Elgin Middlesex Oxford Workforce Planning and Development Board & Local Employment Planning Council
3-647 Wilton Grove Rd., London ON N6N 1N7 Toll free 1-844-245-9985Tel. 519-672-3499, Fax 519-672-9089
Labour Force Participation in London
Economic Region – Follow-up study
Emilian Siman, Data Analyst
Bashir Adeyemo, GIS Support and Data Analyst
January 2019
PAGE 1
ACKNOWLEDGEMENT
This report presents an investigation of the labour force participation in the London Economic Region. It extends
the study done by Sanchez-Keane and Zonruiter (2017, February) through recent access to custom order data from
Census 2016 as well as more recent data from the Labour Force Survey and other sources. Authors of the document
attempt a comprehensive review of the factors influencing labour force participation in the London Economic
Region, a geography including Elgin, Middlesex and Oxford counties in the province of Ontario. In a sequential
order, the document reveals answers to the basic research questions: What is investigated? Is it unique? Who is
affected? Why is this happening? And, how can it be corrected?
If you have feedback, please do not hesitate to contact the authors at [email protected] or
[email protected]. Your help is greatly appreciated.
Report written by: Emilian Siman, Data Analyst
Bashir Adeyemo, GIS Support and Data Analyst
Guidance and expertise kindly provided by Debra Mountenay - Executive Director of the Elgin, Middlesex and
Oxford Workforce Planning and Development Board (EMOWPDB), Tamara Kaattari – Executive Director of
Literacy Link South Central (LLSC), and by members of the Central Planning Table of the Local Employment
Planning Council (LEPC).
© February 2019
“The material contained in this report has been prepared by the Local Employment Planning
Council London, the Elgin Middlesex Oxford Workforce Planning and Development Board and
Literacy Link South Central under the guidance of the Central Planning Table and it draws
information from a variety of sources considered to be reliable. We make no representation or
warranty, express or implied, as to its accuracy or completeness. In providing this material, the
Local Employment Planning Council, the Elgin Middlesex Oxford Workforce Planning and
Development Board and Literacy Link South Central does not assume any responsibility or
liability.”
This project was developed by In partnership with
This project is funded in part by the Government of Canada and the Government of Ontario. The views expressed in this document do not necessarily reflect those of the Government of Ontario.
PAGE 2
TABLE OF CONTENTS
1. Executive summary ……...................................................................... 3 2. Introduction ……...................................................................... 7 3. Research problem ……...................................................................... 7 4. Is the drop in the labour force participation rate
a unique problem for London ER? ……......................................................................
9
5. Why is a drop in participation rate? ……...................................................................... 10 5.1. Economic development of the geography ……...................................................................... 11 5.2. Aging population ……...................................................................... 12 5.3. Increased appetite for education ……...................................................................... 18 5.4. Gender-based roles and responsibilities ……...................................................................... 22 5.5. Technological revolution and AI ……...................................................................... 27 5.6. Employment barriers faced by certain
categories of population ............................................................................
29
5.7. Mobility of the labour force ............................................................................ 37 5.8. Age of retirement and readiness ............................................................................ 43 5.9. Attraction and retention of the local employers ............................................................................ 46 5.10. Unconventional factors: entry, exit, and respite ............................................................................ 50 6. Who is “not in labour force”? ............................................................................ 52 7. What are their reasons for not participating in
the labour market? ............................................................................
55
8. Methodology ............................................................................ 65 9. Recommendations ............................................................................ 66 10. References ............................................................................ 67 11. Appendix - Abbreviations ............................................................................ 69
PAGE 3
1. EXECUTIVE SUMMARY
The follow-up study of labour force participation in the London ER has been developed because of recent access to
customized tabulations of Census 2016 data and more recent information from the Labour Force Survey and other
sources. This investigation emerged in response to the dropping labour participation rate trend dominating the
London Economic Region in the past fifteen years. Because of analyzing this new body of data, several issues have
been noted about the local labour market. A list of recommendations has been compiled to inform policy decision
making.
Issues:
The industrial structure of the local economies played an important role in the recovery of the local labour markets. The local economies reliant on one or a few industries that restructured after the recession 2008-2009 have been recovering at a slower pace than the rest, e. g. Newbury, Tillsonburg, Aylmer, West Elgin, St. Thomas, and Bayham.
Between 2006 and 2016, the London Economic Region went through a demographic change led by the aging population. The proportion of the mature age cohort (55 years and over) was larger in 2016 than in 2006 across all labour market characteristics;
o Within the same time frame the mature age cohort increased its share of the labour force participation while youth (15 to 24 years) and prime age (25 to 54 years) cohorts decreased their share of labour force participation.
The labour force participation of the youth cohort showed a lot of volatility, which explained most of the seasonality observed for the labour force participation of the working age population.
The drop in labour force participation rate of the youth cohort suggests that the group might be involved more in education in 2016 than 10 years earlier due to an increased appetite of employers for a highly educated and skilled labour force.
There was an observable demographic shift between 2006 and 2016, in the London ER, towards a more educated labour force. The proportion of those holding a “university certificate or degree (bachelor level or above)” and “college, CEGEP or other non-university certificate or diploma” has significantly increased demonstrating an increased interest among local employers for a better educated labour force. Consequently, a larger proportion of the local population is involved in education and training, and for longer periods of time. This reduced the level of labour force participation in the London ER.
The educational level groups within the youth and prime age cohorts that experienced the largest reductions in labour force participation were “no certificate, diploma or degree,” “high school certificate or equivalent” and “university certificate or diploma below bachelor level.”
The local results suggest that after the financial crisis 2008-2009 due to increased economic uncertainties, employers increased their hiring preference for candidates with higher levels of education. Because the economic recovery after the recession in 2008-2009 was slow and new technologies emerged (3-D printing, AI, machine learning, big data, etc.), the preference for highly educated candidates was maintained.
A tighter regulatory HR selection environment emerged after the financial crisis 2008-2009, which was supported by the local educational institutions and professional associations. Certification, diploma earning and professional licensing increased their relevance among HR recruiters after 2008-2009 recession. The evolution towards a more constrained local labour market after the 2008-2009 financial crisis disadvantaged the educational groups identified earlier and led to a larger drop in labour force participation among them.
In contrast, the mature age cohort has been able to leverage its extensive work experience when facing the increasingly tighter educational level scrutiny after 2008-2009 recession.
Overall, men have a higher labour force participation rate than women in the London ER. In the aftermath of the financial crisis 2008-2009, men had reduced their labour force participation more than women. Men started reducing their labour market participation with the beginning of the recession 2008-2009 while women in the London ER, started reducing their participation starting in 2014. These results in the London ER can be associated with the loss of manufacturing jobs during the recession 2008-2009 where men were more likely working than women, and the loss of retail and food manufacturing jobs during the retail and
PAGE 4
food manufacturing sectors’ consolidation that started in 2013-2014 where women were more likely working than men.
Women “55 to 64 years old” increased their labour force participation rate between 2006 and 2016. Both cohorts, males and females, “65 years old and over” increased their labour force participation within the same time horizon.
All educational cohorts exhibited a loss in labour force participation between 2006 and 2016 in the London ER, either for men or women.
While the overall trend of the labour force participation in the London ER between 2006 and 2016 was trending downwards, the “university certificate or degree below bachelor degree,” “men,” “55 to 64 years old” increased their participation rate as well as the “high school certificate or equivalent,” “college, CEGEP or other non-university certificate or diploma,” and “university certificate or degree (bachelor and above),” “males,” “65 years old and over” increased their participation rates.
Both mature age groups of “females,” “55 to 64 years old” and “65 years old and over” have increased their participation between 2006 and 2016 for all educational levels.
These developments may have occurred because of a reactive behaviour of the mature age cohort to the uncertainty of the economic environment developed after the financial crisis 2008-2009, which also may have reduced the number of work opportunities for the youth cohort, considering the tight labour market generated during the slow economic recovery.
Due to the technological revolution involving automation, big data, machine learning and AI, the labour market suffered a polarization of jobs at both ends of the skill level spectrum - low-skill jobs and high-skill jobs. Because of this labour market change, the participation rate is more likely to drop.
The working age population in the London ER is diverse, including visible minorities, Aboriginal people, Francophone individuals, immigrants and other population groups, which generates a variety of labour market experiences associated with various levels of access to the labour market.
The participation rate for those who self-identified as visible minority, Aboriginal, and Francophone in the London ER was lower than the labour force participation rate exhibited by the overall population 15+ years old. Overall, the Francophone group displayed the lowest values of labour force participation rate among all groups compared.
In 2016 males displayed a higher propensity for labour force participation than females. When comparing the London ER and Ontario results, a significantly lower (about 5%) participation rate is noted for both genders in the London ER for the visible minority population. Slightly lower participation rates were exhibited by both gender groups of the Francophone population in the London ER than in Ontario. Therefore, visible minority and Francophone self-identified individuals of both genders experienced more barriers to entering the London ER labour market than in the province overall.
The prime age (25 to 54 years) cohort exhibited the highest participation rate in the London ER, as does Ontario. Within this age cohort, the visible minority and Aboriginal individuals in the London ER experienced significantly lower labour force participation rates than in Ontario. In contrast, the Francophone individuals of prime age in the London ER and in Ontario exhibited the highest participation rate than any other self-identified group. Provincially, the Francophone youth (15 and 24 years) individuals exhibited higher labour force participation than any other self-identified group within the same age cohort.
Individuals with higher educational attainment across all self-identified groups exhibited higher labour force participation rates in 2016 than those with lower educational attainment, in the London ER and/or Ontario. The “university certificate or degree (bachelor and above)” educated individuals, Aboriginal and/or Francophone in the London ER and/or Ontario experienced the highest labour force participation rates. In the London ER, in 2016, the Aboriginal individuals with “College, CEGEP or non-university certificate or diploma” had higher labour force participation rates than any individuals from other self-identified groups or the general population.
The immigrant population in the London ER is participating in the labour market at lower rate than the general population. High concern is associated with the youth and prime age immigrant groups in the London ER because they exhibited a significantly lower labour market participation than general population. The decreasing trend of labour force participation characterizes the immigrant population in the London ER at all levels of education. The additional barriers to entering the labour force encountered by immigrants through the social and cultural integration process contributes to their reduced labour market activity.
PAGE 5
The prime age and youth age groups are leading the net total migration per year in the London ER. If adding across years over a period of 10 years, a sizeable number of mature age people have been migrating in and out of the region.
The immigrants coming to London ER every year are more likely to be of prime and youth age, considering that the most common immigration reason is economic, in the “skilled worker” category. Younger people are more likely to migrate for economic reasons.
A fair amount of people migrates from London ER to other parts of the world. About a half of those are returning. Others are using this status temporarily. It would be very helpful to know their reasons for emigration to identify ways to retain people locally.
The net intra-provincial migration component suggests that there is a fair proportion of mature age people moving into London ER from other parts of the province. This data cannot identify if they are specifically from the GTA.
The average and median retirement ages in Canada increased in the past twenty years, extending labour force participation of the mature age cohort (55 years and over). This result can have positive and negative implications for the labour market. A positive effect is the resulting increased labour force participation rate overall. A negative effect is the increased competition across age cohorts for the same job opportunities with the youth cohort being most affected.
Variation among the average and median retirement ages was observed for various categories of workers (self-employed, private sector and public sector) and genders.
On average, people in the London ER working in the occupational groups NOC 9 (occupations in manufacturing and utilities), NOC 7 (trades, transport and equipment operators and related occupations) and NOC 3 (health occupations) earned higher employment income than people in Ontario working in the same occupational groups.
The “entry-exit-respite” labour force behaviour exhibited most likely by people engaged in temporary employment contributes to the diminishing labour force participation rate in the London ER. Industries where this type of employment (temporary) became very popular contribute to the expansion of the entry-exit-respite labour market dynamic; e.g. Agriculture, Education, Public Administration, Nonprofit, Retail and other.
Geographic areas with a higher concentration of the industries preferring and promoting contract/term employment, seasonal, or casual are more exposed to this unconventional dynamic of the labour force, which also makes it difficult to interpret the labour market results.
The economic context surrounding the 2008-2009 recession, the oil crisis 2014-2015 and the economic activity contraction during 2015 explain the variation of the number “not in labour force but wanted to work,” particularly the spikes in 2009, 2010 and 2011.
The number of individuals who were “not in labour force but wanted to work” increased during the recession in 2008-2009 and in the years immediately after.
Only a small proportion (about 4%) of the “not in the labour force” indicated that they “wanted to work” but they were constrained by some reason.
Organizing the reasons by the size of the group in a decreasing order, it was determined: o Tier 1: Reasons – “school” and “other” (about 25% each of the two form the total), o Tier 2: Reasons – “illness” and “personal/family responsibilities” (around 19% each of the two form
the total), o Tier 3: Reasons – “discouraged” and “awaiting recall/reply” (approximately 6% each of the two form
the total).
A major gender discrepancy was observed for the “wanted to work, reason – personal/family responsibilities” for which women are more likely to cite this reason than men.
Men were more likely than women to “await for recall/reply,” be “discouraged” or cite “other” as a reason for not participating.
People of prime age and youth were more likely than any other age group to claim “wanted to work but … reason …”
People of prime age followed by youth were more likely than any other age group to cite “illness,” “personal/family responsibility,” “awaiting for recall/reply,” “discouraged,” and “other” reasons.
“Youth” were more likely than any other age group to cite “school” as a reason for not participating to the labour market.
PAGE 6
Recommendations:
Local economic development should constantly strive for industrial diversification and job creation.
Development of and support for leading industries that create steady job creation locally; e.g. R&D in Health, IT, Manufacturing, Transportation, Education, Services, and Agriculture; digitization of Financial and Marketing Services and Retailing; Construction and Home Renovation, etc.
Provide economic incentives that support natality and raising children, labour force attraction from outside the London Economic Region and retention of the mature age cohort. These efforts should be backed accordingly by job creation policies.
Develop and promote work arrangement alternatives locally that provide flexibility for the population groups constrained by time: e.g. care givers (mothers, people caring for family members or relatives, etc.), students, mature age people who want to supplement their income.
Increase access to training and reskilling programs to engage visible minority, Aboriginal, Francophone and immigrant groups within the local labour market. More local promotion of the standards for and processes involved, in licensing for regulated professions. Expand educational alternatives and labour market integration for the Aboriginal group.
London ER employers should change their attraction-retention strategies by offering equal or higher wages than the average in Ontario, or relative to the earnings in the neighboring areas.
Develop local workforce development policies that reward employers who create permanent full-time work alternatives. The temporary work arrangements create high volatility for the size of the local labour force. The late development of the gig economy perpetuates the expansion of the precariousness of work, fatigue, discouragement, and economic vulnerability, which ultimately reflects on local labour force participation.
PAGE 7
2. INTRODUCTION
The present document is a follow-up study to the London Economic Region Labour Force Participation report by
Sanchez-Keane & Zonruiter (2017). The recent acquisition of custom data from Census 2016 made available in 2018
through the Consortium of the Western Ontario Workforce Planning Boards generated local interest for a follow-up
study. The extended access to the Census 2016 data, along with current labour information from other sources
provides a newer insight into the issue of local labour market participation than the one available at the time of the
first report release. Furthermore, the current document extends the research focus from the prime age population
(25 to 54 years old) investigated by Sanchez and Zonruiter (2017) to the total working age population of 15 years old
and above. This extension adds more substance to the topic of labour force participation at both ends of the age
spectrum, by looking also at the labour-related behaviour of the youth population (15 to 24 years old) and the
mature age population (over 55 years old). Tailored conclusions will be explored for each of the above-mentioned
age groups.
