Habitat International xxx (2014) 1e5
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New economy jobs and economic health, prosperity in Canada's midsize urban areas Gary Sands* Urban Planning Program, Wayne State University, 1051 Hartsough St., Plymouth, MI 48170, USA
a r t i c l e i n f o
a b s t r a c t
Article history: Available online xxx
Many large North American metropolitan areas are becoming increasingly reliant on services (financial, health and education) and high tech manufacturing as local economic drivers. Have mid-size metropolitan areas (population 50,000 to 500,000) been able to similarly restructure their economies to remain prosperous and competitive? This paper examines the recent changes in the economies and prosperity of mid-size Canadian urban areas, comparing them to the Canadian economy as a whole. Midsize urban areas are found to have had mixed success in economic restructuring and attracting New Economy jobs. Overall, this decade has seen a substantial decline in the average Economic Prosperity Index of these communities, relative to the nation as a whole. In many cases, Economic Prosperity appears to be path dependent: prosperous communities with substantial proportions of New Economy jobs are likely to remain prosperous and to attract more such jobs. There are, however, few significant correlations between metropolitan employment profiles and maintaining or increasing prosperity. Higher levels of economic prosperity are found in urban areas with a well-educated, diverse population. © 2014 Elsevier Ltd. All rights reserved.
Keywords: Canadian cities Prosperity New economy Economic restructuring
Introduction Two important trends increasingly shape perspectives on urban economic prosperity in the 21st Century. The first of these is the “deindustrialization” of much of North America, as the manufacturing of goods has increasingly been shifted to locations (generally overseas) where wages and other production costs are lower. Canada has been somewhat more successful than the United States in retaining its manufacturing jobs. While US manufacturers were shedding some 5.5 million jobs in manufacturing over the past two decades, Canadian manufacturing employment decreased by just 34,000.1 Nevertheless, the proportion of Canadian jobs in manufacturing has fallen from 1 in 6 in 1986 to 1 in 10 in 2011. In many communities, the loss of manufacturing jobs has been largely offset by the rise in Services, especially higher order business and financial services, engineering and information technology. These jobs typically pay well but also require considerable education and training (Duderstadt, 2005; Erickcek & McKinney,
* Tel.: þ1 734 255 5997. E-mail addresses:
[email protected],
[email protected]. 1 The decline in manufacturing's share of total employment mentioned above is largely the result of the more rapid growth of other industries, rather than because of a decrease in manufacturing jobs. See also Wial & Friehoff, 2006.
2004). As a result, these new employment opportunities may be of little value to displaced manufacturing workers, who often lack the necessary education. The second important trend is a renewed interest in human capital based strategies. Since the early 1990s, Harvard's Edward Glaeser (Feser, 2003; Glaeser, Kallal, Scheinkman, & Schlief, 1992) has advocated economic development strategies based on investments in education and skills development. Rapid changes in technology and work environments place a premium on workers who are not only well educated and skilled, but who are also flexible and creative (Chappele et al., 2004; Glaeser & Mare, 2001; Malecki, 1997). Communities with a lively cultural scene may also attract talented individuals (Florida, 2002). The impact of these changes are evident in large metropolitan areas across North America. Some metropolitan areas (Chicago, Toronto) have restructured their economies, developing a greater reliance on higher order services and high tech manufacturing. Others (Detroit, Cleveland) have been less successful in replacing lost heavy manufacturing jobs with New Economy jobs. This transition has been difficult for many mid-size urban areas (Chappele et al., 2004; Coffey & Shearmur, 1996; Gottlieb, 1995). Mid-size urban areas typically have less diverse economic bases, providing them with fewer resiliencies when faced with a plant closing or other economic downturn (Erickek & McKinney, 2004).
