Growth and Decline in the Canadian Urban System: The Impact of Emerging Economic,
Policy and Demographic Trends
Pierre Filion
Urban Planning
University of Waterloo
Keywords: Urban Systems, Urban Economics, Urban Polarization, Global Economy
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Growth and Decline in the Canadian Urban System: The Impact of Emerging Economic,
Policy and Demographic Trends
Pierre Filion
Abstract
The Canadian urban system was first shaped by exogenous demand for staples and,
subsequently, by the dichotomy between an industrial heartland and a resource based hinterland.
Presently, transformations affecting the economy, policy-making and demography herald
profound changes in the future configuration of the Canadian urban system. One possible
scenario is a revival of the staples economy as economic globalization raises demand for
commodities. Another scenario would entail a concentration of growth in large urban centres, by
virtue of their attractiveness to specialized and high-order service occupations, two rapidly
expanding economic sectors, and their strong pull on immigrants. In the case of either scenario,
we can expect further polarization between growing and shrinking portions of the urban system
(parts of the heartland in the first case and small urban areas in the second) in a neo-liberal policy
context that is unfavourable to regional economic development interventions. The evolution of
the Canadian urban system between 1971 and 2006 and present distributions of factors of growth
and decline point to the second scenario, a growing large city-small city dichotomy. The article
closes by discussing likely consequences of the resulting urban system configuration on labour
market adjustments and public sector expenditure.
Introduction
In the last few decades, the Canadian urban system has been quite dynamic. Unlike many
national systems of cities that have a rigid hierarchical structure, Canada’s has changed
considerably in recent years. This dynamism is likely to continue in the coming decades, with
new directions supplanting the most recent trends. Future trends are likely to be driven more by
demographic and global economic trends than by explicit policy choices. As a result, while it is
possible to outline potential configurations for the Canadian urban system, it is not certain which
will prevail.
The article analyzes the profound changes that will contribute to the continued
transformation of the Canadian urban system: the clustering of growth in a few large urban
centres and the decline of many smaller urban areas. How will modifications affecting the
economy, policy and demography reshape the urban system over the next decades? This is an
important topic, for trends affecting urban growth have far-reaching consequences. For example,
economic and demographic growth translates into additional political influence at the national
scale, which itself provides conditions for further development. Likewise, with decline come
reduced political impact and a lesser capacity to secure conditions for improved economic
fortunes. Moreover, a polarized urban system will inevitably pit expanding urban regions,
confronted with the need for additional and improved infrastructures, against declining regions,
unable to maintain infrastructure networks that exceed their needs and fiscal capacity. The more
unbalanced the urban system becomes, the higher the public sector costs related to social and
infrastructure expenditures, incurred as a result of having to deal simultaneously with growth and
decline. Also, one cannot ignore the richer employment opportunities and superior life chances
in rapidly expanding areas than in slow or negative growth regions.
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To add historical perspective and help define the context influencing the configuration of
the contemporary and future urban system, two historical phases that have moulded Canadian
urban settlements are considered. The first, “staples” phase is responsible for pre-industrial
settlement patterns, extending from the early European settlement to the late 19th century. A
second, “heartland-hinterland,” phase accounts for subsequent uneven development between a
generally rapidly growing industrialized core and the remainder of the nation, where
development has been far more dispersed and cyclical. In the early years of the 21st century,
rapidly advancing deindustrialization accompanied by robust world-wide demand for
commodities point to a possible reversal of the heartland-hinterland disparities, whereby the
resource-rich hinterland would grow faster than the manufacturing-oriented heartland.
A second possible scenario is based on a different economic driver and leads to a quite
different result. This alternate interpretation is based on a much enhanced role of the service
sector, which accounts for an ever growing proportion of employment and consumer spending. It
may be that the increasing service-sector orientation will foster a concentration of growth in
large urban areas. Demographic trends are also expected to contribute to large-city growth.
Immigrants, the main, and soon only, factor of population expansion, are attracted to large urban
centres, which are known for their multiculturalism and where ethnic communities are wellestablished. In either circumstance, we can anticipate a widening gap between areas that are
experiencing economic and demographic growth and those that are either stagnating or
shrinking, given waning commitment to public sector compensatory measures, as neo-liberalism
dislodges interventionism as the dominant political ideology.
This article charts demographic and economic trends that have affected the Canadian
urban system between 1971 and 2006. It then concentrates on more recent tendencies and 2006
variables that point to future trajectories.
Historical Concepts
Staples theory, as formulated by Harold Innis, provides an explanatory model for Canadian
settlement patterns until industrialization emerged in the late 19th century. In this view,
transportation systems, political institutions, demographic growth and the distribution and size of
human settlements, were all driven by an exogenous demand for commodities. The development
of Canada was propelled by the commodity needs of France and then Great Britain. The nature
of the commodities in demand determined the form of transportation systems and the level of
demographic growth. In the words of Innis (1995a [1931], 128):
“The effects, on the economic development of the St Lawrence basin, of dependence on
lumber as a staple product, were the opposite of the effects of dependence on fur.
Whereas fur involved a heavy incoming cargo, lumber favoured a large return cargo and
consequently provided a stimulus to immigration and settlement.”
While the harvesting of fur and lumber and the extraction of minerals did not require a
large population, the production of grain for export required a sizable rural population, provided
mostly by immigration. In the same vein, as commodities became increasingly bulky and their
flows ever larger, governments incurred debt to create required transportation systems – first
canals, then railways. Successive institutional structures, culminating with Confederation, were
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largely a response to the need to borrow and secure the resulting debt. Settlement patterns
reflected the export-led staples economy (Innis 1995a [1931]; 1995b [1938]). Small population
centres associated with the harvesting and extraction of commodities, along with the market and
service centres catering to a rural population, and a small number of larger cities serving as
points of transhipment and administrative centres for staples extraction and transportation
enterprises constituted the early Canadian urban system (Sitwell and Seifried 1984).
The heartland-hinterland model focuses on the division between an industrial heartland
and a hinterland comprised of the remainder of the country (McCann and Gunn 1998). Protected
by tariffs, and thus impelled largely by branch plants, Canadian industrialization mostly took
place in the more densely populated rural basin, already the site of major cities, including
Montréal and Toronto, the country’s two largest metropolitan regions. The heartland runs from
Québec City to Windsor, an industrial corridor referred to as Canada’s main street (Blank 2008;
Yeates 1975) (see Figure 1). The hinterland, in contrast, is more sparsely populated and
continues to be mostly reliant on the extraction and harvesting of natural resources. It also
includes vestiges of early Canadian industrialization in the Maritime Provinces. Still, the
hinterland has spawned a number of sizable urban centres – Winnipeg, Calgary, Edmonton and
Vancouver.
From 1951 to 1971 demographic growth in the heartland exceeded that of the country as
a whole, causing its share of the national population to reach 55 percent (Yeates 1998, 115).
After this, rapid growth tended to concentrate in certain parts of the heartland: typically those
areas associated with expanding sectors of the economy such as, until recently, the car industry.
Meanwhile, the demographic expansion of the Québec portion of the heartland was challenged
by the departure of some Anglophones reacting to the growing place given to the French
language in this province, and a strong presence of sunset labour-intensive industries, such as
textiles and garments.
The 1988 Free Trade Agreement (FTA) between Canada and the US and the 1994 North
American Free Trade Agreement (NAFTA) involving Canada, the US and Mexico, caused major
industrial realignments, as did the rapid industrialization of developing countries as global trade
was liberalized (Barnes et al. 2000). Smaller branch plants were particularly affected, as were
industrial sectors unable to compete with cheaper imports. Yet, lately the heartland has enjoyed
rapid development in knowledge-intensive sectors such as information technology in Ottawa,
Toronto and Waterloo, pharmaceuticals in Montréal and Toronto, and aeronautics in Montréal.
In the interventionist climate that prevailed from the 1950s to the early 1980s, the pursuit
of territorial equity objectives led to public sector support for industrial development in the
hinterland as well as less prosperous parts of the heartland. The federal government and the
provinces devised a succession of programs encouraging the location of industrial investments in
such areas (Coffey and Polèse 1987; Savoie 1992). In the end, these programs did little to alter
predominant industrial location patterns. Public sector incentives proved to be no match to
advantages such as production and supplier linkages, the availability of an abundant and
diversified labour force and proximity to markets. For example, all efforts to spread car assembly
beyond the Southern Ontario automobile production cluster, either elsewhere in the heartland or
in the hinterland, ultimately failed. Some eccentric assembly plants were short lived: Renault
operated from 1964 to 1972 south of Montréal, Bricklin from 1974 to 1976 in New Brunswick
and Hyundai from 1989 to 1993 in the Québec Eastern Townships. Other facilities were longer
lasting. This was the case of the Nova Scotia Volvo plant, in production from 1963 to 1998, and
the GM plant north of Montréal, which operated from 1966 until 2002. However, with the
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closure of the GM plant, once again, all car assembly activities were located in Southern Ontario.