3. RESEARCH PROBLEM
Tremendous effort was invested in the economic recovery and growth after the global recession generated by the
financial crisis 2007-2009. Locally, the success can be easily identified in the positive trend of the unemployment
rates illustrated in Figure 1. Although this evolution is impressive, a single labour market indicator cannot capture
the complexities of the labour market. A holistic view upon the state of the labour market is provided by the
composite index named Labour Market Indicator (LMI) developed by the Bank of Canada, a measure factoring out
the common movement of eight labour market variables (Zmitrowicz & Khan, 2o14). Unfortunately, the LMI
composite index is not yet available for lower tier geographies to use in assessing the local labour markets, but there
are numerous other individual labour market measures. Therefore, it is suggested that before pronouncing the
success or failure of the local labour market, multiple indicators should be reviewed.
As announced, the focus of the present study is labour market participation, therefore our attention will turn to an
equally important labour market indicator named labour force participation rate. It measures the proportion of the
working age population (15 years old and over) actively involved with the labour market, either employed or
temporarily unemployed but actively seeking work.
The results presented in Figure 2 intrigue most economists and business professionals since the conventional
economic theory suggests that under normal conditions one should observe a counter-sync movement between the
unemployment rate and the participation rate. Contrary to this conventional knowledge, the results illustrated in
Figure 2 demonstrate a synchronized movement of the two indicators and leads one to the following observations:
1) the labour force participation rates in Canada, Ontario and London ER dropped continuously since the financial
crisis 2008-2009, and 2) specifically in London Economic Region (ER), the dropping trend is more severe and the
variation of the monthly results is larger than for the province or the nation. These observations intrigued local
economic actors who consequently asked for the current investigation.
Labour force is a driving factor of economic growth. The late evolution of the labour force in London Economic
Region became a major concern for the local and regional leaders.
The present study attempts to answer several questions regarding the labour force participation rate in the London
ER: Is the drop in labour force participation rate a unique problem for London ER? Why is there a drop in
participation rates? What factors are contributing to this evolution? Who is part of the “not in the labour force”
group? What are their reasons for not participating? Can the current situation be corrected?
PAGE 8
Source: Statistics Canada, Table 14-10-0293-01
Figure 1
Source: Statistics Canada, Table 14-10-0293-01
Figure 2
R² = 0.7596
0
2
4
6
8
10
12
Jan
-06
Jun
-06
No
v-0
6
Ap
r-0
7
Sep
-07
Feb
-08
Jul-
08
De
c-0
8
May
-09
Oct
-09
Mar
-10
Au
g-1
0
Jan
-11
Jun
-11
No
v-1
1
Ap
r-1
2
Sep
-12
Feb
-13
Jul-
13
De
c-1
3
May
-14
Oct
-14
Mar
-15
Au
g-1
5
Jan
-16
Jun
-16
No
v-1
6
Ap
r-1
7
Sep
-17
Feb
-18
Jul-
18
Unemployment rate by geography(three-month moving average, unadjusted for seasonality)
Canada Ontario London ER Poly. (London ER)
Fin
anci
al c
risi
s 2
00
8-2
00
9
R² = 0.8026
54
56
58
60
62
64
66
68
70
72
Jan
-06
Jun
-06
No
v-0
6
Ap
r-0
7
Sep
-07
Feb
-08
Jul-
08
Dec
-08
May
-09
Oct
-09
Mar
-10
Au
g-1
0
Jan
-11
Jun
-11
No
v-1
1
Ap
r-1
2
Sep
-12
Feb
-13
Jul-
13
Dec
-13
May
-14
Oct
-14
Mar
-15
Au
g-1
5
Jan
-16
Jun
-16
No
v-1
6
Ap
r-1
7
Sep
-17
Feb
-18
Jul-
18
Participation rate by geography(three-month moving average, unadjusted for seasonality)
Canada Ontario London ER Poly. (London ER)
Fin
anci
al c
risi
s 2
00
8-2
00
9
PAGE 9
4. IS THE DROP IN LABOUR FORCE PARTICIPATION RATE A UNIQUE PROBLEM FOR
THE LONDON ER?
This question develops naturally and leads to a comparison with the neighbouring economic regions, the province,
the nation, and eventually the global rates.
The neighbouring economic regions experienced the same drop in labour force participation rate as the London ER,
particularly evident after the economic shock of the financial crisis 2008-2009 (see Figure 3). However, visually, the
curve representing the labour force participation rate in the London ER reflects a more acute slope than those of the
other illustrated regions, see Figure 3.
Although before the financial crisis 2008-2009 the labour force participation rate in the London ER was above the
provincial and national levels (Figure 3), during the recovery and economic growth periods following the financial
crisis 2008-2009, the labour force participation rate in the London ER sat below the provincial level. These results
suggest that the recovery from the economic recession following the years 2008-2009 was more difficult for London
ER than for the other neighbouring regions, except for Windsor-Sarnia.
Source: Statistics Canada, Table 14-10-0090-01
Figure 3
50
55
60
65
70
75
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
Participation rate by economic region (%)
Ontario Kitchener-Waterloo-Barrie Hamilton-Niagara Peninsula
London Windsor-Sarnia
Fin
anci
al c
risi
s 2
00
8-2
00
9
PAGE 10
Source: OECD data, https://data.oecd.org/emp/labour-force-participation-rate.htm
Figure 4
**This somewhat novel trend – the drop in labour force participation rate, has been detected also among multiple
OECD member countries. However, Canada ranked well among the OECD countries (Figure 4).
These findings leads one to conclude that the recent evolution of the labour force participation rate in the London
ER is not unique among the other economic regions in Ontario, or in Canada. Because of its severity in the London
ER, a review of the potential causes could lead to the development of sustainable policies to address the issue at
local, provincial or national levels.
5. WHY IS A DROP IN PARTICIPATION RATES?
Numerous hypotheses have been advanced in explaining the recent drop in the labour force participation rates.
Some are supported by data and statistical testing while others are backed only by anecdotal evidence. It is the
intent within this study to list them as comprehensively as possible and potentially test them using the new body of
data available from Census 2016 and other sources.
Among the most popular hypotheses explaining why the labour force participation rates have decreased in the past
10-15 years are: 1) the economic development of the geography, 2) the aging population, 3) the increased appetite for
education, 4) the gender-based roles and responsibilities, 5) the technological revolution generated by artificial
intelligence (AI), 6) the employment barriers faced by certain categories of population, 7) the mobility of the labour
force, 8) the retirement age and readiness (personal wealth), 9) the attraction/retention efforts of the local
employers (employment income, cost of living, housing, work opportunities, etc.) and 10) the unconventional
factors: entry-exit – respite dynamic, see Figure 5 .
In the next few subsections we are going to explore the validity of these hypotheses at the local level, specifically in
the London ER.
0
10
20
30
40
50
60
70
80
90
ITA
HR
V
GR
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BE
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U
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D
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Participation rate among the OECD countries in 2017(working age population, 15+ years old)
PAGE 11
Figure 5
5.1 ECONOMIC DEVELOPMENT OF THE GEOGRAPHY
A comparison among various geographic subdivisions within the London ER based on labour force participation
rate allows one to identify geographies that were impacted harder by the economic recession 2008-2009. Figure 6
demonstrates this approach, and it shows that due to the abrupt downsizing and restructuring of the automotive
manufacturing sector following the financial crisis 2008-2009, as well as the consolidation of the retail and food
manufacturing 20013-2014 and the Oil crisis 2014, several Census Subdivisions (CSDs) identified in Figure 6 suffered
major economic contractions. Unfortunately, the economic recovery and expansion that followed has not been
uniformly successful across all the CSDs. Geographical units from each county forming London Economic Region
have been performing below the London ER labour force participation rate benchmark.
Labour force participation
rate
1. Economic development of the
geography
2. Aging population
3. Increased appetite for education
4. Gender based roles and
responsibilities
5. Technological revolution (3-D printing,
big data, machine learning & AI)
6. Employment barriers faced by
certain categories of population
7. Mobility of the labour force
8. Retirement age and readiness
9. Attraction and retention efforts of
local employers10. Unconventional factors: Entry, exit,
and respite
PAGE 12
Source: One Hub, custom order tables, Census 2016 – table T3_POR_CSD_CD.
Figure 6
CONCLUSIONS
The industrial structure of the local economy played an important role in restoring the performance of the local
labour markets. The local economies reliant on one or a few industries that fundamentally restructured after the
recession 2008-2009 have been recovering and expanding slower than the rest. A high level of labour force
concentration into one or few industries sets a major local economic risk. Automotive manufacturing, tourism,
retail and finance were industries seriously affected by the financial crisis 2008-2009. Therefore, local economic
development should constantly strive for industrial diversification.
5.2 AGING POPULATION
Figure 7 shows the 5-year age population pyramids for 2006 and 2016 in the London ER. The 2016 population
pyramid was overlapped on the 2006 population pyramid to allow an assessment of changes across the 5-year age
groups over the 10-year time span, 2006 to 2016. Visually one could observe that the population groups exiting the
labour market within the 2006-2016 time-frame were slightly larger than the groups entering the labour market.
This illustration is suggestive for a gross estimation of the flow of the labour force in the London ER, because it
doesn’t provide the percentages of the 5-year age groups that are participating in the labour market. One could
hypothesize that the youth groups (15 to 24 years old) entering the labour market were less likely to be involved in
the labour market than the mature age groups (55 to 64 years old), which were exiting the labour market. The
hypothesized differential of the labour force entry and exit was further compensated by immigration and/or
participation growth of various demographic groups.
Figure 8 shows precisely the size of the labour force by age and gender groups in the London ER. It is worth noticing
the size of the 5-year age groups between ages 45 to 60 relative to any other 5-year age group. These groups are
2016 London ER participation rate benchmark, 63.1 2015 London ER participation rate …
0
10
20
30
40
50
60
70
80
Participation rate within the London ER (%) – Census 2016
PAGE 13
likely going to exit the labour market in the next 10 to 15 years. At the other extreme, the youth groups (15 to 25) do
not seem to balance the exiting labour market groups. As suggested earlier, this disequilibrium between entry and
exit flows of the labour force can be adjusted through prudent local HR attraction and retention policies, as well as
provincial and national policies and regulations. It is worth noticing that there will be an active participation in the
labour market after the age of 65, marginal but important.
Source: One Hub1, Census custom tables, Census 2006 – Table EO1246 Table 1_R and Census 2016 – Table 1 _POR
Figure 7
The intent of this analytical exercise is to determine the local age-related behaviour vis-a-vis the labour force
participation rate. Figure 9 provides a comparative framework across time, between 2006 and 2016 as well as across
1 One Hub data repository of the Western Ontario Workforce Development Boards
30,000 20,000 10,000 0 10,000 20,000 30,000
0 to 4 years
5 to 9 years
10 to 14 years
15 to 19 years
20 to 24 years
25 to 29 years
30 to 34 years
35 to 39 years
40 to 44 years
45 to 49 years
50 to 54 years
55 to 59 years
60 to 64 years
65 to 69 years
70 to 74 years
75 to 79 years
80 to 84 years
85 years and over
Population pyramids for 2006 and 2016 by age and gender group, for London ER
(persons)
Female - 2016 Female - 2006 Male - 2016 Male - 2006
Entry labour market (15 years old)
Exit labour Market (65 years old)
PAGE 14
age cohorts, defined as youth (15 to 24 years old), prime age (25 to 54 years old) and mature age (55 years old and
over).
Overall the participation rate in the London ER dropped between 2006 and 2016 from 67.9% to 64.4%. Looking at
the participation rates by age cohorts, one would observe a 5.7% drop in participation within the 10-year time frame
for the youth cohort and only 1% drop for the prime age cohort. In contrast, during the same time frame the mature
age population in the London ER increased its participation by 2.7%, more specifically for the age group “55 to 64
years old”, the participation rate increased by 1.9%. The absolute size of the age cohorts at both ends of the age
spectrum, the youth and mature age are different, the mature age group being larger than the youth group.
Source : One Hub, Census custom tables, Census 2016 – Table T3_POR and Census 2006 – Table EO1246 T2_3
Figure 8
LABOUR FORCE PARTICIPATION RATE DECOMPOSITION BY AGE
More introspection is required to understand the labour force participation behaviour by age. Therefore, it is
proposed to decompose the labour force participation rate by the three above mentioned age cohorts. The time
horizon chosen for this new perspective upon labour force participation is between January 2006 and December
2018, because it captures the labour market results before the financial crisis 2008-2009 and after. The final
transformation of the data proposed for this analysis picks January 2006 as a reference point, and every value of the
25,000 20,000 15,000 10,000 5,000 0 5,000 10,000 15,000 20,000 25,000
15 to 19 years
20 to 24 years
25 to 29 years
30 to 34 years
35 to 39 years
40 to 44 years
45 to 49 years
50 to 54 years
55 to 59 years
60 to 64 years
65 years and over
Labour force population pyramids for 2006 and 2016 by age and gender group, in the London ER
(persons)
Female - 2016 Female - 2006 Male - 2016 Male - 2006
Entry labour force(15 years old)
Exit labour force(65 years old)
PAGE 15
participation rate in the subsequent months is presented in relative terms to the reference value, capturing the
change (difference).
The participation rate decomposition by age is presented below in equations 1 and 2. The character symbolizes the
difference. The year 2006 is the reference and indices i and j refer to the successive years for which the change is
calculated. A similar decomposition and change computation can be applied to monthly data with the time
reference point January 2006 and K representing any month of the year. The illustration of the monthly
participation rate data transformation and decomposition by age cohort for London CMA2 is provided in Figure 10.
This approach follows the Ketcheson, Kyui and Vincent (2017, July) analytical method.
