Insights on Canadian Society
Labour market outcomes of graduates from universities in the Maritime provinces

by Diane Galarneau, Christine Hinchley and Aimé Ntwari

Release date: April 11, 2017

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Overview of the study

This study uses a new longitudinal dataset that combines information from the Postsecondary Information System (PSIS) with personal income tax data to examine the labour market outcomes of graduates from universities in the Maritime provinces (Prince Edward Island, Nova Scotia and New Brunswick). In this pilot study, the outcomes of six cohorts of young people who graduated from a university in the Maritime provinces between 2006 and 2011 are examined, including 37,425 undergraduate degree holders (those with a bachelor’s degree) and 6,740 graduate degree holders (those with a master’s degree or a doctorate).

  • From 2006 to 2011, at least 95% of graduates from the Maritime universities reported employment earnings in their first year after graduating, which suggests that most of them had a paid job at some point in the year after graduating.
  • One year after graduating with a bachelor's degree, the earnings of graduates from the 2009 cohort (who graduated in the aftermath of the 2008/2009 recession) were 8% lower than the earnings of their counterparts from the 2008 cohort.
  • Subsequent cohorts did not recover. Undergraduate students who graduated in 2010 and 2011 also had lower first-year earnings than those who graduated in 2008.
  • In comparison with the 2008 cohort, the first-year earnings of undergraduate degree holders from the 2011 cohort were lower for both men and women, for those who left and those who stayed in the Maritime provinces, and for nearly all fields of study.
  • Approximately two-thirds of graduates were still living in the Maritimes one year after graduating. Those with a degree in education were the most likely to stay in the Maritimes, while those with a degree in architecture, engineering and related technologies were the least likely to stay.

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Introduction

Labour market transitions and outcomes of postsecondary graduates have always been a topic of interest for policy makers, students, their families and postsecondary institutions. Although higher levels of education are usually associated with better labour market outcomes,Note 1 postsecondary education requires considerable financial and time investment and may not always provide the expected returns, particularly around recessions.Note 2

Statistics Canada has recently developed the Education Longitudinal Linkage Platform (ELLP), which allows for the combination of administrative data on the Postsecondary Student Information System (PSIS) with other databases to enable longitudinal analysis and a better understanding of labour market outcomes following graduation (see “Data sources, methods and definitions”). A pilot projectNote 3 was recently undertaken using the ELLP to examine the outcomes of graduates from Maritime universities from 2006 to 2011 by combining PSIS data for Prince Edward Island, Nova Scotia and New Brunswick with personal income tax data.Note 4 Over the years, the platform will also allow for the addition of more information from multiple sources, which will provide a better understanding of the factors behind access to postsecondary education (PSE), persistence and success in PSE, and the labour market outcomes of graduates.

Using that new dataset, this article looks at the labour market outcomes of graduates from the Maritime universities, with a special focus on differences by year of graduation. Canadian and international economies experienced significant shifts from 2006 to 2011 due to recessions in Canada, the United States and Europe, credit crises and variations in commodity prices. These events may have affected the availability of jobs in the Maritimes and across Canada, and they may have presented different challenges to graduates entering the labour market before and after the 2008-2009 recession. The new dataset therefore provides a unique opportunity to compare the economic outcomes of graduates who earned their degree between 2006 and 2008 with those of later cohorts.

Specifically, this paper examines the employment earnings and employment insurance (EI) benefits of university graduates and provides an overview of job quality indicators such as unionization (based on union contributions), pension plan coverage (based on private pension plan contributions) and the proportion of those who are employed in low value-added service industries. In addition to presenting the outcomes by cohort, results are also shown for men and women, by education level (for undergraduate and graduate degree holders), and by field of study. The analysis focuses on individuals who graduated prior to the age of 35Note 5 who also completed an income tax return and did not pursue their education on a full-time basis after graduating.Note 6 Individuals who reported self-employment earningsNote 7 were excluded.

Tax data can also be used to identify the place of residence of graduates at different points in time. This information can be used to calculate a regional retention rate that corresponds, in this paper, to the number of graduates still living in one of the three Maritime provinces, one year after graduating, as a proportion of all graduates who obtained a degree from Maritime universities. The retention rate is discussed in a box at the end of the article (see “Retention of Maritime university graduates”), with results shown by place of origin, sex and field of study.

Profile of Maritime university graduates

This analysis is based on a population of 37,425 individuals under the age of 35 ─ or about 6,200 people each year ─ who graduated with an undergraduate degree (i.e. a bachelor's degree) from the universities of Prince Edward Island, Nova Scotia and New Brunswick, and met the criteria described above. The sample also includes 6,740 individuals (about 1,100 per year) who obtained a graduate degree (master’s degree or doctorate) over the same period.Note 8

In this population of graduates, nearly two-thirds (62%) were female. The proportion was similar across education levels (undergraduate and graduate degrees) and across cohorts. A little more than 5% of the undergraduate degree holders graduated in Prince Edward Island, 58% in Nova Scotia and 37% in New Brunswick. Among those who obtained a graduate degree, 2% did so in Prince Edward Island, 77% in Nova Scotia and 21% in New Brunswick.

