Policy implications

From a policy perspective, our results shed some light on the perceived benefits of diversity.

That these benefits exist is strongly supported by our evidence. That they can be harnessed by policymakers is far less certain. There are two reasons to doubt whether diversification as a policy aim is realistic. First, a majority of regions do not significantly alter their economic structure over a thirty-year period: the level of inertia is great, and it is not certain that there exist policy tools that can overcome it. Second, even if such policy tools could be found, the link between the process of diversification and employment growth is not clear-cut. During some periods, and for some regions, specialization may be the best growth option. During others periods, a shift in speciality (a change in structure without diversification or specialization) may be more conducive to growth. Finally, over some periods, all regions, whether diversified or not, fare just as well (or as badly).

A related point is made by Randall & Ironside (1996) when they argue that the dangers inherent to over-specialization (principally the danger of a bust) must be set against the benefits derived from a boom. Cuadrado-Roura & Rubalcaba-Bermejo (1998) make the same point for cities. Provided that the specialty of a region or city is in demand, specialization has a lot to recommend it. But when the demand for a clustered industry’s product, or for a particular resource, drops, the regions that are specialized will suffer.

There is sometimes confusion when diversity and speciality are discussed, since they are often seen as alternatives. In this paper we argue that this is not the case, since diversity (and hence urbanization economies) can only be measured at the regional level, and is often associated with region size, whereas speciality (and hence localization economies) are sector-specific and independent of region size. Regional policies premised on the cluster strategy proposed by Porter (1990) and enthusiastically embraced by the OECD can work, but they can also lead to problems if a city or region

19

becomes overreliant on any narrow set of clusters. Likewise, policies based on diversification—no doubt prudent in large metropolitan areas that can be diversified while at the same time harbouring a large number of specialized clusters—are probably unrealistic for many smaller cities and regions.

This does not mean that diversification policies are of no use except in large urban areas. All regions that retained the same relative economic structure over the 30-year period have undergone structural change: no region in Canada has been exempt from the structural changes that have affected the whole economy. But for a majority of regions, their evolution has merely mirrored the changing structure of the Canadian economy. The local perception is, quite correctly, that major change has occurred, but our results show that, in most cases, this change only amounts to keeping up with the economy as a whole. This is not an insignificant achievement for many smaller or remote regions. “Diversification” policies may be necessary to ensure that these regions keep up with broader changes. However, the capacity of such policies to generate employment growth and relative “catching up” with other regions should not be overstated.

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Table 1– Part 1: The Fifteen Clusters – Urban Branch 141312 111098765432 Cluster 27: Diversified and high-order service centres • hva, transport, communication, high-tech services, wholesale, retail, personal services, fire, professional services, health and SS • Metro areas, large peripheral cities • All geographic regions • 20 to 14 Cluster 20: Government and high-order service centres • HIGH TECH SERVICES, communication, fire, profess. services, ADMIN • Metro areas and peripheral cities • All • 10 to 7 Cluster 256: Resource and high-tech services • PRIMARY, HIGH TECH SERVICES, ADMIN. • Peripheral city, peripheral rural area (in 1971) • . • 2 to 0 Cluster 18: Resource and consumer service centres • Primary, wholesale, retail, HOTELS & RESTAU, professional services, health, education • Central urban, peripheral urban, a few peripheral rural • All geographic regions • 61 to 82 Cluster 43: Consumer service and tourism centres • RETAIL, HOTELS & RESTAU, LEISURE, education, health • Small peripheral urban, and small central urban • Quebec, Prairies • 10 to 7 Cluster 16: Resource, heavy services and tourism • Primary, construction, transport, HOTELS + RESTAU, LEISURE • Central rural, and peripheral rural • British Columbia, Ontario • 23 to 17 Cluster 26: Diversified manufacturing centres • MVA, TM, HT, communication, personal services, fire • Central urban, and central rural • Ontario, Quebec • 32 to 34 Cluster 17: High tech manufacturing • TM, MVA, HT, wholesale • Central urban • Ontario, Quebec • 9 to 14 TM: traditional manufacturing; MVA: medium value added manufacturing; HT: high-tech manufacturing; FIRE: finance, insurance and real estate.

