,
2000, 2005, 2011, and 2015.......................................................................................................... 32
Table 15: Human Development Index, Canada and the Provinces/Territories, 2000, 2005,
2011, and 2015.............................................................................................................................. 33
Table 16: Human Development Index Rank, Canada and the Provinces/Territories, 1990,
2000, 2011, and 2015.................................................................................................................... 34
Table 17: Summary of International HDR Ranks, Canada and the Provinces/Territories,
2015............................................................................................................................................... 37

List of Exhibits
Exhibit 1: Structure of the Human Development Index ................................................................. 9

4

List of Charts
Chart 1: Life Expectancy, Raw Estimates, Canada and the Provinces/Territories, 2015 ............. 23
Chart 2: Compound Annual Growth in Raw Estimates of Life Expectancy, per cent per
year, Canada and the Provinces/Territories, 2000-2015............................................................... 24
Chart 3: Average Educational Attainment, Raw Estimates, Canada and theProvinces/Territories, 2015........................................................................................................... 26
Chart 4: Compound Annual Growth in Average Educational Attainment, per cent per year,
Canada and the Provinces/Territories 2000-2015......................................................................... 26
Chart 5: Expected Years of Schooling, Raw Estimates, Canada and theProvinces/Territories, 2015......................................................................................................... 289
Chart 6: Compound Annual Growth in Expected Years of Schooling, per cent per year,
Canada and the Provinces/Territories, 2000-2015........................................................................ 29
Chart 7: GNI per capita, current dollars, Raw Estimates, Canada and theProvinces/Territories, 2015........................................................................................................... 31
Chart 8: Compound Annual Growth in Nominal GNI per capita, per cent per year, Canada
and the Provinces/Territories, 2000-2015..................................................................................... 32
Chart 9: Human Development Index, Canada and the Provinces/Territories, 2015..................... 33
Chart 10: Compound Annual Growth Rate in the HDI, per cent per year, Canada and theProvinces/Territories, 2000-2015 ................................................................................................. 34

5

The Human Development Index in Canada:
Ranking the Provinces and Territories
Internationally, 2000-2015: An Update
Executive Summary
The Human Development Index (HDI) is an internationally recognized measure ofsocio-economic well-being. It is a composite index composed of three dimensions: life
expectancy, education and income. In the most recent Human Development Report (HDR)
produced by the United Nations Development Program, life expectancy is measured by life
expectancy at birth, education is measured by average educational attainment and expected
years of schooling, and income is measured by Gross National Income (GNI) per capita.
Although the HDI is by no means a comprehensive measure of human development, it is a
substantial improvement over the standard income-based metrics.
Canada falls into an impressive tenth place in the international 2015 HDI rankings
published in the most recent HDR released in March 2017. However, this ranking hides
significant regional variations among the Canadian provinces and territories. This reportaims to calculate an internationally comparable HDI for each of the Canadian provinces
and territories in order to evaluate their respective levels of human development relative
not only to each other and the Canadian average, but also to the rest of the world.
To estimate the provincial and territorial HDIs, the Centre for the Study of Living
Standards (CSLS) employs data sources that allow a breakdown by province and territory
and used the methodology of the most recent HDR to replicate the estimates:






In terms of the HDI, Alberta and Ontario ranked first among theprovinces and territories in 2015 and Nunavut last;
For life expectancy, British Columbia was the top region and Nunavut
again ranked last;
For average educational attainment; the Yukon had the highest among
Canadian provinces and territories while Nunavut had the lowest;
For expected years of schooling, Quebec ranked at the top andNunavut came in last;
For GNI per capita, Northwest Territories was in first place and Prince
Edward Island was in last.

6

Using internationally comparable index values for the Canadian provinces andterritories, we can then rank the provinces against the index values of other countries. Of
the 188 countries in the most recent HDR rankings, Canada’s provinces and territories
ranked between:






Fifth and 45th place in overall HDI;
Fourth and 103rd in life expectancy;
Second and 40th in average educational attainment;
13th and 85th in expected years of schooling;
Second and 35th in GNI per capita.

Although most Canadian provinces and territories achieve impressive ranks in theinternational context, evidently Canada’s overall HDI masks substantial variation among
the different regions. For example, according to the HDI, Canadians living in Alberta andOntario enjoy a quality of life similar to those residing in Singapore or Denmark, while
Canadians in Nunavut face a quality of life similar to Latvians or Argentineans.
All provinces and territories experienced improvements in the HDI between 2000
and 2015, with the HDI index advancing between 0.29 per cent per year and 0.54 per centper year. The two jurisdictions with the greatest improvement were Newfoundland andLabrador and Nunavut, which experienced HDI growth of 0.50 per cent per year and 0.54
per cent per year, respectively. Despite its rapid HDI growth, Nunavut remained the lowest
ranked jurisdiction in both 2000 and 2015. There is some evidence of convergence in the
HDI as three of the regions with the highest HDI in 2015 (Alberta, Ontario, and British
Columbia) had below average growth in the HDI between 2000 and 2015, while two of thethree bottom ranked regions (Nunavut and Prince Edward Island) had above average
growth in the HDI.

7

The Human Development Index in Canada:
Ranking the Provinces and Territories
Internationally, 2000-2015: An Update1
Introduction
The Human Development Index (HDI) is an internationally recognized measure ofsocio-economic well-being. It was first published by the United Nations Development
Program (UNDP) in 1990 and estimates of the HDI have been released on an annual basis
ever since.2 The HDI has become a popular tool, particularly because its simple structure
facilitates international comparisons of human development and well-being. The mostrecent Human Development Report contains HDI estimates for 188 of the 193 member
countries of the United Nations.
Canada falls into an impressive tenth place in the international HDI rankings of the2016 Human Development Report (HDR), which reports results up to 2015. However, thisranking glosses over regional variations among the Canadian provinces and territories. An
earlier CSLS research report by Hazell et al. (2012) calculated an internationallycomparable HDI for the provinces and territories in order to compare their respective
levels of human development not only with each other and the Canadian average, but alsowith the rest of the world. Uguccioni (2016) reprised the work of Hazell et al. to update
their findings. This report updates the work completed by Uguccioni (2016) by extending
the HDI to 2015.
This report is divided into three major sections. In the first section, the Human
Development Index is discussed. Next, the Centre for the Study of Living Standards(CSLS) replicates the estimates for Canada in the three dimensions of the HDI (lifeexpectancy, education and income) published in the most recent HDR. The difficulties inprecisely matching these numbers are also discussed. Finally, the provincial and territorial
HDIs are calculated for the 2000-2015 period and the ranking results are discussed. Theseestimates as well as estimates for the pre-2000 period for all variables are provided in the
Appendix Tables online.3

1

This report is an updated and revised version of Uguccioni (2016). The paper was presented at the annual meeting of
the Canadian Economics Association at St. Francis Xavier University, Antigonish, Nova Scotia, June 2-4, 2017. The
authors thank Gordon Anderson for comments. The Centre for the Study of Living Standards thanks the Government ofAlberta for financial assistance to update the HDI database which is posted with this report. Comments are welcome andshould be sent to andrew.sharpe@csls.ca.
2
All of the twenty-six annual HDR reports, containing estimates for HDI in each respective year, are available on the
UNDP website. The most recent report is available at http://hdr.undp.org/en/2016-report.
3
Appendix tables are available at: http://www.csls.ca/reports/csls2017-06Appendix.pdf

8

I. The Human Development Index
In the past two decades, the HDI has become a common tool for evaluating thelevel of human development in a country or a region. Its popularity has arisen for two main
reasons. First, it captures more elements which encompass quality of life than standard
income measures do, namely education and life expectancy. In this sense, it presents a
broader measure of human development than GDP per capita or other common measuresof income and consumption. Second, it is relatively easy to calculate and has minimal datarequirements, allowing it to be calculated for most developing countries. Thus, it isparticularly useful for international comparisons of human development and well-being.
However, this measure of human development is not without its weaknesses. Its
primary failing is that it only considers three elements of economic well-being: education,
life expectancy and income. It does not take into account other critical elements of wellbeing such as income inequality, gender inequality, morbidity, political freedom, civil
liberties, corruption, pollution, or economic security. To address this shortcoming, themost recent HDR supplements its HDI estimates with additional information on humandevelopment, including estimates of an Inequality-adjusted HDI, a Gender Development
Index, a Multidimensional Poverty Index and data on environmental sustainability, humandevelopment effects of environmental threats, and perceptions about well-being and theenvironment, in addition to more detailed health and education statistics. Indeed, theauthors of the HDR reports emphasize that the HDI alone is not a complete description ofhuman development.
Still, the HDI is a very useful tool, particularly because it is easily understood andwidely used owing to its simple structure. Moreover, the UNDP is a high profile
organization with significant reach across the world. As noted, the HDI is a composite
index composed of three dimensions: life expectancy, education, and income. In the mostrecent HDR, life expectancy is measured by life expectancy at birth, education is measured
by average educational attainment in years and expected years of schooling, and income ismeasured by Gross National Income (GNI) per capita. Exhibit 1, taken from the 2011
HDR, illustrates the fundamental structure of the HDI.
Exhibit 1: Structure of the Human Development Index

Source: UNDP (2011: 167)

Before estimating the provincial and territorial HDIs, it is important to understand
not only how the HDI is constructed, but also how the most recent HDR differs from9

earlier reports. This is particularly important because the 2010 report instituted majorchanges in how the HDI is calculated in response to the concerns of researchers ineconomic development.4
The HDI estimates in the most recent HDR are calculated in the following manner.
First, the estimates for the life expectancy, average educational attainment, expected yearsof schooling and GNI per capita data for each country are scaled into indices using thefollowing equation:
=

−

−

(1)

The maximum and minimum values for each dimension are taken from the most recent
HDR, and follow a simple rationale. The minimum values are based on the concept ofsubsistence, that is, they are set at the lowest value needed in that indicator for a society tofunction, or, in the case of income, the lowest value in recorded history. The maximum
values are set as “aspirational goals” which allow for this standardization to take place.5
The life expectancy index calculation is a straightforward application of equation(1), while the income index requires taking the natural logarithm (ln) of each income
statistic before applying it in equation (1). The education index is slightly more
complicated to calculate, as it involves creating two sub-indices and then combining themto create the dimension index. The two education sub-indices are constructed for mean
years of schooling and expected years of schooling, respectively, using equation (1). The
education index is then created by taking the arithmetic mean of the two sub-indices.
Notably, prior to the 2015 HDR the education index was created by taking the geometricmean of the two sub-indices and rescaling the number that results by using the maximum
and minimum values listed for this purpose in the technical notes of the HDR.
The HDI itself is calculated as the geometric mean 6 of the three indices alreadydiscussed, i.e.:
4

For critiques of earlier versions of the HDI, see Srinivasan (1994), Sagar and Najam (1998) and McGillivray (1991). As
a result of the changes, HDI estimates presented in HDR reports from 2010 onwards are not comparable to thosepublished in previous HDR reports, but represent an improvement in methodology in many respects. The current
methodology has been to generate estimates prior to 2010 which are comparable to the post-2010 estimates.
5Life Expectancy: minimum=20.0 years based on long-run historical evidence from Maddison (2010) and Riley (2005),
maximum=85.
Education: minimum=0 years for both average educational attainment and expected years of schooling since survival ispossible without education, maximum=15 years for average educational attainment and maximum=18.0 years for
expected years of schooling.
Income (PPP adjusted 2011 US$): maximum= $75,000 as Kahneman and Deaton (2010) showed that there is essentiallyno gain in human development and well-being beyond an annual income of $75,000, minimum= $100.
For more information see Technical notes in the most recent HDR
6
A geometric mean is calculated by multiplying n numbers and then taking the nth root of that product. The HDI used tobe calculated with an arithmetic mean (or average), which is the sum of n numbers divided by n. This was changed
because geometric means allow less substitutability between measures or dimension indices, so poor performances in one
dimension are not linearly compensated for by better performances in other dimensions. For more information, see
http://hdr.undp.org/en/statistics/hdi/.