At the undergraduate level, more than three-quarters (78%) of women graduated from four fields of study, while just over two-thirds (69%) of men came from four disciplines (Chart 1). The most common fields also differed by sex. For women, the top fields (in descending order) were health and related fields; social and behavioural sciences and law; business, management and public administration; and education. Among men, the top fields were business, management and public administration; architecture, engineering and related technologies; social and behavioural sciences and law; and humanities.

Chart 1 Distribution of Maritime university graduates under the age of 35, by field of study and education level, all cohorts from 2006 to 2011

Data table for Chart 1
Data table for Chart 1.1 and 1.2
Table summary
This table displays the results of Data table for Chart 1.1 and 1.2. The information is grouped by Field of study (appearing as row headers), Undergraduate degree (bachelor degree) and Graduate degree (master's degree or doctorate), calculated using percent units of measure (appearing as column headers).
Field of study Undergraduate degree (bachelor's degree) Graduate degree (master's degree or doctorate)
percent
Men
Other 0.7 0.2
Agriculture, natural resources and conservation 2.2 3.8
Visual and performing arts and communications technologies 2.3 0.2
Mathematics and computer and information sciences 5.0 8.6
Physical and life sciences and technologies 5.8 9.6
Health and related fieldsData table Note 2 6.6 5.2
Education 8.3 9.4
Humanities 8.8 5.4
Social and behavioural sciences and lawData table Note 1 15.3 5.2
Architecture, engineering and related technologies 16.0 21.6
Business, management and public administration 29.0 30.8
Women
Other 0.6 0.4
Mathematics and computer and information sciences 0.8 5.7
Agriculture, natural resources and conservation 1.5 5.0
Architecture, engineering and related technologies 2.4 5.7
Visual and performing arts and communications technologies 3.0 0.4
Physical and life sciences and technologies 5.5 7.1
Humanities 8.3 3.3
Education 16.9 30.1
Business, management and public administration 18.6 18.3
Social and behavioural sciences and lawData table Note 1 20.6 9.1
Health and related fieldsData table Note 2 21.8 15.1

At the graduate level (master’s degree and doctorate), 73% of female graduates were in four fields of study, while 71% of males graduated from four fields. Once again, the top fields differed by sex. Among women, the top four fields were the same as those of undergraduate degree holders, except that education was the top field rather than health and related fields. Among men, business, management and public administration, as well as architecture, engineering and related technologies remained among the four most popular fields of study, followed by physical and life sciences and technologies and education.

Most graduates reported employment earnings in their first year after graduating

During their first year after graduating, most graduates had a paid job at some point—at least 95% of them reported employment earnings on their tax return (Table 1). This proportion was similar for each cohort of graduates and for both levels of education.

Table 1
Selected labour market indicators for Maritime university graduates one year after graduation, by cohort and education level, 2006 to 2011
Table summary
This table displays the results of Selected labour market indicators for Maritime university graduates one year after graduation Cohort, 2006, 2007, 2008, 2009, 2010 and 2011, calculated using number units of measure (appearing as column headers).
  Cohort
2006 2007 2008 2009 2010 2011
number
Undergraduate degree (bachelor's degree) 6,110 6,645 6,310 6,280 5,915 6,165
Proportion of graduates percent
With earnings 97.1 97.0 97.1 96.9 96.7 96.6
With employment insurance benefits 14.1 13.0 15.3 17.5 16.9 15.3
With social assistance benefits 0.3 0.5 0.4 0.6 0.5 0.4
  number
Graduate degree (master's degree or doctorate) 995 965 1,080 1,165 1,230 1,305
Proportion of graduates percent
With earnings 96.0 94.8 95.8 95.7 95.9 96.6
With employment insurance benefits 12.6 11.9 13.4 14.2 13.8 14.6
With social assistance benefits 0.0 0.0 0.0 0.4 0.4 0.4

The proportion of undergraduate degree holders who had received employment insurance benefits (EI) one year after graduating increased from 14% to 18% for the 2006 and 2009 cohorts, but decreased to 15% for the most recent cohort (2011).Note 9 Although they were less likely to report receiving EI benefits, similar trends were observed among cohorts with a graduate degree. Very few graduates received social assistance benefits the year after graduating (less than 1% for all cohorts and both levels of education).

Declines in first-year earnings began with the 2009 cohort

From 2006 to 2008, the median first-year earningsNote 10 of undergraduate degree holders remained relatively constant, at around $35,000 (Table 2). Over the same period, it grew from $53,200 to $56,100 among graduate degree holders.