Table 1 – Part 2: The Fifteen Clusters – Rural Branch 141312 11109876543 Cluster 30: Resources, traditional manufacturing and basic services • PRIMARY, TM, TRANSPORT, HOTELS & RESTAU., admin • Small peripheral urban, and peripheral rural • Ontario, Quebec, Atlantic Canada • 7 to 10 Cluster 24: Resources and traditional manufacturing • PRIMARY, TM • Peripheral rural • Quebec, British Columbia, Atlantic Canada • 29 to 55 Cluster 29: Resources and leisure • PRIMARY, construction, personal services, LEISURE • Central rural, peripheral rural, small peripheral urban • Quebec, Ontario • 22 to 12 Cluster 35: Resources and education • PRIMARY, construction, EDUCATION • Peripheral rural • Quebec, Atlantic Canada • 17 to 7 Cluster 19: Resources and diversified traditional manufacturing • PRIMARY, TM, MVA • Over 50% of central rural (a few peripheral rural) • Ontario, Quebec, Atlantic Canada • 54 to 60 Cluster 15: Resources • PRIMARY, transport • Peripheral rural (and 15-20% of central rural) • Alberta, Prairies • 77 to 49 Cluster 21: Resources and government service centres • PRIMARY, EDUCATION, ADMIN • Peripheral rural • Prairies • 9 to 14 On the left of this table are descriptions of each cluster including the cluster number, the cluster name, a summary of its economic profile (sectors with location quotients over 120 or among the top 3 for the 15 clusters are capitalized), the type of region found in it, the geographic regions it covers, and the size of the cluster in 1971 and 2001 (number of regions in the cluster). On the right is the cluster tree: it describes the way in which clusters join as one moves from 15 to 1 cluster. It gives an indication of how similar or dissimilar the clusters are among themselves (the further up they join the more dissimilar they are).

Table 2: Various Statistics Relating to the 15 Clusters Changes 1971 to 2001 (number or regions) Diversity index Employment growth 1971-2001 stayed out in net 1971 2001 1971 clusters 2001 clusters cl27 1460-60.620.69106%106% cl20 552-30.560.55114%113% cl256 020-20.3143%- cl18 491233210.600.6391%85% cl43 552-30.510.5892%34% cl16 12115-60.510.53100%110% cl26 2391120.580.5893%93% cl17 63850.550.5847%84% cl30 43630.500.5177%18% cl24 191036260.540.5339%48% cl29 4188-100.550.58100%78% cl35 2155-100.560.5254%42% cl19 39152160.540.5485%86% cl15 46313-280.440.3555%55% cl21 81650.450.4684%98% Total 23614614600.530.5493%93% NB: Employment growth is calculated from total employment in each cluster. It is not an average—because the composition of the clusters changes, employment growth and diversification are calculated on the basis of the 1971 and the 2001 members. The diversification index for 1971is based on the 1971 cluster profile for the 1971 members; the diversification index for 2001 is based on the 2001 cluster profile for the 2001 members.