Source : One Hub, Census custom tables, Census 2016 – Table T3_POR and Census 2006 – Table EO1246 T2_3
Figure 9
2 CMA – stands for Census Metropolitan Area, a geographic division used by Statistics Canada
70.3
85.8
63.5
35.2
67.964.6
84.8
65.4
37.9
64.4
0
10
20
30
40
50
60
70
80
90
100
Youth (15 to 24years)
Prime age (25 to 54years)
55 to 64 years Mature age (55 yearsand over)
Total - (15 years andover)
Participation rate, 2006-2016 comparison - London ER(%)
2006 2016
𝑝𝑎𝑟𝑡𝑖𝑐𝑖𝑝𝑎𝑡𝑖𝑜𝑛 𝑟𝑎𝑡𝑒( 15 +) = 𝑙𝑎𝑏𝑜𝑢𝑟 𝑓𝑜𝑟𝑐𝑒 (15+)
𝑝𝑜𝑝𝑢𝑙𝑎𝑡𝑖𝑜𝑛 (15+)𝑥 100
=𝑙𝑎𝑏𝑜𝑢𝑟 𝑓𝑜𝑟𝑐𝑒 (15 𝑡𝑜 24) + 𝑙𝑎𝑏𝑜𝑢𝑟 𝑓𝑜𝑟𝑐𝑒 (25 𝑡𝑜 54) + 𝑙𝑎𝑏𝑜𝑢𝑟 𝑓𝑜𝑟𝑐𝑒 (55+)
𝑝𝑜𝑝𝑢𝑙𝑎𝑡𝑖𝑜𝑛 (15+)𝑥 100
=𝑙𝑎𝑏𝑜𝑢𝑟 𝑓𝑜𝑟𝑐𝑒 (15 𝑡𝑜 24)
𝑝𝑜𝑝𝑢𝑙𝑎𝑡𝑖𝑜𝑛 (15+)𝑥 100 +
𝑙𝑎𝑏𝑜𝑢𝑟 𝑓𝑜𝑟𝑐𝑒 (25 𝑡𝑜 54)
𝑝𝑜𝑝𝑢𝑙𝑎𝑡𝑖𝑜𝑛 (15+)𝑥100 +
𝑙𝑎𝑏𝑜𝑢𝑟 𝑓𝑜𝑟𝑐𝑒 (55 𝑎𝑛𝑑 𝑜𝑣𝑒𝑟)
𝑝𝑜𝑝𝑢𝑙𝑎𝑡𝑖𝑜𝑛 (15+)𝑥100
= % 𝑠ℎ𝑎𝑟𝑒 (15 𝑡𝑜 24) + % 𝑠ℎ𝑎𝑟𝑒 (25 𝑡𝑜 54) + % 𝑠ℎ𝑎𝑟𝑒 (55+) (1)
PAGE 16
Source : Statistics Canada. Table 14-10-0095-01
Figure 10
London CMA is an acceptable surrogate geography for the London ER. Figure 10 shows that participation rate of the
working age population (15 years and over) in London CMA decreased since January 2006. The decomposition of the
change in participation rate by the age cohorts allows one to determine how the age contributed to the total
change. Figure 10 indicates that in time the youth and prime age cohorts reduced their contribution share to the
change in participation rate in London CMA while the mature age cohort increased its contribution share to the
change in participation rate in London CMA, relative to January 2006. Seasonal variation is observed for all three
age cohorts. As expected, due to its involvement with education, the volatility of the share contribution to the
participation rate in London CMA is more evident for the youth cohort. Furthermore, the change in participation is
more evident after the financial crisis 2008-2009, leading us to speculate that the economic shock generated a lot of
discouragement immediately after. Finally, Figure 10 also shows a high correlation between the labour force
R² = 0.807
-12.0
-10.0
-8.0
-6.0
-4.0
-2.0
0.0
2.0
4.0
6.0
8.0
10.0
Jan-06 Jan-07 Jan-08 Jan-09 Jan-10 Jan-11 Jan-12 Jan-13 Jan-14 Jan-15 Jan-16 Jan-17 Jan-18
London CMA - Change in age cohort share of participating population and negative change in the share of age group "65 +" of
the total population relative to January 2006(%) ( three month moving average, unadjusted for seasonality)
Prime age (25 to 54 years) Mature age (55 years and over)
Youth (15 to 24 years) Total all ages (15+)
Population aging (65 year and over) Poly. (Total all ages (15+))
Fin
anci
alcr
isis
20
8-2
00
9
∆𝐽𝑎𝑛,2006𝑝𝑎𝑟𝑡𝑖𝑐𝑖𝑝𝑎𝑡𝑖𝑜𝑛 𝑟𝑎𝑡𝑒 (15 +) = 𝑝𝑎𝑟𝑡𝑖𝑐𝑖𝑝𝑎𝑡𝑖𝑜𝑛 𝑟𝑎𝑡𝑒 (15+)𝐾,20𝑖𝑗 − 𝑝𝑎𝑟𝑡𝑖𝑐𝑝𝑎𝑡𝑖𝑜𝑛 𝑟𝑎𝑡𝑒(15 +)𝐽𝑎𝑛,2006
= % 𝑠ℎ𝑎𝑟𝑒 (15 𝑡𝑜 24)𝐾,20𝑖𝑗
+ % 𝑠ℎ𝑎𝑟𝑒 (25 𝑡𝑜 54)𝐾,20𝑖𝑗
+ %𝑠ℎ𝑎𝑟𝑒 (55 +)𝐾,20𝑖𝑗 − % 𝑠ℎ𝑎𝑟𝑒 (15 𝑡𝑜 24)𝐽𝑎𝑛,2006
− % 𝑠ℎ𝑎𝑟𝑒 (25 𝑡𝑜 54)𝐽𝑎𝑛,2006
− % 𝑠ℎ𝑎𝑟𝑒 (55 +)𝐽𝑎𝑛,2006
= (% 𝑠ℎ𝑎𝑟𝑒 (15 𝑡𝑜 24)𝐾,20𝑖𝑗
− % 𝑠ℎ𝑎𝑟𝑒 (15 𝑡𝑜 24)𝐽𝑎𝑛,2006
) + (% 𝑠ℎ𝑎𝑟𝑒 (25 𝑡𝑜 54)𝐾,20𝑖𝑗
−% 𝑠ℎ𝑎𝑟𝑒 (25 𝑡𝑜 54)𝐽𝑎𝑛,2006
)
+ (% 𝑠ℎ𝑎𝑟𝑒 (55 +)𝐾,20𝑖𝑗 - % 𝑠ℎ𝑎𝑟𝑒 (55 +)𝐽𝑎𝑛,2006)
= ∆𝐽𝑎𝑛,2006 % 𝑠ℎ𝑎𝑟𝑒 (15 𝑡𝑜 24) + ∆𝐽𝑎𝑛,2006% 𝑠ℎ𝑎𝑟𝑒 (25 𝑡𝑜 54) + ∆𝐽𝑎𝑛,2006% 𝑠ℎ𝑎𝑟𝑒 (55 +) (2)
PAGE 17
participation rate and the negative of the share of the 65 years and over group of the total population (named here
aging population).
Finally, looking holistically at all the labour market indicators in the London E R, one would observe the increased
share of the mature age cohort across all labour market characteristics to the detriment of the other two age group
cohorts, the youth and prime age, see Figure 11.
Source : One Hub, Census custom tables, Census 2016 – Table T3_POR and Census 2006 – Table EO1246 T2_3
Figure 11
CONCLUSIONS
Between 2006 and 2016, the London Economic Region suffered a demographic shift led by the aging population. The
proportion of the mature age cohort is larger in 2016 than in 2006 across all labour market characteristics.
Within the same time frame the mature age cohort increased its share of labour force participation while youth and
prime age cohorts decreased their share of labour force participation.
The labour force participation of the youth cohort dropped the most across the age cohorts and it shows a lot of
volatility and explains most of the seasonality observed for the overall labour force participation of the working age
population (15 years old and over).
0 100000 200000 300000 400000 500000 600000
2006
2016
2006
2016
2006
2016
2006
2016
2006
2016
Tota
lp
op
ula
tio
n1
5+
In t
he
lab
ou
rfo
rce
Emp
loye
dU
ne
mp
loye
dN
ot
in t
he
lab
ou
r fo
rce
Labour force characteristics, 2006-2016 comparison - London ER(x 1,000 persons)
Youth (15 to 24 years) Prime age (25 to 54 years) Mature age (55 years and over)
PAGE 18
The drop in labour participation rate of the youth cohort suggests that this age group might have be involved more
in 2016 than 10 years earlier in education because of an increased appetite among local employers for a highly
educated and skilled labour force. This hypothesis is pursued in more detail further in a later section of the current
study.
The increased labour force participation among the mature age cohort members requires a deeper look into
migration within London ER.
The identified demographic trends can be adjusted through economic incentives that support natality and raising
children, labour force attraction from outside, retention within the region and retention of the mature age cohort.
These efforts should be seconded accordingly by job creation policies.
5.3 INCREASED APPETITE FOR EDUCATION
A quick look at the participation rate by educational group in the London ER reveals the same overall decreasing
trend across all the educational groups. As Figure 12 illustrates, for some groups the drop in participation rate has
been larger than for others: e.g. between 2006 and 2016 the “no certificate, diploma or degree” group dropped in
labour force participation by 6.6%, the “high school certificate or equivalent” group reduced its labour force
participation by 7.2%, the “apprenticeship or trades certificate or diploma” group diminished its labour force
participation by 4.8%, the “college, CEGEP or other non-university certificate or diploma” group reduced its labour
force participation rate by 3.8%, the “university certificate or diploma below bachelor level” group dropped its labour
force participation by 6% and the “university certificate or degree” group decreased its labour force participation rate
by 3.3%. As a general trend one would observe that the drop in labour force participation rate diminishes as the
education increases, excepting for the “university certificate or diploma below bachelor level” group.
Source : One Hub, Census custom tables, Census 2016 – Table T3_POR and Census 2006 – Table EO1246 T2_3
Figure 12
45.8
71.2 68.5
79.569.2
79.1
39.2
64 63.7
75.7
63.2
75.8
0102030405060708090
No certificate,diploma or degree
High schoolcertificate or
equivalent
Apprenticeshipor trades
certificate ordiploma
College, CEGEPor other non-
universitycertificate or
diploma
Universitycertificate or
diploma belowbachelor level
Universitycertificate or
degree
Participation rate by education level, 2006-2016 comparison -London ER
(%)
2006 2016
PAGE 19
An increasing amount of anecdotal and scientific evidence indicates that there is an increasing demand among
employers for more educated workers (Psacharopoulos, 1986). As society advances technologically, more educated
workers will be in demand. The overall benefits of a more educated labour force trickles down to all levels of society.
To meet this need, the educational institutions are designing educational programs that respond to the demand,
changing the definitions of the types and levels of knowledge and skills that define the future workforce. Because of
this interaction there is a push for a more educated workforce. The fear of “over-supply” and “over-qualification”
seem to captivate many (Machin & McNally, 2007), while the reality suggests that “shortages of talent” are present
almost everywhere (Bank of Canada, 2018).
Figure 13 provides data support for the recent demographic shift towards a more educated workforce in the London
ER. One can see the growth of the “university certificate or degree” cohort between 2006 and 2016 as well as the
growth of the “College, CEGEP or other non-university certificate or diploma” cohort during the same time frame
while all the other educational level cohorts have somewhat reduced. Large reductions can be observed for the “no
certificate, diploma or degree,” “apprenticeship or trades certificate or diploma”, and “university certificate or diploma
below bachelor level” cohorts.
Source : One Hub, Census custom tables, Census 2016 – Table T3_POR and Census 2006 – Table EO1246 T2_3
Figure 13
Including age within this analysis might provide more insight into the issue of dropping labour force participation.
Figure 14 shows that in the London ER, for the youth cohort, the labour force participation rate significantly
diminished for the “no certificate, diploma or degree,” “high school certificate or equivalent” and “university certificate
or diploma below bachelor level” cohorts, by 9.7%, 8.4% and 15% respectively. All the other educational groups
within the age cohort reduced their labour force participation by less than 2%.
Almost the same kind of behaviour was observed for the prime age cohort (Figure 15), when the labour force
participation significantly reduced for the “no certificate, diploma or degree,” “high school certificate or equivalent”
and “university certificate or diploma below bachelor level” cohorts, by 9.2%, 3.4%, and 3.9% respectively. The labour
53520
39820
99345
98140
28430
22440
81205
97485
9690
5580
61535
80850
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
2006
2016
Labour force by education, 2006-2016 comparison – London ER(%)
No certificate, diploma or degree
High school certificate or equivalent
Apprenticeship or trades certificate or diploma
College, CEGEP or other non-university certificate or diploma
University certificate or diploma below bachelor level
University certificate or degree
PAGE 20
force participation for the other educational groups within the same age cohort marginally increased or were
maintained the same between 2006 and 2016.
Source : One Hub, Census custom tables, Census 2016 – Table T3_POR and Census 2006 – Table EO1246 T2_3
Figure 14
Source : One Hub, Census custom tables, Census 2016 – Table T3_POR and Census 2006 – Table EO1246 T2_3
Figure 15
52.5
81.688.9 89.7
84.578.7
42.8
73.2
87.4 89.4
69.576.8
0102030405060708090
100
No certificate,diploma or degree
High schoolcertificate or
equivalent
Apprenticeshipor trades
certificate ordiploma
College, CEGEPor other non-
universitycertificate or
diploma
Universitycertificate or
diploma belowbachelor level
Universitycertificate or
degree
Youth (15 to 24 years) participation rate by education - London ER
(%)
2006 2016
72.984.7 87.6 90.1 87.4 88.7
63.7
81.388.6 90.2
83.589.1
0102030405060708090
100
No certificate,diploma or degree
High schoolcertificate or
equivalent
Apprenticeshipor trades
certificate ordiploma
College, CEGEPor other non-
universitycertificate or
diploma
Universitycertificate or
diploma belowbachelor level
Universitycertificate or
degree
Prime age (25-54 years) participation rate by education -London ER
(%)
2006 2016
PAGE 21
Source : One Hub, Census custom tables, Census 2016 – Table T3_POR and Census 2006 – Table EO1246 T2_3
Figure 16
Source : One Hub, Census custom tables, Census 2016 – Table T3_POR and Census 2006 – Table EO1246 T2_3
Figure 17
51.1
63.467.7 68.8
6571.6
53.1
63.769.4 69.5 68.9 71.2
0
10
20
30
40
50
60
70
80
No certificate,diploma or degree
High schoolcertificate or
equivalent
Apprenticeshipor trades
certificate ordiploma
College, CEGEPor other non-
universitycertificate or
diploma
Universitycertificate or
diploma belowbachelor level
Universitycertificate or
degree (bachelorand above)
Participation rate of the “55 to 64 year olds” group by education - London ER
(%)
2006 2016
810.6
14.7 13.6 13.5
20.9
9.2
14.816.1 17.2
14.7
23.6
0
5
10
15
20
25
No certificate,diploma or degree
High schoolcertificate or
equivalent
Apprenticeshipor trades
certificate ordiploma
College, CEGEPor other non-
universitycertificate or
diploma
Universitycertificate or
diploma belowbachelor level
Universitycertificate or
degree
Participation rate of the "65 year olds and over"group by education - London ER
(%)
2006 2016
PAGE 22
The preview of the labour force participation rates of the mature age cohort by educational groups was split into
two age groups, the “55 to 64 years old” and the “65 years old and over” to achieve more accuracy in identifying
issues. Therefore, Figure 16 shows that in the case of “55 to 64 years old” all the educational groups increased slightly
their labour force participation rate (between 0.3% and 3.9%) excepting the “university certificate or degree (bachelor
and above)” cohort, which experienced a marginal drop in participation rate of 0.4%.
Unexpectedly, the “65 years old and over” group increased their labour force participation rate across all the
educational level groups, somewhere between 1.2% and 4.2%, see Figure 17. Although this age cohort makes a small
contribution to the overall participation rate in the region, these results are very encouraging and contribute to the
overall participation rate.
CONCLUSIONS
There was an observable demographic shift between 2006 and 2016 in the London ER towards a more educated
labour force. The proportion of those holding a “university certificate or degree (bachelor level or above)” and
“college, CEGEP or other non-university certificate or diploma” has significantly increased between 2006 and 2016 in
the London ER, demonstrating an increased interest among local employers for a better educated labour force. The
immediate consequence of this result is that a larger proportion of the local population is involved in education and
training, and for longer periods of time. This has an immediate negative effect upon the level of labour force
participation.
As noted earlier the educational level groups within the youth and prime age cohorts that experienced the largest
reductions in labour force participation were “no certificate, diploma or degree,” “high school certificate or
equivalent” and “university certificate or diploma below bachelor level.” These results suggest that after the financial
crisis 2008-2009 due to increased economic uncertainties the employers increased their hiring preference for
candidates with higher levels of education, just because a larger pool of talent (unemployed) was available. Because
the economic recovery after the recession in 2008-2009 was slow and new technologies emerged (3-D printing, AI,
decision-making algorithms, etc.) this preference for highly educated candidates maintained, which sent the signal
to the market that education increases one’s chances to get a job more than ever.
Furthermore, these results could be explained by the development of a tighter regulatory HR selection environment
emerging after the financial crisis pushed by educational institutions and professional associations. Certification,
diploma earning, and professional licensing increased their relevance among HR recruiters after the 2008-2009
recession. The development of a more constrained local labour market after 2008-2009 financial crisis
disadvantaged the educational groups identified earlier and led to a larger drop in the labour force participation
among them.
In contrast, the mature age cohort has been able to leverage its extensive work experience when facing the
increasingly tighter educational level scrutiny after 2008-2009 recession.
5.4 GENDER-BASED ROLES AND RESPONSIBILITIES
Gender-based roles and responsibilities in the family have been identified as the root cause of labour market
participation differentials between men and women (Becker, 1985; Antecol, 2000; England, 2005; Fortin, 2005; Baker
and Jacobsen, 2007). However, more recently the gender-based differences in the labour market have been washing
out (The World Bank, 2012).