Table 2
Labour market outcomes of Maritime university graduates one year after graduation, by cohort and education level, 2006 to 2011
Table summary
This table displays the results of Labour market outcomes of Maritime university graduates one year after graduation Cohort, 2006, 2007, 2008, 2009, 2010 and 2011, calculated using number and 2012 constant dollars units of measure (appearing as column headers).
  Cohort
2006 2007 2008 2009 2010 2011
number
Undergraduate degree (bachelor's degree) 6,110 6,645 6,310 6,280 5,915 6,165
  2012 constant dollars
Median earningsTable 2 Note 1 34,800 35,800 35,200 32,400 32,900 32,300
Earnings categories percent
$0 3.0 3.0 2.9 3.1 3.3 3.4
$10,000 or less 8.3 8.4 8.5 9.0 8.4 8.5
$10,001 to $30,000 29.5 28.3 30.2 34.0 33.2 33.7
$30,001 to $50,000 35.4 34.0 32.1 29.4 30.0 31.1
more than $50,000 23.8 26.3 26.4 24.5 25.1 23.3
Proportion of graduates  
Working in low value-added service industriesTable 2 Note 2 15.0 15.1 16.3 18.7 17.0 17.6
Reporting a union contribution 37.5 37.1 36.2 37.6 39.5 36.0
Reporting a private pension plan contribution 36.2 36.9 37.4 35.8 35.0 31.8
  number
Graduate degree (master's degree or doctorate) 995 965 1,080 1,165 1,230 1,305
  2012 constant dollars
Median earningsTable 2 Note 1 53,200 52,900 56,100 51,600 51,600 52,200
Earnings categories percent
$0 4.5 5.7 4.2 4.3 4.1 3.4
$10,000 or less 3.5 4.1 3.2 5.2 5.3 4.6
$10,001 to $30,000 11.6 10.4 11.6 13.7 13.4 14.6
$30,001 to $50,000 25.1 24.9 20.8 24.0 24.4 23.8
more than $50,000 55.3 54.9 60.2 52.8 52.8 53.6
Proportion of graduates  
Working in low value-added service industriesTable 2 Note 2 5.9 6.9 7.2 8.5 7.1 5.7
Reporting a union contribution 47.8 48.8 53.2 51.4 49.7 51.5
Reporting a private pension plan contribution 51.4 51.9 55.2 53.0 51.2 48.9

The years 2008 and 2009 were characterized by the most important economic downturn since the beginning of the 1990s in Canada. Between 2008 and 2009, the first-year earnings of graduates declined by 8%—both at the undergraduate and graduate levels. These differences represented a decline of nearly $3,000 for undergraduate degree holders and a decline of $4,500 for graduate degree holders. Subsequent cohorts in 2010 and 2011 did not recover from the decline.

These trends were similar for both male and female graduates (Chart 2). In both cases, first-year earnings decreased between the 2008 and 2009 cohorts, and subsequent cohorts did not recover.Note 11

Chart 2 Median earnings of Maritime university graduates one year after graduation, by cohort, sex and education level, 2006 to 2011

Data table for Chart 2
Data table for Chart 2
Table summary
This table displays the results of Data table for Chart 2 Cohort, 2006, 2007, 2008, 2009, 2010 and 2011, calculated using 2012 constant dollars (thousand) units of measure (appearing as column headers).
  Cohort
2006 2007 2008 2009 2010 2011
2012 constant dollars (thousand)
Men Undergraduate degree (bachelor degree) 37.3 37.6 37.1 34.4 34.5 34.2
Graduate degree (master's degree or doctorate) 54.4 54.0 56.9 51.2 49.3 51.5
Women Undergraduate degree (bachelor degree) 33.3 34.7 33.8 31.0 32.0 31.0
Graduate degree (master's degree or doctorate) 53.0 52.1 55.8 52.2 53.1 52.3

Although most graduates held a job at some point during their first year after graduating, the data do not provide any indication as to whether the job was full time or part time, or whether it was held part of the year or throughout the entire year. The new dataset on Maritime university graduates also does not provide information about the number of hours worked during the year, or whether the job is in the same field of study. However, additional insight can be obtained by examining the distribution of graduates across earnings categories.

Between 2006 and 2011, the proportion of undergraduate degree holders who earned between $0 and $10,000 remained relatively stable from one cohort to the next, varying between 11% and 12%.

The proportion of those earning between $10,001 and $30,000, however, grew by 4 percentage points between the 2006 and 2009 cohorts; the largest increase was observed between the 2008 and 2009 cohorts. Conversely, the proportion of those earning between $30,001 and $50,000 decreased during the same period, while the proportion earning more than $50,000 fluctuated between 23% and 26%.