Some have maintained that, when considered in their totality, allocations of government
expenditure with an economic development potential (infrastructure development, education,
research and development...) ultimately favoured fast growing areas despite energetic regional
development interventions, thus enshrining relations of dependency between under-developed
and developed regions (e.g., Matthews 1983). In this view, rather than dispersing industrial
activities, government actions furthered their concentration. Although this may overstate the
case to some degree, it seems clear that industrial locations patterns are shaped more by market
forces than by government economic development incentives.
The interventionist decades also marked the launching of interprovincial equalization and
transfer programs and constitute the period when these programs came closest to achieving their
social equity objectives. They resulted in a redistribution of resources from the rich parts of the
heartland, notably Southern Ontario, to less well performing portions of the heartland and much
of the hinterland. But in an economy protected by tariffs, these financial flows did not
necessarily represent a drain on prosperous regions within the heartland, as equalization and
transfer payments helped to deepen markets for their industrial products.
Changing Factors of Urban Growth and Decline
Three factors were instrumental in shaping the Canadian urban system: the economy, public
policy and demography (see Simmons and Bourne 2003). These factors can be seen as drivers of
economic and population growth and decline, and thereby as largely responsible for the
configuration of the urban system at any given time during the staples and heartland-hinterland
periods, as well as in the present and future.
The economy played the leading role in the development of the urban system. Over the
staples era, population centres were linked to the harvesting, transportation and administration of
commodities, adopting an east-west distribution reflecting the predominantly European origin of
demand. Subsequently, manufacturing took advantage of existing concentrations of rural
population and potential linkages. Once in place, manufacturing became a catalyst for further
population expansion in the industrial heartland. Over the staples era, the impact of public policy
on the urban system was manifest mostly in transportation and immigration policies. Later,
tariffs played a central role in the industrialization of Canada; government interventions were for
the most part favourable to a further economic development of the heartland. Finally,
demography is an enabling but passive factor over both periods. The combination of high rates of
natural growth and at times substantial arrivals of immigrants assured an ample supply of
population supportive of economically and policy induced urban development trends.
Economically expanding urban areas were able to rely on their own natural growth in addition to
migratory flows from different parts of the country and their respective rural and small town
basins, as well as from immigration. Together, these factors maintained the dichotomy between
the heartland and hinterland, along with relative stability in the industrial specialization of
regions within the heartland (Davies and Donoghue 1993; Polèse and Shearmur 2006a).
Current and anticipated changes affecting these three factors explain present
transformations within the urban system, which mark a departure from the heartland-hinterland
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divide, and herald deeper modifications in the future. Beginning with economic trends, it is clear
that globalization has had the same devastating effect on manufacturing employment in Canada
as in other developed nations. There is also a Canadian specificity to globalization, which stems
from the presence of an unusually large natural resources sector. With the quick industrialization
of China and India comes a rising world-wide demand for commodities, with evident advantages
for the Canadian natural resources sector. One possible outcome may, however, be a case of the
“Dutch Disease”, whereby rising currency fuelled by strong demand for natural resources results
in a loss of competitiveness within the manufacturing sector. With varying degrees of severity,
Canada has faced such a situation from 2006 to 2008, and this trend is forecast to persist in the
near future (Financial Forecast Center 2008). Alternatively, steep gyrations in the value of the
Canadian dollar, responding to commodity demand cycles (a situation prevailing in late 2008),
can be equally debilitating for manufacturing.
Together, these trends suggest a partial return to a staples-dominated economy. While
heartland manufacturing is hurt by difficulties in competing with developing nations, which are
exacerbated by a strong Canadian currency, the hinterland benefits from a rising world demand
for commodities. The economic balance would thus be tilting in favour of the hinterland. It is
important, however, to realize that the extraction and harvesting of natural resources have less
employment generation potential than manufacturing does.
Beyond those that presently benefit the hinterland, there are other economic factors with
urban system repercussions. This second category includes factors that can be seen as favourable
to the expansion of large urban areas by contributing to, or taking advantage of, economies of
agglomeration enjoyed within such urban centres. Different viewpoints on economies of
agglomeration have been advanced, from the Marshallian perspective on industrial districts, to
the more recent network approach of Michael Porter; work on learning and innovative regions
and the creative class can also be interpreted as variations on the agglomeration economies
theme (Boekema 2000; Doloreux 2004; Florida 2002a; Porter 1990). Economies of
agglomeration have always disproportionately benefited large urban areas, but emerging
circumstances appear to accentuate such advantages.
In order to fill their requirement for an increasingly specialized labour force, large
workplaces need to locate within access range of a substantial pool of workers. This is
particularly the case for those establishments that require highly qualified employees.
Concurrently, specialized workers are attracted to large centres because of a greater chance to
find employment suited to their qualifications. The need for a large employment market is
especially felt by households comprised of two professionals. In addition, presence in a rich
labour market allows the pursuit of “horizontal” careers, a major advantage in times of frequent
employment change (Shearmur and Doloreux 2008, 1062). Concentrations of urban amenities,
such as culture, entertainment, sports and wide consumption choices, also draw highly qualified
workers to large centres (Gertler et al. 2002; Ghent Mallett 2002; Simmons and Bourne 2003).
And, when present in a city, knowledge workers stimulate economic growth by launching new
enterprises and luring in firms dependent on their skills (Florida 2002a; 2002b).
The vertical disintegration of production processes also encourages the presence of
employment in large urban areas because of the resulting need for firms to maintain extensive
linkage networks. In a similar vein, communication advancements have made it possible to
spatially separate activities related to production or extraction processes. The location of
administrative and product development stages of such processes can be dictated by the presence
of the required workforce and the amenities it values, rather than proximity to production or
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natural resources. For example, although the generator of boom towns such as Fort McMurray,
much of the growth benefits of the Alberta tar sands industry are felt in Edmonton and Calgary,
where service-type functions related to this industry are concentrated.
In itself the rapid growth of the service sector also benefits the expansion of large urban
areas. The range of services present in such urban areas is broader than in smaller cities, thanks
to the predilection of high-order and specialized services for large centres (Coffey and Shearmur
1998; Shearmur and Doloreux 2008). Large urban areas are thus better positioned than smaller
ones to export services. This is notably the case of health care, education, government, tourism,
administrative functions and a wide range of business services. The growth of the service sector
advantages large cities in another way. As services account for a rising share of consumption
expenditures at the expense of goods, in part due to cheap imported products, monetary leakages
out of a metropolitan region are reduced. More than goods, services tend to be produced within
the region and thus provide larger multiplier effects. The larger a metropolitan region, the more
extensive the range of available services, and the higher are the chances that service consumption
will take place within the region. Ultimately, by this logic, in a highly developed service
economy, even a narrow basic (export-driven) sector could be sufficient to sustain a vast
metropolitan economy. The global city perspective portrays metropolitan regions that are highly
service-dependent, characterized as they are by a service-oriented export sector and an extensive
and highly diversified consumption sector. But as Sassan (1991) observed, such a configuration
leads to a profound income and working condition gap between high- and low-order service
sector occupations.
It is important to stress that in their present “galactic” configuration, large urban areas
have become complex assemblages of overlapping commuter sheds and retail catchment areas
(Lewis 1983). As a growing proportion of commuter journeys focus on business parks located at
the edge of the urbanized perimeter, large urban areas acquire an extended zone of influence
(Coffey and Shearmur 2001). We can thus expect the growth of these urban areas to reverberate
throughout a wide surrounding sector of 100 kilometres or more. At the same time, however, the
propulsive effect of large urban centres on more distant manufacturing centres is on the wane, as
production increasingly opts for low-wage developing countries.
As regards policy-making, the last two decades have witnessed a sharp shift from
interventionism to neo-liberalism (Graham and Marvin 2001; Hackworth 2007; Leys 2001).
With most relevance to our object of study, this transition has resulted in trade liberalization and
an erosion of regional economic development and redistributive programs. Nominally, welfare
programs are still in place, but their impact is much reduced as a result of funding cutbacks and
an overall inability to keep up with housing and food cost inflation. Meanwhile, little is left of
the regional economic development instruments of the 1960s, 1970s and early 1980s (Brodie
1997). It deserves to be said, as well, that advancing de-industrialization has greatly reduced the
pool of large workplaces sensitive to regional economic development incentives.