10

=

/

×

/

×

/

This results in a number between 0 and 1, where 1 represents the highest possible humandevelopment score. A country achieves a score of 1 only if it matches the highest observed
outcomes to date in all categories. The highest HDI score for 2015 belongs to Norway(0.944), followed by the lowest, belonging to Niger (0.348).
This methodology of the post-2010 HDR reports departs from prior reports in threemain ways.
First, the education index is constructed using average educational attainment andexpected years of schooling, instead of literacy and the gross enrolment rate (which
combines primary, secondary and tertiary enrolment rates), to offer a more
complete picture of education.

Second, income per capita is measured by GNI per capita instead of Gross
Domestic Product (GDP) per capita. This switch occurred because GDP measures
the amount produced in a country without capturing where the income from thisproduction goes. In contrast, GNI reflects the income of the residents of a country
regardless of where the income is generated, and is therefore a better measure ofdomestic purchasing power than GDP.



Finally, the geometric mean has replaced the arithmetic mean for calculating theoverall index. This reduces the substitutability of improvements across measures,
so a country cannot linearly trade off performing poorly in one dimension by
performing well in another. In other words, a country cannot receive a very highhuman development score without impressive scores in all dimensions.

One criticism that remains of the HDI is the arbitrarily determined equal weights
applied to each dimension. Lind (2010) instead proposes a Calibrated Human
Development Index (CDI) that employs revealed preferences to justify the weights applied
to each dimension, and in doing so better reflects the relative roles of education andconsumption in determining quality of life. However, the CDI is tailored to accurately rank
highly developed countries, and in that way is not as useful for international comparisons
as the original HDI.

11

II. Replicating the most recent HDR’s Estimates for Canada
In order to develop an internationally comparable HDI for the Canadian provinces
and territories, the CSLS sought to employ methodologies and data sources that were as
consistent as possible with those used in the most recent HDR. We use Statistics Canada
data that have national, provincial, and territorial estimates for each indicator, and used
these data first to replicate the official HDI results for Canada and then to develop
estimates for the provinces and territories using the same methodology. This section will
outline the process of replicating the most recent HDR official estimates for life
expectancy, education (which includes both average educational attainment and expected
years of schooling) and income for Canada. The difficulties in precisely matching the mostrecent HDR results are also discussed.

A. Life Expectancy
In the most recent HDR, Canada’s life expectancy at birth was estimated to be 82.2
years for 2015, which ranked at 12th place internationally.
Table 1: Life Expectancy at Birth, Canada, 1980, 1990, 2000-2015

Year

UNDP – HDR

Statistics Canada

1980
1990
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015

75.0
77.2
79.1
79.1
79.5
79.8
80.0
80.2
80..4
80.6
80.8
81.0
81.2
81.4
81.7
81.9
82.0
82.2

75.2
77.6
79.4
79.6
79.7
79.9
80.2
80.4
80.8
80.9
81.0
81.4
81.6
81.8
82.0
82.2
82.4
82.6

Sources: The UNDP - HDR data taken from the International Human Development Indicators website(http://hdr.undp.org/en/69206). Statistics Canada data from CANSIM Table 102-0025 for 1980 and 1990, Table 102-0511 for 20002006; Table 102-0512 for 2007-2008;7 the italicized values (2010-2015) are estimated by the CSLS by applying the compound
annual growth rate for 1991-2008 (0.25 per cent) to each year.8

Statistics Canada’s official estimates of annual Canadian life expectancy areavailable for 1979-2009, and are very similar to the estimates in the most recent HDR, as
shown in7

Statistics Canada modified their life expectancy at birth methodology to include three years of data. An annual timeseries can be derived from these data.
8
Note that the annual growth rate is projected using data from 1991 to 2008 because data is unavailable for the Nunavut
and the Northwest Territories before 1991.

12

Table 1. The two estimates may differ due to rounding, the possibility of minor datarevisions by Statistics Canada since the data were extracted by UNDESA, and theforecasting methods employed by UNDESA after 2009. Both sets of estimates show that
Canada had a life expectancy of around 82 years in 2015 (Table 1).9

B. Education
As mentioned earlier, the HDR reports since 2010 differ from earlier reports in thatthe education indicators employed to generate the education index are average andexpected years of schooling, instead of literacy and gross enrolment rates. These newmeasures of education are used because they offer a more complete picture of education.
However, the estimates of average years of schooling, calculated using the Barro and Lee(2010) methodology, are difficult to replicate. In addition, the most recent HDR
extrapolates expected years of school estimates from 2002 to generate their 2015 value.
Although these new measures of education may represent an improvement in theory,
employing them makes the HDI’s results difficult to replicate and the official estimates in
the most recent HDR may not accurately reflect the situation of Canada’s educational
attainment in 2015.
i. Average Educational Attainment
Overall, Canada performs well in the category of average educational attainment
relative to many other nations. According to the most recent HDR, Canadians aged 25 andover have obtained, on average, 13.1 years of schooling in 2015, or sixth place in theinternational rankings for this measure. This estimate of average years of schooling
updates the Barro and Lee (2010) estimates using UNESCO (United Nations Educational,
Scientific and Cultural Organization) Institute for Statistics data on educational attainment.
The HDR estimates for 1980, 1990, 2000, 2005, and 2010 to 2015 are presented in Table
2.10
Although Barro and Lee (2010) do not describe how average educational
attainment is calculated for Canada specifically, their general methodology isstraightforward. They first multiply the duration of each schooling level in years by the
proportion of individuals in different age brackets that have achieved that level as theirhighest level of schooling, where “level of schooling” refers to primary, secondary andtertiary (or post-secondary) schooling levels. 11 The age brackets used for the average
education of those 25 and older are defined by 5 year intervals (i.e. 25-29, 30-34) until age
74, with the final age category being 75 and older. Summing these results across schoolinglevels for each age group yields the average schooling level for each age group. The
9

CSLS’s projected estimate of 82.6 years for 2015, which is estimated using historical growth rates, is 0.4 years above
the most recent HDR’s estimate (82.2 years). Inserting CSLS’s estimate into the most recent HDR international life
expectancy rankings would move Canada into eighth place, instead of its actual ranking of twelfth place.
10
Barro and Lee last revised their estimates for 2010 average years of schooling in June 2014. The revised dataset
estimates that average educational attainment in Canada was 12.3 years in 2010.
11
Specifically, 8 years for those with at most a primary education, 12 years for those with at most a secondary
education, and 14 years for those with at most tertiary schooling.

13

average educational attainment for the entire population is then calculated by adding
together these age group average educational attainments once they have been weighted by
the share of that age group in the total population aged 25 and older.
Table 2: Estimated Average Educational Attainment, Canada, Persons aged 25 and over, 1980-2015

Year
1980
1990
2000
2005
2010
2011
2012
2013
2014
2015

UNDP – HDR
9.8
10.3
11.0
12.2
12.7
12.8
12.9
13.0
13.1
13.1

LFS data
10.5
11.9
12.2
12.5
12.5
12.5
12.6
12.6
12.6

Notes: CSLS allocates 8 years for those with at most primary, 12 years for those with at most secondary and 14 years for those withtertiary schooling.
Sources: LFS data underlying our calculation from CANSIM Table 282-0004; HDR estimates can be found on the International Human
Development Indicators website (http://hdr.undp.org/sites/all/themes/hdr_theme/country-notes/CAN.pdf).

To develop an estimate of average years of schooling, CSLS aggregates data on all
educational attainment categories to create three broad schooling level categories, andallocates individuals into these categories according to the highest level of schooling they
have attained, similar to what is done in Barro and Lee (2010). Individuals are considered
to have attained a certain level of schooling only if they have a certificate or diploma
indicating that they have completed that program. For example, an individual is placed in
the secondary school category if they have a high school diploma or certificate but nocertificates, diplomas or degrees from any further education, such as a university degree,
regardless of whether they attended a post-secondary institution or not.12 Individuals areplaced in the primary schooling category if they do not have a high school certificate or
diploma or if they have no formal education. 13
However, an earlier publication by the same authors (Barro and Lee, 2001), which
performs almost identical calculations, does state that duration data vary between countries
and are taken from the UNESCO (United Nations Educational, Scientific and Cultural)
12

Calver (2015) discusses some of the issues with this methodology. First, there is the issue of completion of a degree –if an individual begins but does not complete some post-secondary program, none of their schooling is counted. Second,
there is the issue of underassigning tertiary schooling. For example, suppose the most common form of post-secondary
school in Country A is a two year program but in Country B it is a more rigorous four year program. If the two countries
have the same enrolment rates, then Barro and Lee would estimate the same average educational attainment in the twocountries. This is likely an issue in Canada, were 2011 National Household Survey data shows that 25.9 per cent of the
population aged 25 to 64 had completed a university degree of some sort (corresponding to 15 years of schoolingminimum). Calver uses microdata on the number of years an individual spent in school to avoid this problem. While thisis likely not possible for the UNDP to do on a global scale, a better measure could use the sort of tertiary schoolingcompleted (e.g. certificate, Bachelor’s, Masters) to avoid the latter source of mismeasurement.
13
In 2015, Labour Force Survey data indicate that 15.2 per cent of Canadians aged 25 and over had not graduated fromhigh school (in the primary schooling category, allocated 8 years of schooling), 24.9 per cent had graduated high schoolor had attended some post-secondary schooling without completion (in the secondary schooling category, allocated 12
years), and 59.9 per cent had earned a post-secondary certificate or diploma or university degree (in the tertiary schoolingcategory, allocated 14 years). The 2011 National Household Survey data shows similar results, with 12.7 per cent, 23.2
per cent and 64.1 per cent of Canadians in the primary, secondary and tertiary school categories, respectively.