Similar trends were observed among graduate degree holders. There was an increase in the $10,001 to $30,000 category and a decrease in the two highest earnings classes; most of the changes occurred between the 2008 and 2009 cohorts.

These shifts in earnings classes may be the result of a reduction in working hours from one cohort to the next,Note 12 but they could also be due to a higher proportion of graduates working in low-paid jobs. Tax data do not provide information on working hours, but they do provide information about the industries in which graduates are employed. Additional insight can thus be obtained by examining the proportion of workers in low value-added service industries, which are defined in this paper as retail trade, accommodation and food services, and other services. On average, jobs in these industries offer lower wages and fewer benefits than jobs in other sectors.Note 13

The proportion of undergraduate degree holders working in such industries increased from 15% to 19% between the 2006 and 2009 cohorts; most of the increase occurred between the 2008 and 2009 cohorts. Among graduate degree holders, the proportion working in low value-added service industries was smaller and fluctuated less over the period. This raises the possibility of an increasing proportion of undergraduate degree holders who may have had no other option but to work in low-paid jobs because of a deterioration in labour market conditions. However, the data do not contain any information on the reasons for working in a given industry.

Lastly, two other important job quality indicators available from the Maritime university graduate dataset are the unionization rate and private pension plan coverage. Using tax data, unionization can be approximated by the proportion of graduates who reported union contributions. While this proportion fluctuated from cohort to cohort, the results do not point to a long-term growth or decline across cohorts. Of note, graduate degree holders were more likely to report union contributions (with proportions between 48% and 53%) than undergraduate degree holders (between 36% and 40%).

Similarly, graduates covered by a private pension plan can be approximated by the proportion of graduates who reported contributions to a registered pension plan. This proportion fluctuated from cohort to cohort in the year after graduation, ranging between 32% and 37% for undergraduate degree holders and from 49% to 55% for graduate degree holders.

Declines in first-year earnings took place in nearly all fields of study

Earnings in the first year following graduation vary considerably across fields of study.Note 14 Male bachelor's degree holders from the 2008 cohort, for example, had median first-year earnings of $37,100, but that amount varied between a high of $55,700 in health and related fieldsNote 15 and a low of $14,700 in visual and performing arts and communications technologies (Table 3). It is important to note, however, that not all graduates were working in occupations corresponding to their field of study.Note 16