Figure 18 demonstrates gender differences in labour force participation within the London ER. Men were more likely
to participate to the labour market than women, by 11.1% in 2006 and by 8.4% in 2016. The labour force participation
rate gap decreased by 2.7% between 2006 and 2016; an encouraging trend towards equality.
PAGE 23
Between 2006 and 2016, within the London ER, men reduced their labour force participation rate by 4.8% whereas
women diminished their labour force participation only by 2.1%.
Source : One Hub, Census custom tables, Census 2016 – Table T3_POR and Census 2006 – Table EO1246 T2_3
Figure 18
Source : Statistics Canada. Table 14-10-0095-01
Figure 19
67.973.6
62.564.468.8
60.4
0
10
20
30
40
50
60
70
80
Total-sex Male Female
Participation rate by gender - London ER(%)
2006 2016
R² = 0.807-10.0
-8.0
-6.0
-4.0
-2.0
0.0
2.0
4.0
Jan-06 Jan-07 Jan-08 Jan-09 Jan-10 Jan-11 Jan-12 Jan-13 Jan-14 Jan-15 Jan-16 Jan-17 Jan-18
London CMA - Change in gender cohort share of participating population relative to January 2006
(%) (three-month moving average, unadjusted for seasonality)
Change in participation rate Both sexes Change in share of participation rate Males
Change in share of participation rate Females Poly. (Change in participation rate Both sexes)
Fin
anci
al c
risi
s2
00
8-2
00
9
PAGE 24
To gain more insight into the gender differentials in the labour force participation rate within the London ER after
2016, a similar decomposition of the labour force participation rate as was done by age group is proposed here but
by gender. Equation (3) and (4) shows the change in the share of labour participation rate by gender relative to the
year 2006 and indices i and j can indicate any year succeeding afterwards.
𝑝𝑒𝑟𝑡𝑖𝑐𝑖𝑝𝑎𝑡𝑖𝑜𝑛 𝑟𝑎𝑡𝑒( 15 +) = 𝑙𝑎𝑏𝑜𝑢𝑟 𝑓𝑜𝑟𝑐𝑒 (15+)
𝑝𝑜𝑝𝑢𝑙𝑎𝑡𝑖𝑜𝑛 (15+)x 100 =
𝑙𝑎𝑏𝑜𝑢𝑟 𝑓𝑜𝑟𝑐𝑒 (𝑚𝑎𝑙𝑒𝑠) + 𝑙𝑎𝑏𝑜𝑢𝑟 𝑓𝑜𝑟𝑐𝑒 (𝑓𝑒𝑚𝑎𝑙𝑒𝑠)
𝑝𝑜𝑝𝑢𝑙𝑎𝑡𝑖𝑜𝑛 (15+) 𝑥100
=𝑙𝑎𝑏𝑜𝑢𝑟 𝑓𝑜𝑟𝑐𝑒 (𝑚𝑎𝑙𝑒𝑠)
𝑝𝑜𝑝𝑢𝑙𝑎𝑡𝑖𝑜𝑛 (15+)𝑥100 +
𝑙𝑎𝑏𝑜𝑢𝑟 𝑓𝑜𝑟𝑐𝑒 (𝑓𝑒𝑚𝑎𝑙𝑒𝑠)
𝑝𝑜𝑝𝑢𝑙𝑎𝑡𝑖𝑜𝑛 (15+)𝑥 100 = % 𝑠ℎ𝑎𝑟𝑒 (𝑚𝑎𝑙𝑒𝑠) + % 𝑠ℎ𝑎𝑟𝑒 (𝑓𝑒𝑚𝑎𝑙𝑒𝑠) (3)
∆𝐽𝑎𝑛,2006𝑝𝑎𝑟𝑡𝑖𝑐𝑖𝑝𝑎𝑡𝑖𝑜𝑛 𝑟𝑎𝑡𝑒 (15 +) = 𝑝𝑎𝑟𝑡𝑖𝑐𝑖𝑝𝑎𝑡𝑖𝑜𝑛 𝑟𝑎𝑡𝑒 (15+)𝐾,20𝑖𝑗 − 𝑝𝑎𝑟𝑡𝑖𝑐𝑝𝑎𝑡𝑖𝑜𝑛 𝑟𝑎𝑡𝑒(15 +)𝐽𝑎𝑛,2006 =
% 𝑠ℎ𝑎𝑟𝑒 (𝑚𝑎𝑙𝑒𝑠)𝑘,20𝑖𝑗 + % 𝑠ℎ𝑎𝑟𝑒(𝑓𝑒𝑚𝑎𝑙𝑒𝑠)𝐾,20𝑖𝑗 − % 𝑠ℎ𝑎𝑟𝑒 (𝑚𝑎𝑙𝑒𝑠)𝐽𝑎𝑛,2006 − % 𝑠ℎ𝑎𝑟𝑒 (𝑓𝑒𝑚𝑎𝑙𝑒𝑠)𝐽𝑎𝑛,2006 =
(% 𝑠ℎ𝑎𝑟𝑒 (𝑚𝑎𝑙𝑒𝑠)𝐾,20𝑖𝑗 − % 𝑠ℎ𝑎𝑟𝑒 (𝑚𝑎𝑙𝑒𝑠)𝐽𝑎𝑛,2006) + (% 𝑠ℎ𝑎𝑟𝑒 (𝑓𝑒𝑚𝑎𝑙𝑒𝑠)𝑘,20𝑖𝑗 − % 𝑠ℎ𝑎𝑟𝑒 (𝑓𝑒𝑚𝑎𝑙𝑒𝑠)𝐽𝑎𝑛,2006 =
∆𝐽𝑎𝑛,2006 % 𝑠ℎ𝑎𝑟𝑒 (𝑚𝑎𝑙𝑒𝑠) + ∆𝐽𝑎𝑛,2006% 𝑠ℎ𝑎𝑟𝑒 (𝑓𝑒𝑚𝑎𝑙𝑒𝑠) (4)
A similar decomposition can be achieved using labour force participation rate monthly data for the London CMA,
using January 2006 as the reference point and K representing the months of the year. London CMA is a close surrogate
geography for the London ER. The symbol stands for the change (difference) relative to the reference point. Figure
19 illustrates the monthly change in gender cohort share of participating population to the London CMA labour
market relative to January 2006. One can identify the overall diminishing trend of the labour force participation rate
after 2006 in London CMA. The drop in the participation rate started with the entry into the economic recession at
the end of 2008 and beginning of 2009. Men’s share of the labour participation rate has been changing more
dramatically than women’s share of the labour participation rate. Moreover, the volatility of the men’s share
contribution to the labour force participation rate is larger than women’s share contribution. Women’s share
contribution started to dip completely in the negative domain only after the second part of 2014 while men’s share
contribution to the labour force participation rate in the London ER started diminishing immediately after 2008.
The cross tabulation by gender and age presented in Figure 20 shows that the labour force participation rate
diminished between 2006 and 2016 in the London ER for both men and women for all age groups excepting for the
mature age cohort. When the mature age cohort is divided in two subgroups, the “55 to 64 years old” and the “65 years
old and over” interesting results are revealed. Specifically, in the case of the “55 to 64 years old” the men’s group suffered
a slight reduction in the labour force participation rate of 1.2% while the women’s group increased their labour force
participation rate by 4.7%. In the case of the “65 years old and over,” men increased their labour force participation
rate by 3.5% and women increased their workforce participation rate by 3.6% between 2006 and 2016.
Unfortunately, the cross tabulation by gender and educational level presented in Figure 21 reveals that both men and
women cohorts at any educational level suffered a reduction in the labour force participation rate between 2006 and
2016 in the London ER. However, the men suffered larger reductions in labour force participation rate between 2006
and 2016 across various educational groups, somewhere between 4.5% for the “apprenticeship or trades certificate or
diploma” cohort and 7.8% for the “no certificate, diploma or degree” cohort. On the other hand, women had incurred
reductions in labour force participation rate between 2006 and 2016 across all education level groups somewhere
between 1.8% for “university certificate or degree (bachelor and above)” and 7.7% for “high school certificate or
equivalent.”
PAGE 25
Source : One Hub, Census custom tables, Census 2016 – Table T3_POR and Census 2006 – Table EO1246 T2_3
Figure 20
Source : One Hub, Census custom tables, Census 2016 – Table T3_POR and Census 2006 – Table EO1246 T2_3
Figure 21
70.2
90.8
72.1
17.2
43.6
64.3
88.7
70.9
20.2
43.9
70.4
81.1
55.6
7
28.1
64.9
81.1
60.3
10.6
32.6
0
10
20
30
40
50
60
70
80
90
100
15 to 24 years 25 to 54 years 55 to 64 years 65 years and over 55 years and over
Participation rate by gender and age groups - London ER(%)
Males 2006 Males 2016 Females 2006 Females 2016
54.9
79.470.9
85.476.5
80.7
47.1
71.866.4
80.3
69.875.7
36.5
63.9 64
75.3
63.6
77.7
31
56.2 57.1
72.5
57.8
75.9
0
10
20
30
40
50
60
70
80
90
No certificate,diploma or degree
High schoolcertificate or
equivalent
Apprenticeshipor trades
certificate ordiploma
College, CEGEPor other non-
universitycertificate or
diploma
Universitycertificate or
diploma belowbachelor level
Universitycertificate or
degree (bachelorand obove)
Participation rate by gender and education level - London ER (%)
Male 2006 Male 2016 Female 2006 Female 2016
PAGE 26
Source : One Hub, Census custom tables, Census 2016 – Table T3_POR and Census 2006 – Table EO1246 T2_3
Figure 22
Source : One Hub, Census custom tables, Census 2016 – Table T3_POR and Census 2006 – Table EO1246 T2_3
Figure 23
0102030405060708090
100
2006 2016 2006 2016 2006 2016 2006 2016 2006 2016 2006 2016
No certificate,diploma or degree
High schoolcertificate or
equivalent
Apprenticeshipor trades
certificate ordiploma
College, CEGEPor other non-
universitycertificate or
diploma
Universitycertificate or
diploma belowbachelor level
Universitycertificate or
degree (bachelorand above)
Males participation rates by education and age - London ER(%)
25 to 54 years 55 to 64 years 65 years and over
0102030405060708090
100
2006 2016 2006 2016 2006 2016 2006 2016 2006 2016 2006 2016
No certificate,diploma or degree
High schoolcertificate or
equivalent
Apprenticeshipor trades
certificate ordiploma
College, CEGEPor other non-
universitycertificate or
diploma
Universitycertificate or
diploma belowbachelor level
Universitycertificate or
degree (bachelorand above)
Females participation rates by age and education - London ER(%)
25 to 54 years 55 to 64 years 65 years and over
PAGE 27
The cross tabulation of gender by education and age presented in Figures 22 and 23 provides more insight about the
changes in labour force participation rate between 2006 and 2016 in the London ER. If one excludes the youth
cohort from this comparison since both genders exhibited similar changes regarding the labour force participation
rate between 2006 and 2016 (Figure 20), he or she would observe that for men, the “65 years old and over” increased
their labour force participation rate across all educational level groups (Figure 22). Furthermore, increases in the
labour force participation rate between 2006 and 2016 for men were observed for the prime age (25 to 54 years old)
with “apprenticeship or trades certificate or diploma” and for the “55 to 64 years old” with “university certificate or
degree (bachelor and above).” In the case of women “55 to 64 years old” and “65 years old and over” there were
increases in labour force participation rate between 2006 and 2016 in the London ER across all educational levels
(Figure 23). Also, for the prime age (25 to 54 years old) women with “college, CEGEP or other non-university
certificate or diploma” and “university certificate or degree (bachelor and above)” there was an increase in the labour
force participation rate within the earlier announced time frame.
CONCLUSIONS
Several lessons were retained from the gender-based analysis of the labour force participation rate:
Overall, men had a higher labour force participation rate than women in the London ER. In the aftermath of the
financial crisis 2008-2009, men had reduced their labour force participation more than women. Men started
reducing their labour market participation at the beginning of the recession 2008-2009 while women in the London
ER, started reducing their participation starting in 2014. These results in the London ER can be associated with the
loss of manufacturing jobs during the recession 2008-2009 for men and the loss of retail jobs during the food
manufacturing and retail sectors consolidation (Strauss, 2013; BDO Canada, 2016) that started in 2013-2014 where
women were more likely working than men.
Introducing age as a variable in this analytical exercise helps identify differential results. Women “55 to 64 years old”
increased their labour force participation rate between 2006 and 2016. Both cohorts, males and females, “65 years old
and over” increased their labour force participation within the same time horizon.
All educational cohorts exhibited a loss in labour force participation between 2006 and 2016 in the London ER, both
for men and women.
While the overall trend of labour force participation in the London ER between 2006 and 2016 was downwards, the
“university certificate or degree below bachelor degree,” “men,” “55 to 64 years old” increased their participation rate
as well as the “high school certificate or equivalent,” “college, CEGEP or other non-university certificate or diploma,”
and “university certificate or degree (bachelor and above),” “males,” “65 years old and over”.
Both mature age groups of “females,” “55 to 64 years old” and “65 years old and over” have increased their
participation between 2006 and 2016 for all educational levels.
These results suggest a reactive behaviour of the mature age cohort to the uncertainty of the economic environment
developed after the financial crisis 2008-2009, which reduced the number of work opportunities for the youth
and/or mature age cohort, considering the tight labour market generated during the economic recovery.
5.5 TECHNOLOGICAL REVOLUTION (AUTOMATION, BIG DATA, MACHINE LEARNING & AI)
Tuzemen and Willis (2013) captured the latest effects of technology on the labour market. Their observation was
that the share of mid-skill jobs in the United States has fallen sharply in the past few decades. The explanatory
factors for this result include the advancement of technology, outsourcing jobs overseas and the contractions that
PAGE 28
occurred in manufacturing. According to the authors, the mid-skill occupations include sales, office and
administration, production, construction, extraction installation, maintenance and repair, transportation, and
material moving. A more precise way of defining these categories of occupations is: “workers in middle-skill
occupations typically perform routine tasks that are procedural and rule-based. Therefore, these occupations are
classified as “routine” occupations. The tasks performed in many of these occupations have become automated by
computers and machines” (Tuzemen & Willis, 2013, p.8).
The definition of medium-skilled, medium paid occupations is not very precise (Burleton, 2013, February). In the
U.S. literature the agreement is that this group of occupations requires some formal education beyond high school,
but less than 4-year bachelor’s degree at a university or college.
With the advent of advanced big data, machine learning and Artificial Intelligence (AI) this polarization
phenomenon is likely going to affect the service sectors as well. As a result, the job polarization will become more
pronounced than before. Because of the disappearance of a wide range of mid-skill occupations, workers have only
two choices: either to get more education and migrate towards the high-skill jobs, or to stay the same, but accept
low-skill jobs. These options will lead to a higher concentration of jobs at the two ends of the skill level spectrum.
Further, the job polarization affects labour force participation. The need for more education to transition from
medium-skill jobs to high-skill jobs will temporarily separate some people from the labour force, therefore lowering
the participation rate. On the other hand, among those accepting, or being forced to accept, low-skill jobs there will
be people unsatisfied with their new employment due to their perception of under-employment. Some will adapt to
this new situation whereas others will drift into discouragement and frequently exit-entry of the labour market,
which will lower the labour force participation rate overall.
Figure 24 illustrates the Internet job postings by skill level in the London ER. Some degree of job polarization is
observed in the regional labour market demand among the postings that allow skill level classification. In the
London ER, a larger number of job postings are requiring skill levels C and A than those requiring skill level B.