14

Organization statistical year book for various years. Examining the data on duration ofschooling available from the UNESCO Institute for Statistics (UIS) yields the following
duration data for Canada: primary is 6 years, secondary adds another 6 years and postsecondary (tertiary) adds another 2 years. 14
The estimates of average years of schooling are presented in Table 2. The LFSbased CSLS estimates are surprisingly quite similar to those in the most recent HDR,
reflecting the small share of Canadians who did not finish high school in the overall
population. For the majority of the period, the LFS-based estimates are marginally lower
than the corresponding HDR estimate. In 2015, the HDR estimate of average years ofschooling is 0.5 years higher than the LFS estimate.15
As average educational attainment is sensitive to the duration assumptions for eachschooling level, it is worth checking the sensitivity of the results to alternate assumptions.
One important test is to assign those with at most primary education 6 years of schooling,in line with UNESCO’s definition, instead of the more realistic 8 years assumed by CSLS.
When those with at most primary education are assigned 6 years of schooling, the datafrom the census gives estimates of 11.1 years in 2001 and 11.9 years in 2006 for those 25
and older. The LFS data similarly yield estimates of 11.4 years in 2000, 11.8 years in
2005, 12.2 years in 2011, and 12.3 years in 2014. These estimates are much closer to theresults of Barro and Lee (2014) than are the first set of CSLS estimates: 12.2 years in 2011
from LFS exceeds Barro and Lee’s estimate (12.1 years) by only 0.1 years. Since theassumption of 6 years of primary education is not realistic given the Canadian context,
CSLS will employ the original assumption of 8 years.
The validity of CSLS’s estimates is confirmed by Cohen and Soto (2007), whenestimate average years of schooling is computed by employing data from surveys
published by UNESCO and from an OECD database on educational attainment. Despiteusing the same UNESCO data source as Barro and Lee for their schooling duration
assumptions, their results for Canada exceed those of both the CSLS and Barro and Lee for
all available data years (11.7 years in 1990, 12.6 years in 2000, and 13.2 years in 2010). 16
Along with the higher estimates in the revised Barro and Lee dataset, this raises theconcern that the most recent HDR may be overestimating Canada’s average years ofschooling relative to the rest of the world, although this issue is not directly relevant to thisreport. More importantly, although the CSLS results are not identical to Barro and Lee’s
14

It is therefore difficult to determine how many years of education should be allocated to those with at most primaryschooling (i.e. those who did not complete secondary school). Although primary schooling is listed as lasting 6 years in
UNESCO’s 1999 Statistical Yearbook, schooling is mandatory in Canada up to at least the age of 16, for a total of 10
years (excluding kindergarten). Thus, 6 years of schooling allocated to those who do not complete high school willgrossly underestimate their years of schooling. As recently as the 1970s, however, the school leaving age was still 15 insome provinces, so there are still some the Canadian population today have received no more than 8 years of formal
schooling, ignoring the kindergarten years (Oreopoulos, 2006). Indeed, according to the LFS data, 4.1 per cent of those
aged 65 and over had eight or fewer years of schooling in 2016. Therefore, the CSLS allocates those with at most the
primary level of schooling 8 years of education. Secondary and tertiary education are more straightforward, and the years
allocated follow the UIS duration data: those with at most secondary schooling are allocated 12 years, and those withtertiary are assumed to have 14 years of schooling.
15
If the CSLS estimate using LFS data for Canada in 2015 (12.6 years) is inserted into the most recent HDRinternational rankings for average years of schooling, Canada would be in twelfth place instead of ranking sixth.
16
Data from Cohen and Soto (2007) can be found at http://soto.iae-csic.org/Data.htm.

15results, it is clear that the CSLS estimates are not unreasonable or inconsistent with theliterature.
ii. Expected Years of Schooling
UNESCO Institute for Statistics (UIS) (2009) defines school-life expectancy, or
expected years of schooling, as the “total number of years of schooling which a child of acertain age can expect to receive in the future, assuming that the probability of his or her
being enrolled in school at any particular age is equal to the current enrolment ratio for thatage.” Thus, school-life expectancy is simply the sum of the enrolment rates of each age ina population, where the enrolment rate of a certain age is defined as the number of peopleof that age enrolled in formal schooling divided by the total population of that same age.
Canada’s expected years of schooling for 2015 in the most recent HDR is 16.3
years, which places Canada in 22nd place in the most recent HDR rankings for thisindicator. The most recent HDR cites UNESCO as its data source for this measure. The
HDR simply uses for data on enrolment rates by age. The methodology used by the UNDP
for estimating school life expectancy is described in the UIS Educational Indicators:
Technical Guidelines (UIS, 2009), and this methodology will be followed here.
Unfortunately, the enrolment data for each age year are not publicly available in
Canada. Thus two sets of estimates of expected years of schooling will be calculated using
different data sources. The first will use administrative data on enrolment from Statistics
Canada, and the second will employ school attendance estimates from the Labour Force
Survey (LFS) for the population aged 15-29.
For the first set of estimates of expected years of schooling, administrative data onenrolment for 1996-2009 are taken from various versions of Summary Public School
Indicators for Canada, the Provinces and Territories, a Statistics Canada publication. Itshould be noted that kindergarten students are included in this enrolment data, and cannot
be separated out. Thus, this measure of expected years of schooling includes kindergarten
while all other education measures (including expected years of schooling using LFS data)
calculated in this paper do not. College and university enrolment data are taken from
Statistics Canada’s CANSIM database. The enrolment rate data can be seen in Appendix
Table 4.17
The CSLS calculates expected years of schooling by dividing the enrolment
numbers for certain levels of education (primary and secondary, college, and university)by the total population of the age group most likely to be in that level of schooling(primary and secondary, including one year of kindergarten: 5-17 years old and university
and college: 18-22 years old) to obtain the enrolment rate. It is assumed that enrolment
below age 5 and above age 22 is zero.18 For Canada in 2015, primary and secondary
17

Appendix tables are available at: http://www.csls.ca/reports/csls2017-06Appendix.pdf
Naturally, if 85.8 per cent of individuals aged 18-22 are enrolled in some form of education, assuming the enrollment
rate falls to zero at 23 is unrealistic. As such, our estimates ought to be understood to be lower bound. Our administrative
estimates are purely for the sake of comparison.
18

16

school enrolment was 99.9 per cent of all those covered by the sample, college enrolment
was 32.0 per cent, and university enrolment was 56.0 per cent.
These enrolment rates are then multiplied by the duration of each level (primaryand secondary: 13 years (including one year of kindergarten), college: 2 years, university:
4 years) to obtain expected years of schooling. This method is by no means perfect, asmany adults over age 22 enroll in secondary school or register in college or university
programs and many students do not complete their programs. However, due to data
limitations, this is the best approximation available.
It should be noted that the primary and secondary school enrolment data are only
for publicly funded schools (including adult high schools), which account for
approximately 93 per cent of Canadian students (Brockington, 2009). The exclusion ofprivate school students results in lower enrolment rates in the primary and secondary
school years and biases the estimates for expected years of schooling downwards.
The second set of estimates of expected years of schooling employs LFS data.19
The LFS captures data on whether an individual is attending school (either full-time orpart-time) during the regular school year (September to June) and organizes these data by
age instead of level of education. Since LFS data on student status are only available forthose aged 15-29 and the current school-leaving age is at least 16 in all Canadian provinces
and territories, the assumption is made that 100 per cent of individuals between the ages of
6 and 14 attend school and zero per cent are enrolled below the age of 6. Enrolment overage 29 is also assumed to be zero due to lack of data beyond this age.

19

Expected years of schooling using LFS data is calculated using the data in Table 3. First, the per cent of people inschool for each age group in a given year is multiplied by the number of years that age group represents (ie 15-19 is 5
years, 20-24 is 5 years and 25-29 is 5 years). These numbers are summed to obtain the expected year of schooling afterage 15. Second, nine years are added to this number to approximate 100 per cent enrolment between ages 6-14
(inclusive), yielding the expected years of schooling for a child born in that year. For Canada in 2011, the calculation is
as follows: Step 1: (5*0.837) + (5*0.419) + (5*0.142) =6.99. Step 2: 6.99 +9=15.99. Thus, Canada's expected years ofschooling result in 2011 is 15.99, rounded to 16.0 years.

17

Table 3: Full-time and Part-time School Attendance by age group, Canada, 2000-2015

Ages 15-19
Year
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015

NumberofStudents
1685.7
1,715.7
1,716.3
1,707.0
1,715.4
1,752.2
1,784.3
1,795.6
1,800.3
1,827.1
1,835.8
1,825.5
1,799.0
1,793.0
1,753.2
1,718.9

Ages 20-24

Population% inschool

2,046.9
2,063.5
2,074.3
2,078.7
2,092.6
2,121.3
2,151.8
2,173.4
2,192.3
2,198.0
2,191.3
2,178.6
2,153.9
2,118.9
2,076.0
2,034.4

82.4
83.1
82.7
82.1
82.0
82.6
82.9
82.6
82.1
83.1
83.8
83.8
83.5
84.6
84.5
84.5

NumberofStudents
757.2
788.2
807.8
824.6
856.2
891.9
876.4
882.3
866.4
885.4
938.4
951.6
1,012.4
1,013.2
1,013.2
1,009.0

Note: Number of students and population are given in thousands.
Source: CANSIM Table 282-0095 (LFS).