A concerted conservative assault has triggered a shift from interventionist to neo-liberal
policy-making. Critiques of interventionist policies were made all the more convincing by the
lukewarm success of past interventionist efforts – limited decentralization of manufacturing
employment, difficulties in breaking the welfare dependency cycle and, worst of all, a ballooning
public sector debt attributed to profligate and ineffective state spending. One consequence of
neo-conservative attacks has been the near elimination from the political narrative of concern
over territorial justice, a popular theme thirty years ago.
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Trade liberalization was a key factor in the demise of regional economic development
programs as it is in present-day critiques of inter-provincial equalization payments. Once tariff
protection was breached, it became even more difficult than in the past for governments to
convince investors to locate in peripheral economic regions. Subsequently, to compete
successfully for investments, governments had to put forward sites with the most advantages to
investors. Once more, the car industry lends itself to an illustration of broad economic and policy
trends. There has been a full turn away from efforts to decentralize the car industry. Government
funding is now directed at Southern Ontario locations to support either the creation of new
facilities or the modernization of existing ones. What is more, with the lifting of tariffs and the
consequent opening of domestic markets to international competition, there has been less interest
for generally prosperous Ontario to contribute to equalization payments, since a declining
proportion of this money goes to the purchase of heartland industrial products. The drop in the
economic performance of de-industrializing Ontario relative to the Canadian norm further
contributes to this attitude. In fact, as of late 2008 Ontario qualifies as a beneficiary province
regarding equalization payments.
There is an additional facet of neo-liberalism with implications for the urban system.
Deregulation of transportation and the privatization of the Canadian National Railway and Air
Canada have ended cross-subsidization arrangements and resulted in deteriorated services in
small markets, with adverse consequences for their growth potential.
Turning to demography, we can expect that, increasingly, population trends will take an
active role in shaping the urban system (Bourne and Rose 2001). The demographic scene is
affected concurrently by low birth rates and growing reliance on immigration to sustain and
expand the workforce and population. Canada has experienced below replacement birth rates
since the early 1970s, which will soon translate into more retirements than entries in the job
market and, from 2020 onwards, more deaths than births (Bélanger, Martel and Caron-Malenfant
2005, 17; Statistics Canada 2006). Not only will Canadian urban areas be confronted with
negative natural growth, but in most cases they will no longer be able to tap surrounding rural
areas and small towns to expand or even maintain their population. Already, this source of
population has largely dried up. To be sure, some urban areas, especially retirement
communities, will benefit from inter-provincial migration flows as population ages. But in
virtually all cases, it is on immigration that urban areas will depend to maintain and expand their
population. Areas that are unable to attract immigrants will experience demographic decline,
with likely adverse economic consequences (Green and Green 2004). If present tendencies hold,
reliance on immigration will concentrate growth in a few large urban centres, while most of the
other urban areas will either stagnate or decline.
At present, about 70 percent of all immigrants settle in the three largest metropolitan
regions (McDonald 2004). Such a distribution pattern is partly explained by the presence of
employment opportunities, but also by ethnic communities hospitable to new immigrants
accounting for a rich multi-cultural environment. Over time, a gap may develop between
demographic and economic trends within these large cities, as sensitivity to welcoming social
environments eventually prevents immigrants from making location choices that are primarily
economically driven. Such a gap may already be partly responsible for a lagging median
household income growth, relative to other census metropolitan areas, in Toronto where
approximately fifty percent of all immigrants to Canada settle (Toronto Dominion 2002; 2007).
In the future, other important metropolitan regions beside the three largest will likely become
more welcoming to immigrants as they host more and larger ethnic communities. But urban
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areas with little appeal to immigrants will inevitably decline. This will especially be the case of
small urban centres.
Despite potential adjustment difficulties in the case of immigration and economic
activity, factors of urban evolution are interconnected. For example, economic globalization is
abetted by neo-liberalism while itself contributing to the adoption of neo-liberal policies. And in
the long run, migration and immigration are responsive to economic prosperity, in other words,
to the uneven capacity of urban areas to take advantage of, rather than being ravaged by, a
globalized economy.
The recent evolution of these factors suggests two potential, although not mutually
exclusive, urban system trajectories. There is first the possibility of a resurgence of the
hinterland, a consequence of rising demand for natural resources and an associated downfall in
heartland manufacturing. The other scenario would entail a growing discrepancy between
expanding large urban areas, benefitting from the ongoing rise of the service economy and the
presence of an important majority of immigrants, and stagnating or declining smaller urban
areas. Note that with the demise of redistributive policies in the wake of neo-liberalism, we can
expect a deeper polarization between growing and declining areas under either scenario, than
encountered over the interventionist decades.
Methodology
In this study of the urban system, census metropolitan areas as well as census agglomerations
with a population floor of approximately 60,000 are considered.1 We set this minimum value to
avoid the steep population gyrations that often characterize smaller places. This approach is,
however, responsible for incomplete time series data for centres whose population reached this
threshold after 1971.2
Census data are used to verify the extent to which anticipated trends have actually
materialized. Time series data from 1971 to 2006 depict the evolving balance between heartland
and hinterland, and between large and small urban centres. They provide historical background
for the interpretation of current tendencies and attempts at forecasting the future of the urban
system. Change in employment structure between 1996 and 2006 is explored, with particular
attention to categories with strong growth potential. And, in an effort to anticipate differences in
the future evolution of urban areas under consideration, their 2006 employment sector
distribution, age structure and presence of immigrants and inter-provincial migrants are assessed.
The large urban area category includes the five census metropolitan areas with a 2006 population
exceeding the million: Toronto, Montréal, Vancouver, Ottawa-Gatineau,3 Calgary and
Statistics Canada defines census metropolitan areas and census agglomerations as follows: “A census metropolitan
area (CMA) or a census agglomeration (CA) is formed by one or more adjacent municipalities centred on a large
urban area (known as the urban core). The census population count of the urban core is at least 10,000 to form a
census agglomeration and at least 100,000 to form a census metropolitan area. To be included in the CMA or CA,
other adjacent municipalities must have a high degree of integration with the central urban area, as measured by
commuting flows derived from census place of work data.” (Statistics Canada n.d.)
2
Over time, Statistics Canada adjust the boundaries of CMAs and CAs to reflect changes in commuting patterns;
such changes generally have limited effect on population totals.
3
Known as Ottawa-Hull in earlier censuses.
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Edmonton. This category also incorporates census metropolitan areas immediately adjacent to
the top five CMAs. Oshawa and Hamilton, both bordering Toronto, are included from 1971
onwards, and St-Jean-sur-Richelieu and Abbotsford, adjacent respectively to Montréal and
Vancouver, are added to the large city category from 1996, when they were first constituted as
census metropolitan areas. All other centres are referred to as small urban areas.
Canadian Urban System Trajectories
Between 1971 and 1986, the hinterland experiences a faster population, employment and income
growth than the heartland, partly a reflection of high energy prices and a robust demand for other
commodities over this period (Tables 1, 2 and 3 and Figures 2, 3 and 4). Another contributing
factor may have been the impact of the especially slow demographic and economic growth over
this period of Montréal, Canada’s largest metropolitan region until 1976. Along with a departure
of Anglophones, Montréal adjusted to a shrinking of its long-established Canada-wide zone of
economic influence (shared with Toronto) to one that is limited to the Province of Québec
(Higgins 1986; Polèse and Shearmur 2004). The urban system situation changes as the
demographic growth rates of the hinterland and heartland converge over the 1986-1996 and
1996-2006 periods (Table 1 and Figure 2). However, between 1986 and 1996, the hinterland
maintains its advantage over the heartland in terms of employment growth, but registers a similar
rate of job creation as the heartland over the subsequent period (Table 2 and Figure 3). Finally,
income follows the same convergent trajectory as population, recording a near absence of growth
in both the hinterland and heartland over the largely recessionary 1986-1996 period, only to
recover afterwards at about the same rate in both regions (Table 3 and Figure 4).
The three tables and figures point to a period of hinterland catching up, followed by
equivalent growth rates in the two regions. Note, however, that the tables indicate a variety of
evolutionary patterns among hinterland and heartland urban areas. In both cases, as some urban
areas experience rapid growth, others either stagnate or, indeed, decline. In the heartland such a
situation is accounted for by the divergent performance of different industrial sectors,
particularly the contrast between sunrise and sunset industries, whereas in the hinterland, varying
growth levels are driven by the absence of synchrony in demand cycles for different natural
resources – the lack of coincidence in demand peaks and valleys for oil and lumber, for example.
