What does Rural – Urban Interaction Look Like? Ray D. Bollman Statistics Canada L. Peter Apedaile Peer Diagnostics Alessandro Alasia University of Saskatchewan

What does Rural – Urban Interaction Look Like?

Ray D. BollmanStatistics Canada

L. Peter ApedailePeer Diagnostics

Alessandro AlasiaUniversity of Saskatchewan

and Statistics Canada

Presentation to the Annual Rural Policy Conference of the Canadian Rural Revitalization Foundation on

“Rural-Urban Footprints: Implications for Governance”Tweed, Ontario, October 14 – 16, 2004


Outline

• What is governance?

• Rural – urban linkages

• flows of goods and services and garbage !

• flows of people commuters, tourists, retirees, young families

• flows of ideas / knowledge

• What is “interaction”?

• A bit more on governance

• Concluding comments


Outline










Outline

• What is governance? as proposed by the World Bank:

“the regulation of power by means of institutions and traditions for taking

decisions in the public interest.”


Outline

• What is governance? as proposed by the World Bank: Note some key concepts:

• regulation of power• “institutions” and “traditions”

• for taking decisions• in the “public” interest


Outline

• What is governance? as proposed by the World Bank: Note some key concepts:

• regulation of power• via processes and networks

• for taking decisions• in the “public” interest


Outline


implication for rural

• rural was, and is, stronger on

• “institutions” and “traditions”

• rural may be relatively disadvantaged as governance moves towards

• processes and networks


Outline


implication for rural

• rural governance is important because we are in an era of simultaneous globalization and localization

• some important governance issues are moving “up” to world bodies (WTO, global corporations)

• some important governance issues are moving “down” to local bodies

• examples of such issues are “supply of skills” and “quality of the local environment”

“Skills” and “environment” are two community assets for which the demand is

increasing


Outline


implication for rural• rural governance is important because we are in an era of simultaneous globalization and localization

• some important governance issues are moving “up” to world bodies (WTO, global corporations)

• some important governance issues are moving “down” to local bodies

• examples of such issues are “supply of skills” and “quality of the local environment”

• thus “local governance” is more important than ever before


Outline

• What is governance?• processes and networks are important

• we are in a knowledge-based economy

• important “tacit” knowledge is transferred by interacting “at the elbow of the master”, it is not in books or on the Internet

• this is one driver of agglomeration economies

• this “within” community interaction is one important type of process and network that is sparse in the low density

rural milieu


Outline









Our Cities Are What We Eat

Corner Post #329, Farm & Countryside Commentary by Elbert van DonkersgoedCanada’s debate about a new deal for our cities is focused on infrastructure, on the assumption that the billion dollar investment in Toronto’s subway system is representative of this new arrangement. Not everyone agrees.A number of voices, my own included through my involvement with the Toronto Food Policy Council, have sent a message to Toronto MP John Godfrey, Parliamentary Secretary for Cities and Mike Harcourt, Chair of our federal government’s new Advisory Committee for Cities – this message: improved urban life means better food solutions. Food plays an important role in the economy of Canada. Food choices account for some 20 percent of retail sales and of service jobs, ten percent of industrial jobs, 20 percent of car trips and traffic, 20 percent of chronic diseases, 25 percent of fossil fuel energy and air pollution, 40 percent of garbage, 80 percent of sewage.Food is about economics: it influences our health and productivity, and our culture. More than with any other of our biological needs, the choices we make around food affect the shape, style, pulse, smell, look, feel, health, economy, street life and infrastructure of our cities.There's an old saying: we are what we eat. It is equally obvious: a city is what it eats.Food habits determine the character of our cities:· Whether our main streets are fast-food strips or lined with spots that breathe local flavour and character. · Whether there's a Little Italy, Little India or Asian Village anchored by restaurants and groceries that nourish entrepreneurs and cultural cooking traditions · Whether the poor, elderly and physically disabled can access nearby grocers that sell fresh nutritious produce. · Whether backyards are splashed with the green hues of vines, squash and corn, or sport fence-to-fence grass. · Whether people treat food scraps as garbage or as valuable compost. · Whether highways are clogged with refrigerated 18-wheelers transferring produce across the continent or local farmers bringing in the day's harvest on pick-up trucks.· Whether our health systems are forced to deal with expensive diet related crises such as heart disease, diabetes, obesity, or cancer.· Whether low incomes families have a place at our bountiful table. · Whether the money spent on food stays in and near the city to create more jobs here, or leaves town overnight to create jobs there.· Whether shoppers drive to pick up convenience foods from box stores or walk to neighborhood outdoor markets for locally grown fresh and homemade products.

A new urban agenda for Canada cannot only be about public transport and infrastructure. Our cities are what we eat, as well as what we build.

Elbert van Donkersgoed P. Ag. (Hon.) is the Strategic Policy Advisor of the Christian Farmers Federation of Ontario, Canada.

20 percent of all census-farms are located within CMAs and CAs

0 10 20 30 40 50 60 70 80 90 100

Forage seed

Tobacco

Wheat

Small grain (exc. wht. spec.)

Field pea and bean

Hog

Maple products

Cattle

Oilseed

Cattle and hog

Mixed crop

Other field crop

ALL CENSUS FARMS

Dairy

Mixed livestock

Fodder

Fur

Other

Potato

Grain corn

Goat

Cattle, hog and sheep

Sheep and lamb

Other animal speciality

Poultry and egg

Horse

Fruit and vegetable

Vegetable speciality

Fruit speciality

Greenhouse

Sod and nursery

Mushroom

Percent of census-farms located with CMAs and CAs

1996

1986

Source: Statistics Canada. Census of Agriculture, 1986 and 1996.