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G. Sands / Habitat International xxx (2014) 1e5
Demographics also work against these communities; relatively low birth rates and few immigrants limit population growth.2 Young adults and seniors may leave for jobs and retirement homes, respectively. Geographic isolation, measured by distance from a major metropolitan area, appears to have a negative effect on the prospects of these urban areas (Polese & Shearmur, 2002). This paper considers the following questions: Are mid-size Canadian urban areas becoming less prosperous when compared to the Canadian average? What factors explain differences in the relative prosperity of these communities? Are mid-size urban areas dependent on their ability to attract New Economy industries and jobs for their economic well-being? The next section of the paper describes the variables used in the analysis and briefly profiles the mid-size communities. The third section looks at employment restructuring in these local economies over the 1996e2006 decade. This is followed by an examination of the growth of New Economy industries and jobs, comparing midsize urban areas to larger cities and to the nation. Finally, we will consider the implications of our findings for local economic development policy. Methodology and definitions Our focus is on the 42 Canadian Census Metropolitan Areas (CMAs) and Census Agglomerations (CAs) with populations between 50,000 and 500,000 in 1996.3 Urban areas in this size range are found in eight of Canada's provinces and include five Provincial capitals. The majority are located in Ontario (17 metros) and Quebec (8 metros). In the aggregate, mid-size urban areas are home to about one of every six Canadians, roughly the same proportion that resides in the Greater Toronto area. Table 1 summarizes the employment profiles of the mid-size metro areas (Sands, 2010). The majority of these areas have a significantly higher than average concentration of employment in the broadly defined categories of Natural Resources (agriculture, mining, forest products), Manufacturing or Services. The Manufacturing centers are concentrated in Ontario and Quebec, and Natural Resources based communities are predominantly located in Quebec and Western Canada. The metropolitan areas that are regional services centers are in outlying areas of Ontario and western Canada. The communities categorized as Diversified do not have a single economic specialization that is significantly above average. Economic prosperity index Community economic prosperity reflects the economic wellbeing of the individuals and households that live there.4 Three measures are used here to define the Economic Prosperity Index: median family income, employment rate (the complement of the unemployment rate) and the proportion of income from private sources (the proportion that does not come from government transfer payments), based on 1996 and 2006 data from the Canadian Census. Higher values for the individual indicators indicate greater prosperity. Each measure was given the same weight. The Economic
2
Three-quarters of immigrants to Canada move to Montreal, Toronto or Vancouver. 3 A number of regional municipalities (ChathameKent ON, Ft. McMurray AB, for example) have been excluded because their population density is very low and they lack a large, high density population center. 4 It is important to remember that this definition omits other significant aspects of city prosperity. See UN-Habitat, 2012.
Table 1 Mid-size metro areas by region and economic Specialization, 1996. Region
Natural Resources
Manufacturing
Services
Diversified
Total
Maritimes Quebec Ontario West Total
0 3 1 0 14
2 5 7 4 8
1 0 3 3 7
2 0 6 5 13
5 8 17 12 42
Source: Calculated from Statistics Canada data.
Prosperity Indices for each of the mid-size metropolitan areas are presented in Appendix 1, along with their 1996 population. A number of other variables were tested including: per capita and median family income, average earnings, labor force participation rates (total and female). None of these alternative measures produced results that differed significantly from the more parsimonious three variable model. Consequently, the basic model was retained. To facilitate comparisons between urban areas that differ widely in size, the elements of the economic prosperity index are standardized as location quotients, utilizing the national averages as the base; for example, an urban area with a median household income 20 percent higher than the national average median household income would have a location quotient of 1.2. The location quotients for the three indicators are summed, then multiplying the result by 100 to create the index. New economy industries The definitions of primary (natural resources) and secondary (manufacturing) industries are generally well understood. But, as the proportion of all jobs in the broad category of services increases, the standard industry categories become less useful as labels for identifying new economy employment. Employment in health care, for example, includes substantial numbers of cooks, laundry workers and parking attendants, as well as highly skilled physicians and technicians. Similarly, aerospace and motor vehicle manufacturing employment totals include skilled engineers and designers, as well as production workers. For this study, we categorize employment in the Finance, Insurance and Real Estate industry and in the Business Services industry as knowledge-based, new economy jobs. In addition, we calculate a separate variable, Professional Employment, using occupational (rather than industry) data from the Census to identify professional employees in Engineering, Information Technology, Consulting and Business Services, University Faculty, Health Care Professional and Designers. In addition to the industry and occupational data, we also include several demographic and socio-economic variables in the analysis, including total metropolitan area population, the proportion of immigrants, visible minorities and university graduates. Other variables included proportion of homeowners, average housing values and knowledge of French and English, Canada's official languages. The importance of the city center in each area was measured by a rating developed by Filion, Hoernig, Bunting, and Sands (2004) and by the proportion of work commuting that is done by public transportation. Economic restructuring The 1996e2006 period began and ended with periods of prosperity, with a mild recession in the middle.5 The overall Canadian
5 This timeframe ends before the Great Recession of 2008e09; pending data availability, extending this analysis through 2011 could provide interesting results in terms of the factors contributing to urban resilience.
