Labour Force Participation in London Economic Region Follow-up … · 2019-03-11 · Elgin...

Elgin Middlesex Oxford Workforce Planning and Development Board & Local Employment Planning Council

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Labour Force Participation in London

Economic Region – Follow-up study

Emilian Siman, Data Analyst

Bashir Adeyemo, GIS Support and Data Analyst

January 2019

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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.

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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

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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

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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.

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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.

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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.

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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?

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Source: Statistics Canada, Table 14-10-0293-01

Figure 1


Figure 2

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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.


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

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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.

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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.


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.


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.


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


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.


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.


Figure 14


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



equivalent





diploma




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



equivalent





diploma




degree

Prime age (25-54 years) participation rate by education -London ER

(%)

2006 2016

PAGE 21


Figure 16


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



equivalent





diploma




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



equivalent





diploma




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%.


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


Figure 20


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



equivalent





diploma




degree (bachelorand obove)

Participation rate by gender and education level - London ER (%)

Male 2006 Male 2016 Female 2006 Female 2016

PAGE 26


Figure 22


Figure 23

0102030405060708090

100

2006 2016 2006 2016 2006 2016 2006 2016 2006 2016 2006 2016



equivalent





diploma





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



equivalent





diploma





Females participation rates by age and education - London ER(%)


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.


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


Participation rate by self-identified status and gender in 2016 -London ER

(%)

Male Female

PAGE 31


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.


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


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


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


PAGE 33


Figure 30


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



College,CEGEP or othernon-universitycertificate or

diploma





Participation rate by self-identified status and educational attainment in 2016 - London ER

(%)



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


High schooldiploma orequivalent

Apprenticeshipor trades certificate

or diploma



diploma





Participation rate by self-identified status and educational attainment in 2016 - Ontario

(%)



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


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


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)


PAGE 39


Figure 36


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)


-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)


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.


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)


PAGE 41


Figure 39


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)


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)


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.


Figure 41


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)


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)


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


Figure 43


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


Figure 45


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.


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


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

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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?


Figure 50

320

330

340

350

360

370

380

Jan

-06

Jul-

06

Jan

-07

Jul-

07

Jan

-08

Jul-

08

Jan

-09

Jul-

09

Jan

-10

Jul-

10

Jan

-11

Jul-

11

Jan

-12

Jul-

12

Jan

-13

Jul-

13

Jan

-14

Jul-

14

Jan

-15

Jul-

15

Jan

-16

Jul-

16

Jan

-17

Jul-

17

Jan

-18

Jul-

18

Jan

-19

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.


Figure 52

R² = 0.8972

0

50

100

150

200

250

Jan

-06

Jul-

06

Jan

-07

Jul-

07

Jan

-08

Jul-

08

Jan

-09

Jul-

09

Jan

-10

Jul-

10

Jan

-11

Jul-

11

Jan

-12

Jul-

12

Jan

-13

Jul-

13

Jan

-14

Jul-

14

Jan

-15

Jul-

15

Jan

-16

Jul-

16

Jan

-17

Jul-

17

Jan

-18

Jul-

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


Figure 53


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


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


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.


Figure 58

0

50

100

150

200

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.


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

anci

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s2

00

8-2

00

9

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.


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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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.


Figure 61


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

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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

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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.


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)


Fin

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00

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PAGE 62


Figure 64


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)


Fin

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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)


Fin

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8-2

00

9

PAGE 63


Figure 66


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)


Fin

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s2

00

8-2

00

9

PAGE 64


Figure 68


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)


Fin

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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)


Fin

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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

on Economic Growth Report. Retrieved February 15, 2019 from https://www.budget.gc.ca/aceg-

ccce/pdf/workforce-marche-travail-eng.pdf

Antecol, H. (2000). An examination of cross country differences in the gender gap in labour force participation

rates. Journal of Labour Economics. 7(4), pp.409-426. DOI: 10.1016/S0927-5371(00)00007-5.

Baker, J. M. & Jacobsen, P. (2007) Marriage, specialization, and the gender division of labour. Journal of Labour

Economics, 25 (4), pp.763-793. DOI: 10.1086/522907.

Bank of Canada (2018, October 15). Business outlook Survey – Autumn 2018. Results of the Autumn 2018 Survey. Vol.

15.3. Retrieved from https://www.bankofcanada.ca/2018/10/business-outlook-survey-autumn-2018/#chart6

BDO Canada (2016). Consolidation intensifies competition. Published on February 20, 2016. Retrieved on January 24,

2019 from www.bdo.ca/en-ca/insights/industries/retail-consumer-business/consolidation-intensifies-

competition/

Becker, G.S. (1985). Human capital, effort, and sexual division of labour. Journal of Labour Economics, 3 (2), pp. s33-

s58.

Bélanger, A., Carrière, Y. & Sabourin, P. (2016). Understanding employment participation of older workers: The

Canadian Perspective. Canadian Public Policy, Mars, doi: 10.3138/cpp.2015-042.

Burleton, D. (2013, February). Are medium-skilled jobs in Canada experiencing a hollowing out, U.S. – style? Special

Report. February 26, 2013. TD Economics. Retrieved January 27, 2019 from

https://www.td.com/document/PDF/economics/special/AreMediumSkilledJobsInCanadaExperiencingAHol

lowingOut.pdf

Coglianese, J. (2018, February 28). The rise of in-and-out: Declining labour force participation of prime age men.