Source: MDB Insight – VicinityJobs.com hiring demand analytics suite
Figure 24
8819
7751
9900
2815
7782
6318
7608
2989
0 2000 4000 6000 8000 10000 12000
A: University Education
B: College or Vocational Education or ApprenticeshipTraining
C: Secondary School and/or Occupation-SpecificTraining
D: On-the-job Training or No Formal EducationRequired
Number of the Internet Job Postings in the London ER by Skill Level - London ER
01Jan17 - 31Dec17 Postings 01Jan18 - 31Dec18 Postings
PAGE 29
In a technical note MDB Insight (n.d.) estimated that about 78% of all job vacancies are advertised on corporate
websites and 76% of all vacancies are advertised through job boards. Based on these statistics, MDB Insight
estimates that it captures about three quarters of the total job vacancies within a specific geography, which confirms
the robustness of these results.
Although Burleton (2013) suggests that in Canada, the labour market followed a uni-polarization (high-skill jobs)
trend, our local data supports the bi-polar pattern, with increases in demand for both low- and high-skill jobs and
the vanishing of middle-skill jobs. However, his observation that “Canada has registered a considerably less
pronounced swing in jobs from the middle to the high end of the skills spectrum” appears to be valid in the context
of the local data (Burleton, 2013, p.1).
CONCLUSIONS
Due to the technological revolution involving automation, big data, machine learning and AI, the labour market
suffers a polarization of jobs at both ends of the skill-level spectrum – low-skill jobs and high-skill jobs. Because of this
labour market change, the participation rate is more likely to drop. Education required for skills’ upgrading and/or
the discouragement due to underemployment are the forces driving a lower labour force participation.
5.6 EMPLOYMENT BARRIERS FACED BY CERTAIN CATEGORIES OF POPULATION
The working age population in the London ER is diverse. The total population of persons over 15 years (working
age) in the London ER was 534,260 in 2016, out of which 1.4% were “Francophone population”, 2.1% were “Aboriginal
identity population”, 11.8% were “visible minority” population and 84.6% were “others.” This diversity has
implications on the labour market experiences lived by these categories of populations.
The participation rate and overall employment outcomes for the Aboriginal population, visible minority and the
Francophone population has been low compared to the total population in Canada. This trend continues to play out
in the London ER as well, as illustrated in Figure 25. The Francophone and visible minority populations are
participating at a rate about 4% lower than the general population in the London ER while the Aboriginal
population labour force participation rate is close to the general population (we should sight a reason as to why the
PR is higher with this group).
Different factors may contribute to the low participation rate of these groups, which may include lack of adequate
information about available employment opportunities and assistance, limited number of available jobs that would
provide competitive advantage relative to the skills and knowledge specific to the self-identified group, or a range of
systemic barriers (such as discrimination) with unintended consequences. Also, it is worth noting that individuals
in the self-identified population groups may spend more time being unemployed than the rest of the population
and the resulting discouragement may contribute to their low participation rates.
PAGE 30
Source : One Hub, Census custom tables, Census 2016 – Table T5_POR
Figure 25
Figure 26 shows that there is a large gap in labour force participation between men and women in all self-identified
groups, with the gap being most noticeable within the visible minority population. When compared to labour force
participation rate of the total population 15+, both genders in these self-identified groups are lagging, with females
participating roughly 10% less than their male counterparts.
Source : One Hub, Census custom tables, Census 2016 – Table T5_POR
Figure 26
64.4
60.8
62.2
59.9
57
58
59
60
61
62
63
64
65
Total Population 15+ Visible minoritypopulation
Aboriginal identitypopulation
Francophone population
Participation rate by self-identified status in 2016(%)
68.8
65.6 65.2
62.7
60.4
56.1
59.9
57.8
50
52
54
56
58
60
62
64
66
68
70
Total Population 15+ Visible minoritypopulation
Aboriginal identitypopulation
Francophone population
Participation rate by self-identified status and gender in 2016 -London ER
(%)
Male Female
PAGE 31
Source : One Hub, Census custom tables, Census 2016 – Table T5_POR
Figure 27
When comparing the participation rates of self-identified groups by gender between the province and the London ER,
the contrast is significant; both male and female labour force participation rates in the London ER being at least 4.6%
less than the provincial rate, see Figure 27.
Source : One Hub, Census custom tables, Census 2016 – Table T5_POR
Figure 28
69.170.3
64.365.9
60.6 60.759.6
58.7
50
55
60
65
70
75
Total - Population 15 yearsand over
Visible minority population Aboriginal identitypopulation
Francophone population
Participation rate by self-identified status and gender in 2016 -Ontario
(%)
Male Female
64.6
84.8
37.9
65.4
15.0
44.6
74.6
43.1
65.4
16.5
55.9
73.9
40.6
55.2
18.9
61.6
87.9
33.1
60.6
14.3
0
20
40
60
80
100
15 to 24 years 25 to 54 years 55 years and above 55 to 64 years 65 years and over
Participation rate by age and self-identified status 2016 - London ER(%)
Total Population 15+ Visible minority population
Aboriginal identity population Francophone population
PAGE 32
Source : One Hub, Census custom tables, Census 2016 – Table T5_POR
Figure 29
The participation rate differs across age-groups and the highest participation rate is usually observed values for the
prime age group (25 to 54 years). Although this remains the case for all the population groups displayed in Figure 28,
it is important to note that the visible minority and the Aboriginal populations have a significantly lower
participation rate compared to others, especially compared to the prime age. The Francophone population shows a
remarkable participation rate for the prime age (25 to 54 years), with 3.1% more than the general population and 13%
above the other two population groups.
The mature age (55 to 64 years) group of the Aboriginal and Francophone working populations were not
participating at their full potential.
Contrasting the provincial and London ER results (Figures 28 and 29), it could be observed that the labour force
participation rate for Ontario’s prime age group is only marginally higher than in the London ER (0.50%), but for
the self-identified population groups the margin is far higher. While the participation rate for the minority
population in Ontario was at 81.8% in 2016, the same population group in the London ER registered 7.2% lower.
Although the participation rate of the Francophone population in the same age group was the same for the province
and the London ER, the Aboriginal population in the London ER experienced a labour force participation rate
slightly lower than in Ontario.
60.2
85.3
38.4
65.5
15.0
48.2
81.8
41.6
67.2
14.8
55.4
75.8
38.2
54.4
15.3
65.9
87.9
33.0
59.0
12.1
0
10
20
30
40
50
60
70
80
90
100
15 to 24 years 25 to 54 years 55 years and over 55 to 64 years 65 years and over
Participation rate by age and self-identified status in 2016 - Ontario (%)
Total population 15+ Visible minority population
Aboriginal identity population Francophone population
PAGE 33
Source : One Hub, Census custom tables, Census 2016 – Table T5_POR
Figure 30
Source : One Hub, Census custom tables, Census 2016 – Table T5_POR
Figure 31
39.2
64.0 63.775.8
63.275.8
33.5
55.5
71.9
74.4
61.572.5
37.8
65.9 60.8
77.668.4
82.7
28.1
59.748.2
70.461.1
77.8
0.010.020.030.040.050.060.070.080.090.0
No certificate,diploma or
degree
High schoolcertificate orequivalent
Apprenticeshipor trades
certificate ordiploma
College,CEGEP or othernon-universitycertificate or
diploma
Universitycertificate or
diploma belowbachelor level
Universitycertificate or
degree (bachelorand above)
Participation rate by self-identified status and educational attainment in 2016 - London ER
(%)
Total Population 15+ Visible minority population
Aboriginal identity population Francophone population
35.8
62.7
63.4
75.0
67.2
78.1
34.359.0
70.676.4
71.178.8
36.8
66.7 65.4
76.1
68.8
83.0
29.7
60.7 59.6
74.4
61.3
78.4
0.010.020.030.040.050.060.070.080.090.0
No certificate,diploma or degree
High schooldiploma orequivalent
Apprenticeshipor trades certificate
or diploma
College, CEGEPor other non-
universitycertificate or
diploma
Universitycertificate or
diploma belowbachelor level
Universitycertificate or
degree (bachelorand above)
Participation rate by self-identified status and educational attainment in 2016 - Ontario
(%)
Total Population 15+ Visible minority population
Aboriginal identity population Francophone population
PAGE 34
As observed in an earlier section, individuals with a “University degree or above” were participating in the labour
force at the highest rate. It is interesting to note that within this cohort, the individuals who self-identified as
belonging to Aboriginal population and Francophone population were participating to the labour force more than
the “total population 15+”. A low education level is generally associated with low employment outcomes, and as
illustrated in Figures 30 and 31, the general working population and self-identified population recorded a less than
average labour force participation rate for individuals with “No certificate, diploma or degree”. However, it is worth
observing that the Aboriginal population individuals exhibited the highest labour force participation rate among the
“No certificate, diploma or degree” category, in the London ER and in Ontario. Individuals among the Francophone
population with “Apprenticeship or trades certificate or diploma” recorded a low participation rate compared to
other categories, in the London ER and in Ontario.
In Figure 31, it could be observed that across all major educational attainment categories, individuals above 15 years
generally had a higher participation rate in Ontario than in the London ER. The contrast is particularly notable
among the following categories: (i) visible minority population with a “High school diploma or equivalent,”
“University certificate or diploma below bachelor level”, and “University certificate or degree (bachelor and above);” (ii)
Francophone population with a “College, CEGEP or other non-university certificate or diploma;” (iii) Aboriginal
population with “Apprenticeship or trades certificate or diploma.”
Looking specifically at the immigrant population in the London ER (Figure 32), one would observe that most
immigrants across different age groups are participating in the labour market at a rate lower than the general
working age population, except for immigrant mature age workers “55 to 64 years old” who are participating at the
same rate as the general working population (15+). The immigrant youth population is participating at a distinctly
lower rate than the general population of youth with an almost 14% difference. The total overall working population
is participating at a rate almost 11% higher than the immigrant population. These results support the argument that
the immigrant population in the London ER faces more barriers to entering the labour market than the overall
population in the region.
Source : One Hub, Census custom tables, Census 2016 – Table T25_MTCU and Table T_19_POR
Figure 32
64.6
84.8
37.9
65.4
15.0
64.4
50.7
78.5
31.7
65.4
12.6
53.7
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
90.0
15-24 years 25-54 years 55 years andabove
55 to 64 years 65 years andabove
AggragateParticipation Rate
Participation rate by age group in 2016, immigrant vs. overall population (15+)
(%)
Overall 15+ population Immigrant population 15+
PAGE 35
Source : One Hub, Census custom tables, Census 2016 – Table T20_POR
Figure 33
As noted earlier in the study, the labour force participation rate of the working age population (15+) in the London
ER (LER) followed a decreasing trend in the past fifteen years. Unfortunately, although the labour force
participation rate of the immigrants in the London ER is lower than of the general population. Its course in time also
follows a decreasing trend. A comparison of the labour force participation rates of the immigrants in the London ER
by period of immigration shows the downward trend over time, indifferent of the period of immigration (Figure 33).
The results presented in Figure 33 suggests that the number of years an immigrant spends in Canada determines his
or her labour force participation rate. The participation rate of immigrants in the LER is well below the provincial
labour force participation rate of the same population. It should be noted that immigrants who arrived between 2011
and 2016 had lower labour force participation rates than immigrants who arrived between 2001 and 2006. The drop
in labour force participation rates of the immigrants in LER between 2016 and 2006 was about 13% whereas at the
provincial level the difference was only of 3.2%. One could conclude that more recent immigrants specifically in 2016
were not engaging with the local labour force at the same rate as 10 years ago maybe experiencing more barriers to
entry. This could have happened due to the rising expectations of the Canadian employers regarding education and
skills and the difficulties encountered by immigrants with assessing their education, the rising cost of getting into
regulated professions, or the rising costs of pursuing more education in general. The longer career pathways
encountered by immigrants generates discouragement and lower labour force participation rates than otherwise.
65.2
69.7
55.1
64.255
45.1
70.5
68.6
67 66.4 64.6
54.9
0
10
20
30
40
50
60
70
80
2001 2002 2003 2004 2005 2006
Paricipation rate of the immigrants that arrived between
2001 and 2006 (%)
LER Ontario
5459.6
54
59.552.4
31.7
65.3 63.159.7
63.9 63.9
51.7
0
10
20
30
40
50
60
70
2011 2012 2013 2014 2015 2016
Paricipation rate of the immigrants that arrived
between 2011 and 2016 (%)
LER Ontario
PAGE 36
Source : One Hub, Census custom tables, Census 2016 – Table T20_POR
Figure 34
As noted with the working age population in the London ER, immigrant labour force participation rate is positively
correlated with the educational attainment level: the higher is the educational attainment, the higher is the labour
force participation rate. Between 2006 and 2016, there has been a significant drop in the labour force participation
rates of immigrants in the London ER across all education levels as seen in Figure 34. These results could be caused
by the same labour market change noted earlier, the increasing preference of employers for certifications and
degrees which more recently, are dominating the job descriptions.
CONCLUSIONS
Working age population in the London ER is diverse, including visible minorities, Aboriginal people, Francophone
individuals, immigrants and other population groups. This diversity generates a variety of labour market experiences,
which in the past have been associated with various levels of access to the labour market. Looking specifically in the
London ER, several facts have been identified:
The participation rate for the self-identified as “visible minority,” “Aboriginal,” and “Francophone” groups was lower
than the labour force participation rate exhibited by the overall population 15+ years old. Overall, the Francophone
group displayed the lowest values of labour force participation rate among all groups compared.
31.5
51.3
48.5
62.9
57.7
70.9
35.8
57.4
57.2
67
63
74.9
0 10 20 30 40 50 60 70 80
No certificate, diploma or degree
High school certificate or equivalent
Apprenticeship or trades certificate or diploma
College, CEGEP or other non-university certificate ordiploma
University certificate or diploma below bachelor level
University certificate or degree
Immigrants' participation rate by highest education attained -London ER
(%)
2006 2016
PAGE 37
When the gender differences across the self-identified status groups and general population was investigated, it was
observed that in 2016 males displayed a higher propensity for labour force participation than females. However, when
comparing the London ER and Ontario results, it could be noted there was a significantly lower (about 5%) labour
force participation rate of both genders in the London ER for the visible minority population. Slightly lower
participation rates were exhibited by both gender groups of the Francophone population in the London ER than in
Ontario. Therefore, visible minority and Francophone self-identified individuals of both genders experienced more
barriers to entering the London ER labour market than in the province overall.
Age is an important factor that creates behavioural differences among the populations compared here. In an earlier
section it was observed that the prime age (25 to 54 years) cohort exhibits the highest participation rate in both the
London ER and Ontario. Within this age cohort, the visible minority and Aboriginal individuals in the London ER
experienced significantly lower labour force participation rates than in Ontario. In contrast, the Francophone
individuals of prime age in the London ER and Ontario exhibited highest participation rates than any other self-
identified group. Provincially, the Francophone youth individuals exhibited higher participation rates than any other
self-identified group within the same age cohort.
The individuals with higher educational attainment across all self-identified groups exhibited higher labour force
participation rates in 2016 than those with lower educational attainment, in the London ER and/or Ontario. The
“university certificate or degree (bachelor and above)” educated individuals, Aboriginal and/or Francophone in the
London ER and/or Ontario experienced the highest labour force participation rates. In the London ER, in 2016, the
Aboriginal individuals with “College, CEGEP or non-university certificate or diploma” had higher labour force
participation rates than any individuals from other self-identified groups or the general population.
The immigrant population in the London ER is participating in the labour market at lower rates than the general
population 15+. High concern is associated with the youth and prime age immigrant groups in the London ER because
they exhibited significantly lower labour market participation rates than the general population 15+. The decreasing
trend of labour force participation characterizes the immigrant population in the London ER at all levels of education.
The additional barriers to entering the labour force encountered by immigrants through the social and cultural
integration process contributes to their reduced labour market activity.