Ages 25-29

Population% inschool

2,021.2
2,054.8
2,086.3
2,119.2
2,150.9
2,176.6
2,194.2
2,204.6
2,210.9
2,226.3
2,252.4
2,286.9
2,336.0
2,378.3
2,398.1
2,397.7

37.5
38.4
38.7
38.9
39.8
41.0
39.9
40.0
39.2
39.8
41.7
41.6
43.3
42.6
42.3
42.1

NumberofStudents
247.0
269.0
271.9
278.9
284.9
288.0
292.5
292.8
297.7
307.6
313.1
321.7
321.7
329.7
317.2
321.9

Population% inschool

2,023.5
2,020.5
2,032.0
2,044.9
2,068.1
2,092.9
2,125.5
2,164.1
2,211.6
2,259.5
2,293.7
2,309.8
2,327.9
2,342.9
2,366.4
2,398.5

12.2
13.3
13.4
13.6
13.8
13.8
13.8
13.5
13.5
13.6
13.7
13.9
13.8
14.1
13.4
13.4

Ideally, the number of individuals of each age (i.e. 15, 16, 17 …) attending school
would be used. However, these data are not publicly available from the LFS, which instead
has attendance by age brackets. One problem with this method is that calculating expected
years of schooling using a wide age bracket (i.e. 15-29) assumes that each age has arelatively similar number of individuals. Using narrower age brackets available from the
LFS (15-19, 20-24 and 25-29) mitigates concerns about the age range’s distributions ofindividuals.20 When the in-school rates for these three age brackets are multiplied by the
number of years they represent (5 years each) and summed together, they represent the
expected years of schooling remaining for someone aged 15 years of age and over. Adding
nine to this number (to represent the 100 per cent enrolment from ages 6 to 14) yields the
expected years of schooling.
Table 3 gives the LFS data for those aged 15-29. In 2015, it is clear that the large
majority (84.5 per cent) of youth aged 15-19 are in school, while the opposite is true forindividuals aged 25-29 (just 13.4 per cent are in school). Not surprisingly, the 20-24 age
group lies between these two extremes, with 42.1 per cent in school in 2015. These series
have shown a slight upward trend since 2000.
20

We would like to stress the importance of this point, as it avoids composition of the group biasing theestimate for expected years of schooling over time. For example, the population of 15-19 year olds only grew
1.4 per cent from 2000 to 2014, while the populations of 20-24 year olds and 25-29 year olds grew 18.7 percent and 17.0 per cent from 2000 to 2014 respectively. As there are simply more children of the baby
boomers than in the subsequent cohort, there will be more students in the older age ranges. As a result, in2014 45.1 per cent of the population aged 15 to 29 was a student. Assuming 15 additional years of school,
our expected years of school estimate is biased downwards to 15.8.

18

Table 4: Expected Years of Schooling, Canada, 1990-201521

Year

UNDP – HDR

LFS data

Administrative Data

1990
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015

16.7
15.8
15.8
15.8
15.8
15.8
15.8
15.8
15.8
15.9
15.9
15.9
15.9
15.9
15.9
16.3
16.3

14.8
15.6
15.7
15.7
15.7
15.8
15.9
15.8
15.8
15.7
15.8
16.0
16.0
16.0
16.1
16.0
16.0

15.2
15.2
15.2
15.2
15.3
15.2
15.2
15.2
15.4
15.6
15.8
15.8
15.9
15.9
16.0
16.0

Sources: LFS data calculated using CANSIM Table 282-0095, HDR data can be found on the International Human Development
Indicators Website (http://hdr.undp.org/en/indicators/69706)

The estimates of expected years of schooling using LFS data are presented in Table
4. The most recent HDR relies on UNESCO data (UNDP, 2017b). The CSLS estimates
based on LFS data are close to UNESCO’s estimates in 2000 and 2005 compared to the
CSLS estimates based on administrative data. Our LFS-based estimate is 15.6 versus
UNESCO’s 15.8 in 2000, and 15.9 years in 2005 compared to UNESCO’s 15.8. CSLS’s
2015 estimate using LFS data is also quite similar to the HDR estimate for 2015: 16.0
compared to 16.3 years, respectively.
C. IncomeIn the most recent HDR, Canada’s Gross National Income (GNI) per capita for2015 is $42,582 in purchasing power parity (PPP) adjusted 2011 US dollars, the 22ndhighest of all nations with an HDI ranking. The most recent HDR uses GNI estimates andpopulation data from the UN Statistical Division National Accounts Main Aggregates
Database. While the GNI estimates are nearly identical those reported by Statistics
Canada, the population figures are slightly different. For the years lacking GNI estimateswhen the UNDP extracted data, projections were developed using information from the
IMF’s World Economic Outlook publications.
National accounts estimates from Statistics Canada state that in 2015 Canada’s
GNI per capita was $54,554 in current Canadian dollars. This nominal GNI is thendeflated by the gross final domestic expenditure implicit price index (2011=100), and21

Note that the CSLS’s estimates have an upward bias as a result of including part-time students in the student
population. Note that in 2015, 97% of students between the ages of 15 and 19 were full-time and for students between theages of 20 and 24, 88% were full-time.

19

adjusted by Canada’s GDP (PPP) in 2011.22 This PPP adjustment simply translates
constant 2011 Canadian dollars into a common unit used in international comparisons(2011 US dollars) so that the cost of a representative basket of goods in Canada will be thesame as in the United States, given the exchange rate.23 Canada’s GNI estimate for 2015 in2011 US PPP adjusted dollars is $43,185. This estimate does differ somewhat from the
projection used in the HDI, which is $42,582 (Table 5).24
Table 5: GNI per capita, PPP adjusted 2011 US dollars, Canada, 1990, 2000, 2005-2015

UNDP – HDR
Year

PPP adjusted
2011 USD

Current
dollars

1990
2000
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015

30,17436,40839,52340,30640,70340,69338,04339,91940,80841,06841,62442,29842,582

24,122
34,97943,04845,08347,13948,98645,80447,91050,561
51,521
53,15154,87854,554CSLS
Gross final domestic
2011 constantexpenditure, implicit
CAD
price index 2011=100
67.8
35,58581.0
43,16089.1
48,32791.2
49,421
93.4
50,486
95.7
51,18496.5
47,44397.9
48,962100.0
50,561
101.7
50,670103.4
51,423105.8
51,875107.4
50,806

PPP adjusted
2011 USD
29,74935,77941,46542,601
43,41844,07040,184
41,47142,82543,01843,60744,094
43,185

Sources: CSLS: Current dollar from CANSIM Table 380-0083, Implicit Price Index from CANSIM 380-0102, Canada’s PPP for GDP in 2015
was 0.85 US dollars per Canadian dollar (PPP from CANSIM table 380-0058).

D. Overall Human Development Index
Table 6 presents the results from the CSLS’s attempt to replicate the 2015 HDI
estimate for Canada. The CSLS is able to closely replicate both the life expectancy index
and the income index. CSLS estimates the 2015 Canadian life expectancy index to be
0.964 compared to that from 2015 HDR data of 0.957. Similarly, using the 2015 GNI per
capita projection from CSLS yields an income index of 0.917, compared to 0.914 using in
the most recent HDR. While the largest discrepancy was found in the education index due
to the average educational attainment component, here too it was reasonably close: 0.889
for the HDR compared to 0.865 by the CSLS. These indices produce an HDI index of
0.914 which closely approximates the official estimate of the 2015 HDI for Canada of
0.920. The insertion of the CSLS HDI estimate for 2015 would change Canada’s tenthplace ranking to fourteenth place.

22

While GNI and GNP are equivalent in current prices, we stress that in constant price terms they are not. Income
concepts like GNI ought to be deflated with the gross final domestic expenditure deflator, while output concepts like
GNP ought to be deflated with the GDP deflator. The UNDP uses the GDP deflator in the most recent HDR, a minor
accounting error.
23
Canada’s PPP for GDP in 2011 was 0.847 US dollars per Canadian dollar (PPP from CANSIM Table 380-0058).
24
Employing our GNI estimate in the most recent HDR’s GNI rankings increases Canada’s ranking from 22nd to 21stplace.

20

Table 6: CSLS Replication of the Official Human Development Index Estimate for Canada, 2015

CSLS estimates
Dimension

Life Expectancy at Birth (years)
Life Expectancy Index
Average Educational Attainment(years)Average Educational Attainment
Index
Expected Years of Schooling
Expected Years of Schooling Index
Education Index
GNI per capita (2011 US PPP adjusted
dollars)
Income Index
HDI

A
82.2
0.957

B
82.6
0.964

Proportion ofHDR
estimates (%)
C=B/A
100.5
100.7

13.1

12.6

96.9

0.873

0.842

96.4

16.3
0.906
0.889

16.0
0.889
0.865

98.2
98.1
97.3

42,582

43,185

101.4

0.914
0.920

0.917
0.914

100.7
99.3

UNDP – HDR

CSLS

Note: For "UNDP - HDR", CSLS uses the data listed in the most recent HDR and calculates the indices and HDI identically to the othercolumn.
Source: CSLS estimates from Table 1, 2, 3, 5 and most recent HDR.

III. Estimates of the Human Development Index for the Canadian
Provinces and Territories
Though we do come quite close, it is clear from the previous section that it is notpossible to precisely replicate the estimates of the HDI indicators for Canada using
Canadian data sources. As a result, directly calculating each province and territory’s HDI
using the raw estimates developed by the CSLS is not the most exact estimation strategy.
To obtain estimates which are the most internationally comparable for the provinces andterritories, we take the proportion that each province and territory’s estimate represents ofthe corresponding Canadian estimate and applying that ratio to Canada’s most recent HDR
official estimates.
To obtain the proportions needed to develop the internationally comparable
estimates, the provincial and territorial estimates are developed using the same
methodology and data sources used in replicating Canada’s HDI in the previous section.
This reduces as much as possible any error arising from using the proportion method of
estimating the provincial and territorial HDIs. Therefore, this section will estimate thethree components of the HDI (life expectancy, education and income) for each Canadianprovince or territory in a manner that is as consistent as possible with the most recent
HDR. The HDI results and rankings for each province will then be discussed.25

25

Due to data limitations, this report will focus on the period 2000 to 2015 when discussing trends over time. Full timeseries on all of the HDI domains are available in the Appendix Tables. Caution should be taken when interpreting
education data for the Territories because of the small sample size involved.