Please cite this article in press as: Sands, G., New economy jobs and economic health, prosperity in Canada's mid-size urban areas, Habitat International (2014), http://dx.doi.org/10.1016/j.habitatint.2014.06.012
G. Sands / Habitat International xxx (2014) 1e5 Table 2 Economic restructuring trends 1996e2006. Industry
Natural resources Manufacturing Trade FIRE Health/Education Business services Other
3
Table 3 Regional average economic prosperity scores.
Mid-size metros
Canada
1996
2006
1996
2006
3.3% 25.4% 23.0% 5.8% 23.8% 6.4% 12.1%
3.9% 19.2% 16.1% 4.8% 18.5% 15.7% 20.6%
5.1% 20.9% 17.3% 6.7% 18.9% 14.7% 16.5%
5.3% 18.2% 15.8% 5.9% 17.0% 18.4% 19.4%
Source: Statistics Canada, Canadian Census, 1996, 2006.
Area
1996
2006
Change
Canada Maritimes Quebec Ontario West
316 318 293 326 316
301 301 289 303 305
15 17 4 23 11
Table 4 Economic health index Correlates 1996 and 2006. Variable
economy enjoyed a substantial gains during this period. Nationally, population and employment increased by about 15%. While the mid-size metro areas gained population at about the same rate as the country as a whole, the average increases in employment and income surpassed the national average. Table 2 illustrates the extent of economic restructuring that occurred in the industry composition of Canada as a whole, as well as in the mid-sized metropolitan areas. Nationally, both Manufacturing and Trade recorded declines in their share of total employment. The increased share of Business Services employment more than offset the declines in FIRE and Health and Education services. All 42 metro areas experienced an increase in total employment during this decade. Substantial declines occurred in the proportion of jobs in manufacturing, wholesale and retail trade and health and education services. Over one-third of the urban areas experienced absolute declines in Manufacturing and Trade jobs; the decline in Health and Education services was only relative. Business services had the largest increase in total share of employment opportunities, but remained the fifth largest employment category among the mid-size metro areas; nationally, it is the second largest. These changes in employment profile were generally not sufficient to produce changes in the economic specializations of a majority of mid-size urban areas. Only 13 metro areas moved into a new category over the decade. Ten of these changes were to the Diversified category; that is, the change occurred because they became less specialized. In 2006, over half of all mid-size urban areas were classified as Diversified. Economic prosperity of mid-size urban areas Table 3 summarizes the prosperity scores for the 42 mid-size metropolitan areas included in this study. Since a prosperity index of 300 indicates parity with the national averages for the three indicators, the score of 316 for all metros in 1996 was above average. By 2006, however, the overall average had fallen to just over 300. (Index values for individual metropolitan areas are provided in Appendix 2.) The Economic Prosperity Index declined in 32 of the metro areas. The results by region reflect significant differences. Ontario communities began with the highest prosperity score, only to suffer the largest decline of any region. Quebec mid-size cities were below average in both 1996 and 2006, but experienced the smallest regional decline. The index value for Halifax is considerably higher than the other metropolitan areas in the Maritimes. There is little relationship between the absolute or relative levels of job growth between 1996 and 2006 and changes in the EPI. Just over half of the urban areas recorded employment growth in
Prosperity96 FIRE96 BUSSERV96 METROPOP96 PRO96 University96 Immigrants96 FIRE06 University06 Immigrant06 VisibleMinority06 METROPOP06
Prosperity96
Prosperity06
Change9606
Correl.