1996 Classifications

Census Metropolitan Areas

Census Agglomerations

Non Census Metropolitan/Census Agglomeration AreasRural and Small Town areas


Outline









Larger urban centres have a larger share of their workforce with a "health occupation", Canada, 2001

0

20

40

60

80

100

120

140

All areas CMAs CAs (50 to99K)

CAs (10 to49K)

Strong MIZ ModerateMIZ

Weak MIZ No MIZ TerritoriesRST

Source: Statistics Canada. Census of Population, 2001 {available at www.statcan.ca/english/IPS/Data/95F0495XCB2001012.htm}.The location quotient is the share of the workforce with a health occupation, relative to the Canadian average share with a health occupation, based on location of residence of worker)

Larger urban centres Rural and small town areas

Location quotient

Larger urban centres have a larger share of their workforce with a "health occupation", British Columbia, 2001

0

25

50

75

100

125

150


CAs (10 to49K)


Weak MIZ No MIZ

Source: Statistics Canada. Census of Population, 2001 {available at www.statcan.ca/english/IPS/Data/95F0495XCB2001012.htm}.The location quotient is the share of the workforce with a health occupation, relative to the provincial average share with a health occupation, based on location of residence of worker.


Location quotient

CMAs and larger CAs have a larger share of their workforce with a "health occupation", Alberta, 2001

0

25

50

75

100

125

150


CAs (10 to49K)


Weak MIZ No MIZ



Location quotient

Larger urban centres have a larger share of their workforce with a "health occupation", Saskatchewan, 2001

0

25

50

75

100

125

150


CAs (10 to49K)


Weak MIZ No MIZ



Location quotient

Larger urban centres have a larger share of their workforce with a "health occupation", Manitoba, 2001

0

25

50

75

100

125

150


CAs (10 to49K)


Weak MIZ No MIZ



Location quotient

Larger urban centres have a larger share of their workforce with a "health occupation", Ontario, 2001

0

25

50

75

100

125

150


CAs (10 to49K)


Weak MIZ No MIZ



Location quotient

Larger urban centres have a larger share of their workforce with a "health occupation", Quebec, 2001

0

25

50

75

100

125

150


CAs (10 to49K)


Weak MIZ No MIZ



Location quotient

Larger urban centres have a larger share of their workforce with a "health occupation", New Brunswick, 2001

0

25

50

75

100

125

150


CAs (10 to49K)


Weak MIZ No MIZ



Location quotient

Larger urban centres have a larger share of their workforce with a "health occupation", Nova Scotia, 2001

0

25

50

75

100

125

150


CAs (10 to49K)


Weak MIZ No MIZ



Location quotient

Larger urban centres have a larger share of their workforce with a "health occupation", Newfoundland and Labrador, 2001

0

25

50

75

100

125

150


CAs (10 to49K)


Weak MIZ No MIZ



Location quotient


Outline









Water

Less than 25 percent

25 to 49 percent

50 to 74 percent

75 percent or over

No population

All sub-drainage

areas

Number of river sub-drainage basins25 38 19 69 13 164

*** as percent of total15 23 12 42 8 100

Total population20,363,665 7,493,100 1,688,039 181,889 0 29,726,693 *


Census rural population2,336,205 2,528,796 982,089 171,306 0 6,018,396 *


Total land area (square kilometres)1,168,332 2,054,138 946,547 4,664,361 988,107 9,821,486


Source: Statistics Canada. Human Activity and the Environment, Annual Statistics 2003 (Ottawa: Statistics Canada, Cat. no. 16-201), Tables A1 and A7.

* missing population will have to be found

Percent of population in sub-drainage area that is 'census rural'

Sub-drainage areas by share of population in 2001 that is census rural.


Outline


• Rural – urban linkages• flows of goods and services and garbage !







Outline








Census urban

(centres of 1,000+)

Census rural

(outside centres of 1,000+)

LARGER URBAN CENTRESCensus Metropolitan Areas

Census Agglomerations

RURAL AND SMALL TOWN AREAS

Share of "census rural" population within CMA/CA labour markets has doubled within 25 years

0

5

10

15

20

25

30

35

40

1976 1981 1986 1991 1996 2001Source: Statistics Canada. Census of Population, 1976 - 2001. "Census rural" refers to the population outside settlements of 1,000 or more. A CMA comprises an urban core population of 100,000 or more, and a CA has an urban core population of 10,000 to 99,999 and both include the population in neighbouring municipalities where 50 percent or more of the workforce commutes into the urban core.

Percent of "census rural" population that lives within Census Metropolitan Areas (CMAs) and Census Agglomerations (CAs)

Share of population in rural and small town areas

continues to decline, Canada, 1971 to 2001

0

5

10

15

20

25

30

35

40

1971 1976 1981 1986 1991 1996 2001

Source: Statistics Canada. Census of Population, 1971 - 2001.Rural and small town refers to the population outside Census Metropolitan Areas (CMAs) and Census Agglomerations (CAs).

Census urban Census rural All areas

All areas 23,908,100 6,098,985 30,007,085

. Census Metropolitan Areas (CMAs) 18,175,700 1,121,220 19,296,920

. Census Agglomerations (CAs) with census tracts 1,472,795 227,965 1,700,760

. Census Agglomerations (CAs) without census tracts 2,202,340 639,055 2,841,395All larger urban centres (LUCs) (i.e., CMAs and CAs) 21,850,835 1,988,240 23,839,075

Rural and small town (RST) areas (i.e., non-CMA/CA areas). Strong metropolitan influenced zone (MIZ) 400,020 1,124,555 1,524,575. Moderate metropolitan influenced zone (MIZ) 741,335 1,544,195 2,285,530. Weak metropolitan influenced zone (MIZ) 872,395 1,096,860 1,969,255. No metropolitan influenced zone (MIZ) 29,045 304,770 333,815. Territories RST 14,470 40,365 54,835All "rural and small town" areas 2,057,265 4,110,745 6,168,010Source: Statistics Canada, Census of Population, 2001 {available at www.statcan.ca/english/IPS/Data/95F0495XCB2001012.htm}.

{and a summary version is available at www.statcan.ca/english/IPS/Data/97F0024XIE2001016.htm}

A CMA comprises an urban core population of 100,000 or more plus the population in neighbouring municipalities where 50 percent or more of the workforce commutes into the urban core.

A CA comprises an urban core population of 10,000 to 99,999 and neighbouring municipalities where 50 percent or more of the workforce commutes in to the core.