5.7 MOBILITY OF THE LABOUR FORCE
There is an increasing amount of anecdotal evidence regarding the population migration from the Greater Toronto
Area (GTA) towards less expensive but attractive locations in Southwestern Ontario. London is listed among the top
10 locations in Southwestern Ontario advertising for retirement. In the balancing act of living comfortably during
retirement with accumulated resources, it is logical for people to search for an affordable location that offers many of
the services provided by a big city. Local press (Daniszewski 2015, 2016) has been pointing to this phenomenon for a
while. In the same time the skyrocketing prices of housing in the GTA would favour labour force migration towards
more affordable places that offer equivalent work opportunities. This population migration could have important and
unforeseen implications upon the labour force and labour market indicators. Although these arguments are logical,
they require further investigation to support their validity. Equation 5 posted below provides a decomposition of the
total migration in the London ER.
𝑡𝑜𝑡𝑎𝑙 𝑚𝑖𝑔𝑟𝑎𝑡𝑖𝑜𝑛
= 𝑖𝑚𝑚𝑖𝑔𝑟𝑎𝑛𝑡𝑠 − 𝑒𝑚𝑖𝑔𝑟𝑎𝑛𝑡𝑠 + 𝑟𝑒𝑡𝑢𝑟𝑛𝑖𝑛𝑔 𝑒𝑚𝑖𝑔𝑟𝑎𝑛𝑡𝑠 − 𝑛𝑒𝑡 𝑡𝑒𝑚𝑝𝑜𝑟𝑎𝑟𝑦 𝑒𝑚𝑖𝑔𝑟𝑎𝑡𝑖𝑜𝑛
+𝑛𝑒𝑡 𝑖𝑛𝑡𝑒𝑟𝑝𝑟𝑜𝑣𝑖𝑛𝑐𝑖𝑎𝑙 𝑚𝑖𝑔𝑟𝑎𝑡𝑖𝑜𝑛 + 𝑛𝑒𝑡 𝑖𝑛𝑡𝑟𝑎𝑝𝑟𝑜𝑣𝑖𝑛𝑐𝑖𝑎𝑙 𝑚𝑖𝑔𝑟𝑎𝑡𝑖𝑜𝑛 + 𝑛𝑒𝑡 𝑛𝑜𝑛𝑝𝑒𝑟𝑚𝑎𝑛𝑒𝑛𝑡 𝑟𝑒𝑠𝑖𝑑𝑒𝑛𝑡𝑠 (5)
PAGE 38
A close look at each component allows one to gain more insight on migration. Figure 35 illustrates the total migration
in the London ER by age group. Across time one would see some variation in the proportions of total migration (net)
of working age population (15 years and over) by age group: youth, prime age and mature age. In 2016/2017, the
migration to the London ER of mature age people (55 years and over) was representing only 16.75% of the total working
age net migration into the London ER. On the other hand, the youth group of people (15 to 24 years old) migrating to
the London ER in 2016/2017 was the largest (43.76%) followed closely by the prime age group representing 39.49% of
the total working age population migrating in the London ER in 206/2017.
Source: Statistics Canada table 17-10-0082-01
Figure 35
These results dispel the hypothesis suggesting that the total migration to the London ER is dominated by the
mature age group. Looking at the components of the total migration as decomposed in equation 5 would provide
more insight on the nature of the total migration.
849 1012
884
1301
11351616 1003 1027 1097 2087
3090
384 634
108
1120 2881234
436 499 630 24032789
361 413174 356
440520
604 603 5921017 1183
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
2006 / 2007
2007 / 2008
2008 / 2009
2009 / 2010
2010 / 2011
2011 / 2012
2012 / 2013
2013 / 2014
2014 / 2015
2015 / 2016
2016 / 2017
Working age net migration to the London ER by age(persons)
15 to 24 years 25 to 54 years 55 years and over
PAGE 39
Source: Statistics Canada table 17-10-0082-01
Figure 36
Source: Statistics Canada table 17-10-0082-01
Figure 37
Figure 36 shows a constant flow of working age immigrants coming into the London ER every year. In 2016/2017,
about 15% of them were in the mature age group (55 years and over), 66% were in the prime age group (25 to 54
years) and around 19% were in the youth group (15 to 24 years). The largest group of immigrants is in the prime age
491 562 489 475 406 429 402 332 409 436 376
1312 1478 1388 1633 1353 13311319 1175
1228 1553 1275
109 170 157 173 128 171 315 214 119 230 291
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
2006 /2007
2007 /2008
2008 /2009
2009 /2010
2010 /2011
2011 /2012
2012 /2013
2013 /2014
2014 /2015
2015 /2016
2016 /2017
Working age immigrant population by age group in the London ER(persons)
15 to 24 years 25 to 54 years 55 years and over
-168 -166 -143-111
-139-113 -162 -175 -133 -133 -133
-790 -682 -685 -645-555
-620 -636 -688 -652 -654 -656
-66 -87 -100 -125 -75 -108 -101 -99 -115 -107 -108-100%
-90%
-80%
-70%
-60%
-50%
-40%
-30%
-20%
-10%
0%
2006 /2007
2007 /2008
2008 /2009
2009 /2010
2010 /2011
2011 /2012
2012 /2013
2013 /2014
2014 /2015
2015 /2016
2016 /2017
Working age emigrants by age group - London ER(persons)
15 to 24 years 25 to 54 years 55 years and over
PAGE 40
group followed by the youth group, a distribution explained by the most common immigration category
“economic/skilled worker immigrant” which select immigrants based on a points’ score that factors in their skills as
well as their age.
The flow of people migrating out of the London ER is illustrated in Figure 37. The negative signs attached to the
numbers in Figure 37 symbolize the migration out of the region. A fair amount of people from the London ER are
emigrating. Prime age and youth groups had the largest proportions of this population. It would be helpful to know
their reasons for emigrating from the LER to see if there are any ways to reverse this flow out of the region.
Source: Statistics Canada table 17-10-0082-01
Figure 38
Looking at Figure 38, one would realize that slightly more than a half the number of emigrants are returning back to
the region, and the largest proportions of this population are in the prime and youth age groups. To complete the
picture of emigration, Figure 39 illustrates the net temporary emigration from the London ER, which displays again
negative values since temporarily these people are leaving the region. The numbers for this migration component
are small.
Figure 40 helps visualize the nature of the net intra-provincial migration of the working age population in the
London ER. About 34% of the net intra-provincial migration is from the mature age group while around 55% belong
to the prime age group and approximately 11% were part of the youth group. These results might support the idea of
a migration from GTA towards more affordable locations in Ontario, among which is London.
223 232 148 228 193 164 164 152 222 188 188
312 284237
313310 292 324 298 330 333 333
72 61 50 54 64 66 70 51 62 69 69
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
2006 /2007
2007 /2008
2008 /2009
2009 /2010
2010 /2011
2011 /2012
2012 /2013
2013 /2014
2014 /2015
2015 /2016
2016 /2017
Working age returning emigrants by age - London ER(persons)
15 to 24 years 25 to 54 years 55 years and over
PAGE 41
Source: Statistics Canada table 17-10-0082-01
Figure 39
Source: Statistics Canada table 17-10-0082-01
Figure 40
-37 -38 -32 -30 -35-20
-45 -39 -36 -32 -32
-201 -164 -193-192
-159-143
-160 -159 -149 -159 -159
-14 -18 -18-34 -19 -24 -17 -19 -19 -17 -17
-100%
-90%
-80%
-70%
-60%
-50%
-40%
-30%
-20%
-10%
0%
2006 /2007
2007 /2008
2008 /2009
2009 /2010
2010 /2011
2011 /2012
2012 /2013
2013 /2014
2014 /2015
2015 /2016
2016 /2017
Working age net temporary emigration - London ER(persons)
15 to 24 years 25 to 54 years 55 years and over
570668
499 497512
650
316334 353 281 281
44985
-21
463 137571
413 868 10311444 1444
361 323180
307321 469
446 567 656 904 904
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
2006 /2007
2007 /2008
2008 /2009
2009 /2010
2010 /2011
2011 /2012
2012 /2013
2013 /2014
2014 /2015
2015 /2016
2016 /2017
Net intra-provincial migration of working age population in the London ER
(persons)
15 to 24 years 25 to 54 years 55 years and over
PAGE 42
The net inter-provincial migration in the London ER (Figure 41) has been flowing-out of the region (negative signs)
between 2006/2007 until 2014/2015, most likely driven by the reduction of the manufacturing sector in the region
and the well-paid opportunities offered by the soaring oil/energy sectors in other provinces in Canada during the
indicated time frame. Once the oil and energy sectors have been affected by the steep drop in price (below $100 per
barrel) during 2014- 2015 (Dos Santos, 2014; Kilian, 2015), one will observe a reversal of the net interprovincial
migration towards a flow into the London ER.
Source: Statistics Canada table 17-10-0082-01
Figure 41
Source: Statistics Canada table 17-10-0082-01
Figure 42
-349 -445 -455 -318 -245 -327 -496 -465 -421 -103
17
-622-471 -713 -343 -241 -360 -693 -539 -487
134
507
-69 -12 -65 3 -39 -18 -67 -50-67
-13
71
-100%
-50%
0%
50%
100%
2006 /2007
2007 /2008
2008 /2009
2009 /2010
2010 /2011
2011 /2012
2012 /2013
2013 /2014
2014 /2015
2015 /2016
2016 /2017
Working age net interprovincial migration by age - London ER(persons)
15 to 24 years 25 to 54 years 55 years and over
119199
378 560
443
833 824888
703
14502393
-76
10495
-109
-557
163
-131
-456
-671
-248
45
-32
-24-30
-22
60
-36
-42
-61
-44
-49
-27
-20%
0%
20%
40%
60%
80%
100%
2006 /2007
2007 /2008
2008 /2009
2009 /2010
2010 /2011
2011 /2012
2012 /2013
2013 /2014
2014 /2015
2015 /2016
2016 /2017
Working age net non-permanent residents by age - London ER(persons)
15 to 24 years 25 to 54 years 55 years and over
PAGE 43
As illustrated in Figure 41, the net inter-provincial migration is dominated by people of prime age and youth age.
Finally, Figure 42 shows the flow of non-permanent residents into the London ER between 2006/2007 and 2016/2017.
The volatility of this component of migration is high and depends on the temporary work programs managed at the
federal level (the Temporary Foreign Worker Program, the International Mobility Program, other pilot programs).
Youth and prime age are the dominant groups for this migration component.
CONCLUSIONS
The prime age and youth age groups are leading the net total migration per year in the London ER. If adding across
years over a period of 10 years, for example, a sizeable number of mature age people have been migrating in and out
of the region.
The immigrants coming to the London ER every year are more likely to be of prime and youth age, considering that
the most common immigration reason is economic/skilled worker. People are selected based on a points’ merit
system that factors in education and skills as well as age. Younger people self-select into immigration.
A fair number of people migrate from the London ER to other parts of the world. About a half of those are
returning. Other are using this status temporarily. It would be very helpful to know their reasons for emigration to
identify ways to retain people locally.
The net intra-provincial migration component suggests that there is a fair proportion of mature age people moving
into the London ER from other parts of the province. This data cannot point out if they are specifically from the
GTA.
Some caution in interpreting this data is required since in the technical notes Statistics Canada informs the user that
“The estimates for most migration components are preliminary for 2016/2017, updated for 2013/2014 to 2015/2016 and
final up to 2012/2013. Exception: the estimates for immigrants, net inter- and intra-provincial migration are
preliminary for 2016/2017 and final up to 2015/2016.”
5.8 RETIREMENT AGE AND READINESS
In a seminal work Belanger, Carriere, and Sabourin (2016) reviewed the determinants of retirement age and labour
force participation of older workers. They grouped the determinants of the retirement age into ten domains covering
all three economic levels (micro, meso and macro): labour market, legislation, financial factors, social position,
domestic domain, human resource management, work-related factors, health, work availability and motivation.
The retirement age decision has immediate implications upon labour force participation and the sustainability of the
pension systems. An early retirement would reduce the labour force participation rates and increase the payment
burden of the pension systems. In contrast, a later retirement would increase the labour force participation rates and
reduce the costs of the pensions’ system. As illustrated in Figures 43 and 44, the average and median retirement age
in Canada is 64. Variation across different population groups is currently present. For example, the self-employed, stay
in the labour force longer, to retire on average at 68, while public sector employees retire earlier, on average at an age
around 62 (see Figure 43). The same idea is reinforced by the median retirement ages of various population groups
presented in Figure 44. On average, in Canada, males retire around 65 years of age while females retire around 63
years of age (Figure 45). These results are supported by the median values presented in Figure 46. Due to the economic
uncertainties born by the economic cycles, the retirement age varies to a certain degree with the status of the economy.
As Belanger, Carriere and Sabourin (2016) showed, average retirement age decreased for two decades after 1976, to
increase again after 1996, for both genders.
PAGE 44
Source: Statistics Canada, Table 14-10-0060-01
Figure 43
Source: Statistics Canada, Table 14-10-0060-01
Figure 44
Total, all retirees
Public sector employees
Private sector employees
Self-employed
54
56
58
60
62
64
66
68
70
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018
Average retirement age in Canada by class of worker(years)
Fin
anci
al c
risi
s 2
00
8-2
00
9
Total, all retirees
Public sector employees
Private sector employees
Self-employed
54
56
58
60
62
64
66
68
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018
Median retirement age in Canada by class of worker(years)
Fin
anci
al c
risi
s 2
00
8-2
00
9
PAGE 45
Source: Statistics Canada, Table 14-10-0060-01
Figure 45
Source: Statistics Canada, Table 14-10-0060-01
Figure 46
Males
Females
58
59
60
61
62
63
64
65
66
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018
Median retirement age in Canada by gender(years)
Fin
anci
al c
risi
s 2
00
8-2
009
Males
Females
58
59
60
61
62
63
64
65
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018
Average retirement age in Canada by gender(years)
Fin
anci
al c
risi
s 2
00
8-2
00
9
PAGE 46
It is worth noting the current increasing retirement age trend that dominates Figures 43 to 46, suggest that after the
financial crisis 2008-2009, many of the mature age cohort (55 years and over) didn’t feel ready to retire and decided
to stay longer in the labour force. As noted in an earlier section, Figures 9 and 11, the mature age cohort in London ER
increased its presence within the labour force in 2016 relative to 2006.
Under the current legislation the age of eligibility for the Canada Pension Plan (CPP) and the Old Age Security (OAS)
is 65 years old, which is a determinant for the retirement of many Canadians. However, public debates suggest that
the age of eligibility of OAS will be gradually increased from 65 to 67 by 2029 to ease the burden of the pension system,
while the age eligibility to collect CPP retirement benefits will remain 65 (Bélanger, Carrière & Sabourin, 2016).
The decision to retire and separate from the labour force is driven by multiple interacting factors. As suggested by
Bélanger, Carrière and Sabourin (2016), individual factors such as gender, age, education, marital and socio-economic
status interact with organizational and contextual factors such as legislation, labour force conditions, economy, and
others in determining the retirement age.
The results illustrated in Figures 43 to 46 and 9 and 11 suggest that after the 2008-2009 recession fewer Canadians in
the London Economic Region felt ready for retirement and consequently they decided to continue their labour force
participation, contributing to the increase of the retirement age the past 10-15 years.
CONCLUSIONS
The average and median retirement ages in Canada increased over the past twenty years, extending labour force
participation of the mature age cohort (55 years and over). This result can have positive and negative implications
upon the labour market. A positive effect is the resulting increased labour force participation rate overall. A negative
effect is the increased competition across age cohorts for the same job opportunities, with the youth cohort being
most affected.
Among the potential explanations are the economic shocks generated by the millennium scare of 2000 and the recession in 2008-2009, which might have induced a perceived non-readiness for retirement.
Variation among the average and median retirement ages was observed for various categories of workers (self-
employed, private sector and public sector) and genders.