Correl.
Sig.
Correl.
Sig.
.514 .369 .216 .389 .326 .190 .027 .397 .291 .360 .343 .389
.001 .016 .170 .011 .035 .228 .967 .009 .061 .019 .026 .011
¡.835 .236 ¡.441 ¡.526 .389 .274 .390 .322 ¡.449 ¡.468 ¡.428 ¡.523
.000 .133 .003 .000 .011 .079 .011 .037 .003 .002 .005 .000
.406 .498 .663 .514 .340 .350
Sig. .008 .001 .000 .001 .028 .023
Correlation (values in bold) is significant at the 0.01 level (2-tailed). Correlation (values in italic) is significant at the 0.05 level (2-tailed). Source: Statistics Canada, Canadian Census, 1996, 2006.
excess of 50% over the decade. Fourteen of these saw their EPI decline. For 5 of the 7 metro areas where employment rose by less than 15%, the index declined. Job growth alone is not sufficient to ensure increasing economic prosperity.6 We now turn to the question of what explains these differences in absolute scores, as well as changes over the decade. Does prosperity depend on an urban area's initial job profile or on how this profile has changed over the decade? Or are the differences related to demographic factors? First, consider the correlations between the Economic Prosperity Index in 1996 and the contemporary variables of interest.7 All of the statistically significant correlations are shown in Table 4. The strongest correlation with economic prosperity is the population of the metropolitan area; larger urban areas have higher prosperity indices. There is also a statistically significant positive relationship between the EPI and three indicators of new economy jobs: Finance, Insurance and Real Estate; Business Services; and professional employment across industry categories. The proportions of university graduates and immigrants are significantly correlated. Fewer highly significant correlates were found for the 2006 Economic Prosperity Index. The highest correlation in 2006 is between the 1996 and 2006 Health Indices, suggesting the presence of path dependency; urban areas that have attained a measure of economic prosperity are likely to continue to be prosperous. Likewise, below average communities have generally made only modest improvements. Two 1996 measures of new economy employment (FIRE and professional occupations), along with total metropolitan population, are also significantly correlated with the
6 Recall that these declines in economic prosperity are not absolute but are measured relative to the national average; these communities are worse off only relative to the national averages. 7 There is a high level of multicollinearity among the independent variables, confounding regression results.
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G. Sands / Habitat International xxx (2014) 1e5
2006 index, but at a lower level of significance. FIRE employment, university graduates and immigrant populations in 1996 are not correlated with the 2006 EPI. The only contemporary employment indicator that is significantly correlated with 2006 prosperity is FIRE employment. The 2006 proportions of immigrants, visible minorities and university graduates, along with total population, are all significantly correlated with prosperity levels in 2006. These results suggest a decline in the importance of what people do (the industries) and an increase in the importance of socio-economic characteristics of the population. In addition to the level of the prosperity indices, correlations were also calculated for the change in prosperity between 1996 and 2006. These results are shown in the last column of Table 4. Over the decade, there were substantial changes in the EPI for most of the mid-size urban areas. The average change was a decline of just over 15 points, or about 5%. One-quarter of the metro areas recorded an increase in their EPI.8 With the exception of FIRE employment and university graduates in 1996, all of the variables are significantly correlated. The EPI in 1996 and the metropolitan population in both years are the most highly correlated indicators. Several population attributes, especially the 2006 indicators, are also highly correlated with the EPI change.