Census agglomerations with census tracts have a population of 50,000 to 99,999 in the urban core.

Metropolitan influenced zones (MIZ) are assigned on the basis of the size of commuting to any CMA or CA.

Census urban refers to the population in settlements of 1,000 or more and census rural is the population outside settlements of 1,000 or more.

Larger urban centres (LUCs) (i.e., CMAs and CAs)

Total population by "Statistical Area Classification" and Census Urban / Rural classification, Canada, 2001

In each MIZ zone, over one-half of the population lives in 'census rural' areas; and in smaller CAs, 22 percent live in 'census rural' areas

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

CMAs CAs (50 to99K)

CAs (10 to49K)



Per

cen

t o

f to

tal

po

pu

lati

on

wit

hin

eac

h "

Sta

tist

ical

Are

a C

lass

ific

atio

n"

gro

up

Census urban

Census rural

Source: Statistics Canada, Census of Population, 2001 {available at www.statcan.ca/english/IPS/Data/95F0495XCB2001012.htm}.


In each MIZ zone (outside the Territories), over 60 percent of the population was living in the same residence in 1996 and 2001, Canada

0

10

20

30

40

50

60

70

80


CAs (10 to49K)



Per

cen

t o

f th

e p

op

ula

tio

n (

5 ye

ars

and

old

er)

livin

g a

t th

e sa

me

add

ress

in 1

996

and

200

1

Source: Statistics Canada. Census of Population, 2001 {available at www.statcan.ca/english/IPS/Data/95F0495XCB2001012.htm}.


The census rural population is more likely to stay at the same address, within each type of zone, Canada, 2001

0

10

20

30

40

50

60

70

80


CAs (10 to49K)



Per

cen

t o

f th

e p

op

ula

tio

n (

5 ye

ars

and

old

er) li

vin

g a

t th

e sa

me

add

ress

in

1996

an

d 2

001

Census urban Census rural


Larger urban centres

Rural and small town areas

Government transfer income is 23 percent of total income in the No MIZ zone, Canada

0

5

10

15

20

25


CAs (10 to49K)


Weak MIZ No MIZ TerritoriesRSTP

erce

nt

of

tota

l in

com

e fr

om

go

vern

men

t tr

ansf

ers,

200

0



Government transfer income is 23 percent of total income in the rural areas of the No MIZ zone, Canada

0

5

10

15

20

25


CAs (10 to49K)



Per

cen

t o

f to

tal i

nco

me

fro

m g

ove

rnm

ent

tran

sfer

s, 2

000




CMAs report the highest share of their population be living below the Low Income Cut-off, Canada

0

4

8

12

16

20


CAs (10 to49K)


Weak MIZ No MIZ TerritoriesRSTP

erce

nt

of

po

pu

lati

on

in

pri

vate

ho

use

ho

lds

wit

h i

nco

me

bel

ow

th

e L

ow

In

com

e C

ut-

off

, 20

00



LICO is not

assign-ed for house-

holds in the Terri-

tories

Census rural areas in each type of zone has a lower share of its population living below the Low Income Cut-off, Canada

0

4

8

12

16

20


CAs (10 to49K)



Per

cen

t o

f to

tal i

nco

me

fro

m g

ove

rnm

ent

tran

sfer

s, 2

000




LICO is not

assign-ed for house-

holds in the Terri-

tories

Table 1. Number of Census Subdivisions by Population Size, Canada, 2001

Number Percent Number PercentNo inhabitants 416 7 0 0

1 to 49 359 6 7,893 050 to 99 233 4 17,066 0

100 to 199 377 7 56,193 0200 to 299 319 6 79,609 0300 to 399 379 7 132,414 0400 to 499 308 6 137,684 0500 to 749 601 11 368,483 1750 to 999 422 8 364,691 1

1,000 to 2,499 980 18 1,535,309 52,500 to 4,999 479 9 1,700,611 65,000 to 9,999 327 6 2,303,986 8

10,000 to 24,999 240 4 3,629,891 1225,000 to 49,999 68 1 2,383,484 850,000 to 99,999 51 1 3,606,808 12

100,000 to 499,999 33 1 6,064,762 20500,000 and over 8 0 7,618,210 25

All census subdivisions 5,600 100 30,007,094 100A census subdivision is, generally, is an incorporated town or municipality.

For the exact definition, see Statistics Canada. (2002) 2001 Census Dictionary

(Ottawa: Statistics Canada, Catalogue No. 92-378) (www.statcan.ca/english/census2001/dict/index.htm)

Source: Statistics Canada. Census of Population, 2001.

Census subdivisions PopulationPopulation size of census subdivision

Table 2. Number of Census Subdivisions by Statistical Area Classification, Canada, 2001

Number Percent Number Percent

Census Metropolitan Areas (CMAs) 471 8 19,296,926 64Census Agglomerations (CAs) with census tracts 93 2 1,700,766 6Census Agglomerations (CAs) without census tracts 431 8 2,841,394 9Subtotal: Larger urban centres (CMAs and CAs) 995 18 23,839,086 79

Strong metropolitan influenced zone (MIZ) 566 10 1,524,579 5Moderate metropoltain influenced zone (MIZ) 1,388 25 2,285,538 8Weak metropolitan influenced zone (MIZ) 1,016 18 1,969,211 7No metropolitan influenced zone (MIZ) 1,538 27 333,847 1Territories RST 97 2 54,833 0Subtotal: Rural and small town areas (non-CMA/CA) 4,605 82 6,168,008 21

Total: All census subdivisions 5,600 100 30,007,094 100A census subdivision is, generally, an incorporated town or municipality.

For the exact definition, see Statistics Canada. (2002) 2001 Census Dictionary

(Ottawa: Statistics Canada, Catalogue No. 92-378) (www.statcan.ca/english/census2001/dict/index.htm)

A CMA comprises an urban core population of 100,000 or more plus the population in neighbouring municipalities where

50 percent or more of the workforce commutes into the urban core. A CA comprises an urban core population of 10,000 to 99,999

and neighbouring municipalities where 50 percent or more of the workforce commutes into the core.