21

A. Life Expectancy
The life expectancy data for the provinces and territories are taken from the same
Statistics Canada table as that for Canada, and are only available up to 2009. CSLS
developed estimates for 2010-2015 by employing the historical growth rates of life
expectancy in each province and territory from 1991 to 2009 (Appendix Table 1).26 While
extending any series five years forward is not ideal, because life expectancy moves slowly
and steadily over time we do not believe it is a large source of error.
Table 7 shows these raw CSLS estimates in addition to the HDR consistentestimates and the resulting life expectancy index for 2000, 2005, 2011, and 2015. It isnotable that the spread between the lowest and highest life expectancy decreased between
2000 (12.7 years) and 2015 (10.7 years). This decreased variation is largely caused by the
5.1 year increase in the average life expectancy of Nunavut between 2000 and 2015.
Despite this relatively large improvement, Chart 1 illustrates that in 2015, Nunavut still
had by far the lowest life expectancy of all the regions. For 2015, this territory’s life
expectancy was estimated to be 72.9 years, which was 4.6 years lower than the next lowest
jurisdiction (Yukon, 77.5 years).
Table 7: Life Expectancy Estimates and Index, Canada and the Provinces/Territories, 1990, 2000, 2011, and 2015

Year

CAN

NL

PEI

NS

NB

QC

ON

MB

SK

AB

BC

YT

NWT

NU

78.6
79.3
80.2
81.2

78.8
79.8
80.1
80.9

79.2
80.4
81.5
83.0

79.5
80.7
81.7
83.0

78.1
79.0
79.3
79.9

78.6
79.3
79.7
80.2

79.5
80.3
80.8
81.7

80.5
81.2
82.3
83.6

75.6
77.0
76.7
77.5

75.9
78.0
77.4
78.0

67.8
72.0
71.6
72.9

78.3
79.1
80.1
80.8

78.5
79.6
80.0
80.5

78.9
80.2
81.6
82.5

79.2
80.5
81.7
82.5

77.8
78.8
79.1
79.5

78.3
79.1
79.5
79.8

79.2
80.1
80.7
81.3

80.2
81.0
82.3
83.2

75.3
76.8
76.6
77.1

75.6
77.8
77.2
77.6

67.5
71.8
71.7
72.5

0.897
0.909
0.925
0.935

0.900
0.917
0.923
0.931

0.906
0.926
0.947
0.962

0.911
0.931
0.949
0.962

0.889
0.905
0.909
0.915

0.897
0.909
0.915
0.920

0.911
0.925
0.934
0.943

0.926
0.938
0.959
0.972

0.851
0.874
0.870
0.878

0.856
0.889
0.880
0.886

0.731
0.797
0.795
0.808

Raw Estimates (years)

2000
79.4
77.3
78.2
2005
80.4
78.2
79.8
2009
81.4
79.4
79.9
2015
82.6
80.3
81.1
HDR Consistent Estimates (years)
2000
79.1
77.0
77.9
2005
80.2
78.0
79.6
2011
81.4
79.3
79.9
2015
82.2
79.9
80.7
Life Expectancy Index
2000
0.909
0.877
0.891
2005
0.926
0.892
0.917
2011
0.945
0.912
0.921
2015
0.957
0.921
0.933

26

Appendix tables are available at: http://www.csls.ca/reports/csls2017-06Appendix.pdf

22

Chart 1: Life Expectancy, Raw Estimates, Canada and the Provinces/Territories, 2015

86
84
82

79.9 80.2 80.3

80

83.6

77.5 78.0

78
Years

81.7
80.9 81.1 81.2

82.6 83.0 83.0

76
74

72.9

72
70
68
66

The growth rates for the provinces and territories ranged between 0.14 to 0.48 percent per year over the 2000-2015 period. Notably, the three provinces with the fastest
growth were Ontario (0.29 per cent per year), Quebec (0.31 per cent per year), andNunavut (0.48 per cent per year) (Chart 2). As three quarters of Canada’s population
resides in Ontario, Quebec, and British Columbia, their high rates of growth in life
expectancy result in the national growth rate exceeding 10 provinces and territories.
Table 8 shows the ranking of the provinces and territories (where 1 is the highest
performing province in that indicator) for 2000, 2005, 2011, and 2015. Most of theprovinces and territories maintained the same relative position between 2000 and 2015; forexample, Nunavut was 13th for all three years and British Columbia remained the top
province. The province that fell the most in the rankings was Saskatchewan, from sixth toninth place. This was reflected in the compound annual growth rates, as Saskatchewan had
the worst growth rates of all thirteen regions (Chart 2). On the other hand, despite the very
rapid growth in life expectancy between 2000 and 2015, Nunavut continued to lag behindthe other provinces and territories.

23

Average per cent change per year

Chart 2: Compound Annual Growth in Raw Estimates of Life Expectancy, per cent per year, Canada and theProvinces/Territories, 2000-2015

0.60
0.48

0.50
0.40
0.30
0.20

0.14

0.15

0.16

0.18

0.18

0.18

0.22

0.24

0.25

0.27

0.26

0.29

0.31

0.10
0.00

Examining the rankings of the regions’ life expectancies in the 2011 HDRinternational rankings highlights the discrepancies between the regions. Table 8 reports the
rankings of the provinces and territories from entering each (alone) into the international
rankings as if it were a country. British Columbia, the top Canadian province or territory,
would rank fourth, while Nunavut, the lowest ranking province or territory, would be in103rd place.
Table 8: Life Expectancy Rank, Canada and the Provinces/Territories, 2000, 2005, 2011, and 2015

Year

CAN

NL

PEI

NS

NB

QC

ON

MB

SK

AB

BC

YT

NWT

NU

5
5
5

4
3
3

2
2
2

9
9
8

6
7
9

2
4
4

1
1
1

12
12
12

11
11
11

13
13
13

35

33

21

4

46

43

103

Regional Rank (Based on Raw Estimates)
2000
2005
2011
2015

-

10
10
10

8

8
5
6

6

6
7
7

5

7

3

2

10

9

4

1

12

11

13

2016 International HDR Rank (Based on HDR Consistent Estimates)
2015

12

33

28

27

30

9

9

Note: The "2016 International HDR Rank" is based on inserting that province alone into the most recent HDR international rankings as if it were a country.

24

B. Education
i. Average Years of Education
Average educational attainment for the provinces and territories is calculated using
LFS data (Appendix Table 8).27 It is calculated in exactly the same manner as described
for Canada, allocating 8 years for those with at most primary education, 12 years for thosewith at most secondary and 14 for those who have a tertiary education. The resulting
estimates are reported for 2000, 2005, 2011, and 2015 in Table 9.
Examining the raw estimates for average educational attainment, the gap between
the lowest and highest average educational attainment estimates were similar in 2000 (1.5
years) and 2015 (1.9 years). The primary reason for this widening of the gap was due to
Nunavut’s slow growth in educational attainment. Nunavut’s average educational
attainment was 0.7 years lower than the second lowest province or territory in 2000
(Newfoundland and Labrador, 11.4 years), slipping to be 1.3 years lower than the next
lowest province or territory in 2015 (Newfoundland and Labrador, 12.2 years). These
values translate into rankings between second and 40th place in the most recent HDRinternational rankings for every region.
Table 9: Average Educational Attainment Estimates and Index, Canada and the Provinces/Territories, 2000,
2005, 2011, and 2015

Year

CAN

NL

PEI

NS

NB

QC

ON

MB

SK

AB

BC

YT

NWT

NU

11.6
11.9
12.1
12.3

11.6
12.0
12.3
12.5

12.1
12.3
12.6
12.7

11.7
12.0
12.3
12.5

11.7
12.0
12.3
12.4

12.2
12.4
12.6
12.7

12.2
12.4
12.7
12.8

12.2
12.4
12.7
12.8

12.2
11.9
12.2
12.3

10.7
10.6
10.7
10.9

10.7
11.9
12.4
12.8

10.7
12.0
12.6
12.9

11.1
12.3
12.9
13.2

10.8
12.0
12.6
12.9

10.8
12.0
12.6
12.9

11.2
12.4
12.9
13.2

11.2
12.4
13.0
13.2

11.2
12.4
13.0
13.3

11.2
11.8
12.5
12.8

9.9
10.6
11.0
11.3

0.711
0.790
0.826
0.851

0.715
0.799
0.841
0.863

0.742
0.821
0.860
0.879

0.722
0.797
0.838
0.862

0.718
0.798
0.839
0.861

0.748
0.827
0.861
0.880

0.750
0.825
0.865
0.883

0.749
0.826
0.864
0.887

0.748
0.790
0.831
0.853

0.657
0.704
0.733
0.751

Raw Estimates (years)

2000
11.9
11.4
11.5
11.8
2005
12.2
11.8
12.0
12.1
2011
12.5
12.1
12.3
12.4
2015
12.6
12.2
12.4
12.6
HDR Consistent Estimates (years)
2000
11.0
10.5
10.6
10.9
2005
12.2
11.7
12.0
12.1
2011
12.8
12.4
12.6
12.7
2015
13.1
12.7
12.9
13.0
Average Educational Attainment Index
2000 0.733 0.701 0.708 0.726
2005 0.813 0.782 0.797 0.8052011 0.853 0.827 0.841 0.843
2015 0.873 0.845 0.859 0.868

Source: CANSIM Table 282-0004 (LFS). Territorial data obtained by special request from Statistics Canada. LFS data are not available for Nunavut before
2004. Since there is no clear pattern in the yearly growth rates for Nunavut, estimate for 2000 (italicized) is assumed to be equal to the 2004 estimate.

27

Appendix tables are available at: http://www.csls.ca/reports/csls2017-06Appendix.pdf

25

Chart 3: Average Educational Attainment, Raw Estimates, Canada and the Provinces/Territories, 2015

13.0
12.2 12.3

12.5

12.3 12.4

12.4

12.6
12.5 12.5 12.6

12.7 12.7 12.8

12.8

Years

12.0
11.5
11.0

10.9

10.5
10.0
9.5

Table 10 also shows the ranking of each province and territory within Canada.
There is some change between 2000 and 2015 in terms of rankings among the different
provinces and territories. The rank of average educational attainment in the Northwest
Territories has declined significantly since 2000, dropping from fourth to tenth place.
Quebec and Ontario, conversely, improved their relative position (ninth to sixth and fifth
to fourth place, respectively). British Columbia, Alberta, and Yukon are consistently
among the top provinces and territories, while New Brunswick, Newfoundland andLabrador, as well as Nunavut consistently rank in the bottom four throughout the period.

Average per centchange per year

Chart 4: Compound Annual Growth in Average Educational Attainment, per cent per year, Canada and theProvinces/Territories 2000-2015

0.6
0.5
0.4
0.3
0.2
0.1
0.0

0.47 0.51
0.43 0.46
0.41
0.41
0.40
0.34 0.35 0.38
0.30 0.31
0.09 0.11

There is some evidence that provinces and territories are converging in average
educational attainment by the growth rates for 2000-2015 despite slow growth in Nunavut,
which are illustrated in Chart 4. Chart 3 and Chart 4 show British Columbia and Alberta
were among the top ranked provinces in 2015 but were also among the regions with theslowest growth (less than 0.35 per cent per year), while Newfoundland and Labrador andPrince Edward Island had compound annual growth rates that were above the national
average (0.38 per cent per year) despite a low ranking among the provinces and territories.
26

The Northwest Territories and Nunavut were the exceptions, as they had both lower ranks
in 2015 and the weakest compound annual growth rates of all Canadian regions.
Table 10: Average Educational Attainment Rank, Canada and the Provinces/Territories, 2000, 2005, 2011, and
2015

Year

CAN

NL

PEI

NS

NB

QC

ON

MB

SK

AB

BC

YT

NWT

NU

10
10
12
11

9
6
6
6

5
4
4
4

7
9
9
7

8
7
8
8

3
1
3
3

1
3
1
2

2
2
2
1

4
11
10
10

13
13
13
13

Regional Rank (Based on Raw Estimates)
2000
2005
2011
2015

-

12
12
11
12

11
8
7
9

6
5
5
5

2016 International HDR Rank (Based on HDR Consistent Estimates)
2015
6
8
7
7
7
7
3
7
7
3
3
2
8
40
Note: The "2016 International HDR Rank" is based on introducing that province alone into the most recent HDR international
rankings as if it were a country.