Another factor of hinterland-heartland convergence may be the strong growth of large urban
areas, irrespective of their regional location.
The trend revealed by the comparison of large and small urban areas is sharper than the
one that emerges from our observation of heartland-hinterland distinctions. Large cities
experience more rapid growth on all three variables over all periods, with the sole exception of
income over the economically troubled 1986-1996 period (Figures 2, 3 and 4). Population
growth discrepancy between large and small urban areas increases after 1986, partly due to a
post-1986 Montréal rebound. But differences in the growth rate of the two other variables remain
largely constant over the entire 1971-2006 period. The methodology may in fact underestimate
the large city category growth advantage, for a number of fast growing urban areas classified
within the small urban area category – Peterborough, Guelph, Kitchener and Brantford – are in
the orbit of the Toronto metropolitan region and thus benefit from its propulsive effect (Coffey
and Polèse 1988; Polèse and Shearmur 2006a; Phelps, Fallon and Williams 2001; Portnov 2006;
Shearmur and Polèse 2005).
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Table 4 and Figure 5, which monitor the evolution of employment categories between
1996 and 2006, paint a similar picture to that of previous tables and figures.4 For one, while
disproportionately affected by manufacturing employment losses, the hinterland experienced
faster growth than the heartland in two employment categories with an important knowledge
content and economic growth potential: management occupations and natural and applied
sciences and related occupations. For another, these two employment categories along with
occupations in arts, culture, recreation and sport (a sector of employment that contributes to the
appeal of an urban area for knowledge workers), grew much more rapidly in large than in small
urban areas.
To help forecast future trends, the next three tables and the next figure concentrate on
2006 variables that point to future economic and demographic trajectories. Table 5 and Figure 6
show little difference between heartland and hinterland urban areas in the concentration of
management occupations, natural and applied sciences and related occupations, and of
occupations in arts, culture, recreation and sport. Yet, as expected, Table 5 and Figure 6 do
present important variations in primary and manufacturing sector employment between these two
regions. Concentration of manufacturing employment is much higher in the heartland than in the
hinterland, and the opposite holds for primary sector employment. But even in the hinterland,
primary sector employment as a proportion of all employment is low; manufacturing
employment is declining everywhere. Evolutionary trends identified in Table 4 and Figure 5 are
reflected in an overrepresentation of management occupations, natural and applied sciences and
related occupations, and of arts, culture, recreation and sport occupations in large relative to
small cities. All large urban areas score near or above the national average for these three
occupation categories, with the exception of arts, culture, recreation and sport occupations in
Calgary and Edmonton. Table 5 also indicates that, with the exception of Ottawa, heartland large
metropolitan regions record a presence of manufacturing employment that exceeds the national
average, while posting a below average presence of primary industry jobs. The three large
hinterland urban areas, all located in Western Canada, register primary employment levels above
the national norm and manufacturing employment below this level.
Alongside the concentration of propulsive employment sectors, demographic features
allow us to forecast future growth in the listed urban areas. Table 6 shows that the age profiles
of large metropolitan regions are, as expected, less extreme than those of small urban areas.
Large urban areas tend to approximate the national distribution, with somewhat of an older
profile in Montréal and a younger one in Calgary and Edmonton. The most striking observation
to emerge from Table 6 concerns the aging profile of the population of many small urban areas
(see Statistics Canada 2007). These fall into three categories: 1) Economically struggling
hinterland urban areas, which have lost much of their working age population and thus people in
the child-rearing age (Chicoutimi-Jonquière, Sault Ste Marie, Thunder Bay and Nanaimo); 2)
Urban areas in the heartland, which are facing similar demographic circumstances because of deindustrialization (Trois-Rivières, Kingston, Peterborough and Sarnia); 3) Retirement
communities (Kelowna and Kamloops).
Québec City is in a category of its own because it is the largest metropolitan region with
such an aging population. The aging pattern of Québec City cannot be attributed primarily to a
poor performance of national resource industries or the loss of manufacturing activity, but rather
more likely to the combined effect of a low birth rate, the depletion of the regional basin from
4
It is for reasons of consistency in Statistics Canada employment categories that we focus on a ten year period in
Table 4 and Figure 5.
12
which it traditionally drew its population and, we will see in Table 7, a low presence of
immigrants and inter-provincial migrants.
After decades of below-replacement birth rates, only migration and immigration can
maintain or increase the population of urban areas. Thus, those areas capable of attracting
migrants and immigrants will see their population grow or remain stable, while the ones that are
unable for a variety of reasons to lure new residents will inevitably experience a downward trend
at some point over the next twenty years. Table 1 has offered a foretaste of things to come by
listing seven urban areas in decline between 1996 and 2006, whereas only one area faced similar
circumstances over either the 1971-1986 or 1986-1996 periods. Table 7 indicates very low interprovincial migration with Province of Québec urban areas as a destination, a consequence of
linguistic differences with the rest of Canada. Even Montréal, which pulls in large numbers of
immigrants, registers an exceptionally low presence of inter-provincial migrants. Windsor and
Sault Ste Marie also benefit little from inter-provincial migration.
Immigration is more vital than inter-provincial migration because it provides a larger
influx of population. Table 7 reveals important discrepancies in levels of immigration. It shows
that immigration contributed little to the population of urban areas east of Montréal, to small
centres in Southern Ontario (Belleville and Peterborough), to Northern Ontario communities
(North Bay and Sudbury), to small Prairies urban areas and to Prince George in Northern British
Columbia. The tendency is for large urban areas to post the highest proportion of immigrants
(this is especially the case for Toronto and Vancouver) and for the small ones to register a lower
presence of immigrants, although with important regional differences.
Unless they experience a sharp change in their level of immigration, all urban areas with
a low score will be in a perilous demographic situation over the coming decades. This will
particularly be the case for the numerous urban areas that combine low inter-provincial migration
and especially immigration, with an older age profile: Moncton, St John, Chicoutimi-Jonquière,
Québec City, Sherbrooke, Trois-Rivières, Belleville, Peterborough, North Bay, Sudbury, Sault
Ste Marie and Thunder Bay.
The Coming Polarization of the Canadian Urban System
Findings question past conceptualizations of growth dynamics within the Canadian urban
system. The heartland-hinterland distinction seems to be on the wane, with the hinterland in a
catching up phase between 1971 and 1986 but then experiencing a general stabilization of its
growth level at the same rate as that of the heartland. Of course, demand cycles for different
natural resources have played a role, but present and anticipated long-term, structural factors
point to an ongoing robust demand for natural resources. As the heartland-hinterland divide
dissipates, the large city-small city discrepancy widens. We anticipate that differences between
these two groups of cities will be the major force shaping the future Canadian urban system.
There is, to be sure, a persistent difference in the respective presence of primary and
manufacturing sector employment in large heartland and hinterland urban areas, but it is largely
the extensive service sector (both in terms of size and specialization) they share, that accounts for
their rapid growth. In this light, the future of Canada will take the form of a clustering of
population in a few large centres, at the expense of the remainder of the urban system.
Polarization is the dominant theme to emerge from this study. As large centres will enjoy
rapid growth, many small ones will decline. These contrasting trajectories will be propelled by
multiple causation mechanisms responsible for durable ascending and descending trends (Myrdal
13
1963). In large urban areas, growing labour and consumer markets will attract investment, which
in turn will further stimulate these markets. Also, with economic and demographic expansion
comes additional political influence, which secures government interventions favourable to
further growth. An opposite sequence of events will maintain a descending course in many small
urban areas. If growth abets growth, decline abets decline.
Conditions are thus present for a bifurcated demographic and economic evolution of the
Canadian urban system. The coming age will be one of extremes, especially given reduced
government capacity and determination to counteract territorial decline in a neo-liberal policy
environment. The Canadian urban system of tomorrow will be polarized, confronted at once with
steep urban growth and decline (Polèse and Stren 2000). In this perspective, the future will
advantage Toronto, Montréal, Vancouver, Ottawa-Gatineau, Calgary and Edmonton. Urban areas
within the orbit of these regions will also enjoy rapid growth. There will be other expanding
settlements, but they will account for a minute share of national urban growth. This will be the
case of resource-based centres benefitting from international demand cycles and retirement
communities such as Kelowna and Victoria. Having seen how the economy, policy and
demography have driven the evolution of the Canadian urban system, we now look at how these
three aspects of society will be affected by the future configuration of this system. Such a
polarized urban system will introduce economic rigidities hindering labour force adjustments to
changing economic trends. On the one hand, economic victims of small urban area decline will
find it difficult to move to large centres, where cost of living and especially that of housing far
exceed those of small centres. At the same time, large urban areas themselves may at times face
a labour force oversupply due to their strong attractive power on immigrants. In these
circumstances, their ability to draw immigrants, associated with their advanced cosmopolitanism,
would exceed their job creation capacity.