Discussion The Economic Prosperity Index used in this study is a fairly narrow measure, based on only three indicators. The City Prosperity Index proposed by UN Habitat (2012), for example, includes eight separate indicators for Productivity, as well as four other dimensions of prosperity (Infrastructure, Environmental Sustainability, Equity and Access, and Quality of Life), producing a CPI that is based on more than 25 individual indicators. While the UN Habitat CPI is obviously much richer, the Economic Prosperity Index nevertheless has some positive attributes. It is reasonably easy to calculate from common data; it produces results that are consistent with expectations. It can easily be recalculated using a different base to produce regional indicators. On a broader scale, it is evident that mid-size urban areas are undergoing industrial restructuring, but at widely different rates. This study has not closely examined what might be the causes of these differences. Communities that are provincial capitals or are home to a major research university seem to be shifting to New Economy profiles more rapidly than communities that rely on manufacturing or natural resources. This observation is not very helpful to local economic developers (becoming a provincial capital or attracting a major research university are not practical strategies). But further exploration of how cities with these attributes are changing and the types of economic development strategies that they pursue could be warranted. Similar to the results of other studies (Reese & Sands, 2007; Sands, 2010), the single best predictor of future Economic Prosperity is current Economic Prosperity. Although changes in economic fortunes do occur, for the most part, one can expect that well off communities will continue to prosper, while struggling communities will seldom realize substantial gains in economic wellbeing.
8
Recall that the EPI compares the local indicators to the comparable national averages; the actual number of communities with absolute improvements is greater than the number with relative improvement.
This analysis also supports the importance of human capital in determining a community's economic prosperity. The positive correlation between the proportion of university graduates and economic prosperity suggests that an educated work force may provide more benefits than any particular employment profile. (The positive correlations for immigrants, many of whom are visible minorities, is more likely a result, rather than a cause, of economic prosperity.) These findings may be relevant to local economic development strategies. A strategy to increase the number of jobs in professional service industries or jobs in the arts and other creative fields, will not automatically lead to improvements in city prosperity. (This is perhaps just another reminder that local economic development is a difficult task). The finding that New Economy occupations are more relevant to Economic Prosperity than are New Economy industries could be useful to local economic developers. Even traditional manufacturing can make a large contribution to economic prosperity if it provides added employment for engineers and designers. None of the variables considered were reliable predictors of future changes in Economic Prosperity.
Acknowledgments The Canadian Embassy in Washington, DC provided financial support for this research through its Faculty Research Grant Program.
Appendix 1. Variables
Variable Employment Share 1996 Natural resources Manufacturing Trade Finance, insurance, Real estate Health/Education Services Business services Other Professional occupations Employment share 2006 Natural resources Manufacturing Trade Finance, insurance, real estate Health/Education services Business services Other Professional occupations Socio-economic variables 1996 Visible minorities Public transit use Immigrants University graduates Metropolitan population Socio-economic variables 2006 Visible minorities Public transit use Immigrants University graduates Metropolitan population Prosperity index 1996 Prosperity index 2006 Change in prosperity index City center rating
Mean
Standard deviation
.0326 .2536 .2303 .0576 .2379 .0638 .1206 .1214
.0285 .0720 .0287 .0145 .0486 .0162 .0523 .0271
.0392 .1920 .1608 .0483 .1852 .1568 .2063 .2051