ii. Expected Years of Schooling
Expected years of schooling are estimated for the provinces and territories using
LFS data. Once again, the methodology used here is the same as the one used to replicate
the Canadian estimates. In 2015, the raw estimates for Canada closely approximate theofficial estimate from the most recent HDR, and as such there ought to be minimal error asa result of scaling the raw provincial values in Table 11 to obtain HDR consistentestimates.
Table 11: Expected Years of Schooling Estimates and Index, Canada and the Provinces/Territories, 2000, 2005,
2011, and 2015

Year

CAN

NL

PEI

NS

NB

QC

ON

MB

SK

AB

BC

YT

NWT

NU

15.7
15.6
15.7
15.5

14.9
15.3
15.3
15.2

15.7
16.1
16.4
16.6

15.9
16.2
16.2
16.2

15.0
15.5
15.3
15.3

15.1
15.1
15.1
15.1

14.8
14.9
15.0
15.1

15.6
15.7
15.9
15.6

15.7
14.6
14.1
14.8

14.5
14.1
14.6
14.7

13.1
13.8
13.1
13.2

15.9
15.5
15.6
15.8

15.1
15.3
15.2
15.5

15.9
16.0
16.3
17.0

16.1
16.2
16.2
16.5

15.2
15.4
15.3
15.6

15.3
15.1
15.0
15.4

15.0
14.9
15.0
15.4

15.8
15.6
15.9
15.9

15.9
14.6
14.0
15.1

14.7
14.0
14.5
15.0

13.3
13.8
13.0
13.4

0.883
0.861
0.869
0.880

0.837
0.848
0.845
0.862

0.885
0.891
0.907
0.942

0.893
0.897
0.897
0.919

0.842
0.855
0.849
0.868

0.848
0.838
0.833
0.854

0.836
0.826
0.831
0.856

0.880
0.867
0.881
0.884

0.886
0.809
0.778
0.839

0.816
0.780
0.808
0.831

0.737
0.764
0.725
0.745

Raw Estimates (years)

2000
15.6
15.7
15.1
2005
15.9
15.7
15.3
2011
16.0
15.5
15.5
2015
16.0
15.8
15.4
HDR Consistent Estimates (years)
2000
15.8
15.9
15.3
2005
15.8
15.7
15.2
2011
15.9
15.5
15.4
2015
16.3
16.1
15.6
Expected Years of Schooling Index
2000
0.878
0.883
0.851
2005
0.878
0.870
0.847
2011
0.883
0.859
0.855
2015
0.906
0.897
0.869

Source: CSLS calculations using CANSIM Table 282-0095 (LFS). Territorial data obtained by special request from Statistics Canada.
LFS data are not available for Nunavut before 2004. Since there is no clear pattern in the yearly growth rates, estimate for 2000
(italicized) is assumed to be equal to the 2004 estimate.

27

An examination of these raw estimates shows that roughly one year and a half
separates the lowest and highest ranking provinces in both 2000 and 2015 (from 15.1 years
to 16.6 years), with all three territories consistently ranking below the lowest provincethroughout the period. The similarity in expected years of schooling across provinces is
illustrated for 2015 in Chart 5. The highest expected years of schooling in 2015 was inQuebec at 16.6 years, closely followed by Ontario (16.2 years). 28
Compared to average educational attainment, there was less movement in theregional rankings between 2000 and 2015 for this measure of education (Table 12).
Quebec and Ontario remained in the top two positions, while the Yukon and Nunavut
territories occupied the bottom two places between 2000 and 2015. None of the provinceschanged their relative position by more than four places in the time frame. It is noteworthy
that the top and bottom regions in 2015 are not the same for average educational
attainment and expected years of schooling. Indeed, Alberta was in third place for theformer and tenth place for the latter, while Newfoundland and Labrador was twelfth for theformer and third place for the latter in 2015. As average educational attainment reflects thecurrent population’s level of education and expected year of schooling estimates in part the
future level of schooling, it could be the case that we will see a reversal of educational
attainment levels down the road. However, it may also be the case that the educated tend to
migrate to certain provinces instead of others.
Chart 5: Expected Years of Schooling, Raw Estimates, Canada and the Provinces/Territories, 2015

18.0

16.6
15.8 16.0 16.2
15.6
15.5
15.4
15.3
15.2
14.7 14.8 15.1 15.1

16.0
14.0

13.2

Years

12.0
10.0
8.0
6.0
4.0
2.0
0.0

The growth rates indicate that the gap in expected years of schooling over time
between the top and bottom ranked regions is increasing (Chart 6). Nunavut was the lowest
ranked region in 2000 and experienced significant negative growth from 2000 to 2015,28

In 2015, the LFS shows that 48.8 per cent of the population aged 15 to 29 in Quebec was attending school, comparedto the Canadian average of 44.6 per cent. The respective figures for the 15-19 age group were 85.1 per cent versus 84.5
per cent, for the 20-24 age group 49.7 per cent versus 42.1 per cent, and for the 25-29 age group 18.0 per cent versus 13.4
per cent.

28

while Quebec, the second ranked province in 2000, experienced the highest growth of allprovinces. However, other than these two regions, there does not seem to be significant
positive or negative correlation between the regions’ ranking and their growth rate.
Table 12: Expected Years of Schooling Rank, Canada and the Provinces/Territories, 2000, 2005, 2011, and 2015

Year

CAN

NL

PEI

NS

NB

QC

ON

MB

SK

AB

BC

YT

NWT

NU

10
7
8
8

3
2
1
1

1
1
2
2

9
6
7
7

8
9
9
10

11
10
10
9

6
4
3
4

2
11
12
11

12
12
11
12

13
13
13
13

Regional Rank (Based on Raw Estimates)
2000
2005
2011
2015

5
3
5
3

-

7
8
6
6

4
5
4
5

2016 International HDR Rank (Based on HDR Consistent Estimates)
2015
22
27
35
32
36
13
18
35
38
38
31
45
47
85
Note: The "2016 International HDR Rank" is based on introducing that province alone into the most recent HDR international
rankings as if it were a country.

Since many developed countries are clustered around the same values for expected
years of schooling in the most recent HDR international rankings, the provinces andterritories are remarkably spread out in terms of ranking considering how close theirestimates are in absolute terms. Indeed, while Quebec would be in 13th place, Nunavut
would be 85th.
Chart 6: Compound Annual Growth in Expected Years of Schooling, per cent per year, Canada and theProvinces/Territories, 2000-2015

Average per cent change per year

0.50

0.38

0.40
0.30
0.20
0.10

0.01 0.03

0.00
-0.10

-0.06

-0.20

0.07

0.12
0.08 0.11

0.15 0.16 0.16 0.17

-0.01

-0.30
-0.40
-0.50

-0.40

29

C. Income
In the most recent HDR, the indicator for the income dimension is GNI per capita.
Unfortunately, Statistics Canada has not developed a GNI measure for the Canadianprovinces and territories despite measuring it for the Canadian economy on the whole.29
The best way to approximate this income measure is to adjust provincial and territorial
GDP by the national difference observed between nominal GNI and GDP in that year
(Canada’s GNI was 98.2 per cent of Canada’s GDP in 2011).30 Once a province or
territory’s GDP is adjusted by the national nominal GDP to GNI ratio, population
estimates are used to obtain GNI per capita. 31 The raw estimates for 2000, 2005, 2011, and2015 are presented in Table 13.
It should be noted that there are no purchasing power parity (PPP) data available tocorrect for price differences across Canada, so one dollar is assumed to buy the sameamount of goods in all provinces.32 For example, when comparing food prices in Nunavut
with the CPI Food Price Basket from Statistics Canada, the Nunavut Bureau of Statistics(2015) found that in general, Nunavummiut pay around twice as much as Canadians forthe same basket of goods. It may well be unrealistic to ignore regional price differences
altogether, but without PPP data by region no other assumptions can be reasonably madeto try and capture variations in purchasing power.

29

This is largely a matter of accounting difficulties. The difference between GNI and GDP is income earned by residents
abroad less income earned by non-residents domestically. At the provincial level it is harder to define what income isearned “abroad.” Statistics Canada would have to somehow account for workers who cross a provincial border to work,
as well as a company based in one province doing business across the country.
30
Nominal GNI is by definition equal to nominal GNP, which is equal to GDP plus net production from non-residents.
See Ross and Murray (2010) for a greater discussion.
31
It is worth noting that the GDP to GNI ratio almost certainly differs significantly across the country. As a result ofenergy resources in provinces such as Newfoundland and Labrador, a significant amount of income earned in theprovince is attributable to corporations located outside of province.
32
Thomas (2016) does provide an alternative to making no adjustment whatsoever. Thomas uses a Statistics Canada
series on the consumer price in the Canadian provincial capital cities to roughly estimate purchasing power differences
across provinces. While this is an alternative, it exclusively looks at consumer prices, and altogether ignores the prices
faced by firms. For example, the prices faced by the Albertan oil firms who earned an extremely significant portion of theprovince’s income would not be included in the price adjustment. Rather than introduce more assumptions, we opt not toadjust our GNI figures whatsoever.