From a policy perspective, governments will be confronted simultaneously with demands
for interventions that are supportive of growth and measures to either reverse decline or attenuate
its consequences. Large urban centres will call for extended infrastructure networks to
accommodate growth along with expanded services to cater to their swelling population. Large
city lobbies will use their rising political clout to pressure senior governments for additional
financial support. A coalition of large city mayors is pressing for additional senior government
physical and social infrastructure investments in order to maintain a healthy social climate and a
well-performing economy (Globe and Mail June 2, 2006; Toronto Star May 5, 2007). It stresses
the central role these centres play in the Canadian economy, and thus the need to take necessary
measures to maintain their economic vitality (see also Conference Board of Canada 2006; 2007).
Significantly, large city mayors underscore distinctions between requirements of their cities and
those of smaller urban areas, and thus the need for a special treatment for large cities on the part
of senior governments (Toronto Star September 17, 2004).
The concentration of population in large urban centres will represent a source of tensions
within provincial structures of government, as the political weight of large urban centres within
provinces will increase at the expense of small centres and rural areas. Provincial governments
will be loathe (as they presently are) to create powerful metropolitan-wide administrations, for
fear that they could become a source of political competition.
The situation is different in small urban areas, many of which will clamour for
interventions to address their decline. In doing so, they will be confronted with obstacles. First,
there is little evidence of government capacity to arrest economic decline. We have seen that in
the past regional economic development programs met with lukewarm success. What is more,
14
there is no effective planning model to deal with declining economic activity and population
(Andersen 2005; Polèse and Shearmur 2006b; Rieniets 2005). What is an urban area to do in the
face of a downward demographic and economic trend and resulting shrinking financial
resources? Selectively close down neighbourhoods to consolidate the remaining population or
lower infrastructure and service standards (more or less) evenly throughout its territory? It is also
important to recall the prevalence of a neo-liberal ideological climate suspicious of ambitious
government interventions. In sum, even if senior governments were willing to intervene, their
capacity to deal effectively with decline would be uncertain. In any event, given the depleted
political clout that comes with a falling population and economic activity, it is unlikely that small
urban areas experiencing decline will be capable of convincing senior governments to expend
large amounts of resources to redress their demographic and economic conditions or, even
minimally, to assuage these conditions.
Finally, anticipated demographic trajectories will result in deepening social and cultural
contrast between large urban areas with their rising presence of immigrants, and the remainder of
the country, where the proportion of people born in Canada will remain very high. The
distinction between large diversified cities and small culturally homogenous urban areas in
decline will be particularly sharp. There is danger that such a polarized social environment will
eventually translate in cultural and political clashes.
Conclusion
Findings challenge the enduring effectiveness of the heartland-hinterland perspective as an
explanation of uneven development in the Canadian urban system. Evidence of heartland growth
advantages over the hinterland dissipates from 1971 onwards. The interpretation of past trends
and present statistics suggests a much transformed Canadian urban system in the future. The
article explored the possibility of a hinterland revival that would take it back to a staples oriented
model of development. While robust world-wide demand for commodities would appear to
support such a development pattern, statistics on the evolution of the Canadian urban system do
not point to hinterland revival as the main trend affecting the evolution of the urban system.
Absence of strong growth across the entire hinterland is due to jarring demand cycles for
commodities and the low employment creation potential of resource harvesting and extraction,
relative to the manufacturing and service sectors. It rather appears that changes affecting the
economy, policy-making and demography will result in a highly polarized pattern consisting of a
few large urban areas experiencing high rates of growth and numerous smaller centres caught in
a cycle of decline. The transition is driven by a rise of the service sector within the economy,
which advantages large metropolitan regions, and a preference of immigrants for these regions.
Diminished redistribution policies will prevent any significant growth deflection away from
these centres, which could attenuate progressing polarization.
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18
Table 1: Population Change 1971-2006
St John’s1, 2
Halifax1, 2
Moncton1, 2
St John1, 2
ChicoutimiJonquière1, 2
Québec2, 3
Sherbrooke2, 3
Trois-Rivières2, 3
St-Jean-surRichelieu3, 4
Montréal3, 4
Ottawa-Hull3, 4
Kingston2, 3
Belleville2, 3
Peterborough2, 3
Oshawa3, 4
Toronto3, 4
Hamilton3, 4
St Catharines2, 3
Kitchener2, 3
Brantford2, 3
Guelph2, 3
London2, 3
Windsor2, 3
Sarnia2, 3
Barrie3, 4
North Bay1, 2
Sudbury1, 2
Sault Ste Marie1, 2
Thunder Bay1, 2
Winnipeg1, 2
Regina1, 2
Saskatoon1, 2
Lethbridge1, 2
Calgary1, 4
Red Deer1, 2
Edmonton1, 4
Kelowna1, 2
Kamloops1, 2
Abbotsford1, 4
Vancouver1, 4
Victoria1, 2
Nanaimo1, 2
Prince George1, 2
Population
1971
Population
1986
Population
1996
Population
2006
131805
222650
161901
295990
102084
121265
158468
174051
332518
113491
125705
160454
181113
372858
126424
122389
151643
480500
84570
97925
603267
129960
128888
671889
147384
139956
76461
715515
186952
141529
87492
2743175
602520
85880
2921357
819263
122350
63540
120325
2627980
498520
303425
226840
80280
62665
285990
258650
78430
87083
203543
3427168
557029
343258
311195
90521
85962
342302
253988
85700
3326510
1010498
143416
93442
100193
268773
4263757
624360
372406
382940
100238
105420
398616
278685
86480
118695
64785
160488
83619
125562
667209
193652
219056
63053
821628
60075
862597
136541
84914
136480
1831665
304287
85585
75150
3635571
1130761
152358
91518
116570
330594
5113149
692911
390317
451235
124607
127009
457720
323342
88793
177061
63424
158258
80098
122907
694668
194971
233923
95196
1079310
82772
1034945
162276
92882
159020
2116581
330088
92361
83225
106760
155415
81270
112090
540245
140720
126455
403300
57422
148877
84617
122217
625304
186521
200665
58841
671326
495700
785465
89730
61773
1082280
195795
1380729
255547
67621
%
change