Table 3
Median first-year earningsTable 3 Note 1 of Maritime university graduates, by sex, education level and field of study, 2008 and 2011 cohorts
Table summary
This table displays the results of Median first-year earnings of Maritime university graduates Men, Women, Median first-year earnings, Proportion of graduates, 2008 cohort, 2011 cohort, 2008 to 2011 cohorts and 2006 to 2011 cohorts combined, calculated using 2012 constant dollars, percentage change and percent units of measure (appearing as column headers).
  Men Women
Median first-year earnings Proportion of graduates Median first-year earnings Proportion of graduates
2008 cohort 2011 cohort 2008 to 2011 cohorts 2006 to 2011 cohorts combined 2008 cohort 2011 cohort 2008 to 2011 cohorts 2006 to 2011 cohorts combined
2012 constant dollars percentage change percent 2012 constant dollars percentage change percent
Undergraduate degree (bachelor's degree)  
All fields of study 37,100 34,200 -7.8 100.0 33,800 31,000 -8.3 100.0
Education 42,900 33,800 -21.2 8.3 39,200 29,900 -23.7 16.9
Visual and performing arts and communications technologies 14,700 20,200 37.4 2.3 16,700 17,200 3.0 3.0
Humanities 22,200 20,900 -5.9 8.8 18,300 19,100 4.4 8.3
Social and behavioural sciences and lawTable 3 Note 2 27,300 26,800 -1.8 15.2 24,900 22,100 -11.2 20.6
Business, management and public administration 36,100 35,100 -2.8 29.1 34,200 33,800 -1.2 18.6
Physical and life sciences and technologies 27,800 26,300 -5.4 5.8 21,500 21,100 -1.9 5.6
Mathematics and computer and information sciences 41,700 38,400 -7.9 5.1 28,500 21,600 -24.2 0.8
Architecture, engineering and related technologies 53,900 51,700 -4.1 16.0 51,200 52,800 3.1 2.4
Agriculture, natural resources and conservation 39,900 31,800 -20.3 2.1 25,900 19,800 -23.6 1.5
Health and related fieldsTable 3 Note 3 55,700 41,600 -25.3 6.6 65,600 62,000 -5.5 21.8
Other Note x: suppressed to meet the confidentiality requirements of the Statistics Act Note x: suppressed to meet the confidentiality requirements of the Statistics Act Note x: suppressed to meet the confidentiality requirements of the Statistics Act Note x: suppressed to meet the confidentiality requirements of the Statistics Act Note x: suppressed to meet the confidentiality requirements of the Statistics Act Note x: suppressed to meet the confidentiality requirements of the Statistics Act Note x: suppressed to meet the confidentiality requirements of the Statistics Act Note x: suppressed to meet the confidentiality requirements of the Statistics Act
Graduate degree (master's degree or doctorate)  
All fields of study 56,900 51,500 -9.5 100.0 55,800 52,300 -6.3 100.0
Education 69,400 70,300 1.3 9.4 63,100 63,500 0.6 30.0
Visual and performing arts and communications technologies Note x: suppressed to meet the confidentiality requirements of the Statistics Act Note x: suppressed to meet the confidentiality requirements of the Statistics Act Note x: suppressed to meet the confidentiality requirements of the Statistics Act Note x: suppressed to meet the confidentiality requirements of the Statistics Act Note x: suppressed to meet the confidentiality requirements of the Statistics Act Note x: suppressed to meet the confidentiality requirements of the Statistics Act Note x: suppressed to meet the confidentiality requirements of the Statistics Act Note x: suppressed to meet the confidentiality requirements of the Statistics Act
Humanities 42,200 24,500 -41.9 4.8 25,500 28,900 13.3 3.4
Social and behavioural sciences and lawTable 3 Note 2 46,800 44,800 -4.3 5.3 52,800 40,000 -24.2 9.0
Business, management and public administration 60,300 56,200 -6.8 31.0 56,700 53,200 -6.2 18.4
Physical and life sciences and technologies 42,800 32,900 -23.1 5.5 38,200 39,100 2.4 6.9
Mathematics and computer and information sciences 55,900 44,400 -20.6 7.9 49,200 37,900 -23.0 5.7
Architecture, engineering and related technologies 49,500 51,000 3.0 19.2 50,900 47,900 -5.9 5.9
Agriculture, natural resources and conservation 49,400 40,000 -19.0 3.8 42,300 32,100 -24.1 4.9
Health and related fieldsTable 3 Note 3 59,100 59,900 1.4 5.2 60,800 57,700 -5.1 15.2
Other Note x: suppressed to meet the confidentiality requirements of the Statistics Act Note x: suppressed to meet the confidentiality requirements of the Statistics Act Note x: suppressed to meet the confidentiality requirements of the Statistics Act Note x: suppressed to meet the confidentiality requirements of the Statistics Act Note x: suppressed to meet the confidentiality requirements of the Statistics Act Note x: suppressed to meet the confidentiality requirements of the Statistics Act Note x: suppressed to meet the confidentiality requirements of the Statistics Act Note x: suppressed to meet the confidentiality requirements of the Statistics Act

Among female bachelor's degree holders from the same cohort, the overall median was $33,800, but varied between $65,600 in health and related fields and $16,700 in visual and performing arts and communications technologies. Similar variations across fields were seen for those in other cohorts.

In most fields of study, first-year earnings declined between the 2008 and 2011 cohorts. Male undergraduate degree holders with a degree in health and related fields (-25%) and education (-21%) experienced the largest declines. For their female counterparts, the largest declines were seen among those with a degree in mathematics and computer and information sciences, and education (-24% for both).

Among male graduate degree holders, the largest declines were in humanities (-42%), physical and life sciences (-23%), and mathematics and computer and information sciences (-21%). Large declines were also seen among their female counterparts with a graduate degree in social and behavioural sciences and law (-24%), agriculture, natural resources and conservation (-24%), and mathematics and computer and information sciences (-23%).

Graduates who left the Maritimes also saw declines in first-year earnings

Although all graduates examined in this article obtained their degree in one of the three Maritime provinces, one-third reported another region of residence on their tax return one year after graduating.Note 17 Many of those who left the Maritimes originated from outside the Maritimes, which suggests that some may have returned to their region of origin (for additional details on region of residence after graduating, see “Retention of Maritime university graduates”). Examining the first-year earnings of graduates by region of residence is important, given that labour market conditions may differ from one region to the next.

In general, graduates from Maritime universities who left the region earned more in their first year than those who stayed in the Maritimes (Table 4). These gaps reflect many factors such as the differences in the characteristics of the graduates who moved compared to those who did not move, and differences in economic conditions across regions as well as the cost of living.