Table 3: The Diversity of Canadian Regions by Region Type, 1971-2001 Mean values of diversity index ANOVA test 19711981199119962001 R2 n F P (F=0 AMA 0.6310.6280.6720.6700.669 0.074400.700.59 ACA 0.5910.6000.6370.6410.640 0.0721152.150.08 ACB 0.5540.5560.5860.5620.576 0.0251801.140.34 APA 0.6220.6340.6560.6580.662 0.1041153.180.02 APB 0.5570.5680.5770.5870.581 0.0163101.220.30 RC 0.5190.5310.5380.5340.528 0.0053650.470.76 RP 0.4980.4960.4990.5020.485 0.0047850.760.55 Atlantic 0.5560.5600.5670.5710.561 0.0052950.350.84 Quebec 0.5420.5560.5720.5690.554 0.0215402.890.02 Ontario 0.5520.5520.5870.5790.590 0.0414054.250.00 Prairies 0.4740.4610.4480.4590.440 0.0092800.630.64 Alberta 0.4970.4960.4920.4830.466 0.0091450.310.87 BC 0.5390.5530.5620.5690.568 0.0162450.970.43 All 0.5330.5370.5490.5490.541 0.00419101.940.10 NB: To perform the ANOVA test, index values for each of the five years are pooled. The test measures whether there is a signifi difference between mean index values across the five years. The diversification index has an approximately normal distribution in each of the five years. Note: AMA: metro areas over 500K; ACA: central urban areas, 50-500K; ACB: central urban areas 10-50K; APA: peripheral urban areas, 50-500K; APB: peripheral urban areas 10-50K; RC: central rural areas; RP: peripheral rural areas.

Table 4: Relationship between Initial Diversity and Subsequent Employment Growth, 1971-2001 Ten-year periods Five-year periods Thirty years Twenty years DF 1971-81 1981-91 1991-01 1991-96 1996-01 1971-01 1981-01 Diversity index alone Model R2 381 0.02** 0.03** 0.05** 0.000.05** 0.03** 0.06** Index F value1 (+) 7.86**(+)11.39**(+)19.07** (+) 1.60(+)19.01**(+)11.25**(+)23.76** Diversity index, controlled for region type (AMA, ACA, ACB, APA, APB, RC, RP) Model R2 374 0.07** 0.10** 0.20** 0.03 0.34** 0.08** 0.19** Index F value1 (+) 1.15(+)12.87**(+)10.27** (+) 2.41(+)10.45**(+)4.19*(+)21.92** Region-type F value 7 3.47** 4.75** 11.91** 1.57 27.12** 3.76** 10.11** Diversity index, controlled for broad geographic region Model R2 375 0.26** 0.05** 0.16** 0.25** 0.22** 0.20** 0.13** Index F value1 (+) 16.85**(+)13.18**(+)19.89** (+) 8.55**(+)13.03**(+)19.40*(+)27.28** Geographic F value 6 24.10** 1.72 10.27** 24.38** 16.78** 15.75** 6.00** Diversity index, controlled for changing economic structure (6 clusters) Model R2 367 0.07** 0.14** 0.20** 0.11** 0.27** 0.09** 0.20** Index F value1 (+) 4.59*(+)6.32*(+)6.86** (+) 1.07(+)5.28*(+)4.52*(+)14.63** Cluster F value 6 2.80** 6.90** 9.84** 6.32** 16.20** 3.33** 9.69** ** = Significant at the 99% level; * = Significant at the 95% level. Note: i) The General Linear Model used here is identical to a regression analysis. Its advantage is that instead of adding a dummy variable for each control class, a single fixed effect that accounts for all the variance attributable to the control dimension can be added. ii) The region-type and geographic region controls are fixed over time. The classification by cluster changes: the cluster in which the region is found at the beginning of the period is used. iii) AMA: metro areas over 500K; ACA: central urban areas, 50-500K; ACB: central urban areas 10-50K; APA: peripheral urban areas, 50-500K; APB: peripheral urban areas 10-50K; RC: central rural areas; RP: peripheral rural areas.

