This post documents key characteristics of selected labour markets within Ontario. It establishes benchmarks for future assessments of these communities. Statistics Canada reports findings of the Labour Force Survey for defined geographic areas in compliance with scientifically defined rules for professional statisticians. Findings are published monthly for the highest levels of geography Canada and the ten provinces (Table 14-10-0287-03). Findings for three territories are published monthly but only as 3-month moving averages (Table 14-10-0292-02). Findings for the Census Metropolitan Areas having a minimum population of 100,000 are published as 3-month moving averages (Table 14-10-0378-01). Finally survey findings for Census Agglomerations, areas with at least 10,000 people only once a year (Table 14-10-0391-01). There are eight Ontario CAs in the Labour Force Survey.

Note findings scale with the appropriate level of geography and population.

Why establish benchmarks? Great advances were made to reduce the cost and logistics impact of distance for businesses and workers over the last couple of centuries. The pace of growth may be maintained well into the future depending on the willingness and capability of society to adapt and grow. The scientific and engineering foundations are already in place: (i) the internet is a foundational technology, (ii) Amazon Prime a glimpse of the next generation of business model and (iii) currently embryonic technologies such as 3-D printing can revolutionize manufacturing and its supporting logistics, maybe even human parts. And so forth but that is beyond the scope of this post. Some communities will recognize and seize opportunities, others will not.  Understanding the dynamics of success and the challenges of failure will reveal important lessons to support the sharing of the benefits of the new socio-economy.  And as with any scientific and disciplined study, the initial conditions must be documented.

The balance of this post will be in two parts. First documenting the inventory of occupations by community as of the 2021 Census and second comparing the performance of the key labour force factors over time and benchmarked against the provincial performance.

Inventory of existing occupations and skills

The 2021 Census of Population identified the occupation of respondents as defined by the National Occupation Classification system. The detailed results for each of the CAs surveyed by the Labour Force Survey are published in Table 98-10-0449-01. There are 141 occupations at the 3-digit level. Given the volume of data for each of the seven communities, the information was summarized at the 2-digit level and normalized to the provincial results where zero means the share of the occupation in the community labour force is the same as the provincial share, above zero means the occupation accounts for a larger share of the community labour force, than of the provincial labour force. It is a weak indicator of comparative advantage which includes a large dose of historical luck. The data presented in Figure 1 is very aggregated and should not be the basis for a detailed community analysis. Detailed data is available to support a more detailed analysis. Some observations can be made even at this level of detail:

1. Only three of the seven communities were over-represented in the natural resource occupations.
2. All were underrepresented in the business and finance occupations.
3. Four of the seven communities did not have a significant specialization relative to the provincial occupation profile.

Labour Force Survey Findings

The common variables reported for each jurisdiction in the Labour Force Survey including their formal definitions are:

• Size of the population:  Number of persons of working age, 15 years and over.
• Labour force: Number of civilian, non-institutionalized persons 15 years of age and over who, during the reference week, were employed or unemployed. 
• Number employed: Number of persons who, during the reference week, worked for pay or profit, or performed unpaid family work or had a job but were not at work due to own illness or disability, personal or family responsibilities, labour dispute, vacation, or other reason. Those persons on layoff and persons without work but who had a job to start at a definite date in the future are not considered employed. 
• Number unemployed: Number of persons who, during the reference week, were without work, had looked for work in the past four weeks, and were available for work.
• Number not in labour force: Persons in the civilian non-institutional population 15 years of age and over who, during the reference week, were neither employed nor unemployed.
• Unemployment rate: Number of unemployed persons expressed as a percentage of the labour force.
• Participation rate: Number of labour force participants expressed as a percentage of the population 15 years of age and over.
• Employment rate: Number of persons employed expressed as a percentage of the population 15 years of age and over. 

Annual data is available for each community starting 2006 until 2023.

Given the volume of data the working spreadsheet with the Statistics Canada data and some working tabs is included for additional reference.

Some general comments:

• Three Figures are prepared and included in the spreadsheet
  • Population
  • Employment rate
  • Participation rate
• Each figure includes all communities for 2006 to 2023.
• All data to prepare figures for the other variables are included in the spreadsheet.

Briefly there are no surprises. The communities are generally performing below provincial levels and some are losing population.

The socioeconomic health of the community and its labour force moving forward will, in part be related to the community’s embrace and support for the emerging labour employment model – hybrid employment. Hybrid employment is a flexible working environment mixing work-from-home and office attendance. The hybrid employment model was boosted with business adapting to the covid-19 pandemic and the potential to reduce office costs. Critical to the success of this model will be quality and reliable internet connectivity as well as the quality of life offering to the employee. But this is a topic for a future posting.

Concluding comment: Given the older worker-business paradigm, smaller communities in a big economy slowly fall behind the average, unless they get absorbed by an expanding city. Think Toronto. A shift may be in process providing more choice to workers while reducing costs to business. Critical will be community support for the needed communications and networking infrastructure.