Census agglomerations with census tracts have a population of 50,000 to 99,999 in the urban core.

Metropolitan influenced zones (MIZ) are assigned on the basis of the size of commuting to any CMA or CA.

Source: Statistics Canada. Census of Population, 2001.

Census subdivisions PopulationStatistical area classification (SAC)

Table 3a. Number of census subdivisions by "Statistical area classification" and population size, Canada, 2001

Statistical area classification (SAC) 0 to 199 200 to 999 1,000 to 9,99910,000 and

overAll census

sub-divisions

Census Metropolitan Areas (CMAs) 44 54 171 202 471Census Aggomerations (CAs) with census tracts 8 12 42 31 93Census Aggomerations (CAs) without census tracts 96 82 153 100 431Subtotal: Larger urban centres (CMAs and CAs) 148 148 366 333 995

Strong metropolitan influenced zone (MIZ) 34 230 270 32 566Moderate metropoltain influenced zone (MIZ) 75 723 568 22 1,388Weak metropolitan influenced zone (MIZ) 41 462 500 13 1,016No metropolitan influenced zone (MIZ) 1,046 427 65 0 1,538Territories RST 41 39 17 0 97Subtotal: Rural and small town areas (non-CMA/CA) 1,237 1,881 1,420 67 4,605

Total: All census subdivisions 1,385 2,029 1,786 400 5,600

*** number of census subdivisions ***

Population size class of census subdivision

The State of Rural Canada:

From Strength to Strength

Questions / Discussion

Population Growth, Canada, 1966 to 2001

-10

-5

0

5

10

15

20

25

1966 to 1971 1971 to 1976 1976 to 1981 1981 to 1986 1986 to 1991 1991 to 1996 1996 to 2001

Per

cen

t ch

ang

e in

po

pu

lati

on

wit

hin

co

nst

ant

bo

un

dar

ies Census Metropolitan Areas (CMAs)

Census Agglomerations (CAs)

Rural and Small Town (RST) areas

Source: Statistics Canada. Census of Population, 1971 to 2001.CMAs have an urban core of 100,000 persons plus neighbouring municipalities where 50 percent or more of the workforce commutes to the urban core.CAs have an urban core of 10,000 to 99,999 persons plus neighbouring municipalities where 50 percent or more of the workforce commutes to the urban core.RST areas are outside the commuting zones of CMAs and CAs.




Population Growth, Newfoundland, 1966 to 2001

-15

-10

-5

0

5

10

15

20

25

1966 to 1971 1971 to 1976 1976 to 1981 1981 to 1986 1986 to 1991 1991 to 1996 1996 to 2001

Per

cen

t ch

ang

e in

po

pu

lati

on

wit

hin

co

nst

ant

bo

un

dar

ies

Census Metropolitan Areas (CMAs)



Source: Statistics Canada. Census of Population, 1971 to 2001.

CMAs have an urban core of 100,000 persons plus neighbouring municipalities where 50 percent or more of the workforce commutes to the urban core.CAs have an urban core of 10,000 to 99,999 persons plus neighbouring municipalities where 50 percent or more of the workforce commutes to the urban core.RST areas are outside the commuting zones of CMAs and CAs.




Population Change, Prince Edward Island, 1966 to 2001

-10

-5

0

5

10

15

20

25

1966 to 1971 1971 to 1976 1976 to 1981 1981 to 1986 1986 to 1991 1991 to 1996 1996 to 2001

Per

cen

t ch

ang

e in

po

pu

lati

on

wit

hin

co

nst

ant

bo

un

dar

ies








Population Growth, Nova Scotia, 1966 to 2001

-10

-5

0

5

10

15

20

25

1966 to 1971 1971 to 1976 1976 to 1981 1981 to 1986 1986 to 1991 1991 to 1996 1996 to 2001

Per

cen

t ch

ang

e in

po

pu

lati

on

wit

hin

co

nst

ant

bo

un

dar









Population Growth, New Brunswick, 1966 to 2001

-10

-5

0

5

10

15

20

25

1966 to 1971 1971 to 1976 1976 to 1981 1981 to 1986 1986 to 1991 1991 to 1996 1996 to 2001

Per

cen

t ch

ang

e in

po

pu

lati

on

wit

hin

co

nst

ant

bo

un

dar








Population Growth, Quebec, 1966 to 2001

-10

-5

0

5

10

15

20

25

1966 to 1971 1971 to 1976 1976 to 1981 1981 to 1986 1986 to 1991 1991 to 1996 1996 to 2001

Per

cen

t ch

ang

e in

po

pu

lati

on

wit

hin

co

nst

ant

bo

un

dar








Population Growth, Ontario, 1966 to 2001

-10

-5

0

5

10

15

20

25

1966 to 1971 1971 to 1976 1976 to 1981 1981 to 1986 1986 to 1991 1991 to 1996 1996 to 2001

Per

cen

t ch

ang

e in

po

pu

lati

on

wit

hin

co

nst

ant

bo

un

dar

ies









Population Growth, Manitoba, 1966 to 2001

-10

-5

0

5

10

15

20

25

1966 to 1971 1971 to 1976 1976 to 1981 1981 to 1986 1986 to 1991 1991 to 1996 1996 to 2001

Pe

rce

nt

ch

an

ge

in

po

pu

lati

on

wit

hin

co

ns

tan

t b

ou

nd

ari

es








Population Growth, Saskatchewan, 1966 to 2001

-10

-5

0

5

10

15

20

25

1966 to 1971 1971 to 1976 1976 to 1981 1981 to 1986 1986 to 1991 1991 to 1996 1996 to 2001

Per

cen

t ch

ang

e in

po

pu

lati

on

wit

hin

co

nst

ant

bo

un

dar








Population Growth, Alberta, 1966 to 2001

-10

-5

0

5

10

15

20

25

1966 to 1971 1971 to 1976 1976 to 1981 1981 to 1986 1986 to 1991 1991 to 1996 1996 to 2001

Pe

rce

nt

ch

an

ge

in

po

pu

lati

on

wit

hin

co

ns

tan

t b

ou

nd

ari

es Census Metropolitan Areas (CMAs)







Population Growth, British Columbia, 1966 to 2001

-10

-5

0

5

10

15

20

25

1966 to 1971 1971 to 1976 1976 to 1981 1981 to 1986 1986 to 1991 1991 to 1996 1996 to 2001

Pe

rce

nt

ch

an

ge

in

po

pu

lati

on

wit

hin

co

ns

tan

t b

ou

nd

ari

es





Strong growth in metro areas and rural areas strongly influenced by metro areas, Canada, 1996 to 2001

-18

-15

-12

-9

-6

-3

0

3

6

9

12

15

18

CensusMetropolitan

Areas

CensusAgglomerations

Rural and SmallTown areas

Strong MIZ Moderate MIZ Weak MIZ No MIZ Territories

Source: Statistics Canada. Census of Population, 1996 - 2001. MIZ refers to Metropolitan Influenced Zone.