Table 4
Median first-year earningsTable 4 Note 1 of Maritime university graduates, by cohort, sex, education level and region of residence one year after graduation, 2006 to 2011
Table summary
This table displays the results of Median first-year earnings of Maritime university graduates Cohort, Change between 2008 and 2011 cohorts, 2006, 2007, 2008, 2009, 2010 and 2011, calculated using median first-year earnings (2012 constant dollars) and percent units of measure (appearing as column headers).
Cohort Change between 2008 and 2011 cohorts
2006 2007 2008 2009 2010 2011
median first-year earnings (2012 constant dollars) percent
Undergraduate degree (bachelor's degree)
Men by region of residence
Maritimes 34,500 35,400 35,800 32,700 32,700 32,400 -9.5
Outside the Maritimes 43,400 41,900 40,800 39,300 39,300 40,100 -1.7
Women by region of residence
Maritimes 32,500 33,200 32,900 31,400 31,500 30,500 -7.3
Outside the Maritimes 36,100 38,800 36,200 30,100 33,400 33,600 -7.2
Graduate degree (master's degree or doctorate)
Men by region of residence
Maritimes 50,100 53,300 55,800 50,500 49,100 50,500 -9.5
Outside the Maritimes 57,600 55,500 59,100 52,600 51,000 54,100 -8.5
Women by region of residence
Maritimes 51,700 51,500 55,300 53,200 54,100 51,500 -6.9
Outside the Maritimes 54,700 53,600 56,500 51,000 51,700 53,800 -4.8

However, both stayers and leavers experienced similar declines in their first-year earnings between the 2008 and 2011 cohorts, with the exception of men with an undergraduate degree. Among them, the decline was lower for those who left (-2%) than for those who stayed (-10%).

First-year earnings declined after 2008 for undergraduate degree holders even after accounting for other factors

Which factors explain the decline in first-year earnings of graduates from Maritime universities? One possibility is the economic recession of 2008/2009, while another is the potentially changing characteristics of graduates from one cohort to the next. To isolate the possible impact of the recession, a model was estimated by taking the year of graduation into account, as well as demographic and field of study differences across cohorts (Table 5).Note 18

Table 5
Percentage difference in first-year earnings between the 2008 cohort and other cohorts among Maritime university graduates, by cohort and education levelTable 5 Note 1
Table summary
This table displays the results of Percentage difference in first-year earnings between the 2008 cohort and other cohorts among Maritime university graduates Undergraduate degree (bachelor degree), Graduate degree (master's degree or doctorate), Unadjusted gap, Adjusted gap, Model A and Model B, calculated using percent units of measure (appearing as column headers).
  Undergraduate degree (bachelor's degree) Graduate degree (master's degree or doctorate)
Unadjusted gap Adjusted gap Unadjusted gap Adjusted gap
Model A Model B Model A Model B
percent
Cohort  
2006 -1.9 -1.8 -0.6 -5.8 -3.7 1.7
2007 -0.5 0.6 0.7 -15.8Note * -13.1 -8.2
2008 (ref.) Note ...: not applicable Note ...: not applicable Note ...: not applicable Note ...: not applicable Note ...: not applicable Note ...: not applicable
2009 -7.6Table 5 Note  -7.3Table 5 Note  -7.8Table 5 Note  -9.8 -8.1 -9.4
2010 -7.7Table 5 Note  -7.2Table 5 Note  -10.0Table 5 Note  -13.6 -9.8 -8.4
2011 -10.1Table 5 Note  -8.5Table 5 Note  -11.1Table 5 Note  -3.2 2.1 0.5

Among undergraduates, the decline in first-year earnings remained significant for the three cohorts who graduated after 2008. This supports the view that the 2008/2009 downturn might have played a role in the declining first-year earnings of undergraduates. Even after taking demographic and field of study differences into account, undergraduate students who graduated in 2009 earned 8% less than those who graduated in 2008, while those who graduated in 2010 and 2011 earned 10% and 11% less, respectively. Among graduate degree holders, however, the differences in first-year earnings between the 2008 cohort and other cohorts were not significant.Note 19

Did graduates from the 2009 cohort eventually recover from the decline?

Cohorts of undergraduate degree holders were followed over three years to see if those from the 2009 cohort, who had significantly lower earnings than earlier cohorts, eventually recovered.Note 20

Undergraduate degree holders of both sexes from the 2006 and 2007 cohorts followed a similar trajectory over their first three years after graduating (Chart 3). However, the next two cohorts, in 2008 and 2009, generally had lower earnings in all three years of observation compared with the preceding cohorts; the largest decline between cohorts was registered for the 2009 cohort. The gap between the cohorts did not narrow over subsequent years. This means that graduates from the 2009 cohort did not experience a decline in earnings in their first year only, but also in subsequent years.

Chart 3 Median earnings of Maritime university graduates in the three years following graduation, men and women with an undergraduate degree (bachelor degree), 2006 to 2009 cohorts

Data table for Chart 3
Data table for Chart 3.1 and 3.2
Table summary
This table displays the results of Data table for Chart 3.1 and 3.2. The information is grouped by Year (appearing as row headers), Number of years after graduation, 1 year, 2 years and 3 years, calculated using 2012 constant dollars (thousand) units of measure (appearing as column headers).
Year Number of years after graduation
1 year 2 years 3 years
2012 constant dollars (thousand)
Men
2006 41.0 47.3 51.7
2007 41.0 47.6 51.9
2008 40.0 46.1 50.1
2009 37.2 43.7 48.0
Women
2006 37.4 43.1 45.7
2007 38.9 43.8 45.8
2008 37.2 41.0 42.8
2009 34.9 39.3 41.9

Other studies have documented the earnings penalty associated with entering the labour market during recessionary years.Note 21 The lasting effects of entering the labour market during a downturn can vary, depending on the economic activity following the recessionary years. Although this study does not formally evaluate the role of the recession, the descriptive results are at least consistent with the notion that economic conditions shortly after graduation generally mattered for Maritime university graduates.