19711986
22.83
32.94
%
change
19861996
7.5
12.34
11.17
3.66
1.25
%
change
19962006
4.06
12.13
11.4
-2.64
-5.49
%
change
19712006
37.41
67.46
25.55
53.67
31.62
11.38
13.41
8.59
6.49
26.85
1.12
14.43
48.91
121.06
44.53
6.5
35.97
42.47
13.87
23.34
17.22
32.53
87.67
77.41
37.05
69.16
30.41
11.74
13.13
37.19
12.76
37.18
19.69
-1.8
9.27
15.05
32.05
24.41
12.09
8.49
23.05
10.73
22.64
16.45
9.72
0.91
9.29
11.9
6.24
-2.06
16.35
23
19.92
10.98
4.81
17.83
24.31
20.48
14.83
16.02
2.67
49.17
-2.1
-1.39
-4.21
-2.11
4.12
0.68
6.79
50.98
31.36
37.78
19.98
18.85
9.38
16.52
15.56
8.48
7.92
10.75
13.59
-4.21
4.12
9.03
15.74
32.55
58.68
66.46
12.82
7.8
-1.18
2.74
6.7
3.82
9.17
7.16
22.39
58.46
9.82
52.17
37.46
27.58
30.52
32.66
19.07
11.13
19
14.64
83.46
174.75
94.57
38.99
28.64
98.92
55.22
102.68
60.05
25.01
13.21
1.83
-1.44
9.65
28.58
38.55
84.99
167.62
108.78
95.57
68.59
1 Hinterland
2 Small urban area (2006 population less than 1 million)
3 Heartland
4 Large urban area (census metropolitan area with 2006 population of more than 1
million or adjacent census metropolitan areas)
20
Table 2: Employment Change 1971-2006
St John’s1, 2
Halifax1, 2
Moncton1, 2
St John1, 2
ChicoutimiJonquière1, 2
Québec2, 3
Sherbrooke2, 3
Trois-Rivières2, 3
St-Jean-surRichelieu3, 4
Montréal3, 4
Ottawa-Hull3, 4
Kingston2, 3
Belleville2, 3
Peterborough2, 3
Oshawa3, 4
Toronto3, 4
Hamilton3, 4
St Catharines2, 3
Kitchener2, 3
Brantford2, 3
Guelph2, 3
London2, 3
Windsor2, 3
Sarnia2, 3
Barrie3, 4
North Bay1, 2
Sudbury1, 2
Sault Ste Marie1, 2
Thunder Bay1, 2
Winnipeg1, 2
Regina1, 2
Saskatoon1, 2
Lethbridge1, 2
Calgary1, 4
Red Deer1, 2
Edmonton1, 4
Kelowna1, 2
Kamloops1, 2
Abbotsford1, 4
Vancouver1, 4
Victoria1, 2
Nanaimo1, 2
Prince George1, 2
Employment
1971
Employment
1986
Employment
1996
Employment
2006
45260
90410
66835
148215
44300
49540
58705
74930
163035
54095
53390
63905
88130
199555
66565
59035
69175
168690
30100
31610
270505
57770
51060
315045
66645
58670
34340
383465
91665
65715
45265
1007385
248600
35270
1348190
426765
60330
25305
46580
1177535
200470
117870
100795
33150
26515
122915
97945
30465
40600
102180
1870765
274260
158555
162050
41425
44660
174885
116695
40310
1502380
502070
66850
41050
43135
126865
2061615
294225
165230
192055
45380
54690
190405
130770
38165
56895
28385
70170
34860
57765
324745
96400
107150
31190
441575
30130
434020
62480
40475
60645
908320
148890
38285
37490
1835840
601540
74930
44475
56665
170020
2627350
347490
192400
243340
63475
69700
235430
152990
43050
93410
29835
75340
36720
59250
366430
106425
125530
50425
632020
48770
583215
82005
47910
79665
1104760
175055
44260
44490
40155
59490
30605
43605
229635
58220
49745
167425
25435
62630
35950
57555
310860
92960
96390
27765
352435
206055
392950
35635
26945
440220
75865
670805
114255
30020
21
%
change
19711986
47.67
63.94
%
change
19861996
12.11
10.00
22.11
7.77
8.86
%
change
19962006
17.62
22.4
23.05
10.57
8.25
%
change
19712006
94.72
120.72
60.36
91.93
61.53
16.47
15.36
14.9
21.72
37.54
12.01
31.81
127.32
204.53
107.89
33.83
71.67
71.05
11.44
17.65
10.81
82.24
141.97
112.45
60.44
119.36
58.87
36.81
34.52
60.77
24.96
68.43
42.28
19.14
32.32
6.24
24.16
10.20
7.28
4.21
18.52
9.55
22.46
8.87
12.06
-5.32
22.2
19.81
12.09
8.34
31.37
34.02
27.44
18.1
16.44
26.7
39.87
27.45
23.65
16.99
12.8
64.18
5.11
7.37
5.34
2.57
12.84
10.4
17.15
61.67
43.13
61.87
34.38
31.25
18.37
31.36
21.63
17.57
15.61
18.67
23.37
5.28
17.46
31.99
35.37
59.67
93.77
110.50
11.6
12.04
-3.03
0.36
4.47
3.7
11.16
12.34
25.29
90.70
10.45
75.33
50.21
52.38
50.60
35.41
30.31
24.88
47.02
123.93
265.01
123.12
73.34
63.23
141.42
91.48
162.87
91.54
56.2
41.31
26.64
19.98
35.88
59.57
82.8
152.35
277.49
183.04
150.96
130.75
See notes at the bottom of Table 1.
22
Table 3: Average Household Income Change 1976-2006 (in 2005 dollars)
St John’s1, 2
Halifax1, 2
Moncton1, 2
St John1, 2
ChicoutimiJonquière1, 2
Québec2, 3
Sherbrooke2, 3
Trois-Rivières2, 3
St-Jean-surRichelieu3, 4
Montréal3, 4
Ottawa-Hull3, 4
Kingston2, 3
Belleville2, 3
Peterborough2, 3
Oshawa3, 4
Toronto3, 4
Hamilton3, 4
St Catharines2, 3
Kitchener2, 3
Brantford2, 3
Guelph2, 3
London2, 3
Windsor2, 3
Sarnia2, 3
Barrie3, 4
North Bay1, 2
Sudbury1, 2
Sault Ste Marie1, 2
Thunder Bay1, 2
Winnipeg1, 2
Regina1, 2
Saskatoon1, 2
Lethbridge1, 2
Calgary1, 4
Red Deer1, 2
Edmonton1, 4
Kelowna1, 2
Kamloops1, 2
Abbotsford1, 4
Vancouver1, 4
Victoria1, 2
Nanaimo1, 2
Prince George1, 2
Income 1976
Income
1986
Income 1996
Income 2006
47437
53974
60860
62094
55347
51672
54446
58727
58578
55289
53648
49915
65852
66325
59995
61234
55552
52398
47186
46324
55884
49059
48744
53359
47180
47768
48795
60884
53301
51683
57928
52580
62351
54406
56183
69596
59335
53167
54695
63128
56213
51178
55125
49730
54527
54899
58110
58477
55842
68910
73143
62387
57054
60807
53715
61263
59395
61515
64726
54403
69247
60394
56604
56246
70944
73334
65464
57428
65260
57212
65970
61338
65926
63713
63796
56154
60280
56758
61965
55763
59354
54885
55564
69331
57743
60888
56318
60960
60455
65947
61366
54938
68110
63038
80838
69185
60372
65316
82205
87820
76787
65053
78223
67694
77920
70345
72796
72448
76128
61159
68071
62487
64470
64533
68280
66059
64257
98253
77761
79163
64515
63797
66041
73258
67838
57819
69859
46072
63368
56717
51684
50700
48661
46674
56699
55087
59042
58004
61907
56911
62144
57241
55726
69345
55400
63262
50101
56234
53830
48251
61346
53851
61855
23
%
change
19711986
28.3
15.04
%
change
19861996
-3.5
-5.66
-0.1
3.83
-8.32
%
change
19962006
12.13
13.22
8.51
14.14
11.29
%
change
19712006
38.82
22.88
6.65
3.97
5.23
-4.52
-3.83
-2
14.1
12.97
8.2
18.72
16.2
12.96
11.57
6.85
11.62
9.06
-3.17
-0.5
1.78
19.89
29.65
27.16
5.03
25.99
15.86
10.98
11.48
10.31
8.01
12.35
8.19
5.86
10.69
0.72
2.95
0.26
4.93
0.66
7.32
6.51
7.68
3.27
7.17
-1.56
15.87
16.74
14.56
6.66
16.13
15.87
19.75
17.3
13.28
19.86
18.32
18.11
14.68
10.42
13.71
19.33
8.91
12.92
10.09
4.04
15.73
15.04
20.36
15.65
41.72
34.67
30.01
14.56
4.65
9.24
11.09
10.55
5.24
2.57
12.15
-11.56
2.27
19.78
12.25
27.71
22.64
22.3
1.94
7.56
-2.15
0.09
-2.02
-4.49
-4.11
-0.29
-0.02
14.19
-3.75
12.41
8.4
13.96
11.61
7.5
13.96
10.11
32.91
22.85
50.3
39.11
36.6
27.11
41.9
36.12
42.9
28.13
25.27
23.89
7.42
10.17
24.74
27.28
40.32
41.53
73.29
42.89
36.09
40.59
See notes at the bottom of Table 1.
24
Table 4: Percent Change in the Number of Workers in Different Employment Sectors 1996-2006*
St John’s1, 2
Halifax1, 2
Moncton1, 2
St John1, 2
ChicoutimiJonquière1, 2
Québec2, 3
Sherbrooke2, 3
Trois-Rivières2, 3
St-Jean-surRichelieu3, 4
Montréal3, 4
Ottawa-Hull3, 4
Kingston2, 3
Belleville2, 3
Peterborough2, 3
Oshawa3, 4
Toronto3, 4
Hamilton3, 4
St Catharines2, 3
Kitchener2, 3
Brantford2, 3
Guelph2, 3
London2, 3
Windsor2, 3
Sarnia2, 3
Barrie3, 4
North Bay1, 2
Sudbury1, 2
Sault Ste Marie1, 2
Thunder Bay1, 2
Winnipeg1, 2
Regina1, 2
Saskatoon1, 2
Lethbridge1, 2
Calgary1, 4
Red Deer1, 2
Edmonton1, 4
Kelowna1, 2
Kamloops1, 2
Abbotsford1, 4
Vancouver1, 4
Victoria1, 2
Nanaimo1, 2
Prince George1, 2
Total
Total
Employment
Management
Business
etc.