Working paper. Retrieved January 29, 2019 from https://scholar.harvard.edu/coglianese/publications/rise-

of-in-and-outs

Daniszewski, H. (2015). Retirees are picking up stakes and heading to London where housing costs are a fraction of

those in the Toronto area. The London Free Press, June 28, 2015 edition. Retrieved January 25 2019 from

https://lfpress.com/2015/06/28/retirees-are-picking-up-stakes-and-heading-to-london-where-housing-

costs-are-a-fraction-of-those-in-the-toronto-area/wcm/097849c9-d3bb-7413-59ad-e10877532533

Daniszewski, H. (2016). With population growth middling, youth leaving and boomers set to retire, affordable

London could use lots more newcomers. The London Free Press, December 2, 2016 edition. Retrieved

January 25, 2019 from https://lfpress.com/2016/12/02/with-population-growth-middling-youth-leaving-and-

boomers-set-to-retire-affordable-london-could-use-lots-more-newcomers/wcm/fc0801c6-a473-b70c-5d5a-

1a2b93bc1381

Dos Santos, N. (2014). 2015: The Year when the oil crisis ends? CNN Money December 5, 2014 edition. Retrieved in

January 21, 2019 from https://money.cnn.com/2014/12/05/news/economy/oil-power-shift/index.html

England, P. (2005). Gender inequality in labour markets: the role of motherhood and segregation. Social Politics:

international Studies in Gender, State & Society, 12(2), pp.264-288. DOI: 10.1093/sp/jxi014.

PAGE 68

Fortin, M. N. (2005). Gender role attitudes and the labour-market outcomes of women across OECD countries.

Oxford Review of Economic Policy, 21(3), pp. 416-438. DOI: 10.1093/oxrep/gri024. Retrieved January 24, 2019

from http://faculty.arts.ubc.ca/nfortin/FortinOXF.pdf

Hardy, V., Lovei, M. & Patterson, M. (2018, August 31). Recent trends in Canada’s labour market: A rising tide or

passing wave? Labour Statistics at a Glance. Retrieved from https://www150.statcan.gc.ca/n1/pub/71-222-

x/71-222-x2018001-eng.htm

Ketcheson, J., Kyui, N. & Vincent, B. (2017, July). Labour force participation: A comparison of the United States and

Canada. Staff Analytical Note, 2017-9. Bank of Canada. Retrieved from

https://www.bankofcanada.ca/2017/07/staff-analytical-note-2017-9/

Kilian, L. (2015). Why did the price of oil fall after June 2014. VOX CEPR Policy Portal. Research-based policy analysis

and commentary from leading economists. Retrieved February 4, 2019 from

https://voxeu.org/article/causes-2014-oil-price-decline

Machin, S. & McNally, S. (2007). Tertiary education systems and the labour market. A paper commissioned by the

Education and Training Policy Division, OECD, for Thematic Review of Tertiary Education. Retrieved January

23, 2019 from http://www.oecd.org/education/innovation-education/38006954.pdf

MDB Insight (n.d.). Find jobs online: How many of Canada’s jobs are posted online? Retrieved January 28, 2019 from

https://blog.mdbinsight.com/find-jobs-online-how-many-of-canadas-jobs-are-posted-online

Psacharopoulos, G. (1986). Links between Education and the Labour Market: a broader perspective. European

Journal of Education, 21 (4), pp.409-415.

Sanchez-Keane, M. & Zonruiter, G. (2017). London Economic Region Labour Market Participation. Final Report,

February 2017. Centre for Organizational Effectiveness. Retrieved January 23, 2019 from

http://www.localemploymentplanning.ca/resources

Statistics Canada (2019, February 14). Labour force characteristics by economic region, three-month moving average,

unadjusted for seasonality, last 5 months. Table 14-10-0293-01. Retrieved February 4th, 2019 from

https://www150.statcan.gc.ca/t1/tbl1/en/tv.action?pid=1410029301&pickMembers%5B0%5D=2.7&pickMemb

ers%5B1%5D=3.1

Strauss, M. (2013). Grocery wars spur industry consolidation. The Globe and Mail. Published on August 14, 2013.

Retrieved January 24, 2019 from https://www.theglobeandmail.com/report-on-business/metro-to-

reorganize-ontario-network-close-some-stores/article13751650/

The World Bank (2012). Gender differences in employment and why they matter. Chapter5 of the World

Development Report 2012. Gender Equality and Development. The World Bank, Washington DC., pp.198-253.

Retrived February 15, 2019 from https://siteresources.worldbank.org/INTWDR2012/Resources/7778105-

1299699968583/7786210-1315936222006/Complete-Report.pdf

Tuzemen, D. & Willis, J. (2013). The vanishing middle: Job polarization and workers’ response to the decline in

middle-skill jobs. Economic Review. First Quarter 2013. Federal Reserve Bank of Kansas City. Retrieved from

https://www.kansascityfed.org/publicat/econrev/pdf/13q1tuzemen-willis.pdf

Zmitrovicz, K. & Kan, M.(2014). Beyond the unemployment rate: Assessing Canadian and U.S. labour markets since

the great recession. Bank of Canada Review. Spring 2014. Retrieved January 23, 2019 from

https://www.bankofcanada.ca/wp-content/uploads/2014/05/boc-review-spring14-zmitrowicz.pdf

PAGE 69

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

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