Population decline in Newfoundland, 1996 to 2001

-18

-15

-12

-9

-6

-3

0

3

6

9

12

15

18

CensusMetropolitan

Areas



Strong MIZ Moderate MIZ Weak MIZ No MIZ



Population decline in weaker MIZ in Prince Edward Island, 1996 to 2001

-18

-15

-12

-9

-6

-3

0

3

6

9

12

15

18

CensusMetropolitan

Areas






Population decline in weaker MIZ in Nova Scotia, 1996 to 2001

-18

-15

-12

-9

-6

-3

0

3

6

9

12

15

18

CensusMetropolitan

Areas






Population decline in most RST areas in New Brunswick, 1996 to 2001

-18

-15

-12

-9

-6

-3

0

3

6

9

12

15

18

CensusMetropolitan

Areas






Population decline in weaker MIZ in Quebec, 1996 to 2001

-18

-15

-12

-9

-6

-3

0

3

6

9

12

15

18

CensusMetropolitan

Areas






Population growth in No MIZ zones in Ontario, 1996 to 2001

-18

-15

-12

-9

-6

-3

0

3

6

9

12

15

18

CensusMetropolitan

Areas




Per

cen

t ch

ang

e



Population growth in strong MIZ zones in Manitoba, 1996 to 2001

-18

-15

-12

-9

-6

-3

0

3

6

9

12

15

18

CensusMetropolitan

Areas






Population decline in weaker MIZ zones in Saskatchewan, 1996 to 2001

-18

-15

-12

-9

-6

-3

0

3

6

9

12

15

18

CensusMetropolitan

Areas






Population decline in all zones in Alberta, 1996 to 2001

-18

-15

-12

-9

-6

-3

0

3

6

9

12

15

18

CensusMetropolitan

Areas






Strong population growth in British Columbia metro areas, 1996 to 2001

-18

-15

-12

-9

-6

-3

0

3

6

9

12

15

18

CensusMetropolitan

Areas






Strong growth in metro areas and rural areas strongly influenced by metro areas, Canada, 1996 to 2001

-18

-15

-12

-9

-6

-3

0

3

6

9

12

15

18

CensusMetropolitan

Areas



Strong MIZ Moderate MIZ Weak MIZ No MIZ Territories




Outline








“Coping Skills in the New Rural Economy:

Inter-municipal Tax-sharing in

an Agriculturally Dependent Region --

A Case Study of the Russell, Manitoba Region”

Richard Rounds, Brandon University

Paper to the Annual Rural Policy Conference of the CANADIAN RURAL

REVITALISATION FOUNDATION, Alfred, Ontario, October, 2000.


Inter-municipal Tax-sharing in an Agriculturally Dependent Region --



“A local development emphasis necessarily weakened regional development as communities prepared to determine their own futures by successfully competing against other, which were often neighbouring areas.” (p. 3)





“A local development emphasis necessarily weakened regional development as communities prepared to determine their own futures by successfully competing against other, often neighbouring, areas.” (p. 3)

“Statistics Canada’s place-of-work place-of-residence data . . . indicated a close relationship between the urban and rural municipalities in the region.” (p.3)





“A local development emphasis necessarily weakened regional development as communities prepared to determine their own futures by successfully competing against other, often neighbouring, areas.” (p. 3)

“Statistics Canada’s place-of-work place-of-residence data . . . indicated a close relationship between the urban and rural municipalities in the region.” (p.3)

“Social cohesion is further strengthened by the Town of Russell providing regional health, education and cultural services to all residents.” (p. 3)





“1. Only commercial property tax would be shared.

2. There would be no change in municipal boundaries.

3. Municipalities would retain all current taxing powers.

4. No new taxing authority would be created.

5. No existing fiscal resources would be involved.” (p. 5)





“three tax-sharing scenarios:

• population based model

• labour market participation model

• fiscal capacity model” (p.5)

The relationship of a rural community to a larger urban centre is important.


Outline








Are commuting patterns a good

measure of “rural-urban” interaction?


Outline



flows of people commuters, tourists, retirees, young families

Old rural sociology textbooks suggest that the “reach” of a community can be indicated by whether the wagon tracks leaving a farm yard generally turned to your community or to the neighbouring community.

Another measure of the “reach” of a city is to observe the communities for which houses are listed for sale – or you could look at the name of the newspaper on the deliver box at the end of the lane.

Thus, there are alternatives to using “commuting patterns” to define the influence of a city.

Are commuting patterns a good

measure of “rural-urban” interaction?


Outline









Rural and Small Town Canada gains population from net migration for all age groups from 25 to 69 years of age

-14.00

-12.00

-10.00

-8.00

-6.00

-4.00

-2.00

0.00

2.00

4.00

6.00

8.00

15-19years

20-24years

25-29years

30-34years

35-39years

40-44years

45-49years

50-54years

55-59years

60-64years

65-69years

70-74years

75-79years

80yearsandover

Ave

rag

e fi

ve-y

ear

rate

of

net

mig

rati

on

, 197

1 to

199

1 (p

erce

nt)



Outline




• flows of people commuters, tourists, retirees, young families, land issues





Since 1981, each urban person is consuming more land

0.0000

0.0002

0.0004

0.0006

0.0008

0.0010

0.0012

0.0014

1971 1981 1991 1996Source: Statistics Canada. Environment Accounts and Statistics Division.