.0240 .0636 .0127 .0117 .0302 .0385 .0343 .0442
.0607 .1089 .1005 .1597 142,829
.0923 .0404 .0628 .0475 97,151
.0547 .1130 .1005 .1454 159,466
.0448 .0383 .0628 .0448 110,037
316.1 300.6 15.45 405.4
25.95 14.28 22.28 124.1
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G. Sands / Habitat International xxx (2014) 1e5
Appendix 2. Mid-size Canadian cities
References
CMA/CA
1996 Population Employment Economic Prosperity Index growth 1996e2006 1996 2006
Abbotsford BC Barrie ON Belleville ON Brantford ON Chilliwack BC Cornwall ON Drummondville QC Fredericton NB Granby QC Greater Sudbury ON Guelph ON Halifax NS Kamloops BC Kelowna BC Kingston ON Kitchener ON Lethbridge AB London ON Medicine Hat AB Moncton NB Nanaimo BC North Bay ON Oshawa ON Peterborough ON Prince George BC Red Deer AB Regina SK Saguenay QC St. Hyacinthe QC Saint John NB St.Jean-sur-Richelieu QC Sarnia ON Saskatoon SK Sault Ste. Marie ON Shawinigan QC Sherbrooke QC St.Catherines-Niagara ON St. John's NL Thunder Bay ON Trois Rivieres QC Victoria BC Windsor ON
136,480 118,695 87,871 84,754 66,754 58,495 65,119 78,950 58,872 160,488 105,420 332,518 85,407 136,541 143,416 382,940 63,053 398,616 56,570 113,491 85,585 64,785 268,773 100,285 87,731 60,080 193,652 160,454 50,027 76,461 125,705 86,480 219,056 83,619 59,851 147,384 372,406 174,051 125,562 139,562 304,287 278,685
57.7% 105.8% 43.0% 65.0% 57.2% 10.3% 52.5% 65.5% 1.9% 13.8% 50.8% 72.1% 60.5% 59.4% 48.4% 46.5% 106.7% 45.3% 98.3% 65.3% 51.3% 44.5% 66.1% 81.8% 15.1% 55.8% 49.5% 38.4% 51.0% 59.2% 43.0% 37.2% 52.1% 32.4% 32.2% 62.5% 42.1% 61.1% 2.5% 6.6% 10.5% 3.5%
5
329 343 300 328 275 258 282 300 289 335 351 337 304 324 339 348 297 343 294 320 323 295 360 292 324 304 342 313 284 291 315 347 332 291 258 314 327 316 339 312 348 352
292 318 297 205 281 269 303 296 306 291 312 310 301 299 310 320 300 312 320 299 283 292 330 297 312 322 320 287 292 291 301 285 309 307 286 266 291 299 306 281 317 311
Chappele, K., Markusen, A., Schrock, G., Yamamoto, D., & Yu, P. (2004). Gauging metropolitan “high tech” and “i-tech” activity. Economic Development Quarterly, 18(February), 10e29. Coffey, W. J., & Shearmur, R. (1996). Employment growth and change in the Canadian urban system. Ottawa: Canadian Policy Research Network. Duderstadt, J. J. (2005). A roadmap to Michigan's future. Ann Arbor, MI: University of Michigan. Erickek, G. A., & McKinney, H. (2004). “Small city blues”: Looking for growth factors in small and medium-sized cities (pp. 04e100). Kalamazoo, MI: Upjohn Institute for Employment Research. Feser, E. J. (2003). What regions do rather than make: a proposed set of knowledge based occupation clusters. Urban Studies, 40(10), 1937e1958. Florida, R. (2002). The rise of the creative class. New York, NY: Basic Books. Filion, P., Hoernig, H., Bunting, T., & Sands, G. (2004). The successful few: healthy core areas of small metropolitan regions. Journal of the American Planning Association, 70, 328e343. Glaeser, E. L., Kallal, H., Scheinkman, J., & Schlief, A. (1992). Growth in cities. Journal of Political Economy, 100, 1126e1152. Glaeser, E. L., & Mare, D. C. (2001). Cities and skills. Journal of Labor Economics, 19(2), 316e342. Gottlieb, P. (1995). Residential amenities, firm location and economic development. Urban Studies, 32(9), 1413e1436. Malecki, E. (1997). Technology and Economic Development: The Dynamics of Local, Regional and National Competitiveness. Harlow: Addison, Wesley, Longman. Polese, M., & Shearmur, R. (2002). The periphery in the knowledge economy. Moncton and Montreal: INRS_Ubanisation, Culture et Societe and Canadian Institute for Research on Regional Development. Reese, L. A., & Sands, G. (2007). Making the least of our differences?: trends in Canadian and US local economic development, 1990-2005. Canadian Public Administration. Sands, G. (2010). Prosperity and the new economy in Canada's major city regions. GeoJournal, 75(6), 539e551. UN-Habitat. (2012). State of the world cities report 2012/2013 prosperity of cities. Nairobi Kenya: UN human Settlements program. Wial, H., & Friehoff, A. (2006). Bearing the Brunt: Manufacturing job Loss in the Great Lakes region, 1995-2005. Washington: The Brookings Institution. Metro Economy Series.
Source: Statistics Canada, Canadian Census, 1996, 2006.
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