5.9 ATTRACTION AND RETENTION EFFORTS OF LOCAL EMPLOYERS
In the Fall of 2018, the intensity of labour shortages reported by Canadian employers moved up to a near-record high
(50% more intense) according to the Business Outlook Survey conducted by Bank of Canada (2018, October 15), while
the percentage of firms confirming that they experienced labour shortages increased to about 40%. In this context,
attraction and retention efforts of local employers appears to be a key ingredient contributing to labour force
participation.
The most relevant action that local employers can take to attract and retain labour locally is to increase wages. Figure
47 shows a comparative view between London ER and Ontario on the median employment income by major
occupational groups. The employers in the London ER offered competitive wages for some occupational groups while
for others the employers in the region lag employers in the province overall. Specifically, local people employed in
occupations belonging to groups NOC 9 (occupations in manufacturing and utilities), NOC 7 (trades, transport and
equipment operators and other related occupations) and NOC 3 (health occupations) earned slightly higher incomes
than people overall in the province associated with the same occupational groups. By contrast, local people within
NOC groups 8 (natural resources, agriculture and related occupations), 6 (sales and service occupations), 5
PAGE 47
(occupations in art, culture, recreation and sport), 4 (occupations in education, law and social, community and
government services), 2 (natural and applied sciences and related occupations), 1 (business, finance and administration),
and 0 (management occupations) earned significantly lower income relative to their peers at the provincial level.
These income differences were reflected in the local labour force participation rates observed by occupational groups.
The London ER has mostly seen a reduction in participation rate in occupations where incomes are significantly lower
than in the province, as illustrated in an earlier section for NOCs 5, 6 and 8, see Figure 48.
Source : One Hub, Census custom tables, Census 2016 – Table T26_POR
Figure 47
$63,971
$42,947
$67,389
$47,477
$46,330
$17,312
$17,495
$40,029
$18,018
$37,300
$53,936
$40,613
$59,618
$48,927
$43,241
$14,199
$16,388
$42,322
$14,120
$41,886
0 10000 20000 30000 40000 50000 60000 70000 80000
0 Management occupations
1 Business, finance and administration occupations
2 Natural and applied sciences and relatedoccupations
3 Health occupations
4 Occupations in education, law and social,community and government services
5 Occupations in art, culture, recreation and sport
6 Sales and service occupations
7 Trades, transport and equipment operators andrelated occupations
8 Natural resources, agriculture and relatedproduction occupations
9 Occupations in manufacturing and utilities
Median employment income by occupation in 2016($)
London Economic Region Ontario
PAGE 48
Source: One Hub, Census 2016 Custom Table T26_POR_Boards_CD.ivt
Figure 48
Comparing employment income levels across occupational groups and neighboring workforce planning areas
(Figure 49) reveals that employment incomes earned in the London ER (Elgin-Middlesex-Oxford) in NOC groups 0,
1, 3, 6 and 8 were competitive relative to the employment income earned within the same occupational groups in
the neighboring workforce planning areas. Specifically, the employment income of people working in NOC 3 (health
occupations) in the London ER was the highest across the compared areas. Generally, in the London ER NOC
groups 5, 6 and 8 had the lowest median employment incomes across all geographies included in the chart.
Although the London ER did not rank the lowest in terms of employment incomes, it was average and it ranked below
the best-in-class across many occupational groups.
84.5
84.7
89.9
91.1
91.4
93.8
94.0
94.1
94.9
94.9
78 80 82 84 86 88 90 92 94 96
5 Occupations in art, culture, recreation and sport
8 Natural resources, agriculture and related productionoccupations
6 Sales and service occupations
1 Business, finance and administration occupations
4 Occupations in education, law and social, communityand government services
9 Occupations in manufacturing and utilities
2 Natural and applied sciences and related occupations
7 Trades, transport and equipment operators andrelated occupations
0 Management occupations
3 Health occupations
Labour force participation rate in the London ER by occupational group
(%)
PAGE 49
Source : One Hub, Census custom tables, Census 2016 – Table T26_POR
Figure 49
CONCLUSIONS
People in the London ER working in the occupational groups NOC 9 (occupations in manufacturing and utilities),
NOC 7 (trades, transport and equipment operators and related occupations) and NOC 3 (health occupations) earned
higher employment income than people in Ontario working in the same occupational groups. For the rest of the one-
digit NOC groups, people working in the London ER earned less employment income than people working in the
same occupational groups in Ontario overall.
The more severe drop in the labour force participation rate might be explained by these results and consequently the
London ER employers could easily change their attraction-retention strategies by offering equally or higher wages
than the average in Ontario, or than can be earned in the neighboring areas. Such a move would improve the labour
participation numbers locally, due to a potentially higher influx of labour towards the London ER.
0
10000
20000
30000
40000
50000
60000
70000
80000
90000
0 M
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t o
ccu
pat
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s
1 B
usi
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s, f
inan
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nd
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occ
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ns
2 N
atu
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and
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cien
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and
rela
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occ
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ns
3 H
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s
4 O
ccu
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s in
ed
uca
tio
n,
law
and
so
cial
, co
mm
un
ity
and
go
vern
men
t se
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es
5 O
ccu
pat
ion
s in
art
, cu
ltu
re,
recr
eati
on
an
d s
po
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6 S
ales
an
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ervi
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ccu
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s
7 T
rad
es,
tran
spo
rt a
nd
eq
uip
men
to
per
ato
rs a
nd
rel
ated
occ
up
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ns
8 N
atu
ral
reso
urc
es,
agri
cult
ure
an
dre
late
d p
rod
uct
ion
occ
up
atio
ns
9 O
ccu
pat
ion
s in
man
ufa
ctu
rin
gan
d u
tili
ties
Median employment income by occupation in 2016($)
Waterloo-Wellington-Dufferin Grand Erie Elgin-Middlesex-Oxford
Sarnia-Lambton Bruce-Grey-Huron-Perth Chatham-Kent
PAGE 50
5.10 UNCONVENTIONAL FACTORS: ENTRY, EXIT AND RESPITE
In a working paper, Coglianese (2018, February 28) advanced a somewhat unconventional explanation for the
declining labour force participation of prime age men. Specifically, the author suggests that the decline in labour force
participation of the U.S. prime age men comes from an “in-and-out” dynamic, which the author defines as men who
temporarily leave the labour force. Furthermore, it is suggested that most “in-and-outs” take an occasional short break
(respite) in between jobs. It is advanced that this behaviour is explained by a wealth effect generated by the partner’s
growing earnings, as well as by changes in household structure.
The labour force size in the London ER (Figure 50) between January 2006 and January 2019, unadjusted for seasonality,
displays quite a bit of variation. Seasonality is visually identifiable, with lows at the end/beginning of the year and
highs during mid-year. These variations suggest a lot of “in-and-out” labour force dynamics during the year.
Coglianese’s (2018, February 28) theory regarding this phenomenon focuses on prime age men, but it is proposed here
that the phenomenon is extended to other categories of population. Moreover, the present study advances that the
“in-and-out” dynamic depends on the type of employment (permanent vs. temporary). It is more likely that the “in-
and-out” labour force is specific to people engaged in temporary work than people engaged in permanent work. All
types of temporary employment (seasonal, term-contract, and other forms) involve entry into and exit from the labour
market, with potential respite periods most likely afforded by those who have other means to live on during these
pauses. Living with a partner that earns enough to sustain the household, and/or having other financial resources
(saving, investments, or inheritances) facilitates this behaviour.
In Canada, growth in temporary work has outpaced permanent employment since 1998/1999, see Figure 51. Temporary
employment includes seasonal, term or contract, casual, and other forms of non-permanent employment.
According to Hardy, Lovery and Patterson (2018, August 31), the share of people employed on a temporary basis rose
from 12.0% to 13.6% over this period (Jan 2006 – Jan 2018). Therefore, is it expected that the “entry-exit-respite”
behaviour will have stronger effects upon labour market participation?
Source: Statistics Canada, Table 14-10-0293-01
Figure 50
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18
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Labour force in the London ER, three month moving average, not adjusted for seasonality
(x 1000 persons)
Labour force Linear (Labour force)
PAGE 51
Hardy, Lovery and Patterson (2018, August 31) suggest that there is a lot of variation in the share of temporary
employment across the economic regions. Specifically, the values will lay somewhere between 9.5% for Stratford-
Bruce Peninsula, Ontario (the lowest value) and 28.1% for South Coast-Burin Peninsula and Notre Dame – Central
Bonavista Bay, Newfoundland and Labrador (the highest value). The information provided by Hardy, Lovery and
Patterson (2018, August 31) also suggests a positive correlation between the share of temporary employment and the
unemployment rate across economic regions. Consequently, it is expected that the effect of the “entry-exit-respite”
behaviour on the labour market results would vary across economic regions.
However, since the temporary employment share seems to grow year-over-year, the “entry-exit-respite” labour market
behaviour will increasingly explain the diminishing labour force participation trend.
Note: the number of employees was calculated using the 12-month average ending in June from 2008 to 2018.
Source: Hardy, Lovey and Patterson (2018, August 31, para 5) – Labour Force Survey, custom tabulations
Figure 51
CONCLUSIONS
The “entry-exit-respite” labour force behaviour exhibited most likely by people engaged in temporary employment
contributes to the diminishing trend of the labour force participation rate in the London ER. Industries where this
type of employment (temporary) became very popular contribute to the expansion of the entry-exit-respite labour
market dynamic: e.g. Agriculture, Education, Public Administration, Nonprofit, Retail and other.
Geographic areas with a higher concentration of the industries preferring and promoting contract/term employment,
seasonal, or casual work are more exposed to this unconventional dynamic of the labour force, which also makes it
difficult to predict.
0
20
40
60
80
100
120
140
160
180
June June June June June June June June June June June June June June June June June June June June June
1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018
Index of the number of employees with permanent or temporary jobs, Canada, June 1998 to June 2018
(June 1998 = 100)
Permanent employees Temporary employees
PAGE 52
6. WHO ARE THE “NOT IN LABOUR FORCE” PEOPLE?
Over 200,000 people of working age (15+) in the London ER are classified as “not in labour force.” Specifically, on
December 2018, there were 227,300 people “not in labour force” in the London ER (Statistics Canada, 2019). Figure 52
shows the growth of this population since January 2006. The “not in labour force” cohort has exhibited a growing
trend since 2006. However, some seasonal variation is systematically present with this data across time. Several
hypotheses develop from the results illustrated in Figure 52:
1. The number of seniors (retirees) in the region grew every year in the London ER since 2006, 2. The number of students in the region grew in the past thirteen years, 3. The number of working age people disconnected from the regional labour market (discouraged, having
health issues, caring for children or relatives, etc.) was growing during the time horizon.
The three hypotheses could have materialized all in the same time, or grew over combinations of two at various
times, or each hypothesis could have happened individually at specific times during the time frame of this analysis.
A deeper look into various demographic characteristics of this cohort might provide insight into why the cohort is
growing.
Figure 53 shows that there are more females in the “not in labour force” cohort in the London ER. However, the male
group grew between 2006 and 2016 by 29% while female group increased only by about 14% within the same time.
Source: Statistics Canada table 14-10-0293-01
Figure 52
R² = 0.8972
0
50
100
150
200
250
Jan
-06
Jul-
06
Jan
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07
Jan
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08
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18
"Not in labour force" in the London ER(x 1,000 persons)
( three-month moving average, unadjusted for seasonality)
Not in labour force Poly. (Not in labour force)
PAGE 53
Source : One Hub, Census custom tables, Census 2016 – Table T3_POR and Census 2006 – Table EO1246 T2_3
Figure 53
Source : One Hub, Census custom tables, Census 2016 – Table T3_POR and Census 2006 – Table EO1246 T2_3
Figure 54
62660
80845
95465
109095
0
20000
40000
60000
80000
100000
120000
2006 2016
"Not in labour force" in the London ER by gender(persons)
Male Female
2571536430
9598086760
3004538665
121225
99415
0
20000
40000
60000
80000
100000
120000
140000
Youth (15-24 years) Prime age (25 to 54years)
Mature age (55 years andover)
15 to 64 years
"Not in labour force" in the London ER by age groups(persons)
2006 2016
PAGE 54
Source : One Hub, Census custom tables, Census 2016 – Table T3_POR and Census 2006 – Table EO1246 T2_3
Figure 55
These findings support the third hypothesis regarding the growth in the number of people disconnected from
labour market (or marginally attached to the labour market) due to various reasons: discouragement, caring for
children or relatives, ill, having a disability, etc. Specifically, the data shows that women, who most likely care for
children or close relatives are “not in labor force” in larger numbers than men in the London ER.
Figure 54 shows the “not in labour force” population changes in the London ER by age group. The largest age cohort
among all is the mature age (55 years and over), followed by the prime age (25 to 54 years) cohort. The youth (15 to
24 years) has the smallest proportion of the “not in labour force” population. It is worth noting that the largest
change between 2006 and 2016 across these three population groups in the London ER was owned by the mature
age (55 years and over) group, followed by youth (15 to 24 years) and next by the prime age (25 to 54 years) group, by
26.3%, 16.8 % and 6.2% respectively. These findings suggest that the aging of the population contributed to the
growth of the mature age cohort in the London ER within the earlier mentioned time frame. Furthermore, the total
population “not in labour force” between “15 and 64 years” old in the London ER in 2016 was about 99,415 people and
it grew by approximately 20% since 2006.
Figure 55 shows the “not in labour force” population in the London ER by age group and gender. The mature age (55
years and over) is split further into “55 to 64 years” and “65 years and over.” Percent growth of the age groups by
gender are presented in Table 1. At first view, one could conclude that among the “not in labour force” the male
groups had overall larger growth between 2006 and 2016 than female groups. These results partially might explain
why the participation rate has dropped in the region between 2006 and 2016 among the males. The group that had
the largest growth (37.4%) between 2006 and 2016 among male groups “not in labour force” was the “55 t0 64 years
13090 12625 15500 14545
1152024910 14030
246359060
15555
12445
1826028995
42370
38870
51650
0
20000
40000
60000
80000
100000
120000
Males Females Males Females
2006 2016
"Not in labour force" in the London ER by age and gender(persons)
Youth (15-24 years) Prime age (25 to 54 years) 55 to 64 years 65 years and over
PAGE 55
old.” The female group with the largest growth (21.9%) between 2006 and 2016 among the “not in labour force” was
the “65 years and over.”
The growth within the time frame of the youth groups (Table 1), both males and females, among the “not in labour
force” supports the hypothesis that recently more people have become involved in education and training than
before.
Table 1. Percent change between 2006 and 2016 of the “not in labour force” by age and gender
Males Females
Youth (15-24 years) 18.4% 15.2% Prime age (25 to 54 years) 21.8% -1.1% 55 to 64 years 37.4% 17.4% 65 years and over 34.1% 21.9% Mature age (55 years and over) 34.8% 20.7%
Source: EMOWPDB computations based on One Hub, Census custom tables, Census 2016 – Table T3_POR and
Census 2006 – Table E1246 T2_2
The group that sparks interest for the employment service agencies and community planning groups in the London
ER is the “15 to 64 years” old, which is large at 99,415 individuals. Understanding their motives for not being
involved with the labour market may generate new strategies for how to engage or reengage them with the labour
market.
7. WHAT ARE THE REASONS FOR NOT PARTICIPATING TO THE LABOUR MARKET?
Based on a customized survey, Sanchez-Keane and Zonruiter (2017) have identified several reasons why people are
not participating in the London ER’s labour market:
Lack of transportation
Not being successful in the past
Lack of jobs or not qualified for jobs in the area
Health or disability
Family responsibilities
Experiencing discrimination (Sanchez-Keane & Zonruiter, 2017, p. VI).
The present report adds provincial level information from the Labour Force Survey that provides robust data
support for several of the reasons identified by Sanchez-Keane and Zonruiter (2017) and adds other reasons.