2/3 of urban sprawl is now due to more urban land per capita;1/3 of urban sprawl is now due to population increase

0

10

20

30

40

50

60

70

80

90

100

1971 to 1981 1981 to 1991 1991 to 1996

Population increase

Increase in per capita land consumption

Source: Statistics Canada. Environment Accounts and Statistics Division.

Factor "causing" urban sprawl:

Five provinces have over one-quarter of their total land base under urbanising pressure

0 5 10 15 20 25 30 35 40 45

Manitoba

Newfoundland

Quebec

Saskatchewan

CANADA (10 provinces)

Alberta

Ontario

Nova Scotia

British Columbia

New Brunswick

Prince Edward Island

Percent of provincial land under urbanising pressure (percent of total provincial land within CMAs, CAs and Strong MIZ areas)

Larger urban centres Strong MIZ

Source: Statistics Canada. Census of Population,1996.Larger urban centres are Census Metropolitan Areas (CMAs) and Census Agglomerations (CAs). A CMA has an urban core of 100,000 or more population and includes the surrounding municipalities where 50 percent or more commute to the urban core. A CA is similarly defined with an urban core of 10,000 to 99,999. Strong Metropolitan Influenced Zones (MIZ) have 30-49 percent commuting to any CMA or CA.


Outline



• flows of people commuters, tourists, retirees, young families, land use issues





Rural and Small Town Canada gains population from net migration for all age groups from 25 to 69 years of age

-14.00

-12.00

-10.00

-8.00

-6.00

-4.00

-2.00

0.00

2.00

4.00

6.00

8.00

15-19years

20-24years

25-29years

30-34years

35-39years

40-44years

45-49years

50-54years

55-59years

60-64years

65-69years

70-74years

75-79years

80yearsandover

Ave

rag

e fi

ve-y

ear

rate

of

net

mig

rati

on

, 197

1 to

199

1 (p

erce

nt)



Outline









Predominantly rural regions have more than double the tourism intensity of predominantly urban regions

0

2

4

6

8

10

12

14

Predominantlyurban regions

Intermediateregions

All predominantlyrural regions

Rural metro-adjacent regions

Rural non-metro-adjacent regions

Rural northernregions

Tourism intensity: Tourists per resident

Source: Statisitics Canada, Canadian Travel Survey, 2002 and Census of Population , 2001.Note: A tourist is an individual who travels more than 80 kilometres, for business or for leisure.The percent with a destination "not stated' for the total tourist population was 3 percent.

Predominantly rural regions


Outline• from demographic strength

• from resource sector strength

• from & to manufacturing strength

• to Aboriginal identity strength• to rural amenity strength

• to community cohesion strength

In NO MIZ areas (outside the Territories), 37 percent of the population has an Aboriginal identity, Canada, 2001

0

10

20

30

40

50

60

70

80


CAs (10 to49K)





In the rural areas of NO MIZ zones (outside the Territories), 38 percent of the population has an Aboriginal identity, Canada, 2001

0

10

20

30

40

50

60

70

80


CAs (10 to49K)




Source: Statistics Canada. Census of Population, 2001 {available at www.statcan.ca/english/IPS/Data/95F0495XCB2001012.htm}.The location quotient is the share of the workforce with a health occupation, relative to the Canadian average share with a health occupation, based on location of residence of worker)



Outline









Outline

• flows of ideas / knowledge• this is important as we move from a resource / material economy to a

knowledge / weightless economy

• the price of transporting goods is declining – this is “globalization” – thus, the rural-urban flow of goods is increasing

Output price of the railroad transport industry has fallen, relatively, since the 1960s

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

1961 1963 1965 1967 1969 1971 1973 1975 1977 1979 1981 1983 1985 1987

Imp

licit

pri

ce o

f o

utp

ut

of

the

railr

oad

tra

nsp

ort

aio

n s

ecto

r, r

elat

ive

to

the

GD

P im

plic

it p

rice

ind

ex (

1986

= 1

00)

Source: Statistics Canada, GDP Implicit Price Index.

Output price of the truck transport industry has fallen, relatively, since the late 1970s

0.8

0.9

1.0

1.1

1.2

1961 1963 1965 1967 1969 1971 1973 1975 1977 1979 1981 1983 1985 1987

Imp

licit

pri

ce o

f o

utp

ut

of

the

tru

ck t

ran

spo

rtai

on

sec

tor,

rel

ativ

e to

th

e G

DP

imp

licit

pri

ce in

dex

(19

86 =

100

)



Outline




• the price of transporting people is not declining – thus, any increase in the rural-urban flow of people is not a price effect

Transportation price, relative to the overall CPI, increased throughout the 1990s (1992 = 100)

y = 0.0002x + 0.9758

R2 = 0.3725

0.8

0.9

1.0

1.1

1.2

Jan

1949

May

1950

Sep

1951

Jan

1953

May

1954

Sep

1955

Jan

1957

May

1958

Sep

1959

Jan

1961

May

1962

Sep

1963

Jan

1965

May

1966

Sep

1967

Jan

1969

May

1970

Sep

1971

Jan

1973

May

1974

Sep

1975

Jan

1977

May

1978

Sep

1979

Jan

1981

May

1982

Sep

1983

Jan

1985

May

1986

Sep

1987

Jan

1989

May

1990

Sep

1991

Jan

1993

May

1994

Sep

1995

Jan

1997

May

1998

Sep

1999

Jan

2001

May

2002

Sep

2003

Tra

nsp

ort

atio

n p

rice

rel

ativ

e to

th

e o

vera

ll C

PI

(19

92 =

100

)

Transportation price relative to the overall CPI(1992 = 100)Linear (Transportation price relative to theoverall CPI (1992 = 100))

Source: Statistics Canada, Consumer Price Index, CANSIM database.