Table 5: Structural Change and Diversification: Movement out of 1971 Clusters Cluster information Information on stayers and movers ANOVA to compare ANOVA to compare 1971 Diversity index stayed / n mean % mean % stayer/ mover Dp stayer/ mover growth Cluster (Dp) for clustermoved change in Dpemp growth R2 P(R2=0) R2 P(R2=0) Resource + high-tech services stayed 0. . . . . . cl256 0.31moved 2104.2%32% resources stayed 46-18.1%53% 0.450.0000.000.855 cl15 0.44moved 318.1%56% Resource + government services stayed 81.4%155% . . . cl21 0.45moved 117.9%16% Resource. 'heavy' services + tourism stayed 129.8%120% 0.020.5540.000.828 cl16 0.51moved 116.5%111% Consumer service + tourism stayed 525.5%44% 0.270.1220.190.208 cl43 0.51moved 58.3%102% Resource. trad.manuf + basic services stayed 48.3%29% . . . cl30 0.50moved 312.3%213% Resource. trad. + MVA manuf. stayed 391.7%90% 0.080.0450.070.057 cl19 0.54moved 15-4.8%64% Resource + trad. manuf stayed 19-3.4%37% 0.130.0530.010.594 cl24 0.54moved 104.6%46% Resource + leisure stayed 49.0%121% 0.170.0570.000.782 cl29 0.55moved 180.2%104% High-tech manuf.stayed 615.3%55% . . . cl17 0.55moved 321.0%53% Government + high-order services stayed 5-2.2%116% 0.000.8670.140.280 cl20 0.56moved 5-1.0%89% Resource + education stayed 28.1%34% . . . cl35 0.56moved 154.4%55% Diversified manuf. stayed 234.8%98% 0.000.9070.010.538 cl26 0.58moved 93.9%82% Resource + consumer servicesstayed 492.7%96% 0.080.0310.000.692 cl18 0.60moved 12-4.3%107% Diversified + high-order servicesstayed 149.1%102% 0.010.6890.000.909 cl27 0.62moved 67.6%99% Note: the ANOVA results are only shown if n stayers and n arrivers >= 4. Bearing in mind the small number of observations in most cases, the results are indicative only. Comparisons significant at the 90% level or higher are shown in bold.

Table 6: Structural change and diversification: Movement into 2001 clusters Cluster information Information on stayers and arrivers ANOVA to compare ANOVA to compare 2001 Diversity index stayed / n mean % mean % stayer/arriv. Dp stayer/arriv. growth cluster (Dp) for clusterarrived change in Dpemp growth R2 P(R2=0) R2 P(R2=0) resource + high tech services stayed 0. . . . . . cl256 . arrived 2104.2% resources stayed 46-18.1%53% 0.110.018. . cl15 0.35arrived 3-3.2%92% resource + government services stayed 81,4%155% 0,090.2840.050.428 cl21 0.46arrived 67.3%113% resource, trad.manuf + basic services stayed 48,3%29% 0,270.1270.010.791 cl30 0.51arrived 62.0%36% resource + education stayed 28,1%34% ..0.040.663 cl35 0.52arrived 58.8%55% resource, 'heavy' services + tourism stayed 129,8%120% 0,030.4730.010.783 cl16 0.53arrived 53.8%108% resource + trad. manuf stayed 19-3,4%37%0,020.3470.060.066 cl24 0.53arrived 36-0.7%54% resource, trad. + mva manuf. stayed 391,7%90% 0,020.2320.030.214 cl19 0.54arrived 21-2.0%74% government + high order services stayed 5-2,2%116% .... cl20 0.55arrived 235.8%165% consumer service + tourism stayed 525,5%44% .... cl43 0.58arrived 2-0.6%26% resource + leisure stayed 49,0%121% 0,000.9270.110.291 cl29 0.58arrived 810.0%62% high tech manuf.stayed 615,3%55% 0,150.1770.140.180 cl17 0.58arrived 8-4.8%151% diversified manuf. stayed 234,8%98% 0,000.8770.000.714 cl26 0.58arrived 113.7%90% resource + consumer services stayed 492,7%96% 0,140.0010.000.735 cl18 0.63arrived 3317.1%90% diversified + high order services stayed 149,1%102% .... cl27 0.69arrived 0. . note: the ANOVA results are only shown if n stayers and n arrivers >= 4. Bearing in mind the small number of observations in most cases, the results are indicative only. Comparisons significant at the 90% level or higher are shown in bold.