PAGE 56
Source: Statistics Canada, Table 14-10-012801
Figure 56
Only a small fraction of the “not in the labour force” wanted to work, see Figure 56. The “not in labour force” cohort
is very diverse and includes all the retirees, full-time students, discouraged people, people with disabilities, and
other categories permanently or temporarily detached from the labour market.
In 2017 about 4% of the “not in labour force” group indicated that they were “not in labour force but wanted work”
while 96% of the same group specified that they were “not in labour force and did not want work or were not
available.” The “not in labour force but wanted to work” group incites further investigation. If one assumes that the
London ER is not different from the province overall, one can estimate that in the London ER, there were about
9,100 people (227,300 people x 0.04) who were “not in labour force but wanted to work.” This is a hypothetical
exercise to assess the potential increase in labour force participation if this group is reconnected to the local labour
market.
0
500
1000
1500
2000
2500
3000
3500
4000
4500
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
Ontario - Reasons for not looking for work(x 1,000 persons)
Not in the labour force but wanted work Not in the labour force and did not want work or not available
PAGE 57
Source: Statistics Canada, Table 14-10-012801
Figure 57
Figure 57 suggests that, as expected, in Ontario the amount of people “not in labour force but wanted to work”
increased in the years immediately following the recession in 2008-2009, but it dropped afterwards to the pre-
recession levels. The efforts made to restore the provincial labour markets to the pre-recession levels included
members of this population too.
Source: Statistics Canada, Table 14-10-012801
Figure 58
0
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100
150
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250
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
Not in the labour force but wanted to work - Ontario(x 1,000 persons)
Not in the labour force but wanted work
Fin
anci
al c
risi
s 2
01
7-2
01
8
Wanted work, reason - illness
19%
Wanted work, reason -personal/family responsibilities
19%
Wanted work, reason -school26%
Wanted work, reason -awaiting recall/reply
6%
Wanted work, reason -discouraged
5%
Wanted work, reason - other
25%
Not in the labour force but wanted to work by reason in 2017 -Ontario
(x 1,000 persons)
PAGE 58
The “not in labour force but wanted to work” were asked further about their reasons, and the reasons presented in
Figure 58 surfaced as:
Discouraged
Awaiting for recall/reply
School
Personal/family responsibilities
Illness
Other.
The largest groups were “wanted work, reason – school” and “wanted work, reason- other,” with 26% and 25%
respectively. Results that support again the hypothesis that participation dropped due to the increased appetite for
education and training. The “other” category requires further discovery. However, estimating the size of these
groups for the London ER leads us to the following values: 2366 people = 9,100 people x 0.26 “wanted work, reason –
school” and 2275 people = 9,100 people x 0.25 “wanted work, reason other.”
The next group of reasons by share size include “wanted work, reason – personal/family responsibilities“ and “wanted
work, reason – illness” both with a share of 19%. Each of these two groups in the London ER would have about 1,729
people (9,100 people x 0.19)
And finally, the group of reasons with the smallest share size were including “wanted work, reason - awaiting
recall/reply” and “wanted work, reason – discouraged” with 6% and 5% shares respectively. Estimating them for
London, using the 2017 information, gives us 546 people ( 9,100 people x 0.06) “wanted to work, reason – awaiting
recall/reply” and 455 people (9,100 x 0.05) “wanted work – reason discouraged.” Surprisingly, the number of
discouraged people among the “not in labour force” seems to be very small, contrasting anecdotal evidence.
Source: Statistics Canada, Table 14-10-012801
Figure 59
0
10
20
30
40
50
60
70
80
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
Not in the labour force but wanted to work - Ontario(x 1,000 persons)
Wanted work, reason - illness Wanted work, reason - personal/family responsibilities
Wanted work, reason - school Wanted work, reason - awaiting recall/reply
Wanted work, reason - discouraged Wanted work, reason - other
Fin
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00
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PAGE 59
A longitudinal view upon the evolution of these reasons, pre- and post-recession (Figure 59), reveals that the
“school” reason was the top reason until 2013 after which it decreased significantly, to levels below pre-recession.
These results were somewhat expected, because during bad economic times it is wise to update your education and
training if you are unemployed. The “other” reason increased after the financial crisis 2008-2009 until 2011 and
decreased afterwards to levels lower than during pre-recession. However, the “illness” and “personal/family
responsibilities” reasons increased immediately after the recession up until 2011 and decreased afterwards to levels
still higher than during pre-recession. A similar behaviour was exhibited by the groups associated with “awaiting
recall/reply” and “discouraged.” They increased after the recession up to 2010 after which they slightly decreased and
settled at a level still higher than during pre-recession.
Gender and age are variables included in this Labour Force Survey data collection and they could provide more
insight into the evolution of the “not in labour force” cohort over time.
Source: Statistics Canada, Table 14-10-012801
Figure 60
The behaviour of the male and female cohorts “not in labour force but wanted to work” was slightly different. Starting
with 2011, the number of females “not in labour force but wanted to work” increased to a higher level than the
number of males “not in labour force but wanted to work.” However, after 2011 both gender groups reduced their size,
achieving pre-recession levels in 2017. The gender gap has been closing in 2016, Figure 60.
Comparing gender cohorts across the six reasons for “not working” identified by the Labour Force Survey (LFS), one
can view major gender differences for the “personal/family responsibilities” motive. As illustrated in Figure 61 the
female cohort invokes this reason more than the male cohort invoking this reason for not participating to the labour
market. One would see an increase in females’ cohort mentioning this reason between 2007 and 2009 and between
2010 and 2014, then dropping in size after 2014 almost to the pre-recession levels. In contrast, the male cohort
0
20
40
60
80
100
120
140
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
Not in the labour force but wanted to work, by gender – Ontario(x 1,000 persons)
Males Females
Fin
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risi
s 2
00
8-2
00
9
PAGE 60
mentioning “personal/family responsibilities” as a reason for not participating to the labour market displayed a slow
and steady increase over the years.
Source: Statistics Canada, Table 14-10-012801
Figure 61
Source: Statistics Canada, Table 14-10-012801
Figure 62
0
5
10
15
20
25
30
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
Wanted work, reason - personal/ family responsibilities, by gender -Ontario
(x 1,000 persons)
Males Females
Fin
anci
al C
risi
s 2
00
8-2
00
9
0
1
2
3
4
5
6
7
8
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
Wanted work, reason - awaiting for recall/reply, by gender - Ontario(x 1,000 persons)
Males Females
Fin
anci
al C
risi
s 2
00
8-2
00
9
PAGE 61
Another reason for which one would observe a gender difference is “awaiting for a recall/replay” (see Figure 62).
More males than females cited this reason for not participating in the labour market. One would see some
variability over time, with spikes in 2009, 2015 and 2016 for males and 2012 and 2017 for females, and dips in 2010,
2014, and 2017 for males and in 2015 for females. This variability is related to economic cycles, particularly the
financial crisis 2008-2009 as well as the economic contraction during 2015 due to the oil crisis 2014-2015. Also, we
see one to two years’ lag between the genders displaying similar behavior vis-à-vis the “awaiting for recall/reply”
reason for not participating in the labour market.
For all the other reasons, the gender differences were minimal.
Regarding the age group differences across the “not in labour force but wanted to work” cohort, the prime age (25 to
54 years) and youth (15 to 24 years) groups owned the largest shares, Figure 63. After 2011-2012 both age groups –
prime age and youth reduced in time. The prime age group settled in 2017 at levels higher than pre-recession times,
whereas the youth group dropped in 2017 to levels way below the pre-recession time. These results might reflect the
investment in employment programs targeting youth after 2012. The mature age group displayed a spike in 2010
after which it slowly diminished to achieve, in 2017 levels like the pre-recession.
Source: Statistics Canada, Table 14-10-012801
Figure 63
For all the reasons identified by the Labour Force Survey for not participating to the labour market, the prime age
group was dominant in size, except for the “school” reason where the youth group was dominant, see Figures 64 to
69.
0
20
40
60
80
100
120
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
Not in the labour force but wanted work, by age - Ontario(x 1,000 persons)
15 to 24 years 25 to 54 years 55 years and over
Fin
anci
al c
risi
s2
00
8-2
00
9
PAGE 62
Source: Statistics Canada, Table 14-10-012801
Figure 64
Source: Statistics Canada, Table 14-10-012801
Figure 65
0
5
10
15
20
25
30
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
Wanted work, reason - illness, by age - Ontario(x 1,000 persons)
15 to 24 years 25 to 54 years 55 years and over
Fin
anci
al c
risi
s2
00
8-2
00
9
0
5
10
15
20
25
30
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
Wanted work, reason - personal/family responsibilities - Ontario(x 1,000 persons)
15 to 24 years 25 to 54 years 55 years and over
Fin
anci
al c
risi
s 2
00
8-2
00
9
PAGE 63
Source: Statistics Canada, Table 14-10-012801
Figure 66
Source: Statistics Canada, Table 14-10-012801
Figure 67
0
10
20
30
40
50
60
70
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
Wanted work, reason - school by age - Ontario(x 1,000 persons)
15 to 24 years 25 to 54 years
Fin
anci
alcr
isis
20
08
-20
09
0
1
2
3
4
5
6
7
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
Wanted work, reason - awaiting for recall/reply Ontario(x 1,000 persons)
15 to 24 years 25 to 54 years 55 years and over
Fin
anci
al c
risi
s2
00
8-2
00
9
PAGE 64
Source: Statistics Canada, Table 14-10-012801
Figure 68
Source: Statistics Canada, Table 14-10-012801
Figure 69
0
1
2
3
4
5
6
7
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
Wanted work, reason - discouraged - Ontario(x 1,000 persons)
15 to 24 years 25 to 54 years 55 years and over
Fin
anci
al c
risi
s2
00
8 -
20
09
0
5
10
15
20
25
30
35
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
Wanted work, reason - other - Ontario(x 1,000 persons)
15 to 24 years 25 to 54 years 55 years and over
Fin
anci
al c
risi
s 2
00
8-2
00
9
PAGE 65
CONCLUSIONS
Economic context surrounding the 2008-2009 recession, the oil crisis 2014-2015 and the economic contraction
during 2015 explains the variation of the number of people “not in labour force but wanted to work,” particularly the
spikes in 2009, 2010 and 2011.
The size of the “not in labour force but wanted to work” group increased during the recession in 2008-2009 and in
the years immediately after.
Only a small proportion (about 4%) of those “not in the labour force” indicated that they “wanted to work” but they
were constrained for some reason.
Organizing the reasons by the size of the group in decreasing order, it was determined:
Tier 1: Reasons – “school” and “other” (about 25% each),
Tier 2: Reasons – “illness” and “personal/family responsibilities” (around 19% each),
Tier 3: Reasons – “discouraged” and “awaiting recall/reply” (approximately 6% each).
A major gender discrepancy was observed for the “wanted to work, reason – personal/family responsibilities” in that
women are more likely to invoke this reason than men.
Men were more likely than women to “await for recall/reply,” be “discouraged” or invoke “other” as a reason for not
participating.
People of prime age and youth were more likely than any other age group to claim “wanted to work but … reason …”
People of prime age followed by youth were more likely than any other age group to invoke “illness,”
“personal/family responsibility,” “awaiting for recall/reply,” “discouraged,” and “other” reasons.
Youth were more likely than any other age group to invoke the “school” reason for not participating in the labour
market.
8. METHODOLOGY
The current study is mostly based on secondary data provided by Statistics Canada. As announced in the
Introduction, recent access by the LEPC London to custom tables from Census 2016 for the London ER increased
local interest in a follow-up study of labour force participation in the London ER. Labour Force Survey and
Employment Insurance (EI) Survey results are also explored in the study. MDB Insight - Vicinity Jobs labour market
demand reports were used to support various arguments presented in the current study.
The London ER was the geographical focus for the analyzed data. However, where information was not available at
this level of geography, provincial or national data was used to sustain the advanced hypotheses.
Comparing descriptive statistics obtained through Excel data processing was the main approach across the study.
Time, geography, and other demographics were the central criteria for comparison.
Where data was unavailable to demonstrate propositions, anecdotal evidence was noted.
PAGE 66
9. RECOMMENDATIONS
The growth of the labour force is a source of economic growth, and therefore there is a concern regarding low
labour force participation. The past fifteen to twenty years have been dominated by a succession of major economic,
demographic and technologic events that have shaped the local development of the labour force. Among these
economic events are the Millennium scare (2000) and the recession afterwards, the financial crisis 2008-2009, retail
and food manufacturing sectors’ consolidation of 2013-2014, oil crisis 2014-2015 and the following economic
contraction in 2015 which generated high economic uncertainties across the markets and a slow recovery. The
demographic force that has prevailed lately is the aging population. Finally, the technological advancement in
developing new materials and technologies (e.g. 3-D printing, big data, machine learning and AI) has been
demanding new sets of skills. Local labour force development is in the middle of this higher-level storm shaped by
economic uncertainties, aging and the development of new technologies. Designing good labour force development
policies is essential for successful local economic development. The list of recommendations provided below can
inform local leaders in adopting policies and promoting strategies that are effective and efficient for the local labour
force.
Highlights:
A high level of labour force concentration into one or few industries sets a major local economic risk. Automotive manufacturing, tourism, retail and finance were industries seriously affected in the London ER by the financial of crisis 2008-2009. Therefore, local economic development should constantly strive for industrial diversification.
Economic uncertainties can also be avoided through the local development of, and support for, leading industries that bring local and steady job creation (e.g. R&D in Health, IT, Manufacturing, Transportation, Education, Services, and Agriculture; digitization of Financial and Marketing Services and Retailing; Construction and Home Renovation)
The identified demographic trends can be adjusted through economic incentives that support natality and raising children, labour force attraction from outside the London ER and retention of the mature age cohort. These efforts should be backed accordingly by job creation policies.
Develop and promote locally work arrangement alternatives that provide flexibility for the population groups constrained by time: e.g. care givers (mothers, people caring for family members or relatives.), students, mature age people who want to supplement their income. Flex-time, job sharing, compressed work weeks, phased-retirement plans, and part-time options for older workers are common options considered thus far, but other innovative alternatives would be welcomed (ACOEG, 2017, February 6).
Engaging visible minority, Aboriginal, Francophone and immigrant groups with the local labour market by increasing access to training and reskilling programs would lead in time to an improved overall participation rate in the London ER. Promoting more intensely at the local level the standards for, and processes involved in, licensing for regulated professions can speed up and expand local knowledge regarding these professions and ultimately straighten the career path or work alternatives for the immigrant population. Expand educational alternatives and labour market integration for the Aboriginal group at all levels of education should be a local priority.
London ER employers could easily change their attraction-retention strategies by offering equally or higher wages than the average in Ontario, or relatively to the earnings in the neighboring areas. Such a bold move would lead to a higher influx of labour into the London ER.
Develop local workforce development policies that reward employers for the development of permanent full-time work alternatives, which provide a healthy economic well-being for local individuals and families. As observed, the share of temporary work arrangements has been expanding lately, which creates high volatility for the local labour force size resulting from the entry-exit-respite approach embraced by people alternating intense periods of work with recovery periods permitted by an income substitution effect, or by a desperate alternative. The late developed gig economy promotes the expansion of the precariousness of work, fatigue and discouragement, which ultimately influences the local labour force participation.
PAGE 67
10. REFERENCES
ACOEG (2017, February 6). Tapping economic potential through broader workforce participation. Advisory Council
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11. APPENDIX – ABBREVIATIONS
ER – Economic Region
CMA – Census Metropolitan Area
EMOWPDB – Elgin Middlesex Oxford Workforce Planning and Development Board
LFS – Labour Force Survey
LLSC – Literacy Link South Central
LEPC – Local Employment Planning Council
CPP – Canada Pension Plan
OAS – Old Age Security
AI – Artificial Intelligence
EI – Employment Insurance
LER – London Economic Region
R&D – Research and Development