Health
10.25
13.10
26.40
17.12
-5.47
Natural
science
etc
54.90
59.33
80.97
88.89
33.11
17.62
22.40
23.05
10.57
8.25
19.12
28.10
30.10
12.94
-0.56
21.72
37.54
12.01
31.81
22.20
19.81
12.09
8.34
31.37
34.02
27.44
18.10
16.44
26.70
39.87
27.45
23.65
16.99
12.80
64.18
5.11
7.37
5.34
2.57
12.84
10.40
17.15
61.67
43.13
61.87
34.38
31.25
18.37
31.36
21.63
17.57
15.61
18.67
24.22
Arts
etc
Sales and
service
Trades
etc
Primary
Manufacturing
and utilities
21.39
34.85
34.28
21.01
25.06
Social
Science
etc
26.72
60.23
28.81
20.33
22.00
24.55
33.74
13.83
-9.77
-14.47
3.90
5.86
10.31
1.06
2.98
14.42
19.18
7.71
-7.66
19.20
34.34
31.86
12.36
-21.90
6.87
-5.06
0.80
-12.32
-33.97
-28.75
6.06
48.31
4.23
3.55
6.21
26.43
-2.46
21.14
44.52
47.75
8.92
68.47
27.60
29.19
14.55
49.75
50.10
50.96
32.46
77.85
27.85
48.27
37.30
16.67
9.09
27.78
12.43
15.80
26.58
62.40
9.88
57.63
10.55
55.13
29.41
-16.79
-2.65
4.82
-10.83
0.84
26.91
8.88
2.77
-4.07
40.21
61.58
35.12
33.61
26.05
32.61
41.15
50.21
17.67
25.23
12.71
80.50
7.39
6.85
10.42
6.26
25.22
21.77
33.11
62.95
64.24
70.02
48.69
53.22
21.60
44.48
26.49
19.09
24.18
35.11
29.91
9.75
8.43
16.23
9.41
16.68
25.54
14.42
5.99
7.65
19.58
37.07
25.61
11.53
5.05
7.98
45.47
-6.48
8.01
0.40
-4.26
5.16
2.73
8.10
39.09
27.28
51.41
21.02
22.65
19.59
13.19
6.50
5.67
6.74
8.98
12.40
45.65
46.04
46.76
91.40
65.08
59.58
76.33
44.90
32.01
83.90
76.74
55.59
72.14
87.31
22.00
106.29
16.80
34.74
50.96
18.20
47.37
38.43
46.89
77.82
91.25
104.31
70.01
63.27
75.91
80.77
64.82
46.85
17.33
27.20
60.70
25.69
24.31
23.82
9.07
38.67
43.95
37.74
31.63
29.49
53.92
59.63
30.36
33.54
32.47
21.21
96.61
24.71
22.77
27.51
21.95
29.01
19.71
35.76
102.81
68.86
60.95
57.19
47.09
24.43
37.69
36.84
24.27
48.41
69.93
34.84
60.11
59.07
29.89
17.15
55.96
73.81
53.83
43.16
28.41
45.24
70.24
52.83
45.47
47.32
24.95
84.11
21.03
36.87
17.52
20.16
42.53
38.59
48.06
65.75
66.42
43.20
55.24
46.59
31.47
56.68
49.02
30.06
28.14
49.62
51.14
30.92
25.67
24.94
23.81
32.37
79.18
35.41
33.33
24.59
22.54
22.05
43.97
17.54
33.41
6.37
75.20
-0.84
39.76
0.00
10.51
20.20
15.10
6.96
41.61
56.97
28.48
25.86
52.55
31.64
16.35
41.74
40.88
44.21
6.62
32.67
15.06
6.67
-1.76
-7.62
21.02
26.96
13.89
9.51
20.82
14.81
24.36
8.57
8.12
15.96
5.42
48.68
-5.92
-5.42
-0.98
-0.49
-1.99
-4.04
-0.78
31.06
15.61
25.16
8.91
11.31
-0.11
12.55
9.76
4.87
7.08
-1.61
11.10
26.52
16.78
14.63
20.37
38.43
39.70
33.79
30.71
17.50
41.14
66.74
41.43
36.08
14.67
16.76
82.62
13.73
4.28
-3.65
-8.14
11.14
17.09
26.71
82.85
58.82
95.96
63.67
42.57
18.83
40.61
18.03
21.74
13.39
27.10
30.10
12.95
7.64
-6.82
-19.93
32.13
20.45
26.46
28.81
5.55
9.74
112.16
7.09
13.62
20.22
20.28
17.87
22.11
-15.19
6.40
17.11
-0.82
-17.15
-0.68
196.46
23.93
88.72
14.68
9.96
4.50
28.18
6.20
2.93
-18.73
5.76
15.16
-21.41
-10.21
-25.19
1.32
3.49
-11.22
7.52
-20.30
-31.32
-2.60
-0.40
10.00
13.81
-4.24
-15.59
41.85
-27.10
-37.79
-40.63
-40.98
-10.64
-21.12
-4.60
71.12
-1.54
63.00
-18.78
-13.64
-12.30
8.78
-1.67
-15.32
-18.21
-12.46
-6.21
*The full definition of the employment categories are: a) management occupations; b) business,
finance and administrative occupations; c) natural and applied sciences and related occupations;
d) health occupations; e) occupations in social science, education, government service and
religion; f) occupations in art, culture, recreation and sport; g) sales and service occupations; h)
trades, transport and equipment operators and related occupations; i) occupations unique to
primary industry; j) occupations unique to processing, manufacturing and utilities.
25
See notes at the bottom of Table 1.
26
Table 5: Percent of Workers in Selected Employment Categories 2006*
Management
St John’s1, 2
Halifax1, 2
Moncton1, 2
St John1, 2
ChicoutimiJonquière1, 2
Québec2, 3
Sherbrooke2, 3
Trois-Rivières2, 3
St-Jean-surRichelieu3, 4
Montréal3, 4
Ottawa-Hull3, 4
Kingston2, 3
Belleville2, 3
Peterborough2, 3
Oshawa3, 4
Toronto3, 4
Hamilton3, 4
St Catharines2, 3
Kitchener2, 3
Brantford2, 3
Guelph2, 3
London2, 3
Windsor2, 3
Sarnia2, 3
Barrie3, 4
North Bay1, 2
Sudbury1, 2
Sault Ste Marie1, 2
Thunder Bay1, 2
Winnipeg1, 2
Regina1, 2
Saskatoon1, 2
Lethbridge1, 2
Calgary1, 4
Red Deer1, 2
Edmonton1, 4
Kelowna1, 2
Kamloops1, 2
Abbotsford1, 4
Vancouver1, 4
Victoria1, 2
Nanaimo1, 2
Prince George1, 2
10.60
11.43
10.07
8.94
7.67
Natural
science etc
8.69
7.38
6.14
7.63
7.21
Art etc
Primary
3.17
3.80
2.66
1.96
1.97
2.02
1.49
1.50
1.81
2.25
Manufacturing
and utilities
2.24
2.21
3.21
3.23
5.46
8.69
8.64
8.24
8.38
8.85
5.91
5.58
5.84
3.49
2.80
2.55
2.01
1.09
1.98
2.18
1.20
3.40
8.31
7.77
9.25
10.81
11.62
9.65
8.75
9.23
10.65
12.20
11.05
9.32
9.84
8.86
10.04
9.18
8.48
7.83
10.85
10.22
8.39
7.94
8.46
9.68
9.96
9.43
8.98
11.41
8.84
10.06
11.88
9.23
9.19
11.80
11.09
10.27
8.82
7.91
12.18
6.35
6.00
5.51
6.29
8.54
6.16
4.33
7.81
4.19
7.39
5.97
6.13
7.67
5.09
4.89
5.30
7.50
5.54
6.35
6.80
6.30
4.69
11.54
5.34
7.39
4.69
6.02
3.83
7.70
7.78
5.35
5.52
4.30
4.47
3.21
2.05
2.81
2.71
4.09
2.77
2.58
2.40
1.87
2.91
2.53
2.02
1.94
2.34
1.98
2.36
2.23
2.40
2.99
3.22
2.69
2.26
3.03
2.08
2.65
2.92
2.43
1.92
4.31
4.19
3.10
1.63
0.82
1.26
1.92
2.48
2.90
1.71
1.00
2.34
3.85
1.57
3.71
1.95
2.66
1.79
2.96
1.84
1.94
5.00
1.81
3.00
1.48
2.29
4.04
6.64
2.00
7.55
2.90
4.58
4.36
9.11
1.86
2.41
3.33
4.74
5.79
1.60
2.58
10.39
6.28
8.42
7.43
6.83
6.54
12.17
11.86
13.41
8.49
13.94
6.23
7.46
3.20
2.28
4.62
3.67
5.79
2.12
4.13
4.70
3.14
4.56
3.19
3.98
3.50
6.77
4.15
1.67
3.20
5.77
Total
10.84
7.90
3.56
1.77
5.64
*See Table 4 note for a full definition of the employment categories and notes at the bottom of Table
1.