Conclusion

This article highlighted some of the results of a new dataset on the labour market outcomes of graduates of universities in Prince Edward Island, Nova Scotia and New Brunswick who earned their degree between 2006 and 2011. As the Education Longitudinal Linkage Platform (ELLP) used to create this new dataset will be developed over time, the same kind of analysis will eventually be possible at the Pan–Canadian level.

Data showed that even though most undergraduate degree holders from the Maritime universities were employed at some point during their first year after graduating, there was a clear downward trend in the first-year earnings of those who graduated in 2009, 2010 or 2011 compared with previous cohorts. The relationship with the graduation year remained significant even after accounting for differences in demographic and field of study characteristics across cohorts. Graduate degree holders also registered a decrease in their first-year earnings after 2008, but the decline was not significant after taking other factors into account.

The new dataset also showed that for some graduates, the earnings gap across cohorts did not narrow in subsequent years: three years after graduating, undergraduate degree holders from the 2009 cohort still earned significantly less than those who graduated in 2008. Future data will show whether this gap will eventually close over the years.

Lastly, the ELLP also allows for an examination of the retention patterns of university graduates from the Maritime provinces. The results of this study indicate that two-thirds of the graduates were still living in the Maritimes one year after graduating. Those in the field of education were the most likely to stay in that region while those in architecture, engineering and related technologies were the least likely to stay.

Diane Galarneau, Christine Hinchley and Aimé Ntwari are analysts with the Section of Special Projects related to postsecondary education, in the Centre for Education Statistics at Statistics Canada.

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Data sources, methods and definitions

The Postsecondary Student Information System (PSIS) provides detailed annual information on enrolments and graduations from Canadian postsecondary institutions (universities and colleges) by field of study and by certain demographic variables. However, PSIS data do not provide information about graduate outcomes on the labour market, such as labour force participation after graduation or employment earnings. This information can be derived from other administrative data sources such as the tax files.

The Statistics Canada Education Longitudinal Linkage Platform (ELLP) was developed to allow for the combination of information from PSIS, as well as the Registered Apprenticeship Information System (RAIS), with information from other datasets. A pilot study using the ELLP was undertaken to link annual PSIS graduate data for Maritime universities (for reporting years 2006 to 2012) with selected variables from the T1 Family File (T1FF) tax data (calendar years 2006 to 2012). The T1FF has the advantage of containing a large number of observations and detailed information on income sources—it does, however, have limited information on demographic and labour market characteristics. For example, it does not provide any information about the number of working hours, the number of months worked or occupational characteristics.

While the dataset of this pilot includes information for all university graduates, the current study focuses on those who were under the age of 35 at the time of graduation. Some adjustments were made to the PSIS records to simplify the matching of PSIS graduates with tax data and simplify the interpretation of the graduates’ outcomes.

To improve the comparability of results across graduates, certain types of graduates were excluded from the sample if they met any of the following criteria: they were missing a tax record, went back to school as a full-time student or had self-employment earnings. The study focuses on the two of the largest groups of university graduates: those who obtained a bachelor's degree (undergraduate degree holders) and those who obtained a master’s degree or a doctorate (graduate degree holders). Master’s and doctorate graduates were grouped together to ensure that the sample size was sufficient. Table 6 shows the number of graduates under the age of 35 who are included in the sample.

Table 6
Number of Maritime university graduates under the age of 35 in the study population, by cohort and number of years after graduation, 2006 to 2011 cohorts
Table summary
This table displays the results of Number of Maritime university graduates under the age of 35 in the study population Number of years after graduation, 1 year, 2 years, 3 years, 4 years, 5 years and 6 years, calculated using number of graduates units of measure (appearing as column headers).
  Number of years after graduation
1 year 2 years 3 years 4 years 5 years 6 years
number of graduates
Cohort  
2006 7,105 6,030 5,315 4,835 4,500 4,240
2007 7,610 6,455 5,675 5,175 4,795 Note ...: not applicable
2008 7,390 6,330 5,645 5,100 Note ...: not applicable Note ...: not applicable
2009 7,445 6,405 5,680 Note ...: not applicable Note ...: not applicable Note ...: not applicable
2010 7,145 6,125 Note ...: not applicable Note ...: not applicable Note ...: not applicable Note ...: not applicable
2011 7,470 Note ...: not applicable Note ...: not applicable Note ...: not applicable Note ...: not applicable Note ...: not applicable

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Retention of Maritime university graduates

Knowing the proportion of graduates from Maritime universities who stay in the Maritimes after earning their degree—the retention rate of university graduates in the Maritime region—is an important question for the provincial governments since university graduates are among the most mobile Canadians.Note 22

Retention rates in the year following graduation were examined by region of origin, sex and field of study, and are based on graduates who completed a valid tax return, reported no self-employment income and did not pursue their education further on a full-time basis. All cohorts were combined since retention rates did not vary much across cohorts.