Price of air transportation has been increasing, relatively, since the early 1980s (1992 = 100)

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

Jan

1949

Dec

1950

No

v195

2

Oct

1954

Sep

1956

Au

g19

58

Jul1

960

Jun

1962

May

1964

Ap

r196

6

Mar

1968

Feb

1970

Jan

1972

Dec

1973

No

v197

5

Oct

1977

Sep

1979

Au

g19

81

Jul1

983

Jun

1985

May

1987

Ap

r198

9

Mar

1991

Feb

1993

Jan

1995

Dec

1996

No

v199

8

Oct

2000

Sep

2002

Au

g20

04

Air

tra

nsp

ort

atio

n p

rice

rel

ativ

e to

th

e o

vera

ll C

PI

(19

92 =

100

)

Air transportation price relative to the overall CPI(1992 = 100)


The price to purchase a vehicle has been declining, generally, over time, relative to the overall CPI (1992 = 100)

0.0

0.5

1.0

1.5

2.0

2.5

Jan

1949

Dec

1950

No

v195

2

Oct

1954

Sep

1956

Au

g19

58

Jul1

960

Jun

1962

May

1964

Ap

r196

6

Mar

1968

Feb

1970

Jan

1972

Dec

1973

No

v197

5

Oct

1977

Sep

1979

Au

g19

81

Jul1

983

Jun

1985

May

1987

Ap

r198

9

Mar

1991

Feb

1993

Jan

1995

Dec

1996

No

v199

8

Oct

2000

Sep

2002

Au

g20

04

Veh

icle

pu

rch

ase

pri

ce r

elat

ive

to t

he

ove

rall

CP

I (

1992

= 1

00)

Vehicle purchase price, relative to the overall CPI(1992 = 100)


Gasoline prices -- up in the early 1980s, then a decline to the late 1990s and generally up in the 2000s,

relative to the overall CPI (1992 = 100)

0.6

0.7

0.8

0.9

1.0

1.1

1.2

1.3

1.4

Jan

1949

No

v195

Sep

195

Jul1

954

May

195

Mar

195

Jan

1960

No

v196

Sep

196

Jul1

965

May

196

Mar

196

Jan

1971

No

v197

Sep

197

Jul1

976

May

197

Mar

198

Jan

1982

No

v198

Sep

198

Jul1

987

May

198

Mar

199

Jan

1993

No

v199

Sep

199

Jul1

998

May

200

Mar

200

Jan

2004

Gas

olin

e p

rice

rel

ativ

e to

th

e o

vera

ll C

PI

(19

92 =

100

)

Gasoline price relative to the overall CPI(1992 = 100)



Outline





• the price of communications is declining – thus, the rural-urban flow of information is increasing

Output price of the telecommunications sector has fallen, relatively, since the 1960s

0.0

0.5

1.0

1.5

2.0

2.5

1961 1963 1965 1967 1969 1971 1973 1975 1977 1979 1981 1983 1985 1987

Imp

licit

pri

ce o

f o

utp

ut

of

the

tele

com

mu

nic

atio

n s

ecto

r, r

elat

ive

to t

he

GD

P im

plic

it p

rice

ind

ex (

1986

= 1

00)


Price of telephone services fell, relatively, from the start of the 1960s to the end of the 1980s

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

Jan

1949

Sep

1950

May

1952

Jan

1954

Sep

1955

May

1957

Jan

1959

Sep

1960

May

1962

Jan

1964

Sep

1965

May

1967

Jan

1969

Sep

1970

May

1972

Jan

1974

Sep

1975

May

1977

Jan

1979

Sep

1980

May

1982

Jan

1984

Sep

1985

May

1987

Jan

1989

Sep

1990

May

1992

Jan

1994

Sep

1995

May

1997

Jan

1999

Sep

2000

May

2002

Jan

2004

Tel

eph

on

e se

rvic

es p

rice

rel

ativ

e to

th

e o

vera

ll C

PI

(19

92 =

100

)

Telephone services price relative to the overallCPI (1992 = 100)


Price of telephone services have been falling, relatively, since early 1998

0.8

0.9

1.0

1.1

1.2

Jan

1990

Jul1

990

Jan

1991

Jul1

991

Jan

1992

Jul1

992

Jan

1993

Jul1

993

Jan

1994

Jul1

994

Jan

1995

Jul1

995

Jan

1996

Jul1

996

Jan

1997

Jul1

997

Jan

1998

Jul1

998

Jan

1999

Jul1

999

Jan

2000

Jul2

000

Jan

2001

Jul2

001

Jan

2002

Jul2

002

Jan

2003

Jul2

003

Jan

2004

Jul2

004

Tel

eph

on

e se

rvic

es p

rice

rel

ativ

e to

th

e o

vera

ll C

PI

(19

92 =

100

)

Telephone services price relative to the overallCPI (1992 = 100)



Outline






• but is the price of rural communications declining more or less than the price of urban communications?

Two digital divides

0

5

10

15

20

25

30

35

40

45

Census MetropolitanAreas


Small towns Rural areas

Per

cen

t o

f in

div

idu

als

(18

year

s an

d o

ver)

1st digital divide: Percent of total populationthat is NOT interested in using the Internet

2nd digital divide: If interested in using theInternet, percent who say that "access tocomputer or Internet" is the greatest barrier.

Source: Statistics Canada. General Social Survey, 2000.

Rural and small town areasLarger urban centres

Two digital divides

0

5

10

15

20

25

30

35

40

45

Census MetropolitanAreas


Small towns Rural areas

Per

cen

t o

f in

div

idu

als

(18

year

s an

d o

ver)

1st digital divide: Percent of total populationthat is NOT interested in using the Internet

2nd digital divide: If interested in using theInternet, percent who say that "access tocomputer or Internet" is the greatest barrier.

Source: Statistics Canada. General Social Survey, 2000.

Rural and small town areasLarger urban centres


Outline






• but is the price of rural communications declining more or less than the price of urban communications?

• and what about the flow of ideas / knowledge?