27
Table 6: Percent of Population in Different Age Groups 2006
St John’s1, 2
Halifax1, 2
Moncton1, 2
St John1, 2
ChicoutimiJonquière1, 2
Québec2, 3
Sherbrooke2, 3
Trois-Rivières2, 3
St-Jean-surRichelieu3, 4
Montréal3, 4
Ottawa-Hull3, 4
Kingston2, 3
Belleville2, 3
Peterborough2, 3
Oshawa3, 4
Toronto3, 4
Hamilton3, 4
St Catharines2, 3
Kitchener2, 3
Brantford2, 3
Guelph2, 3
London2, 3
Windsor2, 3
Sarnia2, 3
Barrie3, 4
North Bay1, 2
Sudbury1, 2
Sault Ste Marie1, 2
Thunder Bay1, 2
Winnipeg1, 2
Regina1, 2
Saskatoon1, 2
Lethbridge1, 2
Calgary1, 4
Red Deer1, 2
Edmonton1, 4
Kelowna1, 2
Kamloops1, 2
Abbotsford1, 4
Vancouver1, 4
Victoria1, 2
Nanaimo1, 2
Prince George1, 2
Total
0-9
10.43
10.16
10.26
10.71
9.25
10-19
12.45
12.53
11.92
13.63
12.75
20-29
14.98
14.52
14.35
11.97
12.19
30-39
14.62
14.29
14.35
12.90
10.65
40-49
16.56
17.25
16.08
16.68
17.43
50-59
14.41
14.30
14.32
14.90
16.49
60-69
8.64
8.44
8.69
9.18
10.53
70-79
4.92
5.26
5.75
5.94
7.09
80+
3.01
3.26
4.27
4.08
3.61
9.37
10.48
8.73
10.60
11.58
12.84
12.14
13.54
14.09
14.49
12.57
12.76
12.46
11.95
10.74
12.79
16.41
15.49
16.61
16.71
15.64
14.54
15.86
14.54
10.22
9.78
11.19
9.36
6.38
6.32
7.72
6.03
3.84
4.12
4.45
3.67
10.72
11.24
9.95
10.58
9.41
12.61
11.94
11.26
10.18
12.29
11.77
12.09
11.01
12.21
9.93
12.86
10.04
10.37
9.26
9.98
11.17
11.27
11.77
11.93
12.07
11.85
11.57
9.57
9.95
12.82
10.28
8.77
9.45
12.06
11.11
12.55
13.49
12.88
13.79
13.53
15.30
13.29
13.43
13.13
13.85
13.98
13.15
13.72
13.61
13.71
15.28
13.65
13.23
13.17
13.21
13.53
14.11
14.33
14.03
13.16
13.77
13.70
12.79
13.53
14.78
12.54
11.34
12.88
14.77
13.12
13.60
13.46
13.77
11.70
12.61
11.85
13.52
12.30
11.55
14.51
12.13
14.82
14.02
13.14
11.58
12.22
12.83
12.35
11.47
11.94
13.82
15.26
16.46
16.24
15.49
19.23
15.80
11.30
12.53
13.41
13.79
13.02
11.72
13.22
13.71
14.16
14.22
12.41
11.67
10.62
14.16
15.35
13.21
11.92
14.70
12.61
14.59
13.14
14.40
10.82
14.79
11.65
12.46
10.69
12.22
13.13
12.57
12.65
11.88
16.07
14.12
14.03
11.34
11.88
13.48
14.74
12.27
11.31
13.86
14.13
16.63
17.35
16.07
16.40
15.17
17.94
16.94
16.35
15.72
16.26
15.96
16.36
16.11
16.02
15.70
17.79
16.72
16.80
16.36
16.55
16.10
16.04
15.73
14.59
17.21
15.90
16.40
15.84
16.25
15.41
17.03
15.56
15.53
16.97
16.66
13.60
13.90
14.21
13.85
14.77
12.73
12.83
13.45
14.19
12.58
14.08
12.45
13.46
12.99
15.54
11.57
14.31
14.57
15.36
14.98
13.83
13.38
12.78
12.67
12.92
11.91
13.25
14.43
15.50
12.39
14.16
15.70
15.75
14.89
13.60
9.00
8.02
9.59
9.83
10.27
7.38
7.70
8.90
10.19
7.43
8.78
7.33
8.49
8.29
10.16
7.26
9.89
9.66
10.64
9.28
8.12
7.61
7.08
8.06
6.43
6.05
7.39
10.90
10.12
8.00
8.26
9.63
10.74
8.04
8.34
6.22
5.13
6.86
7.47
8.02
5.14
5.36
6.81
7.97
5.15
6.39
5.64
6.05
5.85
7.87
5.16
7.15
6.95
8.38
7.10
5.97
5.71
5.38
6.40
4.25
4.37
4.99
8.58
6.71
5.80
5.61
7.34
7.62
4.34
5.79
3.53
3.19
4.26
4.70
5.58
2.90
3.08
4.28
5.14
3.23
4.30
3.57
4.00
3.47
4.68
3.07
3.78
3.61
4.68
4.71
4.34
4.06
3.82
4.23
2.40
2.82
2.87
5.24
3.53
3.91
3.60
6.38
5.02
1.86
3.52
See notes at the bottom of Table 1.
28
Table 7: Percent of Population Born Outside the Province and Outside Canada 2006
St John’s1, 2
Halifax1, 2
Moncton1, 2
St John1, 2
ChicoutimiJonquière1, 2
Québec2, 3
Sherbrooke2, 3
Trois-Rivières2, 3
St-Jean-surRichelieu3, 4
Montréal3, 4
Ottawa-Hull3, 4
Kingston2, 3
Belleville2, 3
Peterborough2, 3
Oshawa3, 4
Toronto3, 4
Hamilton3, 4
St Catharines2, 3
Kitchener2, 3
Brantford2, 3
Guelph2, 3
London2, 3
Windsor2, 3
Sarnia2, 3
Barrie3, 4
North Bay1, 2
Sudbury1, 2
Sault Ste Marie1, 2
Thunder Bay1, 2
Winnipeg1, 2
Regina1, 2
Saskatoon1, 2
Lethbridge1, 2
Calgary1, 4
Red Deer1, 2
Edmonton1, 4
Kelowna1, 2
Kamloops1, 2
Abbotsford1, 4
Vancouver1, 4
Victoria1, 2
Nanaimo1, 2
Prince George1, 2
Total
Born in Canada But
Outside Province
7.15
24.28
20.29
14.36
1.64
Born Outside of Canada
2.26
2.13
1.42
2.64
3.66
5.54
2.17
2.93
3.56
20.92
14.29
14.02
7.11
9.53
6.46
7.92
8.02
9.10
7.32
9.20
7.75
4.67
8.01
9.80
10.35
8.92
5.52
10.30
13.38
12.89
14.98
24.17
30.91
33.39
24.01
39.12
28.61
21.49
17.42
31.98
29.60
26.22
11.80
20.36
17.93
12.15
8.61
9.26
16.31
45.38
24.05
18.02
22.84
12.79
20.29
19.10
23.12
12.61
12.72
5.68
6.60
10.27
10.25
17.46
7.55
7.61
11.54
23.42
9.25
18.34
14.62
10.41
23.31
39.27
18.78
15.08
9.35
25.28
2.90
7.35
3.36
4.11
1.16
29
See notes at the bottom of Table 1.
30
31
Figure 2: Percent Population Change 1971-2006: Heartland and Hinterland, Large Urban Areas
and Small Urban Areas
32
Figure 3: Percent Employment Change 1971-2006: Heartland and Hinterland, Large Urban
Areas and Small Urban Areas
33
Figure 4: Percent Average Household Income Change 1971-2006 (in 2005 dollars): Heartland
and Hinterland, Large Urban Areas and Small Urban Areas
34
Figure 5: Percent Change in Employment Categories* 1996-2006: Heartland and Hinterland,
Large Urban Areas and Small Urban Areas
*For a full description of the employment categories see note at the bottom of Table 4.
35
Figure 6: Percent of Workers in Selected Employment Categories*, 2006: Heartland and
Hinterland, Large Urban Areas and Small Urban Areas
*For a full description of the employment categories see note at the bottom of Table 4.
36