30

Table 13: Gross National Income per capita Estimates and Income Index, Canada and the Provinces/Territories, 2000, 2005, 2011, and
2015
Year

CAN

NL

PEI

NS

NB

QC

ON

MB

SK

AB

BC

YT

NWT

NU

2000
34,97926,092
24,151
2005
43,04842,37230,201
2011
50,561
62,67036,944
2015
54,55456,06041,510Raw Estimates (2011 PPP adjusted USD)

26,56233,552
39,111
41,98427,01133,45840,90343,14430,47436,19342,23645,417

37,68943,52048,79954,472

29,61935,81344,68850,03933,13444,25568,83769,061

47,624
66,484
77,52976,90032,44740,81947,27252,44940,31548,27069,05971,36064,078100,316
106,675
107,446

31,51437,48358,35565,953

2000
2005
2011
2015

27,17032,31833,12733,23527,62932,22734,645
34,15331,171
34,86235,77435,95238,551
41,92041,333
43,12030,29734,49637,851
39,61233,892
42,62758,30554,66948,71364,03965,66760,87533,19039,31840,03941,51941,23746,49558,49356,48965,544
96,62790,35385,05532,235
36,10449,42652,209Raw Estimates (current dollars)

35,77941,46542,82543,185

26,68940,81453,08144,37824,70429,09031,29132,859HDR Consistent Estimates (2011 PPP adjusted US dollars)
2000
2005
2011
2015

36,40839,52340,80842,582

27,15838,90350,58143,75825,13827,72829,81732,40027,64730,80431,567
32,771

28,11430,71833,01333,676

31,71933,23034,08835,45039,22939,95739,38642,51830,82932,881
36,06839,05834,487
40,63155,55953,90549,56961,04062,57460,02533,77337,44738,15340,93941,962
44,31755,73755,70066,695
92,10286,097
83,86732,801
34,41447,09851,480

0.847
0.901
0.940
0.919

0.835
0.850
0.861
0.873

0.849
0.866
0.869
0.875

0.852
0.865
0.876
0.879

0.870
0.877
0.881
0.887

0.902
0.905
0.903
0.914

0.866
0.875
0.889
0.901

0.883
0.907
0.955
0.950

0.937
0.969
0.973
0.966

0.879
0.895
0.898
0.909

0.912
0.921
0.955
0.955

0.982
1.000
1.000
1.000

0.875
0.882
0.930
0.943

Income Index
2000
2005
2011
2015

0.891
0.903
0.908
0.914

Source: CANSIM Table 384-0038 for GNI, PPP from CANSIM Table 380-0058, and Appendix Table 7a for population.33

Unlike the other indicators that make up the HDI, there is quite substantial variation in estimated
GNI per capita between provinces and territories, ranging from $24,151 (current dollars) to $64,078 in
2000 and $41,510 to $107,446 in 2015. The Northwest Territories, the top ranking province or territory, hasnearly triple the estimated GNI per capita of Prince Edward Island, the lowest ranking one (Chart 7).
Chart 7: GNI per capita, current dollars, Raw Estimates, Canada and the Provinces/Territories, 2015

120,000

Current dollars

100,000
80,00060,00040,00020,000
033

Appendix tables are available at: http://www.csls.ca/reports/csls2017-06Appendix.pdf

31

Table 14 illustrates the ranking among provinces and territories in this indicatorfrom 2000 to 2015. Most provinces and territories remain in similar positions. The
Northwest Territories and Alberta dominate the rankings and Prince Edward Island ranked
last throughout the period. Three provinces, however, moved significantly in the rankings:
Newfoundland and Labrador rose from twelfth to sixth place, while Quebec and Ontario
fell from eighth to tenth place and fourth to seventh place respectively. These substantialchanges in relative position among these provinces were also reflected in the growth ratesof these provinces. Newfoundland and Labrador’s nominal GNI per capita grew the fastest
at 5.23 per cent per year from 2000 to 2015, while Ontario and Quebec both experienced
nominal GNI per capita growth below the national average of 3.01 per cent per year (Chart
8).
Chart 8: Compound Annual Growth in Nominal GNI per capita, per cent per year, Canada and theProvinces/Territories, 2000-2015

Average per cent change per year

6.00
5.02 5.05

5.00
4.00
3.00

2.49

2.70

3.01 3.10 3.17

3.25 3.25

3.51 3.56 3.68

5.23

3.88

2.00
1.00
0.00

Looking at the provinces and territories’ placements in the most recent HDRinternational rankings, there is an unsurprisingly substantial difference between the ranksof the top and bottom regions. The Northwest Territories would claim the second overall
spot, while Prince Edward Island and Nova Scotia would rank in 35th place (Table 14).
Table 14: Gross National Income per capita Rank, Canada and the Provinces/Territories, 2000, 2005, 2011, and
2015

Year

CAN

NL

PEI

NS

NB

QC

ON

MB

SK

AB

BC

YT

NWT

NU

10
12
11
11

8
9
10
10

4
5
7
7

9
10
9
9

5
4
4
4

2
2
2
2

6
7
8
8

3
3
3
3

1
1
1
1

7
8
6
5

Regional Rank (Based on Raw Estimates)
2000
2005
2011
2015

-

12
6
5
6

13
13
13
13

11
11
12
12

2016 International HDR Rank (Based on HDR Consistent Estimates)
2015
22
20
35
35
32
30
23
24
11
9
24
10
2
12
Note: The "2016 International HDR Rank" is based on introducing that province alone into the most recent HDR international
rankings as if it were a country.

32

D. Overall Human Development Index
Since the CSLS’s methods and Canadian data sources result in estimates that arequite close to those in the most recent HDR, the CSLS takes the ratio of each jurisdiction’s
raw estimate to the national raw estimate and applies it to the most recent HDR’s official
estimates for Canada in order to obtain an internationally comparable HDI estimate for thejurisdiction. This method results in provincial and territorial estimates that are compatible
with the most recent HDR while still representing the same relationship as is shown
between the raw CSLS estimates for the provinces/territories and Canada.
The CSLS’s HDI estimates for Canada and the provinces/territories are given for
2000, 2005, 2011, and 2015 in Table 15 and the provincial and territorial ranking for 2015
is illustrated in Chart 9. Alberta and Ontario were found to have the highest HDI of all
regions or jurisdictions, while British Columbia came in third. Nunavut and New
Brunswick held the bottom two spots for 2015, though Nunavut was significantly lower
than New Brunswick.
Table 15: Human Development Index, Canada and the Provinces/Territories, 2000, 2005, 2011, and 2015

Year

CAN

NL

PEI

NS

NB

QC

ON

MB

SK

AB

BC

YT

NWT

NU

0.858
0.882
0.900
0.916

0.876
0.898
0.910
0.925

0.844
0.868
0.880
0.894

0.853
0.877
0.900
0.908

0.878
0.905
0.916
0.925

0.872
0.892
0.909
0.921

0.859
0.870
0.880
0.898

0.869
0.896
0.903
0.912

0.764
0.802
0.814
0.829

HDI Estimates (Based on HDR Consistent Estimates)

2000
0.867
0.838
0.834
2005
0.891
0.872
0.862
2011
0.906
0.898
0.876
2015
0.920
0.903
0.890
Source: CSLS Calculations.

0.850
0.869
0.883
0.894

0.840
0.866
0.877
0.888

Chart 9: Human Development Index, Canada and the Provinces/Territories, 2015

0.940
0.920
0.900
HDI

0.880
0.860
0.840
0.820
0.800
0.780

Given the relative stability in provincial and territorial rank observed within
Canada for most regions in most indicators, it is not surprising to see little variation in the33

provincial and territorial HDI rank over time (Table 16). Alberta, Ontario, and British
Columbia were in the top four places throughout the 2000 to 2015 period. The only
province or territory that changed rank significantly was Newfoundland and Labrador,
which rose from 11th place in 2000 to 7th in 2015 as its income per capita increased
dramatically.
Table 16: Human Development Index Rank, Canada and the Provinces/Territories, 1990, 2000, 2011, and 2015

Year

CAN

NL

PEI

NS

NB

QC

ON

MB

SK

AB

BC

YT

NWT

NU

10
11
11
12

6
5
6
4

2
2
2
2

9
10
10
10

7
6
5
6

1
1
1
1

3
4
3
3

5
8
9
8

4
3
4
5

13
13
13
13

Regional Rank (Based on Raw Estimates)
2000
2005
2011

2015

11
7
7
7

-

-

12
12
12
11

8
9
8
9

2016 International HDR Rank (Based on HDR Consistent Estimates)
2015
10
17
25
24
26
13
5
24
17
5
9
20
15
45
Note: The "2016 International HDR Rank" is based on introducing that province alone into the 2016 HDR international rankings as
if it were a country.

Nunavut experienced the fastest growth between 2000 and 2015 at 0.54 per centper year, well above the national average of 0.39 per cent per year. Nunavut was followed
closely by Newfoundland and Labrador at 0.50 per cent per year (Chart 10). The Yukon
and Northwest Territories had the worst performances, at 0.29 per cent year and 0.32 percent per year, respectively. Nova Scotia, Ontario, Alberta and British Columbia displayed
relatively weak growth. There may be some evidence of convergence in HDI as two of theregions with the highest HDI in 2015 (Ontario and Alberta) had below average growth in
HDI, while two of the bottom three ranked regions (Nunavut, Prince Edward Island) had
above average growth in HDI.
Chart 10: Compound Annual Growth Rate in the HDI, per cent per year, Canada and the Provinces/Territories,
2000-2015

Average per cent change per year

0.60
0.50

0.50
0.40
0.30

0.29

0.32

0.34 0.35

0.36 0.36 0.37 0.38

0.39

0.42 0.43

0.54

0.44

0.20
0.10
0.00

34

Examining the provincial performance in the most recent HDR international
rankings, Alberta and Ontario place well above all other provinces and territories, coming
in fifth (Table 16). This implies that these provinces had levels of human development
below Germany (fourth highest HDI in the world), but equal to levels in Denmark (0.925)
and Singapore (0.925), and higher than The Netherlands (ranked seventh). Nunavut, on
the other hand, comes in 45th place in the international HDI rankings, showing a similarlevel of human development as Latvia and Argentina. It is also important to understand
why Alberta and Ontario are the top ranking regions, and why Nunavut is the lowest
ranking one. Given the small differences between provinces and territories in the education
indicators, it is clear that these differences are primarily driven by differences in life
expectancy and income.

IV. Future Research with the Human Development Index
The HDI is a critical area of research into socio-economic well-being, thanks inlarge part to the global reach of the UNDP. With its annual HDR reports, the UNDP
undertakes the herculean task of corralling data produced by national statistical agencies torank 188 countries in terms of socio-economic well-being. The capacities of these national
statistics agencies vary significantly, so the use of four key summary statistics in the HDI
makes production of the HDR a more feasible task. Moreover, the inclusion of othercomponents in a development index would make it more opaque for policymakers, as wellas run the risk of being criticized for which components are included and which are not.
Providing more niche, alternative indices is the best way to provide a bigger picture of thelevel of economic development in a given country, as the UNDP does in every HDR.
While HDI does a commendable job measuring socio-economic well-being, it does
have a few major drawbacks in terms of its construction. Presently, the index is quite
capable of differentiating between advanced economies and developing economies, but has
a difficult time differentiating levels of development among economies which are closer intheir levels of development. One of the primary issues with its ability differentiating
between developed economies is both of the measurements of education employed.
The HDI measures average educational attainment by using statistics on the highest
level of education completed. It assigns 8 years for completing primary education only, 12
for completing secondary education only, and 14 for having completed some form of
tertiary education. By measuring education completed rather than years of schooling, there
is a definite issue with individuals who fail to complete a degree. As suggested by Calver(2015), a better measure would simply use number of years of schooling. While thismethod results in underestimating the average number of years of schooling, it will notaffect the integrity of the HDI rankings assuming that completion rates for degrees are
similar in similar countries.
A much more consequential source of measurement error with average educational
attainment is assessing 14 years of education to those who have completed some form of
tertiary education. For example, if one country has a most of its students complete twoyear certificates whereas another country has most of its students complete four year
35