Higher retention rates are expected among graduates who were already living in the Maritimes at the time of their admission given family ties, friendships and other bonds they developed there. Conversely, students from other Canadian provinces and territories or from outside Canada might have a greater likelihood of returning to the place of residence that they reported at the time of admission, resulting in a lower Maritime retention rate among them.

Retention rates of undergraduates tended to be higher among women (70%) than men (64%) (Chart 4). As expected, retention rates were highest for undergraduates whose place of residence at the time of admission was the Maritimes (83% for women and 77% for men), while it was lowest for those who lived elsewhere in Canada at the time of admission (15% for both men and women). Among those who came from outside the country (and filed a tax return after graduating), more than one-half stayed in the Maritimes after graduating (51% of women and 56% of men).Note 23 Similar patterns were found among graduate degree holders.

Chart 4 Retention rate of Maritime university graduates one year after graduation, by level of education and region of origin, all cohorts from 2006 to 2011

Data table for Chart 4
Data table for Chart 4
Table summary
This table displays the results of Data table for Chart 4 Region of origin (at admission), Total, Maritimes, Rest of Canada and Outside Canada, calculated using retention rate (percent) units of measure (appearing as column headers).
  Region of origin (at admission)
Total Maritimes Rest of Canada Outside Canada
retention rate (percent)
Men with a undergraduate degree (bachelor degree) 64.0 77.4 14.8 55.7
Women with a undergraduate degree (bachelor degree) 70.0 83.4 15.3 51.0
Men with a graduate degree (master's degree or doctorate) 54.2 73.2 17.3 44.1
Women with a graduate degree (master's degree or doctorate) 60.5 82.1 16.9 45.5

High retention rates may also be linked to the key industries and occupations in a given region, and to economic fluctuations in those industries. Similarly, employment opportunities in specific industries located in other regions of Canada may also explain why some graduates choose to leave.

This partly explains why retention rates also vary by field of study. Graduates from education programs, for example, had the highest retention rates, regardless of gender or education level (Chart 5). Other fields such as mathematics and computer and information sciences; humanities; and health and related fields also had relatively high retention rates among men and women. In contrast, graduates from architecture and engineering programs had the lowest retention rates among women and the second lowest among men. The economic prosperity of Western Canada from 2007 to 2012, fostered by the exploitation of natural resources, may have attracted a number of graduates from Maritime universities during those years.

Chart 5 Retention rate of Maritime university graduates one year after graduation, by level of education and field of study, all cohorts from 2006 to 2011

Data table for Chart 5
Data table for Chart 5.1 and 5.2
Table summary
This table displays the results of Data table for Chart 5.1 and 5.2. The information is grouped by Field of study (appearing as row headers), Graduate degree (master's degree or doctorate) and Undergraduate degree (bachelor degree), calculated using retention rate (percent) units of measure (appearing as column headers).
Field of study Graduate degree (master's degree or doctorate) Undergraduate degree (bachelor degree)
retention rate (percent)
Men
Agriculture, natural resources and conservation 47.4 56.7
Architecture, engineering and related technologies 41.4 57.0
Visual and performing arts and communications technologies Note x: suppressed to meet the confidentiality requirements of the Statistics Act 58.5
Social and behavioural sciences and lawData table Note 1 42.9 61.1
Business, management and public administration 52.5 63.1
Health and related fieldsData table Note 2 53.6 64.2
Humanities 63.0 66.0
Physical and life sciences and technologies 50.0 69.6
Mathematics and computer and information sciences 65.1 72.0
Education 85.4 80.8
Women
Architecture, engineering and related technologies 40.4 45.0
Visual and performing arts and communications technologies Note x: suppressed to meet the confidentiality requirements of the Statistics Act 55.1
Agriculture, natural resources and conservation 45.0 67.1
Social and behavioural sciences and lawData table Note 1 58.7 66.1
Business, management and public administration 52.3 67.1
Physical and life sciences and technologies 54.5 68.2
Health and related fieldsData table Note 2 56.1 70.6
Humanities 55.2 71.1
Mathematics and computer and information sciences 40.8 72.2
Education 80.2 83.3

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