Outline










Outline


“An interdependency between individual decisions which is not mediated by markets”

• involves any unpriced interaction

• externalities, spillovers, role models

• “tacit” knowledge


Outline










• Interactions or networks that allow the transfer of “tacit” knowledge are an important component of agglomeration economies.• Adam Smith, in 1776, observed that land rents were lower and wage costs were lower in northern Scotland but all entrepreneurs wanted to start up in central London. • The reason, then and now, is agglomeration economies.• A high density of skilled workers facilitates the transfer of “tacit” knowledge. • This is training that you cannot buy – it is truly an “interaction”.


• The price of telecommunication across distance is falling

• but the price of communications within and between metro areas has fallen more• who has Broadband?

• Now that the price of telecommunications is not a major cost, the advantages of the agglomeration economy for the transfer of “tacit” knowledge is relatively more important


• Are agglomeration economies the only thing?

• Sometimes we hear that metro economies are the drivers of economic growth

• If metro economies are always the drivers of economic growth, then it should not matter which metro economy you are “interacting” with.


Rank Agglomeration CountryPopulation

in 1996 (millions)

1 Tokyo Japan 27.22 Mexico City Mexico 16.93 São Paulo Brazil 16.84 New York United States of America 16.45 Bombay India 15.76 Shanghai China 13.77 Los Angeles United States of America 12.68 Calcutta India 12.19 Buenos Aires Argentina 11.9

10 Seoul Republic of Korea 11.811 Beijing China 11.4

. . . . . . . .45 Baghdad Iraq 4.446 Toronto Canada 4.447 Kinshasa Dem. Rep. of the Congo 4.4

. . . . . . . . 72 Qingdao China 3.473 Montreal Canada 3.374 Berlin Germany 3.3

. . . . . . . . 159 Baku Azerbaijan 1.9160 Vancouver Canada 1.9161 Lanzhou China 1.8

. . . . . . . . 325 Shiraz Iran (Islamic Rep. of) 1326 Ottawa Canada 1327 Shantou China 1

Source: United Nations.

Rank of metropolitan centres

Rank Agglomeration CountryPopulation

in 1996 (millions)

1 Tokyo Japan 27.22 Mexico City Mexico 16.93 São Paulo Brazil 16.84 New York United States of America 16.45 Bombay India 15.76 Shanghai China 13.77 Los Angeles United States of America 12.68 Calcutta India 12.19 Buenos Aires Argentina 11.9

10 Seoul Republic of Korea 11.811 Beijing China 11.4

. . . . . . . .45 Baghdad Iraq 4.446 Toronto Canada 4.447 Kinshasa Dem. Rep. of the Congo 4.4

. . . . . . . . 72 Qingdao China 3.473 Montreal Canada 3.374 Berlin Germany 3.3

. . . . . . . . 159 Baku Azerbaijan 1.9160 Vancouver Canada 1.9161 Lanzhou China 1.8

. . . . . . . . 325 Shiraz Iran (Islamic Rep. of) 1326 Ottawa Canada 1327 Shantou China 1

Source: United Nations.

Rank of metropolitan centres





• In Canada, rural areas “adjacent to metro” have higher incomes and growing populations.





• In Canada, rural areas “adjacent to metro” have higher incomes and growing populations.

However, “adjacency” does not pre-ordain “higher incomes” or “growing populations.”

“Non-adjacency” does not pre-ordain “lower incomes” nor “declining populations.”

There is always some place that is succeeding that does not conform to the statistical average.


Outline









Predominantly rural regions are less intensive in "professional" occupations (even after standardization for industry structure)

and this differential increased slightly in the 1990s

0.00

0.25

0.50

0.75

1.00

1.25

1.50

Predominantly urbanregions

Intermediate regions Rural metro-adjacentregions



Skill Specialization Quotient(intensity of "professional" occupations

standardized for industrial structure) 1991 1996 2001

Source: Statistics Canada, Census of Population, 1991 to 2001. Predominantly rural regions

Predominantly rural regions are more intensive in "unskilled" occupations (even after standardization for industry structure)

and this differential increased slightly in the 1990s

0.00

0.25

0.50

0.75

1.00

1.25

1.50

Predominantly urbanregions

Intermediate regions Rural metro-adjacentregions



Skill Specialization Quotient(intensity of "unskilledl" occupationsstandardized for industrial structure)

1991 1996 2001

Source: Statistics Canada, Census of Population, 1991 to 2001. Predominantly rural regions


Outline










Outline

• A bit more on governance• recall our definition of governance

• regulation of power• via processes and networks• for taking decisions• in the “public” interest

• recall our definition of “interaction” “An interdependency between individual decisions which is

not mediated by markets”• involves any unpriced interaction

• “tacit” knowledge appears strategic in the new economy


Outline

• A bit more on governance• recall our definition of governance

• regulation of power• via processes and networks• for taking decisions• in the “public” interest

• recall our definition of “interaction” “An interdependency between individual decisions which is not mediated

by markets”• involves any unpriced interaction• “tacit” knowledge appears strategic in the new economy

• Thus, what governance “processes and networks” might we imagine for the transfer of “tacit” knowledge to stimulate rural economies in the 2000s

Hence the search for clusters that can achieve

some of these agglomeration economies,

including the transfer of “tacit” knowledge


Outline










Outline• Concluding comments

• Distance matters.

• Close proximity and agglomeration do facilitate the diffusion and accumulation of new ideas.

• The accumulation of ideas does not confront decreasing returns.

• Implications for governance

• These interactions lead to agglomerations and thus favour urban areas

• Rural metro-adjacent will benefit, relative to other rural areas

• Rural non-metro-adjacent areas will be the most challenged to develop “networks and processes” to stimulate development in the 2000s


Ray D. BollmanStatistics Canada

L. Peter ApedailePeer Diagnostics

Alessandro AlasiaUniversity of Saskatchewan

and Statistics Canada

Presentation to the Annual Rural Policy Conference of the Canadian Rural Revitalization Foundation on

“Rural-Urban Footprints: Implications for Governance”Tweed, Ontario, October 14 – 16, 2004


Documents

What does Rural – Urban Interaction Look Like? Ray D. Bollman Statistics Canada L. Peter Apedaile Peer Diagnostics Alessandro Alasia University of Saskatchewan