Bachelor’s degrees, the HDI’s measurement will underestimate the latter country’s average
educational attainment. In the advanced economies, this is especially an issue as most now
have secondary school completion rates well above 90 per cent. A better measure of
average educational attainment could still use the degree completed metric, but focus moreon the sort of degree individuals have completed. We acknowledge that adding too manydifferent sorts of tertiary education is unrealistic because of the number of national
statistics agencies the UNDP deals with, however we believe that breaking tertiary
education into three sorts of post-secondary education is realistic. We suggest that the
average educational attainment metric should include: a “certificate completed” category
for all those who complete a qualification below the level of a Bachelor’s degree (equal to
14 years of education completed); an “undergraduate degree completed” value for all those
who complete a qualification at the Bachelor’s level (equal to 16 years of education
completed); and finally a “postgraduate degree completed” for all those who complete a
qualification beyond the Bachelor’s level (equal to 18 years of education completed). 34
Another issue with the measurement of education in the HDR is its use of
UNESCO enrolment data in constructing the expected years of schooling. Canadiantertiary school enrolment data is not available from UNESCO, and has not been available
since 2000. While the problem does not threaten the integrity of the UNESCO enrolment
data, and most of the advanced economies have data to 2013 or 2014, it is still rather
embarrassing that a G7 country’s HDI relies on data over a decade old. Whether theburden to resolve the problem lies on Statistics Canada, UNESCO, or the UNDP, thesolution should be relatively easy using the LFS microdata as we did in this paper. As
mentioned in Section II, using LFS data to estimate Canada’s expected years of education
yields an estimate which differs very little from the UNESCO estimate.
Finally, from the perspective of Canadian researchers who endeavour to estimate
HDI for the provinces (or to do any work comparing the provinces internationally for thatmatter), we strongly advocate that Statistics Canada create PPP estimates for a Canadiandollar in individual provinces and territories. The capital city cost of living solution
proposed by Thomas (2016) will suffice in the meantime for studies dealing solely with
consumer data, however at the moment there is no solution we are aware of once
producers are included in the data.

V. Conclusion
This report has estimated internationally comparable HDIs for Canada and its
provinces and territories. In 2015, Alberta and Ontario held the top of the table for theoverall HDI and Nunavut the lowest. For life expectancy, British Columbia ranked first
while Nunavut ranked last. With respect to average educational attainment, Yukon was thehighest ranked province or territory. Quebec was the highest ranking province or territory

34

Admittedly there is still an issue with unmeasured quality differences among the sorts of tertiary schoolingreceived at these levels in different countries. While this is an issue, we believe its influence on HDI rank isminor because countries already near each other in rank due to the other components of HDI are likely toprovide similar quality of schooling (e.g. Canada and Australia).

36

for expected years of schooling and Nunavut came last. With regards to GNI per capita,
the Northwest Territories ranked first while Prince Edward Island was in last.
Most provinces experienced similar HDI growth between 2000 and 2015, with two
notable exceptions: Nunavut, and Newfoundland and Labrador, where HDI grew thefastest of all provinces at territories at 0.54 and 0.50 per cent per year, respectively. This
rapid growth was reflected in Newfoundland and Labrador’s rise in the rankings fromeleventh place in 2000 to seventh in 2015. On the other hand, despite its fast HDI growth,
Nunavut was still the lowest ranked jurisdiction in 2015. There is some evidence of
convergence in regional HDI as provinces with the highest HDI in 2015 had below
average HDI growth during the 2000 to 2015 period, while two of the bottom three ranked
provinces had above average growth. One notable exception to this trend was Alberta,
which was the beneficiary of a commodity boom throughout the period.
The of Canada’s provinces and territories in terms of human development in theinternational context is summarized in Table 17.
Table 17: Summary of International HDR Ranks, Canada and the Provinces/Territories, 2015

Dimension
Life Expectancy
Average Educational
Attainment
Expected Years of
Schooling
GNI per capita
HDI

CAN

NL

PEI

NS

NB

QC

ON

MB

SK

AB

BC

YT

NWT

NU

12

33

28

27

30

9

9

35

33

21

4

46

43

103

6

8

7

7

7

7

3

7

7

3

3

2

7

40

22

27

35

32

36

13

18

35

38

38

31

45

47

85

22
10

20
17

35
25

35
24

32
26

30
13

23
5

24
24

11
17

9
5

24
9

10
20

2
15

12
45

Of the countries in the most recent HDR rankings, Canada’s regions ranked
between fourth and 103rd in life expectancy, between second and 40th in average
educational attainment, between 13th and 85th in expected years of schooling and between
2nd and 35th in GNI per capita. For the overall HDI, Canada’s provinces and territories
ranked between fifth and 45th place. It is therefore clear that Canada’s overall HDI masks
substantial variation among the provinces and territories.

37

References
Barro, R. and J.W. Lee (2001) “International Data on Educational Attainment: Updates and
Implications,” Oxford Economic Papers, Vol. 53, No.3, pp. 541-563.
Barro, R. J., and J. W. Lee (2010) A New Data Set of Educational Attainment in the World, 1950–
2010, NBER Working Paper 15902 (Cambridge, MA: National Bureau of Economic
Research).
Barro, R.J., and J.W. Lee (2014). “Educational Attainment for Total Population, 1950-2010:
Version 2.0.” Available at: http://www.barrolee.com/data/yrsch_old.htm
Brockington, Riley (2009) Summary Public School Indicators for Canada, the Provinces andTerritories, 2000/2001 to 2006/2007, Catalogue no. 81-595-M, No. 078 (Ottawa: Statistics
Canada).
Cohen, D. and M. Soto (2007) “Growth and Human Capital: Good Data, Good Results,” Journal of
Economic Growth, Vol.12, pp. 51–76.
Cooke, Martin (2007a) “The Registered Indian Human Development Indices: Conceptual andMethodological Issues,” in Aboriginal Well-being: Canada’s Continuing Challenge, editedby Jerry White, Dan Beavon and Nicholas Spence (Thompson Educational Publishing).
Cooke, Martin (2007b) “Using the UNDP Indices to Examine Gender Equality and Well-being,” inAboriginal Well-being: Canada’s Continuing Challenge, edited by Jerry White, Dan
Beavon and Nicholas Spence (Thompson Educational Publishing).
Cooke, Martin and Dan Beavon (2007) “The Registered Indian Human Development Index, 19812001,” in Aboriginal Well-being: Canada’s Continuing Challenge, edited by Jerry White,
Dan Beavon and Nicholas Spence (Thompson Educational Publishing).
Cooke, Martin, Francis Mitrou, David Lawrence, Eric Guimond, and Dan Beavon (2007)“Aboriginal Well-being in Four Countries: An Application of the UNDP’s Human
Development Index to Aboriginal People in Australia, Canada, New Zealand, and theUnited States,” BMC International Health and Human Rights Vol. 7 No.9.
Hazell, Elspeth, Kar-Fai Gee, and Andrew Sharpe. “The Human Development Index in Canada:
Estimates for the Canadian Provinces and Territories, 2000-2011.” CSLS Research Report
2012-02.
IMF (International Monetary Fund) (2009) World Economic Outlook: Sustaining the Recovery(Washington, DC).
IMF (International Monetary Fund) (2010a) Government Finance Statistics (Washington, DC).
IMF (International Monetary Fund) (2010b) World Economic Outlook Update: An Update of the
Key WEO Projections (Washington, DC).
Lind, Niels (2010) “A Calibrated Index of Human Development.” Social Indicators Research, Vol.
98, No.2, pp. 301-319.
38

Kahneman, Daniel, and Angus Deaton. (2010) “High income improves evaluation of life but notemotional well being.” Proceedings of the National Academies of Science. Vol. 107, No.
38, 16489-16493.
Maddison, A. (2010) Historical Statistics of the World Economy: 1–2008 AD (Paris: Organisation
for Economic Co-operation and Development).
McCracken, Mike, Martha Justus, and Bing He (1996) “Atlantic Canada: Human Development
Index Study,” prepared by Informetrica for the Atlantic Canada Opportunities Agency,
March.
McGillivray, Mark (1991) “The Human Development Index: Yet Another Redundant Composite
Development Indicator?” World Development, Vol. 19, No.10, pp. 1461-1468.
Nunavut Bureau of Statistics (2015) 2015 Nunavut Food Price Survey, Comparison of Nunavut &Canada CPI Food Price Basket Items. Retrieved from:http://www.stats.gov.nu.ca/en/Economic%20prices.aspx
Ross and Murray (2010) “Aggregate Measures of Income and Output in Canada and the UnitedStates: Implications for Productivity and Living Standards,” International Productivity
Monitor Number 19, Spring, pp. 20-39.
Oreopoulos, Philip (2006) “The compelling effects of compulsory schooling: evidence from
Canada,” Canadian Journal of Economics, Vol. 39, No. 1, pp. 22-52.
Riley, J.C (2005) Poverty and Life Expectancy (Cambridge, UK: Cambridge University Press).
Sagar, Ambuj D. and Adil Najam (1998) “The human development index: a critical review”
Ecological Economics, Vol. 25, pp. 249-264.
Statistics Canada (2000) Health Indicators. Catalogue No. 82-221-XIE, December.
Srinivasan, T.N. (1994) “Human Development: A New Paradigm or Reinvention of the Wheel?”
American Economic Review, Vol. 84, No.2, pp. 238-243.
Thomas, Jasmin (2016). “Trends in Low-Wage Employment in Canada: Incidence, Gap andIntensity, 1997-2014.” CSLS Research Report 2016-10.
Uguccioni, James (2016). “The Human Development Index in Canada: Ranking the Provinces andTerritories Internationally, 2000-2014.” CSLS Research Report 2016-14.
UNDESA (United Nations Department of Economic and Social Affairs) (2011) World Population
Prospects: The 2010 Revision (New York).
(UIS) UNESCO Institute for Statistics (2009) Education Indicators: Technical Guidelines.
Retrieved from:http://www.uis.unesco.org/template/pdf/EducGeneral/Indicator_Technical_guidelines_EN.
pdf

39

UNDP (United Nations Development Programme) – Human Development Report Office (2011).
Human Development Report 2011. (New York: Palgrave Macmillan).
UNDP (United Nations Development Programme) - Human Development Report Office (2017a).
Human Development Report 2016 (New York: Palgrave Macmillan). Available at:
http://hdr.undp.org/sites/default/files/2016_human_development_report.pdf
UNDP (United Nations Development Programme) – Human Development Report Office (2017b).
Human Development Report 2016 – Technical Notes. Available at:
http://hdr.undp.org/sites/default/files/hdr2016_technical_notes.pdf
UNESCO Institute for Statistics (2015). Data Centre. See: http://stats.uis.unesco.org.
World Bank (2010) World Development Indicators 2010 (Washington, DC).

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